Socio-Economic Impact of HIV and AIDS in Tamil nadu

Socio-Economic 

IMPACT of HIV and AIDS in 

TAMIL NADU, 

India

Socio-Economic Impact of 

HIV and AIDS 

in Tamil Nadu, India 

Basanta K Pradhan 

Ramamani Sundar 

Geetha Natesh

© United Nations Development Programme, 2006 

All rights are reserved. The document may, however, be freely reviewed, quoted, 

reproduced or translated, in part or in full, provided the source is acknowledged. The 

document may not be sold or used in conjunction with commercial purposes without 

prior written approval from UNDP. The views expressed in documents by named 

authors are solely the responsibility of those authors. 

The analysis and policy recommendations of this Report do not necessarily represent 

the views of the United Nations Development Programme, its Executive Board or its 

Member States. 

Edited and designed by New Concept Information Systems Pvt. Ltd., New Delhi

Study Team 

Core Research Team 

Basanta K. Pradhan : Chief Economist and Project Director 

Ramamani Sundar : Senior Consultant and Project Coordinator 

Geetha Natesh : Consultant and Project Coordinator 

Consultant 

Sampurna Singh : Consultant 

Project Review Committee 

Suman Bery : Director-General 

Abusaleh Shariff : Chief Economist 

Field Coordinators 

T. K. Krishnan 

Computer Programming 

J. M. Chawla 

Technical Support 

Bijay Chouhan 

iii

Acknowledgements 

This report would not have been possible without the encouragement, cooperation, 

feedback and inputs of many people. 

First and foremost, The National Council of Applied Economic Research (NCAER) 

would like to thank Ms. K. Sujatha Rao, Additional Secretary & Director-General, 

National AIDS Control Organisation and Dr. N.S. Dharamshaktu, former Additional 

Project Director (Technical), National AIDS Control Organisation. 

We would also like to thank Smt. Supriya Sahu, the current Project Director and 

Shri S. Vijaya Kumar, IAS, former Project Director, Tamil Nadu State AIDS Control 

Society (TNSACS) without whose unconditional support in organising the data 

collection process, the field work would not have been completed on time. 

At the United Nations Development Programme, New Delhi we would like to thank 

Dr. Maxine Olson, UNDP Resident Representative and UN Resident Co-ordinator 

for her leadership and guidance. We would especially like to acknowledge the 

continuous advice and inputs from Ms. Alka Narang, Head, HIV and Development 

Unit, Dr. Hari Mohan, National Programme Officer and Ms. Sabrina Sidhu, 

Research Associate. 

The study would not be of the same quality if it wasn’t for the time and energy 

invested in the field research by the investigators and the researchers. 

Finally, we would like to thank all the respondents who shared the information 

without any hesitation. Their contributions made this study rich and unique. 

iv 

Socio-Economic Impact of HIV and AIDS in Tamil Nadu, India

Contents 

Abbreviations 

Executive Summary 

xi 

xii 

CHAPTER 1 

Introduction 

1.1 Background 3 

1.2 HIV and AIDS scenario in Tamil Nadu 4 

1.3 Objectives of the present study 7 

CHAPTER 2 

Data and Methodology 

2.1 Sample size 13 

2.2 Qualitative techniques 17 

CHAPTER 3 

Profile of the Sample Households and PLWHA 

3.1 Background characteristics of head of sample households 21 

3.2 Profile of sample PLWHA 26 

CHAPTER 4 

Impact of HIV status on Income and Employment in India 

4.1 Income and its distribution 31 

4.2 Work force participation rate among HIV and non-HIV households 

in the sample 36 

4.3 Change of job/loss of employment of self and caregiver 37 

4.4 Loss of income of PLWHA and the caregiver 40 

4.5 Support from employer 45 

4.6 Observations 46 

CHAPTER 5 

Level and Pattern of Consumption and Savings of the Households 

5.1 Consumption patterns 49 

5.2 Household savings 60 

5.3 Coping mechanism 66 

5.4 Poverty 69 


Executive Summary Contents 

v

CHAPTER 6 

Impact of HIV and AIDS on the Education of Children 

6.1 Ever and current enrolment rates 78 

6.2 Dropout rates and number of years of schooling 79 

6.3 Ever and current enrolment rates by household Income 79 

6.4 Ever and current enrolment rates by level of education 

of household head 80 

6.5 Type of school attended 82 

6.6 School attendance 82 

6.7 Reasons for discontinuation of schooling 83 


CHAPTER 7 

Impact of HIV and AIDS on Health Status 87 

7.1 Prevalence rate of illness 89 

7.2 Details about non-hospitalised illness episodes 93 

7.3 Details about hospitalisation cases 98 


CHAPTER 8 

Stigma, Discrimination and Coping Mechanism 

8.1 Introduction 107 

8.2 Discovering HIV status 107 

8.3 Reaction to HIV status 109 

8.4 Disclosure of HIV status 111 

8.5 Migration 112 

8.6 Stigma and discrimination faced by PLWHA 112 

8.7 Knowledge and awareness about HIV and AIDS and attitude 

towards PLWHA 116 


CHAPTER 9 

Conclusion and Policy Implications 123 

Annexure 

Annexure I Summary of Focus Group Discussions 131 

Annexure II Case Studies 137 

References 140 

List of tables 

Table 1.1 HIV prevalence rates for high-prevalence states – 2004 4 

Table 1.2 

Number of AIDS cases in Tamil Nadu reported 

upto December 2004 5 

Table 1.3 Source of infection in Tamil Nadu upto 2004 6 

vi 


Table 1.4 Observed HIV-prevalence levels in Tamil Nadu (1998 – 2004) 6 

Table 2.1 Distribution of sample HIV households by place of interview 15 

Table 2.2 District-wise distribution of sample HIV households 16 

Table 3.1 Distribution of head of sample households by caste 21 

Table 3.2 Occupation and level of education of heads of the households 22 

Table 3.3 

Table 3.4 

Table 3.5 

Distribution of sample households by 

household income categories 23 


the availability of basic amenities 24 

Distribution of sample households by ownership of 

assets and other consumer durables 25 

Table 3.6 Profile of sample PLWHA 26 

Table 3.7 Current and the past occupation of the sample PLWHA 27 

Table 4.1 

Table 4.2 

Table 4.3 

Table 4.4 

Table 4.5 

Distribution of sample households, population and 

income by occupation 32 

Distribution of households and their share in 

income by income categories in the sample 33 

Average household and per capita annual income by 

occupational categories in the sample 34 

Households by number of earners and annual 

household income in the sample 35 

Work force participation rate by age group and place of 

residence (per 100) 37 

Table 4.6 Change in job due to HIV and AIDS 38 

Table 4.7 

Table 4.8 

Change in occupational distribution due to HIV and AIDS 

(age group 18-60) 39 

Change in sectoral distribution due to HIV and AIDS 

(age group 18-60) 39 

Table 4.9 The situation with respect to provision of care to PLWHA 40 

Table 4.10 Occupational distribution of caregiver 40 

Table 4.11 

Table 4.12 

Table 4.13 

Table 4.14 

Loss of income of workers with HIV if currently working by 

occupational groups 41 

Loss of income of workers with HIV if currently not working by 

occupational groups 43 

Loss of income of caregiver if currently working by occupational 

groups 44 

Average number of work days lost due to leave/absence from 

work of PLWHA 45 

Table 5.1 Share of expenditure on some of the major items 49 

Contents 

vii

Table 5.2 Average per capita per month expenditure on some major items 50 

Table 5.3 

Table 5.4 

Table 5.5 

Table 5.6 

Table 5.7 

Table 5.8 

Average per household consumption expenditure by 

occupation groups 51 

Per capita consumption expenditure on various items by 

occupation groups 53 

Distribution of consumption expenditure cross 

broad groups of consumption items by occupation 56 

Distribution of consumption expenditure by income 

groups and items of expenditure 58 

Average household annual consumption expenditure by 

income group 61 

Per capita item-wise annual consumption expenditure by 

income group 63 

Table 5.9 Average household savings by place of residence 65 

Table 5.10 Distribution of savers and non-savers 66 

Table 5.11 Average household and per capita savings by level of income 67 

Table 5.12 

Table 5.13 

Liquidation of assets or borrowings to cope with 

financial burden of HIV and AIDS after being tested positive 67 

Liquidation of assets or borrowings to cope with financial 

burden of HIV and AIDS after being tested positive by 

occupational classes 68 

Table 5.14 Borrowing in last one year 69 

Table 5.15 Distribution of households by income poverty in the sample 70 

Table 5.16 Consumption poverty in the sample 71 

Table 5.17 Income poverty in the sample group by occupational categories 72 

Table 5.18 

Table 6.1 

Table 6.2 

Table 6.3 

Table 6.4 

Table 6.5 

Table 6.6 

Consumption poverty in the sample group by occupational 

categories 73 

Ever and current enrolment of children in HIV and 

non-HIV households 78 

Dropout rates and number of years of schooling 

completed by dropout children 79 

Ever & current enrolment rates for children by 

annual household income categories 80 

Ever and current enrolment rates for children by level of 

education of household head 81 

Distribution of currently enrolled children by 

type of school attended 82 

School attendance of children In the last academic year by 

type of household 83 

viii 


Table 7.1 

Table 7.2 

Table 7.3 

Table 7.4 

Table 7.5 

Table 7.6 

Table 7.7 

Table 7.8 

Table 7.9 

Table 7.10 

Table 7.11 

Table 7.12 

Table 7.13 

Table 7.14 

Table 7.15 

Table 7.16 

Table 7.17 

Table 7.18 

Table 7.19 

Prevalence rate of illness for the one-month reference 

period by type of households and age and sex 90 

Reported number of hospitalisation cases in the reference 

year by type of households and sex 90 

Prevalence rate of illness and hospitalisation for PLWHA by 

stage of infection and number of years back HIV status detected 91 

Frequency of OIs reported by PLWHA by 

stage of HIV infection(non-hospitalised illness episodes) 92 

Distribution of PLWHA reporting 

prolonged illness as a reason for going in for HIV test 94 

Distribution of non-hospitalised illness 

episodes by nature of illness reported 94 

Illness episodes receiving no treatment and 

reasons for no treatment for PLWHA 95 

Average number of days ill, bedridden and not going to 

work during each non-hospitalised illness episode in the 

last one month 96 

Distribution of non-hospitalised illness episodes by 

source of treatment for male and female PLWHA 97 


source of treatment and by annual household income groups 97 

Expenditure incurred by PLWHA for treatment of 

non-hospitalised illness episodes by source of treatment 98 

Frequency of hospitalisation reported by PLWHA by stage of HIV 

infection and number of years back HIV was detected 99 

Distribution of hospitalisation cases by nature of 

illness suffered by HIV-positive men and women and number of 

days hospitalised. 100 

Distribution of hospitalisation cases by source of 

treatment for PLWHA by rural/urban break-up 100 


treatment and by annual household income groups 101 

Average expenditure incurred per hospitalisation case by 

PLWHA by source of treatment 101 

Expenditure incurred per hospitalisation case by PLWHA by 

source of treatment and annual household income groups 102 

Distribution of hospitalisation cases by source of financing 

hospitalisation and annual household income groups 103 


financing hospitalisation and stage of infection 103 

Table 8.1 Distribution of PLWHA by ways of discovering their HIV status 108 

Contents 

ix

Table 8.2 Distribution of sample PLWHA by reaction to their HIV status 109 

Table 8.3 

Distribution of PLWHA by coping mechanism adopted to get 

over initial shock/disbelief etc 111 

Table 8.4 Distribution of PLWHA by disclosure of status 111 

Table 8.5 Distribution of PLWHA reporting change of residence and reasons 112 

Table 8.6 

Stigma and discrimination faced by PLWHA in the community/ 

neighbourhood by sex 113 

Table 8.7 Distribution of the PLWHA according to their work status 114 

Table 8.8 

Distribution of PLWHA by disclosure of status and discrimination 

faced at workplace 114 

Table 8.9 Distribution of PLWHA reporting discrimination at health facilities 115 

Table 8.10 

Distribution of respondents according to their knowledge and 

awareness about HIV and AIDS 117 

Table 8.11 Distribution of respondents by exposure to media 118 

Table 8.12 

Table 8.13 

Table 8.14 

Distribution of respondents according to their knowledge about 

modes of transmission of HIV and AIDS 119 

Distribution of respondents according to their 

knowledge about usage of condom 120 

Distribution of respondents according to their attitude towards 

PLWHA 120 

Appendix - I Background information on Tamil Nadu 8 

Appendix - II Population growth rate in Tamil Nadu 9 

x 


Abbreviations 

AIDS 

ANC 

APAC 

BSS 

CSW 

FGD 

GDP 

HIV 

ICMR 

IHS 

NACO 

NCAER 

NGOs 

OI 

PLWHA 

PPTCT 

STD 

STI 

TNSACS 

UNDP 

USAID 

VCTC 

VHS 

Acquired Immuno Deficiency Syndrome 

Ante Natal Clinic 

AIDS Prevention and Control Project 

Behavioural Surveillance Survey 

Commercial Sex Worker 

Focus Group Discussion 

Gross Domestic Product 

Human Immuno-deficiency Virus 

Indian Council of Medical Research 

Institute of Health Systems 

National AIDS Control Organisation 

National Council of Applied Economic Research 

Non Governmental Organisations 

Opportunistic Infection 

Persons Living with HIV and AIDS 

Prevention of Parent to Child Transmission 

Sexually Transmitted Diseases 

Sexually Transmitted Infections 

Tamil Nadu State AIDS Control Society 

United Nations Development Programme 

United States Agency for International Development 

Voluntary Counselling and Testing Centre 

Voluntary Health Services 

Abbreviations 

xi


Introduction 

AIDS has emerged as a serious challenge 

for the developing as well as the developed 

world. Although India remains a low 

prevalence country with overall HIV 

prevalence of 0.91 percent, it has 5.206 

million people living with HIV and AIDS 

(PLWHA)(2005). At this critical stage of 

the country’s response to the epidemic, 

a study on the ‘Socio-Economic Impact 

of HIV and AIDS’ was undertaken by 

National Council of Applied Economic 

Research (NCAER) in the six HIV highprevalence 

states of India, namely 

Andhra Pradesh, Karnataka, Maharashtra, 

Manipur, Nagaland and Tamil Nadu. 

The study was carried out with support 

from UNDP and National AIDS Control 

Organisation (NACO). 

Objectives 

The objective of the study was to analyse 

the nature and type of socio-economic 

impact of HIV and AIDS on affected 

individuals and their households. The 

focus of the study is on the impact of 

HIV and AIDS on household income 

and employment, level and pattern of 

consumption, savings and borrowings, 

education of children, health status 

including household expenditure on 

treatment. The stigma and discrimination 

on the affected individuals and the 

families are subjected to is also reflected 

in this stydy. The study is based on 

a p r i m a r y s u r vey c o n d u c t e d by 

NCAER. 

Data and methodology 

In the state of Tamil Nadu, a field survey 

was conducted during the period of 

December 2004 to February 2005. 

Both HIV and non-HIV (control group) 

households were surveyed and their 

socio-economic characteristics, pattern 

of household expenditure and savings, 

prevalence of morbidity and differences 

in enrolment and dropout rates of 

school going children compared. The 

number of HIV households surveyed 

was 410, comprising 223 rural and 

187 urban households. Apart from 

the capital city of Chennai, the survey 

covered five more districts, namely Theni, 

Namakkal, Thiruchirapalli, Erode and 

Tirunelvelli. This was done so that HIV 

high-prevalence districts from different 

geographic regions of the state could be 

covered. 

The Tamil Nadu State AIDS Control 

Society ( TNSACS) suggested that 

selected VCTC/PPTCT counsellors 

canvass questionnaires and two trained 

counsellors – one man and one woman 

– were appointed as field investigators. 

These counsellors were advised to select 

the sample from a diverse socio-economic 

profile of households. However, in spite 

of best efforts, these field investigators 

could not get access to upper middle class 

and rich HIV households. The samples 

were drawn mainly from government 

general hospitals and TB hospitals, care 

and support homes, drop-in centres run 

by NGOs, Network of Positive People etc. 

xii 


which mostly cater to poor/low-income 

households. An attempt was made to 

select PLWHA from both sexes at different 

stages of the infection. In households 

with more than one HIV-positive person, 

a maximum of two adult PLWHA, mostly 

husband and wife, were interviewed. 

For every HIV household that was 

surveyed in a village/urban block, 

approximately three non-HIV households 

belonging to similar economic strata 

were interviewed. The survey of non-HIV 

households commenced immediately 

after completion of the survey of PLWHA. 

The households were matched first on 

the basis of broad income category of 

the HIV households. At the second stage, 

the occupational group of the head of 

the household was matched from within 

each income category. 

Two sets of structured questionnaires 

were used for the household survey 

– one for HIV and another for non-HIVhouseholds. 

These two questionnaires 

had some common sections as well as 

special sections. In order to supplement 

the findings of the quantitative survey, 

qualitative techniques like case studies 

and focus group discussions were also 

used. Two case studies were conducted 

in Tamil Nadu, and the Focus Group 

Discussion was conducted with the 

members of the Cambam Network of 

Positive People in the Theni district of 

the state. 

Profile of the sample 

It was found that nearly 79 percent 

of both HIV and non-HIV household 

heads were in the age group of 20-50 

years. Though the level of education 

of the household heads was poor, it 

seemed comparatively better in non- 

HIV households, with the percentage 

of illiterates in HIV households being 

twice that of the percentage in non-HIV 

households. The average annual income 

of non-HIV households (Rs. 48,878) was 

higher than that of the HIV households 

(Rs. 39,298) selected, though efforts were 

made to capture economically similar 

placed households. Nearly 40 percent 

of the rural HIV households selected 

had an annual income of less than Rs. 

20,000. The average income of the urban 

households was found to higher than 

that of the rural in both categories of 

households. The availability of basic 

amenities, ownership of house/flats and 

consumer durables in the households 

indicated a low economic status of the 

sample households. 

Most of the PLWHA were in the age group 

of 20-40 years, with nearly 60 percent of 

the women between 20-30 years and 56 

percent of the men between 31-40 years. 

Nearly 76 percent of the men and 48 

percent of the women were married at 

the time of the survey. Percentage of men 

separated/divorced/abandoned was 3.7, 

while for women it was 6.7. Three percent 

of the men were widowers and 38 percent 

of the women, widows. The sample 

PLWHA was poorly educated. Nearly 30 

percent men and 28 percent women were 

wage earners while 15 percent men and 

17 percent women were salary earners. 

About 19 percent were engaged in the 

transport sector, which is considered 

one of the high HIV-risk occupational 

sectors. While about 17 percent men were 

unemployed, 33 percent of the women 

were not found to be engaged in any 

income earning activity. 

Impact on employment and 

income 

Analysis of the average annual household 

income based on occupations shows 

the agricultural wage earners with the 

least and the salaried with the highest 

Nearly 40 percent 

of the rural HIV 

households 

selected had an 

annual income of 

less than 

Rs. 20,000 


xiii

The work force 

participation rate 

regarding age 

groups was higher 

in HIV households 

income in both HIV and non-HIV 

categories. Except for self-employed nonagriculturists, 

the average income of HIV 

households in different occupational 

groups is less than that of non-HIV 

households. Inspite of a difference in the 

average annual income of HIV and non- 

HIV households, the per capita income 

of the urban samples in both households 

is nearly the same. 

Analysis revealed that the work force 

participation rate among the different 

age groups was higher in HIV households. 

The work force participation was lower in 

non-HIV among all age groups-children 

of 0-14 years, 15-60 years as well as people 

above 60 years. It was also observed that 

the workforce participation rate was the 

highest for PLWHA in the 15-60 years 

age group. 

Of the 410 HIV households in the sample, 

475 PLWHA in the age group of 18-60 

years were interviewed in detail. While 

314 reported being currently employed, 

43 had changed their jobs after being 

detected positive. However, only seven 

of them had received benefits at the time 

of changing the job with the average 

benefit being Rs. 16,571. The prevalence 

of HIV and AIDS is higher among working 

members of the HIV households across 

all occupational groups. This was seen 

in the occupational and sectoral pattern 

of employment of PLWHA before and 

after being detected positive. Also, the 

percentage of the unemployed among 

men increased from 1 percent before the 

test to 17 percent after the test. Among 

women, this percentage increased from 

2.4 percent to 5.3 percent. 

Of the 475 PLWHA that were interviewed, 

123 (32.7 %) reported a need to be looked 

after, and 128 people were involved in 

taking care of them of which 74 were 

employed. However, no one had to give 

up his or her job to attend to the HIV 

affected person. 

It was reported by 164 PLWHA employed 

that for the one year before the interview, 

there was loss of income due to absence 

from work because of ill health. The 

average income lost was Rs. 4,214. Loss 

of some fringe benefits and additional 

amount spent on hired labourers was also 

reported. With these, the income lost as a 

percentage of current household income 

was 10.53. Estimates were made of the 

loss of income to those forced to withdraw 

from work on being detected HIV-positive. 

The number of such PLWHA was 53 and 

they were spread over all occupational 

groups except cultivators and suchlike. 

The average loss of income was Rs. 24,095 

per person. While the average income 

lost as a percentage of current household 

income amounted to 84.2 percent, there 

was a great variance among the different 

categories of occupation. Further the 

loss of income of the caregivers currently 

employed was estimated at 7.09 percent 

of current household income. 

Impact on consumption, 

savings and borrowings 

Analysis of the share of expenditure 

of both households revealed the 

proportion of expenditure of HIV 

households on all items other than 

healthcare and rent was less than 

that of the non-HIV households. The 

proportion of expenditure on medical 

care by HIV households was found to be 

a little more than double than non-HIV 

households. The salaried class reported 

maximum average consumption 

expenditure between both HIV and 

non-HIV households. However, on the 

whole, average per capita per month 

expenditure of the HIV households was 

slightly more than that of the non-HIV 

households. This was in spite of their 

xiv 


per capita income being lesser than the 

non-HIV households. 

The HIV households had no savings with 

the average annual household savings of 

HIV households being Rs. -1,082, while 

the non-HIV households had savings of 

Rs. 4,329. The non-HIV households had 

positive savings under all the different 

kinds of savings considered, except that 

of agricultural land. The HIV households 

had positive savings only under cash/ 

bank deposits and shares, etc, with a 

higher portion of the saving in the form 

of cash/bank deposits. The percentage 

of zero savers and positive savers was 

higher in non-HIV households, while 

negative savers saw a higher percentage 

in HIV households. Analysis of the per 

capita saving of different income groups, 

revealed a negative rate of savings for 

the three lower income groups in HIV 

households with -26.80 percent for the 

lowest household income group (upto 

Rs. 20,000). The rate was 0.49 percent 

for the same group under non-HIV 

households, and no group under non- 

HIV households had negative savings. The 

rate of savings of non-HIV households 

was found to be higher as compared to 

their HIV counterparts in all the different 

income groups. 

More than half the HIV households 

reported to have either borrowed or 

liquidated assets to cope with the financial 

burden/loss of income after a family 

member tested positive. The percentage 

of such households was highest for the 

lowest income group (58.3%), going 

down with the increasing level of income 

of the households. The average amount 

generated was the highest for the highest 

income group. For the households that 

borrowed in the year before the survey, 

the percentage of average borrowing 

per household was higher for HIV 

households. 

The borrowing per household was high 

for HIV households in the three lower 

income groups. This was higher for non- 

HIV households with income above Rs. 

41,001. 

Households surveyed on the basis of 

income poverty, show the percentage 

of households below poverty line was 

higher in HIV households (26% of HIV 

as against 9% of non-HIV households). 

The average household income of 

non-HIV households was found to be 

more than that of HIV households. The 

consumption poverty in the sample 

shows the HIV households above poverty 

line have bigger per capita expenditure 

than similar non-HIV households. 

However, for households below poverty 

line, consumption expenditure of HIV 

households was lesser than that of non- 

HIV households. 

Impact on education of 

children 

The survey of the impact on education 

of children captured 302 children – 148 

boys and 154 girls – from HIV households 

and 659 children – 351 boys and 308 girls 

– from non-HIV households in the age 

group of 6-14 years, which corresponds 

to class I-VIII. In this group, the ever 

enrolled percentages were similar in 

children from both types of households. 

There was also no noticeable difference 

between the enrolment rate of boys and 

girls. However, the difference between the 

ever enrolled and currently enrolled rates 

was much higher in the case of children 

from HIV households; especially in case 

of girls. This indicates a higher dropout 

rate for the children of HIV households, 

especially for girls. In the age group of 

15-18 years corresponding to class IX to 

XII, the number of children from HIV and 

non-HIV households were 59 and 431 

respectively. While the ever enrolment 

Households 

surveyed on the 

basis of income 

poverty, show 

the percentage 

of households 

below poverty line 

was higher in HIV 

households 


xv

In the HIV 

households, both 

the rate of illness 

and the number 

of hospitalisation 

cases was much 

less for women 

than for men 

was 100 percent for all children from 

both households, the current enrolment 

rates were less for both HIV and non-HIV 

households. The rates for children from 

HIV households were the lesser of two. 

While no gender difference was seen in 

the current enrolment rates of children 

from non-HIV households; the rate was 

lesser for girls than boys in case of HIV 

households. 

Of the 15 HIV-positive children in the age 

group of 6-14 years, 14 were enrolled in 

school. One boy however, could not get 

admission because of his HIV status. One 

boy and two girls dropped out; the boy to 

look after his sick parents and the girls, as 

there was no separate school for girls. 

Impact on health status and 

household expenditure 

From the sample of 410 HIV and 1,203 

non-HIV households, the total number 

of persons in the two households worked 

out to 1,520 and 4,937 respectively. The 

prevalence rate of non-hospitalised 

illness was calculated based on the 

number of illnesses reported for all the 

members of the households. This was 

during one month before the interview, 

and included acute and chronic illnesses. 

The calculation was also based on the 

number of hospitalisation cases reported 

during the one year preceding the date of 

interview. The burden of illness, whether 

hospitalised or non-hospitalised, was 

found to be much higher in the HIV 

households. On comparision with 

reference to age groups, in the age group 

of 15-59, which contains most of the HIV 

sample, the burden on HIV households 

was nearly four times that on non-HIV 

households in respect of both nonhospitalised 

and hospitalised illnesses. 

In the HIV households, both the rate of 

illness and the number of hospitalisation 

cases was much less for women than for 

men. The prevalence rate of both nonhospitalised 

and hospitalised illnesses 

calculated stage-wise showed them as 

increasing with the increase in the stage 

of infection. 

The survey gathered details about various 

non-hospitalised illnesses suffered by 

the interviewed PLWHA during the 

month prior to the date of interview. 

These details included the nature of 

illnesses suffered, duration of each illness 

episode, number of days treatment was 

taken, type of treatment taken and the 

expenditure incurred on the treatment 

of each illness episode. Fever was the 

most highly reported illness (33%), 

followed by respiratory infections, loose 

motion, diarrhoea, TB, skin diseases, 

headache, body ache and weakness. 

While six percent of the illness episodes 

went untreated in the case of men, the 

percentage was higher at 10.6 percent 

for women. Also, in the case of men, 

while 90 percent of untreated episodes 

were not considered serious, financial 

constraint did not seem a reason for not 

taking treatment. However, in the case 

of women, while 74 percent of untreated 

episodes were not considered serious, 13 

percent went untreated due to financial 

constraints. 

Treatment was taken from private health 

facilities in nearly 54 percent of the nonhospitalised 

illness episodes. In 35 percent 

of the episodes; government facilities 

were responsible for the treatment and 

in about 10 percent of the episodes, 

treatment was taken from NGOs. A higher 

percentage of women took treatment 

from government hospitals and NGOs 

as compared to men. While the average 

expenditure per episode was the least in 

case of treatment from NGOs (Rs. 30 per 

episode), it was the highest for treatment 

from private doctors/clinics (Rs. 556 per 

episode). 

xvi 


The percentage of PLWHA reporting 

hospitalisation during the period since 

testing positive was almost the same as 

that during the one year period before 

the survey. However, a higher percentage 

of men (66%) reported hospitalisation 

compared to women (38%) during both 

these periods. The percentage of PLWHA 

hospitalised as well as the average number 

of times they were hospitalised increased 

with advanced stage of infection; however, 

no instance of frequent or continuous 

hospitalisation was reported. During 

the last one year reference period; fever, 

loose motion/diarrhoea and tuberculosis 

were the common health problems for 

which PLWHA were hospitalised. While 

nearly 60 percent sought treatment from 

government hospitals, about 25 percent 

went to private health facilities and the 

rest fell back on NGOs and charitable 

trusts. 

T h e a v e r a g e e x p e n d i t u r e p e r 

hospitalisation was the highest for 

treatment from private institutions 

(Rs. 4,119 per hospitalisation case) 

and lowest for treatment from NGOs/ 

charitable trusts (Rs. 363 per case). 

Overall, the average expenditure per 

hospitalisation worked out to Rs. 1,616. 

The expenditure was lesser in the case of 

women as compared to men in spite of the 

source of treatment. In 69 percent of the 

hospitalisation cases, the households had 

to resort to borrowings and liquidation 

of assets to meet the hospitalisation 

expenses. 

Stigma and discrimination 

A high percentage of men (64%) discovered 

their HIV status after prolonged illness 

while 64 percent of the sample women 

discovered it after voluntary testing. 

Those women who went in for voluntary 

testing did so after discovering the HIV 

status of their husbands. The main mode 

of infection was reported as heterosexual 

contact. 

Although a high percentage of the 

PLWHA revealed their positive status 

(69% of men and 88% of women) to 

their spouses immediately, nearly 3.5 

percent of men and 5 percent women 

have not revealed it. Nearly 70 percent of 

men and 56 percent of women have not 

disclosed their status in the community, 

probably fearing discrimination. Around 

20 percent of the households changed 

their residence after one of their family 

members was reported positive. The 

prominent reasons reported for this 

were inability to afford the earlier place 

of residence, search of employment, 

reasons of anonymity, being asked to 

vacate because of the HIV status and for 

seeking medical treatment. 

Though in most of the cases (66% of 

men and 58% of women) the families 

are presently supportive of the PLWHA, 

the Focus Group Discussions reveal 

incidences of discrimination in the 

family, especially in the case of women. 

Many of the widows were living with 

their parents after being thrown out of 

their in-laws’ house. Although a high 

percentage had not disclosed their 

status in the community, some of the 

PLWHA had reported discrimination by 

the community. Reports of neglect and 

isolation, verbal abuse, social boycott and 

their children not being allowed to play 

with others were found. 

77 percent of the currently employed 

PLWHA have not disclosed their status 

to their employer, mostly out of fear of 

losing their jobs. 

Only 17 percent of men and 11 percent 

of women who had sought treatment 

in a health facility after testing HIVpositive 

had reported experiencing 

77 percent of 

the currently 

employed PLWHA 

have not disclosed 

their status to 

their employer, 

mostly out of fear 

of losing their jobs 


xvii

discrimination. This discrimination 

was in the form of refusal of medical 

assistance, being treated badly, and, 

in a small percentage of cases, denial 

of admission. During the FGD, the 

participants narrated many incidents of 

denial of admission, refusal of medical 

treatment, etc. 

Through the sur vey of non-HIV 

households, 559 men and 643 women in 

the age group of 20-60 were interviewed 

to gauge their level of knowledge and 

awareness about HIV and AIDS. Barring 

a few, nearly all of them had heard about 

HIV and AIDS. The sources of information 

were mostly television and radio, as both 

the mediums are popular with the people. 

However, knowledge regarding different 

aspects of the infection was quite low, 

with women being less knowledgeable 

than men. For instance, only 55 percent 

of men and 34 percent of women knew 

the linkage between HIV, AIDS and STI. 

There were also misconceptions about 

HIV and AIDS. The percentage of people 

reporting right use of condoms was also 

quite low. While a higher percentage of 

women knew about usage of condoms to 

avoid pregnancy and for STI protection, 

a higher percentage of men knew about 

its use in HIV and AIDS prevention. It 

was also found that respondents had a 

negative attitude towards PLWHA with 

women discriminating against them to 

a greater extent.

Introduction

2 


Chapter 1 

Introduction 

1.1 Background 

Tamil Nadu, the southernmost state of 

India, nestles in the Indian peninsula 

between the Bay of Bengal in the East, 

the Indian Ocean in the South and the 

Western Ghats and Arabian Sea in the 

West. In the North and West, the state 

adjoins Karnataka, Andhra Pradesh and 

Kerala. Traditionally, the state has been 

divided into five physiographic divisions 

viz. Kurinji (mountainous area), Mullai 

(forest), Palai (arid zone), Marudham 

(fertile region) and Neidhai (coastal 

region). The state has a linguistic and 

cultural history that dates back about 

6,000 years. The present state of Tamil 

Nadu was part of the Madras Presidency 

during the period of British rule in India. 

The state of Madras was formed during 

the reorganisation of states on a linguistic 

basis in 1956. It was renamed Tamil Nadu 

in 1969. Tamil is the official language and 

Chennai, the capital city. The state has 

been divided into 30 districts. 

Some of the important statistical 

data concerning the state are given in 

Appendix-I. In terms of population, 

Tamil Nadu is the seventh largest state 

in India. The population of the state is 

62.11 million, representing 6.04 percent 

of India’s population. The decadal 

growth rate in population has decreased 

considerably from 17.5 percent in 

1971-81 to 11.2 percent in 1991-2001, 

which is half the decadal percentage 

increase for the country as a whole (21.3%) 

in 1991-2000. Except for Kerala, Tamil 

Nadu recorded the lowest population 

growth rate in 1991-2001 among all the 

states and Union Territories of India. 

However, the population density at 478/ 

km 2 is more than that of all India (325/ 

km 2 ). The increase in population density 

as seen in the state from 1971 (Appendix- 

II) indicates a pressure on the land and 

other major resources. Tamil Nadu has 

become one of the most urbanised states 

in the country. The percentage of urban 

population in the state is 44 as against 

27.8 for the country. 

Tamil Nadu is one of India’s more 

economically and industrially developed 

states. Tamil Nadu’s economy has been 

changing rapidly from a predominantly 

agricultural economy into an industrial 

economy. The per capita GDP (2001- 

2002) of the state was Rs. 23,414 as 

against Rs. 22,007 for India as a whole. 

According to the Planning Commission’s 

estimates, the performance of Tamil 

Nadu on poverty reduction has been 

above India’s average in the 1990s. Tamil 

Nadu’s poverty head count has reduced 

from 35.5 percent in 1993-94 to 21.1 

percent in 1999-2000. 

Introduction 3

Tamil Nadu has 

been identified as 

one of the six 

high-HIV 

prevalence states 

The state is also one of the educationally 

advanced states in the country. According 

to the 2001 Census, the literacy rate 

among the population aged seven and 

above was 73 percent compared with 65 

percent for India as a whole. Although 

female literacy has grown more rapidly 

than male literacy during 1971-2001, 

the female literacy rate continues to be 

lower than male literacy levels in the 

state. However, the gap between male 

and female literacy rates in the state is 

smaller than the gap for all of India. 

T h e r e h a s b e e n a t r e m e n d o u s 

improvement in the performance of the 

state measured by some of the health 

indicators. The life expectancy at birth 

rate (2001-2006) is higher than all India 

levels, while the Infant Mortality Rate 

(IMR) (2002) is lower than all India levels. 

The birth rate and death rate (2002) are 

also lesser than all India levels. In fact 

the natural growth rate of 10.7 per 1,000 

of the population was the lowest among 

the major states in India. 

1.2 HIV and AIDS scenario 

in Tamil Nadu 

the Christian Medical College Hospital 

at Vellore, and Mumbai in Maharashtra 

recorded these. This was possible because 

of the HIV Surveillance System initiated 

by the government through the Indian 

Council of Medical Research (ICMR). This 

initiative was taken a few months before 

it was detected, following reports about 

AIDS in the west. 

Tamil Nadu has been identified as one of 

the six high HIV prevalence states (more 

than 1 percent of antenatal mothers and 5 

percent STD patients were detected HIVpositive) 

as per the state wise prevalence 

of HIV in 2005. It can however be seen 

from Table 1.1 given below that the rates 

in ANC clinics have come down to 0.50 

for Tamil Nadu in 2005. 

According to the monthly update on AIDS 

from NACO, out of the total 1,11,608 AIDS 

cases detected in the country till 31st July 

2005, Tamil Nadu accounts for 52,036 

cases, which makes it 46.6 percent of the 

total number. The district-wise break-up 

of the cases for the period upto December 

2004, which accounts for 48,180 of the 

cases is given in Table 1.2 below. 

The first HIV infection and AIDS cases 

in India were detected in Tamil Nadu 

and Maharashtra in 1986. The Madras 

Medical College Hospital at Chennai, 

States 

Table 1.1 

HIV prevalence rates for highprevalence 

states – 2005 

STD 

clinics 

ANC 

clinics 

Andhra Pradesh 22.8 2.0 

Karnataka 13.6 1.25 

Maharashtra 10.4 1.25 

Tamil Nadu 9.2 0.50 

Manipur 12.2 1.25 

Nagaland 3.5 1.63 

The maximum number of AIDS cases have 

been reported from the state capital itself. 

The other districts which have reported 

large number of AIDS cases are Namakkal, 

Salem, Vellore, Dindigul, Trichy etc. 

A heterosexual promiscuous lifestyle is 

the main source of HIV infection as seen 

from Table 1.3 below. For more than 90 

percent of the cases, the heterosexual 

route has been reported as the mode of 

transmission of the virus. 

AIDS awareness and control have 

received special attention in the state 

since the first case of HIV in the country 

was reported here in 1986. A state-level 

AIDS Control Society was formed in 

4 


Table 1.2 

Number of AIDS cases in Tamil Nadu reported upto December 2004 

S. No. Name of district Upto the month 

Male Female Total 

1 Chennai 7,581 2,737 10,318 

2 Thiruvallur 964 397 1,361 

3 Kanchipuram 695 236 931 

4 Vellore 1,616 716 2,332 

5 Thiruvannamalai 913 361 1,274 

6 Vilupuram 1,433 618 2,051 

7 Cuddalore 1,277 540 1,817 

8 Dharmapuri 1,035 397 1,432 

9 Krishnagiri 65 47 112 

10 Salem 1,715 677 2,392 

11 Namakkal 1,801 650 2,451 

12 Erode 1,249 437 1,686 

13 Coimbatore 553 178 731 

14 The Nilgiris 22 12 34 

15 Perambalur 691 338 1,029 

16 Trichy 1,561 580 2,141 

17 Karur 561 251 812 

18 Pudukottai 304 142 446 

19 Thanjavur 681 364 1,045 

20 Thiruvarur 148 50 198 

21 Nagapattinam 151 55 206 

22 Dindigul 1,497 671 2,168 

23 Madurai 1,522 689 2,211 

24 Theni 332 99 431 

25 Sivagangai 172 65 237 

26 Virudhunagar 145 40 185 

27 Ramanathapuram 80 41 121 

28 Thirunelveli 345 105 450 

29 Thoothukudi 294 103 397 

30 Kanyakumari 48 13 61 

31 Addresses not known 274 41 315 

32 Other States 4,295 2,510 6,805 

Total 34,020 14,160 48,180 

* Source: AIDS Cases Surveillance Report, Tamil Nadu State AIDS Control Society 

1994, the first of its kind. The STD/ HIV/ 

AIDS Preventive Measures in the state 

are bolstered by the AIDS Prevention 

and Control Project (APAC) promoted 

by the Government of India, the US 

Agency for International Development 

(USAID) and the Voluntary Health 

Services (VHS), Chennai. The objective 

Introduction 5

Table 1.3 

Source of infection in Tamil Nadu upto 2004 

Heterosexual 

promiscuity 

Number of Percentage 

cases 

45,273 94.6 

Homosexual 94 0.19 

Peri-natal 

1,807 3.78 

transmission 

Blood and blood 

171 0.36 

products 

Injectable drug users 37 0.08 

Others 475 0.99 

Total 47,857 100 

*Source: AIDS Cases Surveillance Report, Tamil Nadu 

State AIDS Control Society 

is to control this problem effectively as 

well as also to raise awareness on HIV 

infection and AIDS among all sections 

of the population. 

A study on community prevalence of STDs 

in the state, undertaken in 1998, placed 

the prevalence of any STD condition in 

Tamil Nadu at 15.8 percent and the overall 

prevalence of HIV in the community at 1.8 

percent, with wide inter-district variation 

in STD/HIV status. The findings suggest 

a higher prevalence of HIV in rural areas 

than in urban areas and also among 

women rather than men. The age group 

at risk for any STD was 30-39 years. 

The major element in AIDS control 

strategy in the state is awareness 

creation and social immunisation. 

The focus has now shifted from mass 

awareness towards inter-personal and 

behavioural change communication. 

High-risk groups are identified and 

targeted, and interventions are made 

by establishing partnerships with 

NGOs. Supply of safe and tested blood 

is being ensured. Condom usage is 

promoted; students of classes IX and X 

are covered for awareness raising and 

immunisation through the School AIDS 

Education Programme, now operative 

in 1420 schools in the state. Voluntary 

Counselling and Testing Centres have 

been established in 11 places to screen 

the HIV status of individuals and to offer 

immunisation services. A surveillance 

system is also in place to assess the trend 

in the spread of HIV infection. 

Although the number of AIDS cases in 

Tamil Nadu is very high, the trend in 

ANC clinics in the state shows that the 

prevalence rate is coming down. From 

a rate of 1 percent in 1998, it has come 

down to 0.50 percent in 2005. Similarly, 

the prevalence rate of HIV at the STD 

clinics has steadily declined since 2000. 

It has come down from 16.8 percent in 

2000 to 8.4 percent in 2004. 

Behavioural change among the core 

transmitter groups is a prerequisite 

for the slowing down of the epidemic. 

The main source of evidence for this 

behavioural change are the findings from 

Table 1.4 

Observed HIV-prevalence levels in Tamil Nadu (1998-2004) 

(in percentages) 

Surveillance sites * 1998 1999 2000 2001 2002 2003 2004 

STD(11) 16.30 10.40 16.80 12.60 14.7 9.20 8.40 

ANC(30) 1.00 1.00 1.00 1.13 0.88 0.75 0.50 

IDU (1) -- -- 26.70 24.56 33.80 63.8 39.90 

MSM (2) -- -- 4.00 2.40 2.40 4.40 6.80 

6 


four rounds of Behaviour Surveillance 

Surveys (BSS) conducted by the USAIDfunded 

AIDS Project and Control (APAC) 

in Tamil Nadu. For example, condom use 

among Commercial Sex Workers (CSWs) 

went up from 56 percent in 1996 to 88 

percent in 1999. Similarly, condom use 

during paid sex among transport workers 

rose from 55 percent in 1996 to 80 percent 

in 1999 (APAC, 2000). 

However, the battle against HIV and AIDS 

has not yet been won in Tamil Nadu; 

through the first signs of a possibility 

of slowing down the epidemic have 

been seen. Given the scarcity of data, 

even this tentative conclusion must be 

viewed with caution. It is yet to be seen 

whether the flattering trend of antenatal 

HIV prevalence continues in the coming 

years. 

1.3 Objectives of the 

present study 

The factors responsible for the highprevalence 

of HIV in the state clearly 

indicate that the problem of HIV and 

AIDS has deep social and economic 

roots. Hence, its impact reaches far 

beyond the health sector with severe 

social and economic consequences. 

It affects the individual, family and 

the community at the micro-level and 

various sectors of the economy at the 

macro-level. However, it has been 

found that the economic impact of the 

HIV epidemic is most significant at the 

family and community level – especially 

among the poor and marginalised 

groups – rather than at national, macro 

levels, particularly in South Asia (UNDP, 

2003). The present study is an attempt 

to assess the impact of HIV and AIDS 

at the level of affected persons and 

their households. It is hoped that this 

study will throw some light on specific 

strategies that are needed to alleviate 

the problems faced by HIV affected 

households in a developing country. 

The objective of this study is to analyse 

the nature and type of socio-economic 

impact of HIV and AIDS on the affected 

individuals and their households in the 

state of Tamil Nadu. The study focuses 

on: 

1) Impact on household income, 

consumption and savings 

2) Impact on change of job/loss of 

employment of the HIV affected 

individuals and of the caregivers 

3) Impact on the education of the 

children of the affected families 

4) Effect on the health status of the 

PLWHA, pattern of morbidity, their 

health-seeking behaviour and 

the expenditure incurred by the 

households on medical treatment of 

opportunistic infections (OIs) 

5) Coping mechanisms adopted by the 

HIV and AIDS affected families and 

the availability of social security 

6) The social impact on the affected 

persons and their families, which 

includes stigma and discrimination 

faced by PLWHA at various settings; 

namely, in the neighbourhood, 

community, and health facilities 

and at the workplace. The study also 

documents the overall experiences 

of the PLWHA with reference to their 

reaction to their HIV status, discovery 

and disclosure of HIV status and 

the attitude of their family towards 

them. 

This report is divided into eight chapters 

and in the following chapter the 

methodology used for conducting the 

household survey and the qualitative 

research methods used for gathering 

information are discussed. Chapter three 

presents background characteristics 

of the sample households and a brief 

profile of the sample PLWHA who were 

The objective of 

this study is to 

analyse the nature 

and type of socioeconomic 

impact 

of HIV and AIDS 

on the affected 

individuals and 

their households 

in the state of 

Tamil Nadu 

Introduction 7

interviewed for the study. A detailed 

analysis of the pattern of income of HIV 

and non-HIV households, impact of HIV 

on income and employment of both the 

HIV infected and the caregivers of PLWHA 

is provided in Chapter four. The level and 

pattern of consumption and savings of 

the households (both HIV and non-HIV) 

is dealt with in detail in Chapter five. The 

presence of an HIV person can affect 

the education of children due to various 

reasons. Chapter six attempts to measure 

the impact of HIV and AIDS on the 

education of children in terms of school 

enrolment, reasons for non-enrolment and 

dropping out, type of school attended and 

school attendance. The HIV households 

face tremendous financial burdens due 

to medical cost of treating the OIs. In 

Chapter seven, the pattern of morbidity 

and the health seeking behaviour of the 

sample PLWHA and the out-of-pocket 

expenditure incurred on treatment of OIs 

are discussed. Chapter eight deals with the 

social stigma attached to HIV and AIDS as 

the major inhibiting factor in controlling 

the spread of the infection. It not only tries 

to capture the magnitude of stigma and 

discrimination faced by PLWHA in various 

social settings, but also attempts to assess 

the knowledge and awareness about the 

infection among the general population 

and attitude of people towards PLWHA. 

Chapter nine gives the major conclusions 

from the results of the survey along with 

policy implications. 

8 


Appendix - I 

Appendix II 

Background information on Tamil Nadu 

Tamil Nadu All India 

Population (2001 census) in million 62.11 1,028.74 

Area (in lakh sq kms.) (2001 census) 1.30 31.66 

Number of districts 30 593 

Percentage of urban population 43.86 27.78 

Growth rate in population (1991–2001) (%) 11.19 21.34 

Literacy rate for population 7+ 

Total 73.49 64.84 

Male 82.0 75.2 

Female 65.0 53.6 

Gross enrolment rate class I-V (2002–03) 

Total 115.50 95.4 

Boys 116.61 97.5 

Girls 114.34 93.1 

Gross enrolment rate class VI-VIII (2002–03) 

Total 99.08 61.0 

Boys 100.21 65.3 

Girls 97.88 56.2 

Life expectancy at birth (2001–2006) 

Male 67.00 63.87 

Female 69.75 66.91 

Infant mortality rate (2003) 

Total 43 60 

Male 44 57 

Female 41 64 

Birth rate (2003) 18.3 24.8 

Death rate (2003) 7.6 8.0 

Total fertility rate (15–49 years) 

NFHS I (1990–1992) 

NFHS II (1996–1998) 

2.48 

2.19 

Percentage of population below poverty line (1999-2000) 21.10 26.10 

Source: Economic survey 2004–05, Government of India 

Handbook of Social Welfare Statistics, NCAER 

National Family Health Survey, IIPS 

SRS Bulletin, Registrar General of India, April 2005 

Population growth rate in Tamil Nadu: 1971-2001 

Census year Population density Population (in million) Decadal growth rate 

1971 317 41.2 

1981 372 48.4 1971–1981~- 17.5% 

1991 429 55.9 1981–1991~- 15.4% 

2001 478 62.1 1991–2001~- 11.2% 

3.4 

2.9 

Introduction 9

10 


Data and Methodology

12 Socio-Economic Impact of HIV and AIDS in Tamil Nadu, India

Chapter 2 


As mentioned in Chapter one the main 

objective of this study is to assess the 

impact of HIV on infected individuals 

and their households. The study is based 

on the household survey conducted by 

NCAER in all the six HIV high-prevalence 

states. In the state of Tamil Nadu, the 

field survey was conducted during the 

period December 2004 to February 

2005. Keeping in mind the objectives of 

the study, NCAER conducted a survey 

of both HIV and non-HIV households. 

The purpose of surveying both HIV and 

non-HIV households (control group) 

was to compare their socio-economic 

characteristics, pattern of household 

expenditure, prevalence of morbidity, 

differences in enrolment and dropout 

rates of children and time use pattern of 

all the household members. In addition, 

qualitative techniques like case studies 

and Focus Group Discussions have also 

been made use of. 

2.1 Sample size 

In each of the high-prevalence states, the 

survey covered roughly 1600 households, 

nearly one-fourth of which have PLWHA. 

Since for a state-level analysis, it was 

thought that a minimum sample of 400 

households would be required, it was 

decided to draw a sample of 400 HIVpositive 

households from each of the 

selected states. This number is large 

enough considering the difficulties 

involved in identifying People Living 

with HIV and AIDS (PLWHA) and their 

households, and more importantly, 

securing their consent for interview. 

The sample was drawn from both rural 

and urban areas of the states; out of 410 

sample HIV households, there were 223 

households belonging to rural areas of 

Tamil Nadu, while 187 households were 

from urban localities. 

2.1.1 Selection of districts 

Based on the Sentinel Surveillance Reports 

of the respective State AIDS Control 

Societies, the HIV high-prevalence 

districts in the state of Tamil Nadu were 

identified and out of these districts, six 

districts were selected for conducting 

the survey. 

Criteria for selection: 

1. In every state, the state capital, which 

also happens to be one of the highprevalence 

districts, was purposively 

selected as one of the sample sites. In 

Tamil Nadu, Chennai was purposively 

selected and although a primarily 

urban sample was drawn from the 

state capital, the survey covered a 

few rural households surrounding the 

capital city too. 

2. While selecting the districts it was 

kept in mind to get as much of a 

geographic spread as possible in 


13

Household 

selections were 

made with the 

help of counsellors 

of the State AIDS 

Control Societies 

who are directly 

in touch with the 

PLWHA 

order to get a representative picture 

of the state. 

3. The selection of the districts also 

depended upon the concentration/ 

distribution of HIV and AIDS cases. 

The reason for selecting the districts 

where the concentration of HIV and 

AIDS cases was more was again to 

make the survey more cost-effective 

and less time-consuming. A related 

concern was that if the district did 

not have enough number of cases, the 

required number of HIV households 

might not be captured. The selection 

of districts was done in consultation 

with the State AIDS Control Societies 

since it was presumed that they would 

be in a position to provide more 

accurate information. 

In Tamil Nadu, in addition to the state 

capital Chennai, the survey covered 

five districts, namely Theni, Namakkal, 

Tiruchirappalli, Erode and Tirunelveli. 

2.1.2 Selection of HIV 

households 

Generally, in sample surveys, villages/ 

urban blocks are first selected and then 

the household selection is made. However, 

in this study this procedure could not be 

followed for a number of reasons. First, the 

selection of sample sites depended upon 

the presence of HIV and AIDS and not on 

the localities. Secondly, it was not possible 

for NCAER to get a list of PLWHA and their 

addresses from which sample households 

could have been drawn. The Voluntary 

Counselling & Testing Centres (VCTC) 

situated at some of the government 

hospitals do maintain a register with 

the addresses of those who have tested 

positive, but the VCTCs could not provide 

the list to NCAER research team due to 

the confidentiality clause in conducting 

the HIV test. Given these constraints 

and keeping in mind the ethical issues 

and the directions of the Institutional 

Review Board at NCAER, it was decided 

that the NCAER research team would not 

get access to the addresses of PLWHA. 

Instead it was decided to make use of 

the counsellors of the State AIDS Control 

Societies who are directly in touch with 

the PLWHA. 

In the state of Tamil Nadu, as suggested 

by the TNSACS, VCTC counsellors were 

used for canvassing questionnaires and 

from each of the selected districts two 

counsellors – one man and one woman 

were selected. Some of the PLWHA 

who had been trained by the State 

AIDS Control Society to do outreach 

work were also used for canvassing 

the questionnaires. All these persons 

were trained by the NCAER team and 

were advised to select the sample from 

a diverse socio-economic profile of 

households. However, in spite of best 

efforts, these persons who acted as field 

investigators could not get access to the 

upper middle class and rich households 

since they drew their sample mainly from 

those who approach the public health 

facilities or NGOs, which mostly cater to 

poor/low-income households. Generally, 

the middle-income/rich PLWHA would 

approach only private health facilities 

for reasons of anonymity and the doctors 

at a reputed private hospital in the 

state corroborated this. In an informal 

discussion with them, it was learnt that 

PLWHA do visit them for the treatment 

of opportunistic infections but due 

to reasons of confidentiality, the field 

investigators could not approach them. 

An attempt was also made to select PLWHA 

from both sexes and to include PLWHA at 

various stages of HIV infection. Further, 

the sample was selected from different 

places with which the field investigators 

were familiar, such as government general 

hospitals, TB hospitals, care and support 

Homes and Drop-In Centres (DIC) run by 


NGOs, Network of Positive People, PPTCT 

and antenatal centres, and the residences 

of people who had tested positive. The 

following table shows the percentage 

distribution of sample PLWHA according 

to the place of interview. 

Nearly one-fourth of the sample 

households were interviewed at the 

VCTC centres. This is understandable 

since the VCTC counsellors themselves 

acted as field investigators of the survey. 

Also, since many of them were also either 

doing outreach services or were keeping 

in touch with their “patients”, the field 

investigators could also get access to their 

residences. Hence another one-fourth 

were interviewed at their residences. 

Individuals who do not live in a household 

set up (e.g. sex workers, persons living in 

shelter homes, hostels etc) were excluded 

from the sample, as the focus of the 

study was to examine the impact of HIV 

and AIDS on the households. In every 

household a maximum of two adult 

PLWHA, mostly husband and wife, were 

interviewed. 

2.1.3 Selection of non-HIV 

households 

For every HIV household surveyed in a 

village/urban block, approximately three 

non-HIV households were interviewed 

and the survey of non-HIV households 

commenced immediately after the survey 

of PLWHA was completed. The ratio of 1:3 

was arrived at as a compromise between 

two conflicting objectives. The first was 

to select a large number of non-HIV 

households with characteristics matching 

each HIV household. This was intended 

to reduce the variance in the non-HIV 

sample and therefore get as close a match 

as possible. The second objective was 

not to overshoot the budget. Keeping in 

mind these two objectives, the ratio of 1:3 

was taken to be the best possible option. 

Since the purpose of surveying non-HIV 

households was to make comparisons 

with the HIV households, the households 

belonging to similar socio-economic 

strata were selected for the study. The 

towns/cities with sample HIV households 

were stratified according to types of 

localities. Four categories– such as slums, 

low-income localities, middle-income 

localities and high-income localities– 

were defined. Similar localities from the 

same city/urban block were selected for 

non-HIV households. Similarly, in the 

case of rural areas, in each district similar 

type/size of villages were identified in the 

same tehsils. 

Table 2.1 

Distribution of sample HIV households by place of interview 

(in Percentage) 

Place of interview Rural Urban Total 

1. VCTC 26.5 25.1 25.9 

2. TB hospital 9.0 2.7 6.1 

3. Care & support home, community care 

10.3 4.8 7.8 

centre and drop in centres 

4. GH 14.8 15.5 15.1 

5. ANC 2.7 1.6 2.2 

6. Network of positive people’s office 9.4 11.8 10.5 

7. NGO office 2.7 7.0 4.6 

8. Residence 24.2 27.8 25.9 

9. Others 0.4 3.7 1.9 

Total 100 100 100 


15

In o rd e r t o s e l e c t t h e n o n - H I V 

households (control group), a listing of 

the households in the locality/village 

was undertaken. In the case of rural 

areas, if it was a relatively small village, 

all the households in the village were 

listed. In the case of a large village, a 

sampling fraction was used and every 

second or third or fourth household was 

listed depending upon the size of the 

village. A maximum of 150 households 

were listed in each selected village. 

Similarly, in urban areas, around 100 

households were listed in each block. 

While selecting the sample non-HIV 

households from the listing sheets, 

over-sampling was done to compensate 

for non-responses. However, in the end 

the survey landed up interviewing 1,203 

non-HIV households i.e. marginally less 

than three times the number of HIV 

households interviewed. 

In the listing sheets, information about 

the socio-economic characteristics 

of the households, mainly income of 

the household and occupational and 

educational status of the head of the 

household, was gathered. At the first 

step the matching was done on the 

basis of the broad income category 

of the household, i.e. the frequency 

distribution was in terms of the income 

groups of the HIV households. At the 

second stage, the occupational group of 

the head of the household was matched 

from within each income category. It was 

difficult to take this to the next stage of 

matching the level of education of the 

head of the household and hence, this 

variable was ignored. However, since 

income and education are generally 

seen to be highly correlated, it was 

assumed that this might not create very 

serious problems. The respondents from 

non-HIV households were adult males 

or females in the age group of 20-60 

years since questions on knowledge 

and awareness about HIV and AIDS 

could be answered only by this group. 

Accordingly, any household that did not 

have a member in this age group was not 

selected for the survey. 

2.1.4 Household questionnaire 

The household survey was conducted 

using a structured interview schedule. 

Both HIV and non-HIV questionnaires 

gathered basic information like socioeconomic 

characteristics of all the 

household members, household income 

and expenditure, prevalence of morbidity, 

Table 2.2 

District-wise distribution of sample HIV households 

Districts 

Number of sample HIV 

households 

Number of sample non-HIV 

households 

Rural Urban Total Rural Urban Total 

1. Chennai 6 95 101 5 299 304 

2. Theni 50 22 72 188 41 229 

3. Namakkl 55 14 69 155 43 198 

4. Tiruhirappalli 28 31 59 75 99 174 

5. Erode 55 13 68 149 37 186 

6. Tirunelveli 29 12 41 78 34 112 

Total no. of households 223 187 410 650 553 1,203 

No. of PLWHA 

interviewed 

261 217 478 - - - 


differences in enrolment and dropout 

rates of children and time use pattern of 

all the household members. In addition to 

this, the interview schedule for non-HIV 

households had a section on knowledge, 

awareness and attitude (including views 

on stigma and discrimination) towards 

HIV and AIDS. 

The questionnaire for the HIV households 

was designed to gather basic information 

about migration history, HIV status of the 

person, stigma and discrimination in the 

family, community, workplace, health 

facilities and educational institutions. 

Details about the economic impact 

on the household like cost of medical 

treatment, coping mechanisms and 

loss of income/employment were also 

collected. 

2.2 Qualitative techniques 

In addition to the household survey, case 

studies and Focus Group Discussions 

(FGDs) were conducted in order to collect 

information that would supplement 

the findings of quantitative survey 

and probe into the how and why. An 

NCAER research team that is well 

t r a i n e d i n q u a l i t a t i v e re s e a rc h 

techniques they themselves conducted 

the case studies and FGDs. 

2.2.1 Case studies 

Case studies were conducted to capture 

in-depth information on PLWHA. Case 

studies are a better tool to capture 

problems like stigma and discrimination 

within the household. Chatting with 

the PLWHA using semi-structured 

in-depth interview schedules makes 

them feel more relaxed and gives 

them the confidence to reveal facts 

more comfortably. For the purpose of 

conducting case studies, unique/typical 

cases of PLWHA were selected with the 

help of field investigators, NGOs and key 

informants of the locality. In the state of 

Tamil Nadu, two such case studies were 

conducted. 

2.2.2 Focus group discussions 

The FGDs were conducted with the 

members of the Network of Positive 

Persons. The main purpose of conducting 

the FGDs with the Network of Positive 

Persons was to understand social and 

economic problems faced by them and 

the legal and other issues taken up by the 

network. The findings from FGDs are of 

help in the analysis and interpretation of 

data collected by the household survey 

and hence complement the survey. The 

NCAER research team conducted Focus 

Group Discussions in Theni district at 

Cambam on 5th January, 2005 at the 

office of the Cumban Network of Positive 

People and there were 21 participants. (A 

summary of the discussion is presented 

in the Appendix) 

2.2.3 Training of field 

investigators 

Both men and women investigators were 

employed to canvass the questionnaires. 

The questionnaires were translated 

into Tamil and those who were fluent in 

the language were selected for conducting 

the survey. The NCAER researchers 

provided training to the field investigators 

and also supervised the survey. The 

investigators were given both classroom 

and field training to enable them to 

administer the questionnaires. Since 

the subject of the study is of a sensitive 

nature, the investigators were trained 

to conduct the interviews keeping 

in mind the ethical issues involved 

and were required to get the verbal 

consent of the respondents prior to 

interviewing them. 

The questionnaire 

for the HIV 

households was 

designed to gather 

basic information 

about migration 

history, HIV 

status of the 

person, stigma 

and discrimination 

in the family, 

community, 

workplace, 

health facilities 

and educational 

institutions 


17


Profile of 

Sample Households and PLWHA

Chapter 3 

Profile of Sample 

Households and PLWHA 

The socio-economic and demographic 

backgrounds of the sample HIV and non- 

HIV households are presented in this 

chapter. It also contains a brief description 

of the sample PLWHA who were selected 

for the study. As mentioned in the previous 

chapter, the sample households were 

spread across the various districts of Tamil 

Nadu such as Chennai, Theni, Namakkal, 

Thiruchirapalli, Erode and Tirunelveli. 

The sample included both urban and 

rural households and the rural sample 

was slightly more in number than the 

urban sample. 

3.1 Background 

characteristics of head of 

sample households 

The distribution of sample households 

revealed that the sample of HIV households 

included 31 percent households whose 

heads belonged to scheduled castes or 

scheduled tribes, this percentage was 

higher at 40 percent (Table 3.1) in the 

case of non-HIV households. The Other 

Backward Classes category formed 60 

percent of the HIV sample, whereas this 

category accounted for 50 percent of 

the non-HIV households. The sample 

of households included under ‘Others’ 

category was nearly the same for both 

HIV and non-HIV households. 

Nearly 79 percent of the household heads 

in both the households were in the age 

group of 20-50 years and only a small 

percentage was above 60 years (Table 3.2). 

About 17 percent of the heads of non-HIV 

households belonged to the 51-60 age 

group. Only 12 percent of the heads of HIV 

households were in this age group and the 

number of households with heads aged 

less than 20 years was negligible. 

Table 3.1 

Distribution of head of sample households by caste 

(in Percentages) 

Caste groups HIV households Non-HIV households 


SC/ST 37.2 23.5 31.0 50.2 27.1 39.6 

OBC 55.2 66.3 60.2 45.9 53.5 49.4 

Others 7.6 10.2 8.8 4.0 19.4 11.1 

Total 100 100 100 100 100 100 

N (Number of 

households) 

223 187 410 650 553 1,203 

Profile of Sample Households and PLWHA 

21

Table 3.2 

Occupation and level of education of heads of the households 


HIV households 

Non-HIV households 


Age (Years) 

Table 3.3 

Distribution of sample households 

by household income categories 


Characteristics HIV households Non-HIV households 


Annual HH income (Rs.) 

1. Upto 20,000 44.8 20.9 33.9 9.5 4.3 7.2 

2. 20,001-30,000 22.9 16 19.8 34.3 21.2 28.3 

3. 30,001-41,000 10.8 15 12.7 19.2 16.8 18.1 

4. 41,001-84,000 19.3 35.3 26.6 30.3 43 36.2 

5. 84,000 & above 2.3 12.8 7.1 6.6 14.7 10.3 

Average HH income (Rs.) 29,019 51,556 39,298 41,586 57,450 48,878 

household heads and 38 percent of the 

non-HIV household heads were wage 

earners. About 17 percent of the heads 

of HIV households and nearly 22 percent 

of non-HIV household heads were salary 

earners. While the distribution according 

to occupational groups was similar 

between both the households, certain 

variations in the category of distribution 

according to income were observed. 

3.1.1 Economic status of the 

sample households 

Although an effort was made to draw 

the sample of non-HIV households to 

match the income distribution levels of 

HIV households, the two did not work 

out to be exactly similar. While nearly 

34 percent of HIV households are from 

the lowest income group of less than Rs. 

20,000 per annum, only about 7 percent of 

non-HIV households belong to this group. 

While 33 percent of HIV households 

are in the income range of Rs. 20,001 to 

Rs. 41,000, the non-HIV households in 

this range account for 46 percent of the 

sample. Consequently, the percentage 

of households with income above Rs. 

41,001 among the non-HIV sample is 47 

percent while it is only 33 percent among 

HIV households. Because of this, it is seen 

that the average household income of HIV 

households is less than that of non-HIV 

households in all three; rural, urban, and 

total samples. The average household 

income has worked out to Rs. 48,878 for 

non-HIV households and Rs. 39,298 for 

HIV households. Thus, it is clear from 

the table that most of the sample HIV 

households belong to low economic and 

educational strata of society. Although 

there is enough evidence to show that it is 

the poor people who are more vulnerable 

to HIV and AIDS (UNDP, 2003), in the 

present sample there are more households 

from the poor and low-income categories 

due to yet another reason. In spite of 

their best efforts, the field investigators 

could not get access to the middle, upper 

middle class and rich households as they 

drew their sample mainly from public 

health facilities and NGOs, which mostly 

cater to poor/low-income households. 

Generally the middle/rich PLWHA would 

approach only private health facilities 

for reasons of anonymity. The doctors 

at a reputed private hospital in Tamil 

Nadu corroborated this observation. In 

an informal discussion with them, it was 

learnt that PLWHA do visit them for the 

treatment of opportunistic infections but 

due to reasons of confidentiality, the field 

investigators could not get access to such 

persons. 

The average 

household income 

of HIV households 

is less than 

that of non-HIV 

households in all 

three; rural, urban, 

and total samples 


23

Only 40 percent of the sample HIV 

households and 56 percent of the non- 

HIV households live in pucca houses; this 

again indicates the poor standard of living 

of these households (Table 3.4). More than 

65 percent of the sample households are 

dependent on public taps/hand pumps 

for drinking water and only 25 percent 

of the sample HIV households and 28 

percent of the non-HIV households have 

their own tap or hand pump. 

Sanitary facility is also an indicator of 

the standard of living of the households. 

Only 39 percent of HIV and 48 percent 

of non-HIV households have toilet 

facilities in their homes and as expected 

this percentage has turned out to be 

much lower for rural households. All the 

houses do not have electricity; 84 percent 

of the sample HIV households and 92 

percent of the non-HIV households 

have this facility. As compared to sample 

HIV households, the percentage of 

households having electricity has 

turned out to be higher for the non- 

HIV households and expectedly higher 

for the urban households as compared 

to the rural households. 

For cooking, a high percentage of 

both HIV (51%) and non-HIV (46%) 

Table 3.4 

Distribution of sample households 

by the availability of basic amenities 

(in Percentage) 



Type of house 

Pucca 27.8 52.9 39.3 45.5 67.6 55.7 

Semi-pucca 51.1 36.4 44.4 46.2 25.5 36.7 

Kutcha 21.1 10.7 16.3 8.3 6.9 7.7 

Drinking water 

Private tap/hand pump code 14.8 37.4 25.1 19.9 37.6 28 

Public tap/hand pump 70 49.7 60.7 78 55.7 67.7 

Tubewell 7.2 2.1 4.9 0.9 0.4 0.7 

Supply tanker 0.5 9.1 4.4 0.6 3.8 2.1 

Well/river/pond 7.6 1.6 4.9 0.6 2.4 1.4 

Any other -- -- -- -- -- -- 

Sanitation facility 

Percentage of household having toilet 16.6 66.3 39.3 24.5 75.8 48.1 

Electricity at home 

Percentage of household having electricity 79.4 90.4 84.4 88.9 96 92.2 

Type of fuel for cooking 

Firewood 70.4 27.3 50.7 68.2 19.2 45.6 

Coal -- -- -- 1.1 0.5 0.8 

Kerosene 12.6 28.9 20 10.9 28.9 19.2 

(LPG) gas 16.6 43.8 29 19.7 51.4 34.3 

Others 0.5 -- 0.2 -- -- -- 

Total 100 100 100 100 100 100 


households use firewood. Liquified 

Petroleum Gas (LPG seems to be the next 

popular mode with 29 percent of HIV 

and 34 percent of non-HIV households 

using it. Kerosene users form a similar 

percentage in both HIV and non-HIV 

households. 

The ownership of assets and other 

consumer durables in the household 

also indicates that the economic status 

of sample households is quite low (Table 

3.5). Although a significant number of 

households own a house, these houses 

could be just huts. In the case of both HIV 

and non-HIV households, as compared 

to urban areas, in the rural areas higher 

percentage of households own houses. A 

higher percentage of non-HIV households 

have their own houses/flats whether 

in rural or urban areas. The percentage 

of households owning agricultural 

land and livestock is marginally higher 

in case of HIV households. Generally, 

the percentage of households having 

consumer durables like fans, bicycles, 

televisions, refrigerators is slightly lower 

for HIV households as compared to non- 

HIV households since HIV households, as 

already seen, belong to a slightly poorer 

section than the non-HIV households in 

the sample. 

Table 3.5 


ownership of assets and other consumer durables 




Owning agricultural land 22.9 6.9 15.6 22.3 1.6 12.8 

Household having livestock 24.7 3.7 15.2 23.1 2 13.4 

Owning house/flat/plot 55.2 31 44.2 85.9 48.6 68.7 

Owning consumer durables 

Fan 65.9 85 74.6 78 96 86.3 

Bicycle 48 52.9 50.2 74 71.1 72.6 

Radio/transistor 41.7 61 50.5 66.6 53 60.4 

Tape recorder 15.2 41.7 27.3 21.9 45.6 32.8 

Television (b/w) 30 35.3 32.4 46.3 36.7 41.9 

Television (colour) 13 35.8 23.4 26.5 51 37.7 

Refrigerator 3.6 17.1 9.8 4 25.7 14 

Telephone/mobile 12.6 41.2 25.6 16 47.2 30.3 

Washing machine 2.2 10.2 5.8 0.9 12.6 6.2 

Computer 1 4.3 2.4 0.3 3.1 1.6 

Two wheelers 13.9 23 18.1 20 33.5 26.2 

Car/jeep etc. 1.4 2.1 1.7 1.2 2.9 2 

Bullock cart -- -- -- 2.2 -- 1.2 

Tractor 1 0.5 0.7 0.5 -- 0.3 

Thrasher 0.5 -- 0.2 0.2 -- 0.1 

Tube-well 0.5 -- 0.2 0.2 0.4 0.3 

N (Number of households) 223 187 410 650 553 1,203 


25

3.2 Profile of sample 

PLWHA 

As expected, most of the sample PLWHA 

is in the age group of 20 to 40 years (Table 

3.6). In fact, the majority of men (56%) 

are in the age group of 30-40 years, while 

the majority of women (60%) are in the 

lower age group of 20-30 years. While more 

than 75 percent of the men are currently 

married, in the case of women this 

percentage is lower at 48 percent. What 

is significant is that while only 7 percent 

of men are separated or are widowers, 

45 percent of women are separated, 

abandoned or widowed. As expected, the 

percentage of unmarried women is less 

than the percentage of unmarried men. 

The level of education of the sample 

PLWHA is also quite low as 19 percent 

of men and 27 percent of women are 

Table 3.6 

Profile of sample PLWHA 


Male Female 

Age 

≤20 7.1 6.7 

20-30 16.8 60 

31-40 56.2 27.1 

>40 19.9 6.3 

Marital status 

Currently married 75.8 47.6 

Separated/divorced/abandoned 3.7 6.7 

Widowed 3.4 38.4 

Unmarried 17.2 7.1 

Education 

Illiterate 19.2 27.4 

Upto primary 18.5 17.3 

Upto middle 26.6 23.1 

High school 21.9 20.4 

Senior secondary 6.1 6.7 

Graduate/diploma 7.7 5.1 

N (Number of households) 297 255 

illiterate. There are very few persons in 

the sample who have studied beyond high 

school level. The percentage of illiteracy is 

higher among women, and generally, at 

every level of education, the percentage 

of women is less than that of men. 

In Table 3.7 the pattern of occupation 

of the sample PLWHA at the time of the 

survey is compared with the occupation 

pattern at the time when these people 

were detected HIV-positive. The purpose 

of this table is to see whether there 

has been any change in the pattern of 

occupation of the sample population 

as a result of their HIV status. While it 

is seen that in case of both HIV-positive 

men and women the percentage under 

any category of current occupation is 

less than the corresponding figure at time 

of detection of their status, the striking 

observation is the one regarding the 

percentage that is currently unemployed. 

While only 1.1 percent of HIV-positive 

men were unemployed at the time of 

detection of their status, the percentage 

has now gone upto 16.7 percent. Similarly, 

in the case of women, it has more than 

doubled, from 2.4 percent to 5.3 percent. 

Further, the percentage of women as 

housewives has increased from 25.8 

percent to the current 27.7 percent. These 

clearly indicate that while there is some 

marginal change in the occupation of 

the PLWHA after discovery of their HIVpositive 

status, loss of employment for 

many seems to be the bigger problem. 

The sample is generally spread over all 

occupations, the highest percentage 

among men being transport workers 

(18.6%). Among women, the salaried 

(16.8%) form the highest percentage. 

While nearly 17 percent of the HIVpositive 

men are currently unemployed, 

nearly 33 percent of the HIV-positive 

women in the sample are not engaged in 

any income earning activity. 


Table 3.7 

Current and the past occupation of the sample PLWHA 

Current occupation 


Occupation at the 

time of detecting 

HIV status 

Male Female Male Female 

Cultivation 5.2 8.6 6.7 9.6 

Agri. wage labour 12.3 12.4 14.4 16.7 

Construction worker 6.7 2.4 7.8 2.4 

Other non-agricultural labour 11.9 13.9 16 14.3 

Salaried 14.9 16.8 15.2 15.3 

Trade/business 7.4 1.4 7.8 2.4 

Artisan/self-employed 6.3 8.6 8.6 8.6 

Transport workers 18.6 -- 22.3 -- 

Income from, pension, rent, interest, 

dividend etc 

-- -- -- -- 

Domestic servant -- 2.9 -- 2.4 

House wife -- 27.7 -- 25.8 

Student -- -- -- -- 

Unemployed 16.7 5.3 1.1 2.4 

Others -- -- -- -- 

Total 100 100 100 100 

N (Number of households) 269 209 269 209 


27

Impact of HIV Status on 

Income and Employment


Chapter 4 

Impact of HIV Status on 

Income and Employment 

4.1 Income and its 

distribution 

Income is the major determinant of 

household welfare. Households derive 

their income from many sources. This 

study defines the occupational group of 

the household according to the source 

of income of the head of the household. 

For example, if the source of income of 

the head of the household is cultivation, 

then in the occupational classification 

that household is considered to be 

“cultivation household”. The occupation 

of the household is closely related to 

the earnings of the household as well 

as the vulnerability of the household to 

exogenous shocks, including any serious 

disease/illness affecting any member of 

the household. 

The distribution of both HIV and non- 

HIV households among the various 

occupational groups is quite similar 

as can be seen from Table 4.1. While 

wage earners account for 44 percent in 

both households, their contribution to 

income is about 32 percent in non-HIV 

households and about 35 percent in HIV 

households. Agriculturalists account 

for about nine percent of households 

and the same percentage of income 

in non-HIV households whereas they 

account for eight percent of households 

but only four percent of income in HIV 

households. The self employed nonagriculturalists 

and salaried form nearly 

38 percent of the non-HIV households 

with their contribution to income being 

higher at 48 percent. This group, while 

forming 39 percent of HIV households, 

accounts for 45 percent of their income. 

Households belonging to the category 

of ‘others’ under non-HIV constitute 

around 9 percent of the total number 

while this figure is much higher at 19 

percent for HIV households. While 

agricultural wage labourers in the rural 

sample and non-agricultural wage 

earners in the urban sample form the 

single highest percentage of households 

among the non-HIV households, nonagricultural 

wage earners account for 

the highest percentage of households 

in both rural and urban samples of HIV 

households. 

An attempt was made to draw the HIV 

and non-HIV sample from similar 

socio-economic backgrounds. In spite 

of this, it can be seen that the average 

income per household has turned out to 

be higher for non-HIV households and 

particularly so in the rural sample. The 

rural sample in HIV households has only 

2.25 percent of the households earning 

an income above Rs. 84,001 while in 

the non-HIV households, this sample 

Impact of HIV Status on Income and Employment in India 

31

Table 4.1 

Distribution of sample households, 

population and income by occupation 



Occupation Rural Urban Total 

HHs Pop Income HHs Pop Income HHs Pop Income 

Cultivation 15.69 17.26 18.56 0.54 0.66 0.64 8.73 9.60 8.87 

Agri. wage labour 26.00 25.42 19.40 2.35 3.03 1.15 15.13 15.09 9.54 

Non-agricultural wage 25.54 23.51 20.26 33.45 32.88 23.85 29.18 27.83 22.20 

Self-employed nonagriculture 

10.15 10.12 10.67 22.42 22.26 21.78 15.79 15.72 16.67 

Salaried 16.62 17.19 22.99 28.21 27.83 38.32 21.95 22.10 31.28 

Others 6.00 6.51 8.11 13.02 13.35 14.27 9.23 9.66 11.44 

Total 100 100 100 100 100 100 100 100 100 


Occupation Rural Urban Total 

HHs Pop Income HHs Pop Income HHs Pop Income 

Cultivation 13.45 12.02 9.48 1.60 1.42 0.96 8.05 7.11 4.38 

Agri. wage labour 23.32 24.91 16.78 4.81 3.83 1.99 14.88 15.13 7.93 

Non-agricultural wage 29.15 27.73 31.95 28.88 28.37 24.23 29.02 28.03 27.33 


8.07 8.22 9.26 17.11 17.02 23.75 12.20 12.30 17.93 

Salaried 9.42 9.20 18.68 25.13 26.24 32.11 16.59 17.11 26.71 

Others 16.59 17.91 13.86 22.46 23.12 16.96 19.27 20.33 15.71 

Total 100 100 100 100 100 100 100 100 100 

is nearly three times the earlier figure, 

at 6.61 percent. However, in the urban 

sample among non-HIV households, 

14.65 percent of the households belong 

to this income group while 12.82 

percent of the HIV households are 

in this group. As expected, the lower 

income groups have a lower share in 

the income and the higher income 

groups have a higher share. The HIV 

households have a higher percentage of 

houses in the lower income groups and 

a lower percentage in the high-income 

categories in comparison with non-HIV 

households, thus accounting for the 

lower average income per household in 

the HIV category. 

The average annual household income 

analysed on the basis of occupations 

(Table 4.3) shows that the agricultural 

wage earners have the least income and the 

salaried have the highest income in both 

HIV and non-HIV categories. The average 

household income of HIV households in 

different occupational groups is less than 

that of the corresponding groups in non- 

HIV households except in the case of self- 


Table 4.2 

Distribution of households and 

their share in income by income categories in the sample 



Annual income 

category 

Rural Urban Total 

HHs Share in HHs Share in HHs Share in 




Upto Rs. 20,000 9.54 3.97 4.34 1.31 7.15 2.53 

20,001-30,000 34.31 20.82 21.16 9.32 28.26 14.61 

30,001-41,000 20.62 17.82 17.18 10.71 19.04 13.98 

41,001-84,000 28.92 39.21 42.68 43.61 35.25 41.59 

84,001-1,30,000 4.92 12.07 10.49 19.92 7.48 16.31 

1,30,001-1,73,000 1.54 5.32 1.63 4.01 1.58 4.61 

Above 1,73,000 0.15 0.80 2.53 11.12 1.25 6.37 

Total 100 100 100 100 100 100 

Average income per 

household 

41,584 57,450 48,878 



category 


HHs Share in HHs Share in HHs Share in 




Upto Rs. 20,000 44.84 20.63 20.86 5.34 33.90 11.48 

20,001-30,000 22.87 19.34 16.04 7.88 19.76 12.48 

30,01-41,000 11.66 14.43 16.58 11.29 13.90 12.55 

41,001-84,000 18.39 35.26 33.69 38.49 25.37 37.19 

84,001-1,30,000 0.90 3.62 9.09 19.13 4.63 12.90 

1,30,001-1,73,000 1.35 6.74 1.60 4.67 1.46 5.50 

Above 1,73,000 0.00 0.00 2.14 13.19 0.98 7.89 

Total 100 100 100 100 100 100 

Average income 

per household 

29,019 51,556 39,298 

employed non-agriculturalists. However, 

when the annual per capita income is 

taken into consideration it is seen that the 

per capita income of non-agriculture wage 

earners is also higher for HIV households 

indicating that HIV households in this 

group are smaller in size as compared to 

non-HIV households. Also, while there is 

a considerable difference in the average 

annual income of HIV and non-HIV 

households, the difference in annual per 

capita income is much less. In fact, the 

per capita income of the urban sample 

in both types of households is nearly the 

same. This clearly suggests that the size 

of the HIV households is smaller than 

the non-HIV households in the sample. 

One of the important determinants of 

variation in the household income is 

the number of earners. Moving up the 


33

income class, it is seen that while in the 

non-HIV households the percentage of 

households with the number of earners 

higher than four increases (Table 4.4), no 

such trend is noticed in HIV households 

where the number of earners is four or 

more than four. A similar trend is noticed 

when the number of earners is three. 

As the number of earners increases, 

the average income per household, as 

well as the per capita income is seen to 

increase upto three earners in the case 

of both HIV and non-HIV households. 

But both these figures decrease in HIV 

as well as non-HIV households when the 

number of earners is four or more than 

Table 4.3 

Average household and per capita annual income 

by occupational categories in the sample 


(in Rupees) 

Occupational 

category 

Average annual household Annual per capita income 



Cultivation 49,175 67,333 49,694 10,927 13,466 11,008 

Agri. wage labour 31,026 27,987 30,809 7,756 5,273 7,526 

Non-agricultural wage 32,994 40,952 37,189 8,763 10,115 9,500 


43,715 55,803 51,604 10,725 13,648 12,635 

Salaried 57,543 78,045 69,657 13,598 19,203 16,855 

Others 56,240 62,962 60,600 12,678 14,912 14,102 

Total 41,584 57,450 48,877 10,165 13,946 11,910 


Occupational 

category 

Average annual household Annual per capita income 



Cultivation 20,438 30,833 21,383 6,256 9,250 6,533 

Agri. wage labour 20,881 21,366 20,953 5,349 7,122 5,557 

Non-agricultural wage 31,809 43,259 37,004 9,148 11,679 10,337 


33,274 71,550 57,771 8,939 19,080 15,446 

Salaried 57,564 65,858 63,296 16,118 16,731 16,554 

Others 24,239 38,931 32,050 6,142 10,031 8,194 

Total 29,019 51,555 39,297 7,940 13,675 10,600 


Table 4.4 

Households by number of earners 

and annual household income in the sample 



Annual household income Percentage of households by number of earners 

1 2 3 4 & >4 Total 

Upto Rs. 20,000 74.42 25.58 0.00 0.00 100 

20,001-30,000 51.76 44.12 4.12 0.00 100 

30,001-41,000 45.41 39.74 12.66 2.18 100 

41,001-84,000 57.08 25.94 12.50 4.48 100 

84,001 and above 44.35 37.90 12.90 4.84 100 

Total 53.28 34.91 9.31 2.49 100 


47,165 46,910 62,653 61,578 48,877 

household 

Per capita income 12,117 11,329 12,946 11,474 11,910 

Average household size 3.9 4.1 4.8 5.4 4.1 

Dependency ratio 4.05 2.07 1.61 1.32 2.58 


Annual household income Percentage of households by number of earners 

1 2 3 4 & >4 Total 

Upto Rs. 20,000 61.15 31.65 5.76 1.44 100 

20,001-30,000 48.15 43.21 4.94 3.70 100 

30,001-41,000 61.40 31.58 7.02 0.00 100 

41,001-84,000 52.88 34.62 8.65 3.85 100 

84,001 and above 41.38 41.38 17.24 0.00 100 

Total 55.12 35.37 7.32 2.20 100 


37,008 40,001 51,808 43,744 39,297 

household 

Per capita income 10,947 10,175 10,869 9,155 10,600 

Average household size 3.4 3.9 4.8 4.8 3.7 

Dependency ratio 3.62 1.97 1.59 1.16 2.42 

four. The reason is that with four or more 

earners, the HIV households do not have 

any household with an income above 

Rs. 84,001, but do in fact have households 

where the income is less than Rs. 30,000. 

Even in the case of non-HIV households, 

the percentage of households having an 

income above Rs. 84,000 is the least in 

households with four or more earning 

members. Because of this, the average 

household income is lesser in this group 

when compared with households with 

three earning members. Taken along with 

household size in this group, the per capita 

income of the HIV households is also less 

than that of households with three earning 

members. 

As the number of earners goes up, 

the average number of persons in 


35

That the impact 

of the epidemic 

is mainly on the 

working members 

of the household 

is seen from the 

fact that the work 

force participation 

rate among 

PLWHA is very 

high 

the household also goes up but the 

“dependency ratio” declines. Here, the 

term dependency ratio implies the ratio 

of total population to the total number 

of earners in a particular household 

category. Therefore, dependency has 

been taken as the number of people 

dependent on income earners. (This is 

different from the normal definition of 

dependency as the ratio of population 

under 15 and over 65 to the ratio of 

population in the age group 15-64.) This 

in a sense, gives the actual dependency 

burden, which is the number of people 

dependent on a single earner, including 

the earning member. It is seen from the 

table that the rise in income more than 

compensates for the rise in household 

size except in the case of households 

having four or more earning members. 

The above paragraphs along with the 

associated tables present the picture 

with respect to the income profile of 

HIV households as well as non-HIV 

households. The above section clearly 

shows that the sample is dominated by 

lower income households, particularly 

in the HIV and AIDS category. Although 

the non-HIV households were selected 

to match the HIV households, these 

households belong to a slightly higher 

income group. 

4.2 Work force participation 

rate among HIV and non-HIV 

households in the sample 

The impact of HIV and AIDS on 

households and the economy is severe 

because it mainly affects people in 

the working age group. One of the 

consequences of this is that children 

and the elderly of the household are 

forced to bear the additional burden of 

looking after the family. In the case of the 

15-60 years age group, the overall work 

force participation rate is almost similar 

though slightly higher in the case of HIV 

households (Table 4.5). This may partly 

be explained in terms of the smaller 

household size of HIV households, which 

is linked to lower fertility rate among 

these households as the HIV-positive 

members avoid having children. That 

the impact of the epidemic is mainly on 

the working members of the household 

is seen from the fact that the work force 

participation rate among PLWHA is very 

high, almost 75 percent. In the 0-14 age 

group, the work force participation rate 

is 6.67 percent in the rural sample of the 

HIV households for HIV-positive children. 

There are no HIV-positive children of this 

age group working in the urban sample 

and therefore the rate is zero. The HIVpositive 

people in the age group of 60+ 

do not belong to the work force. 

The interesting feature is the comparison 

of work force participation rate in the 

case of children (0-14 years) and the 

elderly (60 and above years) across HIV 

households (non-HIV persons) and 

non-HIV households. The work force 

participation rate for these age groups 

in HIV households is higher than similar 

groups in the non-HIV households. This 

gives credence to the general observations 

made in the literature that the epidemic 

puts additional burden on the people in 

these age groups, particularly the elderly, 

to look after the family. However, the 

non-HIV persons in the age group of 

15-60 years in HIV households have lower 

participation rate than the same age 

group among non-HIV households. The 

explanation for this lies in the fact that 

in the sample, the primary PLWHA was 

an adult male member. This implies that 

the non-HIV population in the age group 

of 15-60 years would be dominated by 

women. Since women have a much lower 

participation rate than men, the work 

force participation rate in this age group 

is low. Further, it is likely that a person 


Table 4.5 

Work force participation rate by age group and place of residence (per 100) 

Age 


Non-HIV 

group 

PLWHA 

Non-HIV 

All 

households 

persons 

Rural Urban Rural Urban Rural Urban Rural Urban 

0-14 6.67 -- 1.22 0.47 1.54 0.43 1.12 0.27 

15-60 76.10 71.72 59.60 45.27 68.20 59.77 67.74 48.39 

60 and 

above 

-- -- 46.87 29.63 45.45 28.57 38.00 13.89 

in this age group would be a student and 

in order not to disturb his/her studies, it 

is the parents who come out to join the 

work force. 

4.3 Change of job/loss of 

employment of self and 

caregiver 

Of the 478 HIV-positive people who 

were interviewed, 475 were in the age 

group of 18-60 years, and only their 

interviews have been considered for this 

chapter regarding the change in their job 

profile. Out of these 475,363 reported 

being currently employed. About 43 

said that they had changed their jobs 

after being detected HIV-positive (Table 

4.6). It is important to note that table 4.6 

gives data related only to those people 

who have changed the job after being 

detected positive. Impact on people who 

completely stopped working after testing 

positive has been considered in the 

next section. Out of the 43 persons who 

changed their job, 21 were from urban 

areas. The average annual household 

income of the workers who changed 

their job was almost similar in rural and 

urban areas. Of the 43 who did change 

their jobs, only seven had received any 

benefits from the previous job, the 

average figure of these benefits being 

Rs. 16, 571. The impact on employment at 

this stage of the epidemic in India appears 

to be minuscule. However, no certain 

conclusions can be drawn from this 

since, as has already been mentioned, 

the amount of sampling bias is not 

known. The impact on employment 

and income is likely to be felt only 

at higher stages of the infection. The 

estimated impact is likely to vary with 

the number of such persons/households 

captured in the sample. But, what is of 

greater concern from the viewpoint of 

the welfare of these households is that 

there is no mechanism of support for 

those who do change or lose their jobs. 

The issue is more serious in the case of 

workers who are wage earners and lack 

social security. 

It is of interest to see what the occupational 

and sectoral pattern of employment is for 

PLWHA (before and after test) and non- 

HIV persons (Tables 4.7 & 4.8). The group 

“others” includes students, housewives, 

pensioners etc. There is a much higher 

share of this group in non-HIV persons 

as compared to PLWHA. From table 4.1 

it was seen that the prevalence of HIV is 

higher among working members of the 

HIV households. The distribution across 

occupations in table 4.7 suggests that 

this is true across all occupation groups. 

Change in occupational distribution 

due to HIV and AIDS (age group 18- 

60) is clearly visible for people who are 

unemployed. Before testing, around 

What is of greater 

concern from the 

viewpoint of the 

welfare of these 

households is 

that there is no 

mechanism of 

support for those 

who do change or 

lose their jobs 


37

Table 4.6 

Change in job due to HIV and AIDS 


Number of workers who changed jobs after being 

detected positive 


22 21 43 

Average monthly income of those who changed jobs 2,470 2,652 2,559 

Number that received any benefit 3 4 7 

Average benefit received at the time of leaving the job 1,333 28,000 16,571 

for those who received benefit 

Average number of times people changed jobs after 

being tested positive 

4 6 10 

The impact of 

HIV and AIDS 

on employment 

can influence 

the pattern of 

employment/ 

non-employment 

of other members 

of the household 

as well 

1.47 percent were unemployed but 

after testing around 11.37 percent are 

unemployed. The number of unemployed 

could well have increased in another way. 

If any of the female PLWHA were working 

before the test and had to give up work, it 

would be reflected in the increase in the 

category of ‘others’, and the table shows 

that such a difference exists. 

Similarly, the difference in the sectoral 

pattern of employment is mainly in 

terms of much higher proportion of 

those for whom the sector is “Not 

available” in the case of non-HIV 

households (Table 4.8). Here the term 

“Not Available” refers to all those who 

are in labour force but unemployed, 

as well as students, housewives etc. 

The percentage of HIV “Not available” 

increased after the test. The change in 

jobs was mainly out of agriculture and 

allied services, manufacturing, trade, 

transport, communication into “Not 

available” category due to increase in 

unemployment and a marginal increase 

in health related and other services. Some 

of the PLWHA are currently working in 

NGO sectors providing services to HIV 

infected persons. The decrease in the 

percentage of people in agriculture and 

allied activities from 24.42 percent (before 

test) to 19.58 percent (after test) is clearly 

seen in the decrease in the percentage 

of people in ‘cultivation’ and ‘agriculture 

wage labour’ occupation groups. 

The impact of HIV and AIDS on 

employment does not remain limited to 

only those who are HIV-positive. It can 

influence the pattern of employment/ 

non-employment of other members of 

the household as well. This is particularly 

true of the person who provides care to 

the PLWHA. However, the direction of 

this impact is not clear. The pressure on 

the time of the caregiver can result in 

that person’s withdrawal from the work 

force. On the other hand, loss of income 

due to withdrawal of PLWHA from work 

force or the increased consumption 

expenditure requirements (especially 

medical expenses) can result in greater 

participation of other members of the 

household in the work force. It needs to 

be noted here that not all PLWHA require 

care. It is only at very advanced stages of 

the infection that some form of care is 

required by the PLWHA. In the sample, 

out of the total of 475 PLWHA in the age 

group 18 to 60 years, 123 reported that 

they needed someone to take care of 

them. Some of the PLWHA have more 

than one family member taking care of 

them and hence the number of caregivers 

is 128. Almost 58 percent of the caregivers 

were employed at the time of the survey. 

However there is no report of anyone 


Table 4.7 

Change in occupational distribution due to HIV and AIDS (age group 18-60) 


Occupational category Distribution of PLWHA Distribution of non- 

Before test After test PLWHA (non-HIV 

households) 

Cultivation 8.0 6.74 5.86 

Agri. wage labour 15.58 12.42 11.33 

Non-agricultural wage 34.32 29.26 17.55 

Self-employed non-agriculture 14.10 12.21 9.16 

Salaried 15.16 15.79 12.11 

Unemployed 1.47 11.37 8.92 

Others 11.37 12.21 35.07 

Total 100 100 100 

Number of persons 475 475 3,328 

Table 4.8 

Change in sectoral distribution due to HIV and AIDS (Age group 18-60) 


Occupational category Distribution of PLWHA Distribution of non- 

Before After test PLWHA (non-HIV 

test 

households) 

Agriculture and allied 24.42 19.58 18.18 

Manufacturing & construction 22.31 19.16 19.65 

Trade, transport, comm, hotels & rest 26.95 22.53 8.38 

Health 2.10 2.74 1.17 

Other services 11.37 12.42 8.92 

Not available 12.84 23.58 43.63 

Others 0.00 0.00 0.06 

Total 100 100 100 

Number of persons 475 475 3,328 

who had to give up his/her job in order 

to take care of the HIV patient. While 

these ratios cannot be taken as true 

population parameters, they may be 

taken as indicative of the impact on 

labour supply due to HIV epidemic. 

Further, this impact is likely to grow 

in the future with an increase in HIV 

prevalence and a higher percentage of 

these patients requiring someone to take 

care of them. Even if the prevalence rates 

remain constant, the impact is going 

to be felt as the number of PLWHA in 

advanced stages of infection tends to 

increase. Further, the absolute numbers 

are going to be very high even if the 

proportion seems to be small. 

The distribution across sectors of the 

caregivers that are employed is shown 

in table 4.10. In the sample, a higher 

proportion of caregivers are working as 

wage labourers in both urban and rural 

samples. A lesser number of them are 


39

Table 4.9 

The situation with respect to provision of care to PLWHA 

PLWHA who need care 123 

Number of caregivers 128 

Number of caregivers who are currently employed 74 

Number of caregivers who gave up their job in order to provide care 0 

self employed or salaried. The caregivers 

are likely to face the problem of time 

poverty in HIV households as they try 

to cope with the burden of providing 

care to the PLWHA as well as meeting 

their commitments at their workplace. 

This problem is going to become more 

serious and visible in the coming years 

as the number of persons suffering 

from AIDS rises and hospital facilities 

are put under greater strain due to such 

patients. 

4.4 Loss of income of 

PLWHA and the caregiver 

There are two possible ways in which 

HIV households may lose income: (a) 

the PLWHA may be currently working 

but may have to take leave/be absent 

from work due to ill health; and, (b) the 

PLWHA may drop out of labour force 

as her/his physical condition worsens. 

While these two possible channels of 

impact have been highlighted in the 

Table 4.10 

Occupational distribution of caregiver 

Occupational category 

Employment pattern of caregiver 


Cultivation 0 0 0 

Agriculture wage labour 20 5 25 

Non-agricultural wage 11 9 20 

Self-employed non-agriculture 8 2 10 

Salaried 3 6 9 

Others 9 1 10 

Total 51 23 74 

existing literature on HIV and AIDS, this 

is not all. The caregiver too may suffer 

a similar loss of income. The reason is 

likely to be leave/absence from work 

to look after the PLWHA and, as the 

condition of PLWHA member worsens, 

a complete withdrawal from labour force 

to provide full attention to the latter. In 

this section all these possible channels 

of impact are explored on the basis of 

the sample. It is difficult to project this 

at the level of the state since the sample 

is not proportionate to population and 

hence, weights cannot be assigned to the 

household/person. 

As noted above, 363 persons reported 

being currently employed among the 

475 persons in the age group of 18-60 

years who were interviewed in detail. 

Within this group, 164 i.e. around 45 

percent (Table 4.11) declared that they 

had suffered loss of income in some 

form. This is clearly a large percentage. 

While this may not reflect the true 

population parameter, given the large 

sampling errors that are possible, it 

does indicate that a large percentage 

of HIV households suffer from loss of 

income. It is seen from the table that 

the income lost is 10.53 percent of the 

current household income. The income 

loss in the sample is higher for the rural 

households (14.46%) in comparison with 

urban households (7.97%). However, it is 

difficult to project this figure to predict 

the impact at the level of the state. Even 

to get a crude measure of the impact, the 

share of the income of HIV households in 


Table 4.11 

Loss of income of workers with HIV if currently working by occupational groups 

Number of 

persons who 

suffered loss of 


Average income 

lost due to leave/ 

absence in last 

one year (in Rs) 

Average fringe 

benefits lost 

during last one 

year 

Income lost as 

a percentage of 

current household 

income (in Rs) 

Rural 

Cultivation * 3 39,833 0 89.31 

Agriculture wage labour 28 1,601 0 6.98 

Non-agricultural wage 31 3,739 161 11.88 

Self-employed non-agriculture 13 2,592 77 9.73 

Salaried 12 4,946 750 12.77 

Others 0 0 0 0.00 

Total 87 4,290 172 14.46 

Urban 

Cultivation 0 0 0 0.00 




Salaried 16 2,900 375 5.26 

Others 0 0 0 0.00 

Total 77 4,127 127 7.97 

Rural + Urban 

Cultivation * 3 39,833 0 89.31 




Salaried 28 3,777 536 7.89 

Others 0 0 0 0.00 

Total 164 4,214 151 10.53 

*Loss of income includes amount spent on hired labourers 

the total income of all households would 

be needed. In trying to measure the 

loss in GDP there are further problems 

such as the possibility of substitution of 

PLWHA workers with other workers and 

substitution of labour by capital. Since 

the total number of PLWHA in India as 

per the estimates released by NACO were 

5.134 million (a section would have never 

been employed) in 2004 and there were 

402.5 million workers in 2001 as per the 

2001 Census, scaling up the figure to the 

state or national level would not show a 

very dramatic impact on the economy 

or households. However, it can only be 

inferred at this point of time that as more 

and more PLWHA turn into PLWHA, the 

impact is likely to become more visible. 

In all, 164 PLWHA – 87 from the rural 

sample and 77 from the urban sample 

– have reported loss of income. Most 


41

Most of the loss in 

income has been 

due to income lost 

by leave/absence 

in the last one 

year 

of the loss in income has been due to 

income lost by leave/absence in the last 

one year. Small losses in fringe benefits 

have also been reported as has been 

the extra amount spent by cultivators 

on hired labourers. This income loss is 

spread across all occupational groups. 

The highest number of PLWHA who 

have suffered from losses belong to the 

wage group (105 out of 164). This is to 

be expected since this group would 

lose earnings for each day that they do 

not report to work. The salaried class 

is likely to enjoy some benefits like 

casual/medical/earned leaves that they 

can make use of. Only non-agricultural 

wage labourer and salaried households 

report loss of fringe benefits. This again 

is to be expected since other groups are 

unlikely to have any fringe benefits which 

relate to such things as overtime pay, paid 

leave etc. 

While Table 4.11 is related to loss of 

income for those PLWHA who were still 

working, Table 4.12 deals with the loss of 

income for those who have withdrawn 

themselves from the labour force. While 

some persons are likely to have never 

been employed, the table here relates 

to only those individuals who stopped 

working after being tested positive. It 

is seen that 53 people stopped working 

after being detected HIV-positive. The 

loss of income per person turned out to 

be approximately Rs. 24,095 per annum 

in the sample. None of the households 

reported having spent any extra amount 

on hiring labourers to substitute the 

PLWHA worker. The impact does not 

appear to be much when seen as a 

percent of the total current income 

of the HIV households in the sample. 

If this ratio were taken as the true 

population parameter then the impact 

at the level of the state, given the current 

prevalence rate, would not amount 

to much. In fact, this may be taken as 

the outermost bound of the reduction 

in GDP due to reduced labour supply 

caused by HIV and AIDS, ignoring the 

large possibilities of substitution at 

the level of the state, particularly in a 

labour surplus economy. Although the 

loss per se does not appear to be much 

considering the fact that the samples 

are taken from households belonging to 

low economic strata, the losses are huge 

to the affected families as evidenced by 

income lost as a percentage of current 

household income which has varied 

between 38 percent and 187 percent, 

with the total at 84.2 percent. For some 

household groups it is more than 100 

percent, i.e. the lost income is more 

than the current household income. 

This can result in great misery at the 

household level and can even increase 

the level of poverty. The scale of impact 

is likely to increase in the future as 

the number of households so affected 

would increase with greater number of 

currently working PLWHA withdrawing 

from labour force due to illness. There 

would be a need to supplement the 

income of HIV households, find some 

form of employment for other members 

of the household or even the PLWHA 

so that the hard fought battle against 

poverty is not reversed. 

The loss of income for HIV households is 

not limited to the loss of fringe benefits or 

jobs of the PLWHA. It is accentuated by 

the loss of income of the person providing 

care to the PLWHA. For those who are 

employed, this can be due to reduced 

time spent in the labour market in order 

to look after the PLWHA. Seventy-three 

persons in the sample reported reduction 

in household income due to loss of 

income of the caregiver, the average loss 

per person being approximately Rs. 2,150 

(Table 4.13). As a percentage of the 

caregivers that are currently employed, 

the number of caregivers reporting 


Table 4.12 

Loss of income of workers with HIV 

if currently not working by occupational groups 

Persons 

Average 

income lost 

due to loss 

of job 

Extra amount 

spent 

on hired 

labourers for 

cultivators 

Income lost as 

a percentage 

of current 

household 


Rural 





5 32,400 0 187.02 

Salaried 4 37,200 0 72.94 

Others 0 0 0 0 

Total 32 23,346 0 113.3 

Urban 





3 30,000 0 72.70 

Salaried 5 29,040 0 38.36 


Total 21 25,343 0 60.44 

Rural & urban 





8 31,500 0 119.76 

Salaried 9 32,667 0 50.46 


Total 53 24,095 0 84.2 

loss of income is very high. However, 

as a percentage of total workers in the 

HIV households in the sample, this 

figure is very small. This suggests the 

macro-economic impact of this may not 

amount to much. However, the long-term 

impact may not remain similarly low. For 

those households that did experience 

reduction in the income of the caregiver, 

the proportion of income lost to current 

household income was nearly 7 percent 

in the sample. However, the impact 

has varied across households, from 36 

percent to 0.47 percent. As a percentage 

of the total income of all HIV households 

together, the impact is minuscule. 


43

Occupational 

category 

Table 4.13 

Loss of income of caregiver if currently working by occupational groups 

No. 

HHs 

Average 


lost due 

to leave/ 

absence 

from work 

(in Rs) 


Income 

lost as a 

percentage 


household 


No. 

HHs 

Average 


lost due 

to leave/ 

absence 

from work 


Income 

lost as a 

percentage 


household 


No. 

HHDS 

Average 


lost due 

to leave/ 

absence 

from work 


Income 

lost as a 

percentage 


household 


Cultivation 0 0 0.00 0. 0 0 0 0 0 

Agriculture 20 1,513 8.28 5 7,924 36.41 25 2,795 14.74 

wage labour 

Nonagricultural 

11 5,520 15.03 9 889 2.67 20 3,436 9.77 

wage 

Self-employed 

nonagriculture 

8 562 1.66 2 1 0.00 10 450 1.45 

Salaried 3 333 0.55 6 333 0.47 9 333 0.49 

Others 9 1,444 8.82 0 0 0 9 1,300 7.20 

Total 51 2,146 8.00 22 2,157 5.67 73 2,150 7.09 

It is also possible that the caregiver 

may have to completely withdraw from 

the labour force in order to take care 

of the PLWHA. However, in the present 

sample there were no such cases. Overall, 

it may be surmised that at the current 

stage of the HIV epidemic in the state, 

the main impact on the economy is going 

to come through lower productivity 

or withdrawal from labour force of 

PLWHA. The impact due to reduced time 

spent by caregivers in the labour market 

is very low. However, the household level 

impact, for the specific households that 

experience the twin impacts, is very 

significant. 

In order to predict some economy-wide 

effects of the impact of HIV and AIDS 

the average number of workdays lost per 

PLWHA worker needs to be observed. 

This would provide an indication of the 

amount of loss that would result due 

to the depletion of manpower. Overall, 

the workdays lost for those who had 

to take leave or be absent from work 

numbered around 44 in a year. The 

loss was highest for the agriculture 

wage labour households. It may be 

emphasised that leave/absence also 

depends on the stage of infection of 

the person and the kind of work one is 

engaged in. 

When using these figures to predict 

economy-wide effects, however, one 

has to keep in mind the possibility of 

substitution of PLWHA workers with 

other non-HIV workers. For instance, in 

agricultural households with the PLWHA 

still active, only one household reported 

having spent an extra amount on hired 

labourers. In the other two households, 

other family members substituted for 


the PLWHA whenever he was ill and 

could not attend to work. There were no 

cases where the agriculturalist PLWHA 

had withdrawn from the work force. This 

implies that even at the household level 

the impact may be muted in economic 

terms due to possibilities of substitution. 

But this impact is likely to be felt by 

the household members in terms of 

effort intensity and time-poverty. At the 

sectoral level, the impact is unlikely to 

be felt till the possibilities of substitution 

have been exhausted, which would be the 

case if the epidemic continues to spread 

without any checks and controls. 

In the survey, an attempt was made to 

find the reason for the withdrawal of 

PLWHA from the work force; while 91.4 

percent of the PLWHA had done so due 

to ill health, around 1.7 percent had 

taken voluntary retirement, while the 

remainder had other reasons. This shows 

that the main reason for reduction in 

labour supply in the economy is going 

to be the ill health of the PLWHA workers 

and efforts to keep them healthy would 

reduce the macro-economic impact to 

some extent. 

Impact on the earnings of the PLWHA 

was also one of the issues discussed at the 

FGD held at Cambam. While one male 

participant mentioned that his income 

had reduced due to ill health, another 

had to give up work since he had been 

suffering from various OIs including 

TB. It was found that most of the male 

participants had suffered loss of income 

after they had tested HIV-positive. 

However, there were also four women 

who had not been working before the 

death of their husbands, but had started 

working with the Network and other 

NGOs only after being widowed. 

4.5 Support from employer 

The survey also tried to find out whether 

the employers were providing some 

form of support to the PLWHA workers 

in the form of reimbursement of medical 

expenditure, paid leave, group insurance 

etc. Primarily, it was found that only a 

small percentage of workers had revealed 

their status in the workplace. While 

there were reports of discrimination in 

the case of some PLWHA, there were also 

cases where they were getting benefits 

from the employers. However, most of 

those receiving benefits were employed 

in NGOs working in the field of HIV 

and AIDS. In view of these reasons no 

detailed study was made on this issue. 

The main reason 

for reduction in 

labour supply in 

the economy is 

going to be the 

ill health of the 

PLWHA workers 

and efforts to 

keep them healthy 

would reduce the 

macro-economic 

impact to some 

extent 

Table 4.14 

Average number of work days lost due to leave/absence from work of PLWHA 

Occupation group 

Average number of work days lost due to 

leave/absence in last one year 


Cultivation 56 17 52 

Agriculture wage labour 44 116 58 

Non-agricultural wage 46 39 42 

Self-employed non-agriculture 56 47 51 

Salaried 41 29 33 

Others 0 0 0 

Total 47 41 44 


45

4.6 Observations 

The prevalence of HIV(within HIV 

households) is higher among working 

people than among those who are not in 

the work force, as also seen in terms of the 

work force participation rates calculated 

from the sample. This is a matter of 

concern from the point of view of the 

economic impact of the epidemic on the 

household as well at a more aggregated 

level. For the HIV households it has 

resulted in slightly higher prevalence of 

child labour as compared to non-HIV 

households. Also there is higher work 

force participation rate among the elderly 

in the HIV households. This raises the 

question of old age security as well as the 

education of the children. 

The loss of income for the HIV households 

varies across occupational and income 

groups. Of particular concern is the 

status of wage labourers who do not 

have any social security and therefore, 

are hard hit by any episode of AIDS 

related illness. The main impact is felt 

through the loss of job or leave/absence 

from work of the PLWHA. It may once 

again be emphasised that it is mainly ill 

health that forces most of the PLWHA to 

give up their jobs. The sample consisted 

of PLWHA in all stages of infection 

and only those in the 3rd or 4th stage 

would be too ill to work. Further, some 

households have more than one PLWHA 

in the work force. Hence, as more and 

more people go into the 3rd or 4th stage 

of infection the impact would be more 

pronounced. 

Although the aggregate economic impact 

of the infection may not appear to be 

much, the impact at the household 

level is extremely serious as seen in 

the present sample, which consists of 

households belonging to poor sections 

of the economy. 


Impact on the Level and Pattern of 

Consumption and Savings 

of the Households


Chapter 5 

Impact on the Level and 

Pattern of Consumption and 

Savings of the Households 

5.1 Consumption patterns 

The pattern of expenditure of the sample 

HIV and non-HIV households is presented 

in table 5.1 separately for rural and urban 

areas. The HIV households spend a 

relatively lower proportion of their total 

consumption expenditure on food than 

the non-HIV households both in rural 

and urban areas. However, both in HIV 

and non-HIV samples, the urbanites 

seem to spend less on food than the 

rural households. From the table, it 

appears that this could be in order to 

make up for the high rents that they 

need to pay. The HIV households in the 

sample seem to be spending quite a huge 

proportion of their income, next only to 

food & other non-food, on rent, and this 

is, in fact, much higher than the non-HIV 

households. This could be because, as 

seen in chapter three, when compared 

to HIV households, a higher proportion 

of non-HIV households have their own 

houses. Here again, it is noticed that the 

urban people pay much higher rents 

than the rural ones. On items like fuel & 

light, durables, education of children and 

other non-food items, the proportion of 

expenditure by HIV households is slightly 

Table 5.1 

Share of expenditure on some of the major items 


Item Non-HIV households HIV households 


Cereals 16.32 11.54 13.73 11.91 8.59 10.03 

Pulses 3.00 2.16 2.55 2.09 1.76 1.90 

Other food 30.43 26.91 28.53 31.30 25.91 28.25 

Total food 49.75 40.60 44.81 45.29 36.26 40.19 

Fuel and light 6.51 9.79 8.29 5.94 8.14 7.18 

House rent 0.99 6.66 4.05 3.83 13.37 9.22 

Clothing & footwear 4.24 4.05 4.14 4.53 3.88 4.17 

Durables 1.66 1.99 1.84 1.57 1.32 1.43 

Education of children 4.23 4.20 4.22 3.84 2.70 3.20 

Medical 5.41 2.54 3.86 11.56 6.10 8.48 

Other non-food 27.20 30.16 28.80 23.44 28.23 26.14 

Total 100 100 100 100 100 100 

Impact on the Level and Pattern of Consumption and Savings of the Households 

49

lesser than that of non-HIV households 

both in rural and urban areas. However, 

on medical expenses, the HIV households 

spend a much higher proportion of their 

consumption expenditure in comparison 

with non-HIV households. In all, it appears 

that in order to compensate for the higher 

expenditure that they are forced to incur 

on health related items and on rent, the 

HIV households may be cutting down 

expenditure on all other items including 

very important ones like (i) food which 

is very essential for their health, and (ii) 

education of children in the household 

which is likely to have adverse effects on 

the family’s future income. 

Table 5.2 below gives the average per 

capita per month expenditure on these 

items for the two sets of households. It 

is seen that even in absolute terms the 

HIV households spend less on food and 

education of children, but spend more 

on house rent and medical expenses in 

comparison with non-HIV households. 

The total per capita expenditure on 

these items is very similar between the 

two kinds of households. While the per 

capita expenditure of the rural samples 

in non-HIV (Rs. 817) and HIV (Rs. 807) 

households are very nearly the same, 

this is slightly higher for the urban HIV 

households (Rs. 1,212) in comparison 

with urban non-HIV households (Rs. 

1,123). On the whole, the average per 

capita per month expenditure of the HIV 

households is slightly more than the non- 

HIV households in the sample in spite of 

their per capita income being lesser than 

the non- HIV households. 

Tables 5.3 and 5.4 present the average 

annual household expenditure and 

the per capita expenditure pattern, 

respectively, of the two sets of households 

with reference to occupation groups. 

While in non-HIV households it is seen 

that the total average income is slightly 

higher than the average expenditure, in 

the case of HIV households, the reverse 

is true, that is, the average expenditure is 

more than the average income and this 

is true across all occupational groups 

(in HIV households) except that of self- 

Table 5.2 

Average per capita per month expenditure on some major items 


Item Non-HIV households HIV households 


Cereals 133 129 132 96 104 100 

Pulses 24 24 24 16 21 18 

Other food 249 303 274 253 315 282 

Total food 408 457 431 367 440 401 

Fuel and light 53 110 79 48 98 71 

House rent 8 75 38 31 162 92 

Clothing & footwear 34 45 39 36 47 41 

Durables 13 22 17 12 16 14 

Education of children 34 47 40 31 32 31 

Medical 44 28 37 93 74 84 

Other non-food 223 339 277 189 343 261 

Total 817 1,123 958 807 1,212 995 


Table 5.3 

Average per household consumption expenditure by occupation groups 



Item 

Rural 

Cultivate 

Agri. wage 

labour 

Non agri. 

wage 

Expenditure per household 

Self emp. 

Non 

Salaried Others Total 

Cereals 9,991 5,477 5,311 5,716 7,687 6,183 6,577 

Pulses 1,357 1,151 1,121 1,197 1,287 1,271 1,210 

Other food 12,981 10,237 11,482 13,124 15,020 13,405 12,264 

Total food 24,329 16,864 17,915 20,038 23,994 20,859 20,050 

Fuel and light 2,276 2,060 2,278 3,114 3,778 3,449 2,625 

House rent 82 277 553 327 742 246 397 

Clothing & footwear 1,804 1,420 1,386 1,747 2,371 2,191 1,709 

Durables 762 258 376 1,095 1,252 1,097 668 

Education of children 1,987 512 1,011 2,448 3,730 2,243 11,706 

Medical 1,259 2,227 1,506 1,383 3,926 3,782 2,181 

Other non-food 11,071 7,489 7,657 9,709 21,988 11,401 10,963 

Total 43,571 31,108 32,682 39,860 61,780 45,269 40,300 

Urban 

Cereals 13,840 3,966 5,736 6,603 6,915 6,969 6,426 

Pulses 2,320 812 1,203 1,104 1,224 1,336 1,201 

Other food 20,416 8,838 12,552 14,966 18,073 15,494 14,989 

Total food 36,576 13,616 19,491 22,674 26,213 23,798 22,616 


House rent 0 1,846 2,914 4,048 4,910 3,067 3,710 


Durables 2,000 223 752 1,266 972 2,185 1,110 

Education of children 333 638 1,686 2,473 3,166 2,401 2,341 

Medical 900 1,465 1,913 1,254 1,058 1,207 1,416 

Other non-food 13,285 4,427 8,372 12,579 28,355 23,079 16,801 

Total 62,311 26,214 40,683 51,788 74,587 65,180 55,704 

All 

Cereals 10,101 5,369 5,535 6,295 7,231 6,693 6,508 

Pulses 1,385 1,127 1,164 1,137 1,250 1,313 1,206 

Other food 13,194 10,137 12,046 14,326 16,824 14,760 13,517 

Total food 24,679 16,632 18,746 21,758 25,305 22,766 21,230 

Fuel and light 2,337 2061 3,212 4,701 5,715 5,164 3,926 

House rent 80 389 1,798 2,756 3,205 2,076 1,920 


Durables 797 256 575 1,207 1,087 1,803 871 

Education of children 1,940 521 1,367 2,464 3,396 2,346 1,998 

Medical 1,249 2,173 1,721 1,299 2,231 2,112 1,829 

Other non-food 11,134 7,271 8,034 11,582 25,750 18,976 13,647 

Total 44,107 30,758 36,899 47,645 69,348 58,184 47,381 

(Contd.) 


51

Table 5.3 ...(Contd.) 



Item 

Cultivate 

Agri. 

wage 

labour 

Expenditure per household 

Non agri. Self emp. Salaried Others Total 

wage non 

Rural 

Cereals 4,892 3,614 4,034 4,421 6,129 3,750 4,233 

Pulses 884 747 649 792 813 714 741 

Other food 11,839 9,163 11,370 11,461 17,058 9,325 11,122 

Total food 17,616 13,523 16,053 16,673 23,999 13,789 16,096 


House rent 20 959 1,588 613 2,543 2,299 1,360 


Durables 683 341 626 640 1,219 230 559 

Education of children 877 2,567 821 908 1,438 1,208 1,365 

Medical 2,950 3,784 2,918 3,610 8,168 5,530 4,108 

Other non-food 6,583 5,359 9,099 8,166 15,950 8,324 8,330 

Total 31,928 29,572 35,149 33,848 58,977 35,049 35,538 

Urban 

Cereals 4,040 3,320 3,959 5,384 5,767 4,389 4,724 

Pulses 556 551 843 1,059 1,126 1,004 969 

Other food 11,612 9,187 12,151 17,290 16,227 13,701 14,252 

Total food 16,208 13,057 16,954 23,733 23,120 19,093 19,945 


House rent 800 2,400 6,978 7,819 11,847 3,994 7,356 


Durables 1,750 450 550 1,547 684 369 728 

Education of children 2,000 589 806 1,973 2,246 1,285 1,484 

Medical 1,133 5,060 2,964 3,194 4,488 2,510 3,356 

Other non-food 7,947 8,452 12,789 22,687 19,182 11,561 15,527 

Total 34,058 33,160 46,339 68,324 70,699 44,630 55,009 

All 

Cereals 4,815 3,570 4,000 5,037 5,879 4,090 4,457 

Pulses 855 718 737 963 1,029 868 845 

Other food 11,819 9,166 11,724 15,192 16,483 11,651 12,549 

Total food 17,488 13,454 16,462 21,192 23,392 16,609 17,851 


House rent 91 1,171 4,034 5,225 8,974 3,201 4,094 


Durables 780 357 592 1,220 849 304 636 

Education of children 979 2,275 814 1,590 1,997 1,249 1,419 

Medical 2,784 3,973 2,939 3,343 5,625 3,924 3,765 

Other non-food 6,707 5,815 10,773 17,459 18,184 10,045 11,612 

Total 32,122 30,102 40,227 55,913 67,079 40,143 44,418 


Table 5.4 

Per capita consumption expenditure on various items by occupation groups 



Item 

Rural 

Cultivate 

Agri. wage 

labour 

Non agri. 

wage 

Per capita 

Self emp. 

non 


Cereals 2,220 1,369 1,411 1,402 1,817 1,394 1,608 

Pulses 302 288 298 294 304 287 296 

Other food 2,885 2,559 3,050 3,220 3,550 3,022 2,998 

Total food 5,406 4,216 4,758 4,916 5,670 4,702 4,901 

Fuel and light 506 515 605 764 893 778 642 

House rent 18 69 147 80 175 55 97 

Clothing & footwear 401 355 368 429 560 494 418 

Durables 169 65 100 269 296 247 163 

Education of children 442 128 268 601 881 506 417 

Medical 280 557 400 339 928 853 533 

Other non-food 2,460 1,872 2,034 2,382 5,196 2,570 2,680 

Total 9,683 7,777 8,680 9,780 14,600 10,205 9,852 

Urban 

Cereals 2,768 747 1,417 1,615 1,702 1,651 1,560 

Pulses 464 153 297 270 301 316 292 

Other food 4,083 1,665 3,100 3,660 4,447 3,670 3,639 

Total food 7,315 2,565 4,814 5,545 6,450 5,636 5,490 

Fuel and light 880 391 1,000 1,357 1,736 1,443 1,324 

House rent 0 348 720 990 1,208 726 901 


Durables 400 42 186 310 239 517 270 


Medical 180 276 473 307 260 286 344 

Other non-food 2,657 834 2,068 3076 6,977 5,466 4,079 

Total 12,462 4,939 10,049 12,666 18,353 15,437 13,523 

All 

Cereals 2,238 1,312 1,414 1,541 1,750 1,558 1,586 

Pulses 307 275 297 278 302 306 294 

Other food 2,923 2,476 3,077 3,508 4,071 3,435 3,294 

Total food 5,467 4,063 4,789 5,327 6,123 5,298 5,173 

Fuel and light 518 504 820 1,151 1,383 1,202 957 

House rent 18 95 459 675 775 483 468 


Durables 177 62 147 295 263 420 212 


Medical 277 531 440 318 540 491 446 

Other non-food 2,466 1,776 2,052 2,836 6,231 4,416 3,325 

Total 9,770 7,514 9,426 11,666 16,781 13,540 11,545 

(Contd.) 


53

Table 5.4 ..... (Contd.) 


Item 

Rural 

Cultivate 

Agri. wage 

labour 

Non agri. 

wage 

Per capita 

Self emp. 

non 



Cereals 1,498 926 1,160 1,188 1,716 950 1,158 

Pulses 271 191 187 213 228 181 203 

Other food 3,624 2,347 3,270 3,079 4,776 2,363 3,043 

Total food 5,393 3,464 4,617 4,479 6,720 3,494 4,404 

Fuel and light 543 370 645 518 1,087 549 577 

House rent 6 246 457 165 712 583 372 


Durables 209 87 180 172 341 58 153 


Medical 903 969 839 970 2,287 1,401 1,124 

Other non-food 2,015 1,373 2,617 2,194 4,466 2,109 2,279 

Total 9,774 7,575 10,109 9,093 16,514 8,882 9,724 

Urban 

Cereals 1,212 1,107 1,069 1,436 1,465 1,131 1,253 

Pulses 167 184 228 282 286 259 257 

Other food 3,484 3,062 3,281 4,611 4,122 3,530 3,780 

Total food 4,862 4,352 4,578 6,329 5,874 4,920 5,290 

Fuel and light 726 580 1,026 1,367 1,533 990 1,188 

House rent 240 800 1,884 2,085 3,010 1,029 1,951 


Durables 525 150 148 413 174 95 193 


Medical 340 1,687 800 852 1,140 647 890 

Other non-food 2,384 2,817 3,453 6,050 4,873 2,,979 4,119 

Total 10,217 11,053 12,512 18,220 17,961 11,500 14,591 

All 

Cereals 1,471 947 1,117 1,347 1,538 1,046 1,202 

Pulses 261 190 206 257 269 222 228 

Other food 3,611 2,431 3,275 4,062 4,311 2,979 3,385 

Total food 5,344 3,568 4,598 5,666 6,118 4,246 4,815 

Fuel and light 560 395 824 1,063 1,404 782 860 

House rent 28 311 1,127 1,397 2,347 818 1,104 


Durables 238 95 165 326 222 78 172 


Medical 851 1,054 821 894 1,471 1,003 1,016 

Other non-food 2,049 1,542 3,009 4,668 4,756 2,568 3,132 

Total 9,815 7,983 11,237 14,950 17,544 10,263 11,981 


employed non-agriculturists. Similarly, 

the total average per capita expenditure 

in non-HIV households is slightly lesser 

than total per capita income while in HIV 

households, the per capita expenditure 

is more than the per capita income. 

Once again, it is noticed that this is true 

across different occupational groups 

except in the case of self-employed nonagriculturists. 

Even when analysed on the basis of 

occupational groups, it is generally 

seen that the HIV households spend 

less than their counterparts in non-HIV 

households on food & education of 

their children, but more on house rent 

and medical expenditure. The medical 

expenditure is more than twice that 

of non-HIV households. Within the 

different occupational groups under 

HIV households, the salaried spend the 

highest on medical expenses followed 

surprisingly by the agricultural wage 

labourers and “Others”. However, it 

may be remembered that the medical 

expenses depend not only on whether 

they are being attended to in government 

or private hospitals, but also on the 

number of sick people in a household, the 

number of times medication is required 

and also the seriousness of the illness. 

Expenditure on health is also linked to 

the perception of the illness and salaried 

and self-employed households are likely 

to be better educated and have a higher 

perception of illness. 

In general, expenditure on food is 

seen to vary between 37 percent to 56 

percent in the different occupational 

categories under non-HIV households 

and between 35 percent to 55 percent 

in HIV households (Table 5.5). Among 

different groups, while the salaried spend 

the least on food, the cultivators spend 

the maximum (in both HIV and non-HIV 

households). While in the case of the 

salaried class in non-HIV households, 

the lower proportion of consumption 

expenditure on food is mainly substituted 

by higher spending on other non-food 

expenditure, which relates to social 

events etc; in the case of the salaried 

in HIV households, low expenditure 

on food is substituted by much higher 

expenditure on rent as well as other 

non-food expenditure. Cultivators, selfemployed 

non-agriculturists and the 

salaried are the groups which are seen 

to spend a higher proportion of the total 

spending on education compared to 

other groups, both in non-HIV and HIV 

households, the percentage being lesser 

in HIV households. In the HIV sample, 

the percentage has turned out to be the 

highest for agricultural wage labourers, 

but this could be due to some sampling 

error in case of rural agricultural wage 

labour households selected where one 

single household could be spending a 

very huge amount. The HIV households 

in different groups devote a lower 

percentage of the total expenditure to 

food as compared to corresponding 

groups in the non-HIV households. These 

households seem to be re-allocating 

consumption expenditure to medical 

expenses mainly by decreasing food 

expenditure even though it is very 

important that they take good food to 

keep in good health. 

One of the important determinants of 

consumption expenditure is income. 

In the above tables, it was seen that 

occupation groups which earn less also 

spend less and the pattern of expenditure 

also differs across these groups. Table 5.6 

presents the pattern of expenditure by 

income groups. As was seen in the tables 

on income distribution, the sample is 

very sparse in the upper tail of income 

distribution. Hence, these income groups 

have been combined. The proportion of 

expenditure on food falls with increase in 

Cultivators, 

self-employed 

non-agriculturists 

and the salaried 

are the groups 

which are seen 

to spend a higher 

proportion of the 

total spending 

on education 

compared to other 

groups 


55

Table 5.5 

Distribution of consumption expenditure cross broad groups of 

consumption items by occupation 



Item Cultivate Agri wage 

labour 

Non agri. 

wage 

Self-emp. 

non 


Rural 

Cereals 22.93 17.61 16.25 14.34 12.44 13.66 16.32 

Pulses 3.11 3.70 3.43 3.00 2.08 2.81 3.00 

Other food 29.79 32.91 35.13 32.93 24.31 29.61 30.43 

Total food 55.84 54.21 54.82 50.27 38.84 46.08 49.75 

Fuel and light 5.22 6.62 6.97 7.81 6.11 7.62 6.51 

House rent 0.19 0.89 1.69 0.82 1.20 0.54 0.99 

Clothing & footwear 4.14 4.56 4.24 4.38 3.84 4.84 4.24 

Durables 1.75 0.83 1.15 2.75 2.03 2.42 1.66 

Education of children 4.56 1.65 3.09 6.14 6.04 4.95 4.23 

Medical 2.89 7.16 4.61 3.47 6.35 8.36 5.41 

Other non-food 25.41 24.08 23.43 24.36 35.59 25.19 27.20 

Total 100 100 100 100 100 100 100 

Urban 

Cereals 22.21 15.13 14.10 12.75 9.27 10.69 11.54 

Pulses 3.72 3.10 2.96 2.13 1.64 2.05 2.16 

Other food 32.76 33.71 30.85 28.90 24.23 23.77 26.91 

Total food 58.70 51.94 47.91 43.78 35.14 36.51 40.60 


House rent 0.00 7.04 7.16 7.82 6.58 4.70 6.66 


Durables 3.21 0.85 1.85 2.44 1.30 3.35 1.99 


Medical 1.44 5.59 4.70 2.42 1.42 1.85 2.54 

Other non-food 21.32 16.89 20.58 24.29 38.02 35.41 30.16 

Total 100 100 100 100 100 100 100 

All 

Cereals 22.90 17.46 15.00 13.21 10.43 11.50 13.73 

Pulses 3.14 3.66 3.15 2.39 1.80 2.26 2.55 

Other food 29.91 32.96 32.65 30.07 24.26 25.37 28.53 

Total food 55.95 54.07 50.80 45.67 36.49 39.13 44.81 


House rent 0.18 1.26 4.87 5.78 4.62 3.57 4.05 


Durables 1.81 0.83 1.56 2.53 1.57 3.10 1.84 


Medical 2.83 7.06 4.66 2.73 3.22 3.63 3.86 

Other non-food 25.24 23.64 21.77 24.31 37.13 32.61 28.80 

Total 100 100 100 100 100 100 100 

(Contd.) 


Table 5.5 .... (Contd.) 


Item 

Rural 

Cultivate 

Agri. wage 

labour 

Non agri. 

wage 

Percentages 

Self-emp. 

non 



Cereals 15.32 12.22 11.48 13.06 10.39 10.70 11.91 

Pulses 2.77 2.52 1.85 2.34 1.38 2.04 2.09 

Other food 37.08 30.98 32.35 33.86 28.92 26.61 31.30 

Total food 55.17 45.73 45.67 49.26 40.69 39.34 45.29 


House rent 0.06 3.24 4.52 1.81 4.31 6.56 3.83 


Durables 2.14 1.15 1.78 1.89 2.07 0.66 1.57 


Medical 9.24 12.80 8.30 10.66 13.85 15.78 11.56 

Other non-food 20.62 18.12 25.89 24.13 27.04 23.75 23.44 

Total 100 100 100 100 100 100 100 

Urban 

Cereals 11.86 10.01 8.54 7.88 8.16 9.83 8.59 

Pulses 1.63 1.66 1.82 1.55 1.59 2.25 1.76 

Other food 34.09 27.70 26.22 25.31 22.95 30.70 25.91 

Total food 47.59 39.38 36.59 34.74 32.70 42.78 36.26 


House rent 2.35 7.24 15.06 11.44 16.76 8.95 13.37 


Durables 5.14 1.36 1.19 2.26 0.97 0.83 1.32 


Medical 3.33 15.26 6.40 4.67 6.35 5.62 6.10 

Other non-food 23.33 25.49 27.60 33.20 27.13 25.90 28.23 

Total 100 100 100 100 100 100 100 

All 

Cereals 14.99 11.86 9.94 9.01 8.76 10.19 10.03 

Pulses 2.66 2.38 1.83 1.72 1.53 2.16 1.90 

Other food 36.79 30.45 29.15 27.17 24.57 29.03 28.25 

Total food 54.44 44.70 40.92 37.90 34.87 41.37 40.19 


House rent 0.28 3.89 10.03 9.34 13.38 7.97 9.22 


Durables 2.43 1.19 1.47 2.18 1.27 0.76 1.43 


Medical 8.67 13.20 7.31 5.98 8.39 9.78 8.48 

Other non-food 20.88 19.32 26.78 31.23 27.11 25.02 26.14 

Total 100 100 100 100 100 100 100 


57

Table 5.6 

Distribution of consumption expenditure 

by income groups and items of expenditure 



Item 

Rural 

Upto 

Rs. 20,000 

20,001- 

30,000 

30,001- 

41,000 

41,001- 

84,000 

84,001 

and above 

Cereals 9 12 12 11 7 11 

Pulses 3 2 2 2 1 2 

Other food 25 22 20 20 16 20 

Total food 37 37 35 33 24 33 


House rent 1 1 1 1 0 1 


Durables 1 1 1 1 3 1 


Medical 4 2 3 4 6 4 

Other non-food 13 14 17 17 33 18 

Total 

Total 100 100 100 100 100 100 

Urban 

Cereals 13 10 9 9 6 8 

Pulses 3 2 2 2 1 2 

Other food 21 23 22 20 16 19 

Total food 37 36 33 30 23 29 


House rent 5 4 7 5 4 5 


Durables 0 0 0 1 2 1 


Medical 2 1 1 2 1 2 

Other non-food 9 12 12 18 35 21 

Total 100 100 100 100 100 100 

All 

Cereals 10 12 11 10 6 9 

Pulses 3 2 2 2 1 2 

Other food 24 22 21 20 16 20 

Total food 37 36 34 31 23 31 


House rent 2 2 3 3 3 3 


Durables 0 1 1 1 2 1 


Medical 3 2 3 3 3 3 

Other non-food 12 13 15 17 34 20 

Total 100 100 100 100 100 100 

(Contd.) 


Table 5.6 ...... (Contd.) 



Item 

Rural 

Upto Rs. 

20,000 

20,001- 

30,000 

30,001- 

41,000 

41,001- 

84,000 

84,001 and 

above 

Cereals 9 9 8 8 8 8 

Pulses 2 2 1 1 1 1 

Other food 23 23 19 21 21 22 

Total food 33 33 28 29 30 31 


House rent 2 3 6 2 1 3 


Durables 0 2 1 1 2 1 


Medical 8 8 9 8 6 8 

Other non-food 14 14 16 18 24 16 

Total 100 100 100 100 100 100 

Urban 

Cereals 8 7 7 7 5 6 

Pulses 2 1 2 1 1 1 

Other food 22 23 22 20 15 19 

Total food 32 31 31 28 21 27 


House rent 6 7 9 10 11 10 


Durables 0 1 0 1 1 1 


Medical 7 6 4 3 5 4 

Other non-food 13 16 15 18 30 21 

Total 100 100 100 100 100 100 

All 

Cereals 9 8 7 7 5 7 

Pulses 2 2 2 1 1 1 

Other food 22 23 21 20 16 20 

Total food 33 32 29 28 22 29 


House rent 3 4 7 7 10 7 


Durables 0 1 1 1 1 1 


Medical 8 8 6 5 5 6 

Other non-food 14 15 15 18 29 19 

Total 

Total 100 100 100 100 100 100 


59

While the non-HIV 

households are 

positive savers 

in both rural and 

urban samples, the 

HIV households, on 

the contrary, are 

negative savers 

income and this fall is substantial moving 

from the income group of Rs. 41,000- 

Rs. 84,000 to the income group of Rs. 

84,000 and above. This is true for both 

HIV and non-HIV households. But 

between non-HIV and HIV households, 

the proportion spent on food is lesser 

in HIV households. While non-HIV 

households devote about 3 percent of 

consumption expenditure on medical 

expenditure, this figure is about 6 percent 

in HIV households. 

T h e a v e r a g e h o u s e h o l d a n n u a l 

consumption expenditure and the per 

capita annual consumption expenditure 

item-wise and income group-wise 

for non-HIV and HIV households are 

presented in tables 5.7 and 5.8. It is 

noticed that although on the whole, the 

average expenditure is slightly higher in 

the case of non-HIV households, except 

in the lowest income group; in all the 

other groups the average expenditure is 

higher in the HIV households. However, 

in terms of per capita expenditure, except 

for the lowest income group, it is higher 

in all income groups as well as in the total 

for HIV households in comparison with 

non-HIV households. 

As can be expected, the average household 

consumption expenditure is higher 

for the higher income groups (Table 

5.7). The rise in expenditure is sharper, 

going from income group of Rs. 41,001- 

84,000 to Rs. 84,001 and above. This 

is clearer on looking at the per capita 

expenditure shown in table 5.8. The rise 

in average household expenditure with 

rise in income could be due to both, 

increase in household size as well as 

increase in per capita consumption. As 

already noticed, the three major items 

of expenditure concerning the study 

are expenditure on food & education of 

children, where the HIV households are 

spending less than non-HIV households 

both in terms of average expenditure 

and per capita expenditure, and medical 

expenses, where the HIV households are 

spending more than twice the amount 

spent by non-HIV households in terms 

of both average expenditure and per 

capita expenditure. The fact that HIV 

households are spending less than non- 

HIV households on the education of 

children corroborates the assumption in 

literature that HIV and AIDS would result 

in lower investment on education of 

children (Bell, Devarajan and Gersbach, 

2003). 

5.2 Household savings 

Although, in the present sample, the 

non-HIV households are slightly better 

placed because of their average household 

income being higher than the HIV 

households, the difference in their savings 

shows how badly the HIV households 

are placed (table 5.9). While the non- 

HIV households are positive savers in 

both rural and urban samples, the HIV 

households, on the contrary, are negative 

savers. Of the different kinds of savings 

considered, the non-HIV households 

have a small negative saving only in the 

case of agricultural land. Considering the 

huge expenses that all households seem 

to incur on “Other non-food” items, which 

relates to expenses on marriages and 

suchlike, it is possible that the households 

would have disposed off some assets for 

the purpose. However, in case of HIV 

households, they possess savings only in 

the form of cash/bank deposits and as 

shares and that too much less than similar 

savings of non-HIV households. The fact 

that HIV households are negative savers 

with respect to assets (house/plot) could 

also be the reason for their paying a high 

proportion of their expenditure as rent. 

Further, for the urban sample of the HIV 

households, even savings under cash/ 

bank deposits are negative and they only 


Table 5.7 

Average household annual consumption expenditure by income group 



Item 

Rural 

Upto 

Rs. 20,000 

20,001- 

30,000 

30,001- 

41,000 

41,001- 

84,000 


above 

Cereals 2,903 5,301 6,921 8,551 8,785 6,577 

Pulses 801 1,056 1,296 1,345 1,743 1,210 

Other food 7,809 9,362 11,559 15,775 20,579 12,264 

Total food 11,512 15,719 19,776 25,671 31,107 20,050 

Fuel and light 1,361 1,734 2,561 3,503 5,438 2,625 

House rent 310 420 407 385 433 397 

Clothing & footwear 804 1,153 1,679 2,147 4,077 1,709 

Durables 166 255 319 900 3,602 668 

Education of children 359 793 990 3,166 4,233 1,706 

Medical 1,261 990 1,859 2,760 8,155 2,181 

Other non-food 4,208 5,839 9,476 12,943 43,256 10,963 

Total 19,981 26,901 37,068 51,475 1,00,301 40,300 

Urban 

Cereals 4,651 4,296 4,986 7,279 9,234 6,426 

Pulses 1,133 959 1,020 1,272 1,575 1,201 

Other food 7,576 9,432 11,932 15,971 25,940 14,989 

Total food 13,359 14,687 17,939 24,521 36,749 22,616 


House rent 1,925 1,764 3,625 4,019 6,252 3,710 

Clothing & footwear 1,043 1,121 1,407 2,483 4,577 2,254 

Durables 152 123 239 1,106 3,856 1,110 

Education of children 310 723 1,453 2,636 5,463 2,341 

Medical 710 614 749 2,009 1,839 1,416 

Other non-food 3,450 4,817 6,506 14,421 57,074 16,801 

Total 23,151 26,638 35,979 57,206 1,26,091 55,704 

All 

Cereals 3,391 4,955 6,118 7,843 9,078 6,508 

Pulses 893 1,023 1,182 1,304 1,633 1,206 

Other food 7,744 9,386 11,714 15,884 24,081 13,517 

Total food 12,028 15,364 19,014 25,031 34,792 21,230 


House rent 760 882 1,742 2,407 4,234 1,920 


Durables 162 209 286 1,015 3,768 871 


Medical 1,108 860 1,399 2,342 4,029 1,829 

Other non-food 3,996 5,487 8,244 13,766 52,283 13,647 

Total 20,866 26,811 36,616 54,665 1,17,148 47,381 

Total 


61

Table 5.7 .... (Contd.) 



Item 

Upto 

Rs. 20,000 

20,001- 

30,000 

30,001- 

41,000 

41,001- 

84,000 


above 

Rural 

Cereals 3,006 4,212 4,565 6,329 10,056 4,233 

Pulses 624 750 829 847 1,670 741 

Other food 7,756 11,014 11,753 17,007 28,006 11,122 

Total food 11,386 15,976 17,147 24,183 39,732 16,096 


House rent 644 1,272 3,503 1,873 1,200 1,360 


Durables 126 802 696 998 2,420 559 

Education of children 549 560 2,700 3,563 940 1,365 

Medical 2,653 4,082 5,450 6,373 7,920 4,108 

Other non-food 4,911 6,771 9,781 14,905 31,137 8,330 

Total 22,858 32,702 43,722 57,862 92,445 35,538 

Urban 

Cereals 2,244 3,412 3,933 5,760 8,700 4,724 

Pulses 576 722 972 1,124 1,504 969 

Other food 5,961 11,012 12,082 17,428 26,240 14,252 

Total food 8,782 15,146 16,986 24,311 36,443 19,945 


House rent 1,769 3,332 4,858 9,076 20,175 7,356 


Durables 128 281 189 979 2,298 728 


Medical 1,864 2,937 1,972 2,977 9,088 3,356 

Other non-food 3,531 7,725 8,285 16,035 52,792 15,527 

Total 18,566 33,795 38,695 63,352 1,39,916 55,009 

All 

Cereals 2792 3,916 4221 5,985 8,933 4,457 

Pulses 611 740 907 1,014 1,532 845 

Other food 7,252 11,013 11,932 17,262 26,544 12,549 

Total food 1,655 15,669 17,060 24,261 37,010 17,851 


House rent 960 2,035 4,240 6,237 16,903 4,094 


Durables 126 609 420 987 2,319 636 


Medical 2,432 3,658 3,558 4,316 8,886 3,765 

Other non-food 4,524 7,124 8,968 15,590 49,058 11,612 

Total 12,654 33,106 40,988 61,188 1,31,731 44,418 

Total 


Table 5.8 

Per capita item-wise annual consumption expenditure by income group 



Item 

Upto 

Rs. 20,000 

20,001- 

30,000 

30,001- 

41,000 

41,001- 

84,000 

84,001- 

1,30,000 

Rural 

Cereals 887 1,433 1,588 1,896 1,898 1,608 

Pulses 245 285 297 298 377 296 

Other food 2,385 2,530 2,652 3,497 4,447 2,998 

Total food 3,516 4,249 4,538 5,691 6,722 4,901 

Fuel and light 416 469 588 777 1,175 642 

House rent 95 113 93 85 93 97 


Durables 51 69 73 200 778 163 


Medical 385 268 427 612 1,762 533 

Other non-food 1,285 1,578 2,174 2,870 9,347 2,680 

Total 6,103 7,272 8,505 11,412 21,673 9,852 

Number of persons 203 825 584 848 199 2,659 

Urban 

Cereals 1,313 1,135 1,287 1,679 2,083 1,560 

Pulses 320 253 263 293 355 292 

Other food 2,139 2,491 3,080 3,684 5,853 3,639 

Total food 3,772 3,879 4,631 5,657 8,292 5,490 

Fuel and light 621 737 1,048 1,387 2,320 1,324 

House rent 544 466 936 927 1,411 901 

Clothing & footwear 295 296 363 573 1,033 547 

Durables 43 32 62 255 870 270 

Education of children 88 191 375 608 1,233 568 

Medical 201 162 193 463 415 344 

Other non-food 974 1,272 1,680 3,327 12,878 4,079 

Total 6,537 7,035 9,288 13,197 28,450 13,523 

Number of persons 85 443 368 1,023 359 2,278 

All 

Cereals 1,012 1,329 1,472 1,777 2,017 1,586 

Pulses 267 274 284 296 363 294 

Other food 2,312 2,517 2,818 3,600 5,351 3,294 

Total food 3,592 4,120 4,574 5,672 7,732 5,173 

Fuel and light 476 562 766 1,110 1,911 957 

House rent 227 237 419 546 941 468 


Durables 48 56 69 230 837 212 

Education of children 103 206 284 651 1,119 487 

Medical 331 231 336 531 895 446 

Other non-food 1,193 1,471 1,983 3,120 11,618 3,325 

Total 6,231 7,189 8,808 12,388 26,033 11,545 

Number of persons 288 1,268 952 1,871 558 4,937 

Total 

(Contd.) 


63

Table 5.8. .... (Contd.) 



Item 

Rural 

Upto Rs. 

20,000 

20,001- 

30,000 

30,001- 

41,000 

41,001- 

84,000 

84,001- 

1,30,000 

Cereals 844 1,214 1,224 1,573 2,514 1,158 

Pulses 175 216 222 210 418 203 

Other food 2,179 3,174 3,150 4,226 7,001 3,043 

Total food 3,198 4,603 4,596 6,009 9,933 4,404 

Fuel and light 370 531 699 867 1,689 577 

House rent 181 366 939 465 300 372 


Durables 35 231 187 248 605 153 


Medical 745 1,176 1,461 1,584 1,980 1,124 

Other non-food 1,380 1,951 2,622 3,704 7,784 2,279 

Total 6,421 9,423 11,719 14,378 23,111 9,724 

Number of persons 356 177 97 165 20 815 

Urban 

Cereals 658 984 1,016 1,469 2,067 1,253 

Pulses 169 208 251 287 357 257 

Other food 1,748 3,176 3,121 4,445 6,235 3,780 

Total food 2,575 4,369 4,388 6,201 8,660 5,290 

Fuel and light 365 722 995 1,360 2,556 1,188 

House rent 519 961 1,255 2,315 4,794 1,951 


Durables 38 81 49 250 546 193 


Medical 546 847 509 759 2,159 890 

Other non-food 1,035 2,228 2,140 4,090 12,545 4,119 

Total 5,444 9,748 9,996 16,159 33,247 14,591 

Number of persons 133 104 120 247 101 705 

All 

Cereals 794 1,129 1,109 1,511 2,141 1,202 

Pulses 174 213 238 256 367 228 

Other food 2,061 3,175 3,134 4,357 6,362 3,385 

Total food 3,029 4,517 4,481 6,124 8,870 4,815 

Fuel and light 369 602 862 1,163 2,413 860 

House rent 273 587 1,114 1,574 4,051 1,104 


Durables 36 176 110 249 556 172 


Medical 691 1,054 935 1,089 2,130 1,016 

Other non-food 1,286 2,054 2,356 3,935 11,758 3,132 

Total 6,155 9,543 10,766 15,446 31,572 11,981 

Number of persons 489 281 217 412 121 1,520 

Total 


Table 5.9 

Average household savings by place of residence 





Cash/bank deposit 1,116.62 2,308.18 1,664.36 1,004.93 -279.14 419.27 

Jewellery 1,147.06 1,204.48 1,173.45 -1,639.24 -482.89 -1,111.83 

Agricultural land -236.92 113.92 -75.64 -681.61 -251.34 -485.37 

Assets (house/plot) 303.08 86.62 203.57 -250.22 -82.89 -173.90 

Financial (shares etc) 1,041.47 1,742.34 1,363.65 419.06 92.51 270.12 

Total 3,371.30 5,455.54 4,329.39 -1,147.09 -1,003.74 -1,081.71 

have a very small positive saving under 

financial assets, that is, shares etc. The fact 

that most of the positive savings of HIV 

households are in the form of cash/bank 

deposits indicates that they are concerned 

about the expenditure they might be 

called on to incur at any time. This may 

be a reason for shifting from fixed assets 

into more liquid assets. 

This movement away from fixed assets 

to relatively liquid assets has important 

long-term implications for the household 

as it implies a loss of wealth and hence 

lower capacity to deal with exogenous 

shocks in the future. 

The percentage of households that have 

negative savings is only about 3.3 percent 

in case of non-HIV households, whereas 

it is very high at 34 percent in the case of 

HIV households (Table 5.10). In keeping 

with this, the share of negative savers 

in income is 3.49 percent in non-HIV 

households while it is nearly 30 percent in 

HIV households. While about 53 percent 

of the non-HIV households are zero 

savers, this percentage in HIV households 

is about 45 percent. Because of this, 

while 43 percent of non-HIV households 

are positive savers, only 21 percent 

are positive savers in HIV households. 

No urban-rural divide is seen either in 

non-HIV households or HIV households 

among the different categories of savers. 

The difference in the saving pattern of 

HIV households and non-households 

shows that the long-term consequences 

of HIV and AIDS on total and household 

savings can be disastrous. The impact on 

savings at macro-level may yet become 

visible in the Indian scenario, given the 

fact that the proportion of households 

affected by HIV is still quite low although 

in absolute terms the number is very 

high. However, if the epidemic grows at 

the same alarming rate, as has been the 

case in many African countries, then the 

impact on savings would become visible 

even at the macro level. While it is not 

possible to assess from this survey, with 

any reasonable degree of accuracy, what 

the impact of the epidemic is on savings, 

at present, or what it would be in the 

future, the indications are that the impact 

on savings would be very significant. 

The main determinant of savings is the 

income of the household. All the income 

classes in the non-HIV households have 

a positive rate of savings although the 

rate is very small. The rate of savings 

has also increased with the increase in 

income. In the HIV households, the three 

lower classes of income have negative 

rates of savings. While in the lowest class 

The movement 

away from fixed 

assets to relatively 

liquid assets has 

important longterm 

implications 

for the household 


65

Table 5.10 

Distribution of savers and non-savers 




percent share in 

percent share in 

Household Income Household Income 

All 

Negative savers 3.33 3.49 33.66 29.98 

Zero savers 53.53 43.01 45.37 35.55 

Positive savers 43.14 53.5 20.98 34.47 

Total 100 100 100 100 

Rural 


Zero savers 55.38 44.2 43.5 34.06 


Total 100 100 100 100 

Urban 


Zero savers 51.36 42 47.59 36.56 


Total 100 100 100 100 

of income upto Rs. 20,000 the rate is 

-26.80, it is -6.83 in the income group of 

Rs. 30,001-41,000. In the income group 

of Rs. 41,001-Rs. 84,000 and Rs. 84,000 

and above, the rate of savings is positive 

for HIV households as well. It is however, 

lesser than the corresponding rates for 

the non-HIV households. Even in HIV 

households, the rate of savings has 

increased with the increase in income. 

On the whole, while non-HIV households 

have a total rate of saving of 8.86 percent, 

HIV households have a rate of -2.75 

percent, and in every income class, the 

rate of savings of HIV households is less 

than that of the corresponding figure in 

non-HIV households. Although the non- 

HIV households in the sample are better 

off economically than the HIV households, 

this huge difference in savings can be 

explained only on the basis of the burden 

of diseases on HIV households. 

5.3 Coping mechanism 

An important question for the HIV 

households is the method by which 

they can cope with the additional 

financial burden imposed on them 

because of the member/members of 

the household turning out to be HIVpositive. 

One method of coping with the 

financial burden/loss of income owing 

to the infection could be liquidation 

of assets or borrowings. In the case 

of HIV households, this question was 

specifically put to them; they were asked 

whether they had to borrow or liquidate 

any assets in order to cope with financial 

burden/loss of income after the family 

members tested positive. It needs to be 

noted that this is not to be compared to 

the change in savings presented above. 

This question relates to liquidation of 

assets/borrowings by HIV households 


Table 5.11 

Average household and per capita savings by level of income 



Annual income category Average household savings Per capita savings Rate of 

Rural Urban Total Rural Urban Total savings 

Upto Rs. 20,000 -17 0 -10 -5 0 -3 0.49 

20,001-30,000 87 177 130 20 42 30 1.65 

30,001-41,000 1,865 1,002 1,352 427 228 308 3.84 

41,001-84,000 7,835 2,580 3,879 1,343 520 749 7.86 

84,001 & above 20,472 28,381 27,441 2,996 5,052 4,762 17.58 

Total 1,772 4,467 3,325 402 974 737 8.86 



Annual income category Average household savings Per capita savings Rate of 

savings 


Upto Rs. 20,000 -2,336 -6,167 -3,995 -739 -1,750 -1,203 -26.80 

20,001-30,000 -551 -2,867 -1,553 -142 -860 -426 -12.09 

30,001-41,000 569 0 277 141 0 71 -6.83 

41,001-84,000 2,948 4,726 4,133 775 1,131 1020 0.75 

84,001 & above 45,000 61,423 57,317 11,250 14,742 13,895 9.17 

Total 1,645 6,536 4,225 445 1,722 1,127 -2.75 

since the time a person was first detected 

positive and is not linked to tables on 

income, consumption, savings and 

borrowings, which relate to the last one 

year only. Also, a comparison with non- 

HIV households is by definition ruled 

out here. 

The response of the HIV households in 

the survey to the question of coping has 

been summarised in table 5.12. More 

than half the households had either 

borrowed or liquidated assets for this 

purpose, the average amount generated 

being Rs. 27,588. The percentage of such 


category 

Table 5.12 

Liquidation of assets or borrowings to cope with financial burden of HIV and AIDS after 

being tested positive 

Percentage of HH that 

borrowed or liquidated 

assets 

Percent share in liquidation of 

assets or borrowings 


Average borrowing or 

liquidation of assets per 

household (Rs.) 

Upto Rs. 20,000 58.27 39.14 14.12 27.32 20,469 

20,001-30,000 58.02 33.45 13.09 23.83 30,770 

30,001-41,000 52.63 19.12 11.88 15.7 31,758 

41,001-84,000 49.04 7.97 47 26.42 31,437 

84,001 & above 37.93 0.31 13.91 6.74 37,182 

Total 53.66 100 100 100 27,588 


67

households is, however, the highest for 

the lowest income group (58.27%), going 

down with the increase in the level of 

income of the households. The average 

amount borrowed or generated through 

liquidation of assets is highest for the 

highest income group. Considering 

that the percentage of households that 

borrow/liquidate assets declines with 

the rise in income, the average amount 

generated by higher income groups 

is likely to be linked to greater credit 

worthiness and better asset position of 

these households. 

While in the first three income categories, 

the borrowings or liquidation of assets 

are higher in the rural sample than in 

the urban, in the two higher categories of 

income, the borrowings or liquidation of 

assets has been higher in urban categories. 

From these tables, it is very difficult to 

make out whether asset holdings have 

any bearing on the amount borrowed or 

in their liquidation. In order to confirm 

the possibility of linkage between asset 

status and amount generated through 

borrowing or liquidation of assets, 

the latter is looked at by occupational 

grouping of the households (Table 5.13). 

Here, however, no trend is seen either 

in the percentage of households that 

have borrowed or liquidated assets or 

the amounts so generated. Although 

the amount generated by the nonagricultural 

wage earners is the least, 

agriculture wage labourers seemed to 

have raised as much as cultivators or 

even more than the salaried. Hence, it 

cannot be inferred straight away that 

possession of assets may have a bearing 

on the amount raised. 

Another aspect that needs to be looked 

into is the difference between HIV and 

non-HIV households, in terms of their 

credit needs. The borrowings of non-HIV 

households as well as HIV households 

in the last one year with reference to 

levels of income is presented in Table 

5.14 below. The average borrowings per 

household presented here are only for 

those households that borrowed and 

not for all households. The borrowing 

per household is seen to go up with the 

income of the household in both non- 

HIV households and HIV households. 

However, while only 28 percent of non- 

HIV households have borrowed during 

the last one year, 59 percent of HIV 

households have resorted to borrowing. 

In the non-HIV households, the percent 

Table 5.13 

Liquidation of assets or borrowings to cope with financial burden of HIV and AIDS 

after being tested positive by occupational classes 

Annual income category 

Percentage of HH 

that borrowed or 

liquidated assets 

Percent share in liquidation of 

assets or borrowings 


Average borrowing or 

liquidation of assets per 

household (Rs.) 

Cultivation 57.58 17.04 1.39 9.65 30,816 

Agri. wage labour 55.74 26.17 6.52 16.88 30,132 

Non-agricultural wage 56.30 20.62 11.93 16.51 14,959 


44.00 11.00 10.86 10.93 30,159 

Salaried 45.59 6.78 21.91 13.93 27,274 

Others 59.49 18.39 47.39 32.10 41,447 

Total 53.66 100 100 100 27,588 


of households that have borrowed has 

decreased as the income level has gone 

up; from about 55 percent in the income 

range of less than Rs. 20,000 to about 

14 percent in the income range of Rs. 

84,001 and above. However, in the HIV 

households, while the percentage is more 

than 60 percent for the first three income 

groups, it has decreased only by a small 

percentage in the next two higher income 

groups. The average borrowing per 

household is higher for HIV households 

in the first three income groups whereas 

it is higher in non-HIV households in the 

last two higher income groups. On the 

whole, while the average borrowing per 

household of those who have borrowed 

in the last one year is Rs. 8,749 in the case 

of non-HIV households, it is higher, at Rs. 

9,811, for HIV households. 

5.4 Poverty 

The direct impact of HIV on poverty and 

inequality has not been demonstrated 

empirically at the national or the state 

level for any country (UNDP, 2003). 

While this is an important issue, since 

purposive sampling was depended upon, 

this measure of poverty will be different 

from the true population parameter. The 

head count ratio has been estimated 

from the sample data in order to see the 

difference between non-HIV and HIV 

households in whether HIV and AIDS 

has differential impact on poor and 

non-poor. One important factor was 

defining the poverty line. The poverty 

line of 1999-2000 obtained from Planning 

Commission for Rural and Urban areas 

has been updated by multiplying the 

Table 5.14 

Borrowing in last one year 


Annual income category Percentage of HH that Percent share in borrowings Average borrowing per 

borrowed 

Rural Urban Total household (Rs.)* 

Upto Rs. 20,000 54.65 10.09 12.27 10.93 6,732 

20,001-30,000 38.24 26.74 20.76 24.44 5,445 

30,001-41,000 31 23.24 11.64 18.78 7,661 

41,001-84,000 15.57 19.69 35.52 25.77 11,308 

84,001and above 13.71 20.24 19.81 20.08 34,198 

Total 27.51 100 100 100 8,749 



Percentage of HH Percent share in borrowings Average borrowing per 

category 

that borrowed Rural Urban Total household (Rs.)* 

Upto Rs. 20,000 64.75 40.59 14.21 31.18 8,226.11 

20,001-30,000 65.43 25.34 15.89 21.97 9,843.4 

30,001-41,000 61.4 14.66 17.25 15.58 10,571.43 

41,001-84,000 50 17.97 32.90 23.29 10,634.62 

84,001 and above 41.38 1.44 19.75 7.97 15,766.67 

Total 59.02 100 100 100 9,810.95 

Note:* Figures are only for those households that borrowed. Also, lendings by households have been ignored, so these are not net 

borrowings. 


69

growth of CPI in 2004-05 over 1999-2000 

of industrial workers in the case of urban 

poverty line & agricultural labourers 

in the case of rural poverty line. The 

updated poverty lines were Rs. 363.96 for 

rural areas, Rs. 551.72 for urban areas and 

Rs. 416.15 as the combined poverty line. 

Table 5.15 presents the estimates in 

terms of income poverty. The head count 

ratio for HIV households (30.07) is much 

more than that for non-HIV households 

(9.82). The poor households have a 

bigger household size than the nonpoor. 

In the present sample the non- 

HIV households have a bigger family 

size as compared to HIV households. 

The reason for smaller household size 

of HIV households could be many. It 

could be related to infected members 

of the household deliberately avoiding 

progeny, since they are often advised to 

do so by the counsellors. It could also 

be related to deaths in the family. 

Table 5.15 

Distribution of households by income poverty in the sample 


Percent share in Average household No. of Rate of Family 

Households Income Population Saving Income households saving size 

BPL 8.65 4.11 9.82 189.44 2,3264 104 0.81 4.66 

APL 91.35 95.89 90.18 4,721.16 5,1301 1,099 9.20 4.05 

Total 100 100 100 4,329.4 48,878 1,203 8.86 4.10 

Rural 

BPL 2.92 1.29 3.50 151.16 18,335 19 0.82 4.89 

APL 97.08 98.71 96.50 3,468.27 42,284 631 8.20 4.07 

Total 100 100 100 3,371.3 41,584 650 8.11 4.09 

Urban 

BPL 15.37 6.52 17.21 198 24,366 85 0.81 4.61 

APL 84.63 93.48 82.79 6,410.44 63,459 468 10.10 4.03 

Total 100 100 100 5,455.54 57,450 553 9.50 4.12 


Percent share in Average household No. of Rate of Family 

Households Income Population Saving Income households saving size 

BPL 26.10 9.94 30.07 -4,296.26 14,972 107 -28.70 4.27 

APL 73.90 90.06 69.93 53.47 47,888 303 0.11 3.51 

Total 100 100 100 -1,081.71 39,298 410 -2.75 3.71 

Rural 

BPL 26.46 12.12 27.94 -5,923.73 13,291 59 -44.57 4.41 

APL 73.54 87.88 72.06 571.34 34,677 164 1.65 3.38 

Total 100 100 100 -1,147.09 29,019 223 -3.95 3.65 

Urban 

BPL 25.67 8.48 27.94 -2,295.83 17,038 48 -13.48 4.10 

APL 74.33 91.52 72.06 -557.55 63,475 139 -0.88 3.65 

Total 100 100 100 -1,003.74 51,556 187 -1.95 3.77 


A very stark contrast is seen in the 

rate of savings of HIV households and 

non-HIV households. While the rate of 

savings for the BPL in HIV households is 

-28.70, it is 0.81 for the BPL in non-HIV 

households. The rate of savings for the 

APL in HIV households is 0.11, while it is 

9.20 in non-HIV households. The below 

poverty line HIV households in the rural 

category seem to be the worst hit with a 

rate of savings of -44.5 percent. However, 

in the urban HIV households, the rate of 

savings of both APL and BPL households 

is negative. 

Table 5.16 presents the share of the 

poor in the total population in terms 

of consumption poverty. Here again, it 

is seen that the head count ratio of HIV 

households (16.38) is much higher than 

that of non-HIV households (9.82). It is 

seen that the per capita expenditure of 

HIV households is slightly more than 

that of non-HIV households. However, 

Table 5.16 

Consumption poverty in the sample 


Poverty 

Percent share in 

No. of Per capita Family 

group Households Income Population households expd size 

BPL 7.23 3.72 8.41 87 5,078 4.77 

APL 92.77 96.28 91.59 1,116 11,495 4.05 

Total 100 100 100 1,203 10,956 4.10 

Rural 

BPL 2.46 1.35 3.05 16 3,843 5.06 

APL 97.54 98.65 96.95 634 9,785 4.07 

Total 100 100 100 650 9,604 4.09 

Urban 

BPL 12.84 5.72 14.66 71 5,377 4.70 

APL 87.16 94.28 85.34 482 13,764 4.03 

Total 100 100 100 553 12,535 4.12 


Poverty 

group 

Percent share in 

Households Income Population 

No. of 

households 

Per 

capita 

expd 

Family 

size 

BPL 13.90 5.36 16.38 57 3,785 4.37 

APL 86.10 94.64 83.62 353 13,587 3.60 

Total 100 100 100 410 11,981 3.71 

Rural 

BPL 9.42 4.34 12.02 21 2,956 4.67 

APL 90.58 95.66 87.98 202 10,649 3.55 

Total 100 100 100 223 9,724 3.65 

Urban 

BPL 19.25 6.05 21.42 36 4,324 4.19 

APL 80.75 93.95 78.58 151 17,389 3.67 

Total 100 100 100 187 14,591 3.77 


71

the expenditure of households that are 

below poverty line in HIV households is 

less than that of the corresponding group 

in non-HIV households in spite of the fact 

that the household size is smaller in HIV 

households. Within their expenditure, 

they have to allocate a heavy sum for 

medical expenses. This would imply that 

although all HIV households bear the 

financial burden of the disease, the poor 

among them are the worst sufferers. 

Tables 5.17 and 5.18 give the income 

poverty and consumption poverty in the 

sample by occupational groups for non- 

HIV households and HIV households. 


The major difference in consumption 

expenditure of non-HIV households 

and HIV households is that the medical 

expenses of HIV households are much 

higher than that of non-HIV households, 

more than two times the per capita 

medical expenses of non-HIV households. 

This is because households have to cope 

with the medical expenses related to 

Table 5.17 

Income poverty in the sample group by occupational categories 


Occupation 

Poverty head 

count ratio 

No. of poor 

persons 


households 

Annual per capita 

expenditure of poor 

All 

Cultivation 0.00 0 0 0 

Agri. wage labour 14.23 20 106 4,459.16 

Non-agricultural wage 15.14 47 208 6,145.27 


9.41 16 73 5,577.37 

Salaried 5.68 14 62 6,537.26 

Others 7.55 7 36 5,568.94 

Total 9.82 104 485 5,698.61 


Occupation 

Poverty head count 

ratio 

No. of poor persons 


households 


expenditure of poor 

All 

Cultivation 16.67 18 5 5,759 

Agri. wage labour 50.00 115 27 5,661 

Non-agricultural wage 20.19 86 22 5,272 


21.93 41 9 5,620 

Salaried 15.77 41 9 6,126 

Others 50.49 156 35 5,471 

Total 30.07 457 107 5,565 


Table 5.18 

Consumption poverty in the sample group by occupational categories 


Occupation 

All 

Poverty head 

count ratio 


persons 


households 


expenditure of 

poor 

Cultivation 2.53 2 12 3,773 



Self-employed 

non-agriculture 

8.51 14 66 5,267 

Salaried 3.39 8 37 5,212 

Others 8.39 8 40 5,594 

Total 8.41 87 415 5,078 


Occupation 

All 

Poverty head 

count ratio 


persons 


households 


expenditure of 

poor 

Cultivation 8.33 9 2 3,994 




16.04 30 7 4,576 

Salaried 9.62 25 5 4,224 

Others 27.83 86 19 3,339 

Total 16.38 249 57 3,785 

the epidemic on their own rather than 

through support from the government. 

These households need much greater 

support from the government in terms 

of access and affordability of medical 

care. It is also seen that HIV households 

are spending much larger amounts on 

house rent than non-HIV households. 

Many of them may have been forced to 

sell off their houses in order to pay for 

medical attention or to cope with loss 

of income due to absence from work or 

loss of employment. Special attention 

has to be directed to the HIV households 

who have to reallocate consumption 

expenditure to medical expenses out of a 

lower level of consumption expenditure, 

mainly by reducing food expenditure. 

In order to meet the heavy burden of 

medical expenditure, the HIV households 

are undercutting the expenditure on 

other items and one of the sectors being 

affected is that of education which 

may later have repercussions on the 

household income. 

The results also show that not only are 

the average and per capita savings of HIV 

households lower than that of non-HIV 

households for lower income groups, but 


73

While the burden 

of illness is being 

borne by all 

families whose 

members are HIVpositive, 

it is the 

poor among these 

who are worst hit 

it also results in a much larger negative 

impact on aggregate savings. This suggests 

that the long-term consequences of HIV 

and AIDS on total and household savings 

can be disastrous even though the impact 

may not be visible at this point in the Indian 

case given the fact that the proportion 

of households affected by HIV is still 

quite low. 

More than half of the households had 

either borrowed or liquidated assets 

to cope with the financial burden 

after being detected HIV-positive. The 

percentage of such households, however, 

was very high for the lowest income 

group, going down with the level of 

income of the households. The average 

amount borrowed or generated through 

liquidation of assets, however, was higher 

for higher income groups. While about 

28 percent of the non-HIV households 

resorted to borrowing in the last one 

year with the average borrowing per 

household at Rs. 8,749, nearly 59 percent 

of the HIV households did the same with 

the average borrowing per household 

being a little higher, at Rs. 9,811. 

A stark contrast is seen in terms of rate 

of savings between poor HIV and poor 

non-HIV households. The former group 

has a negative rate of savings while the 

rate is positive for the latter. The poor 

among HIV households are under much 

serious constraint of trying to meet their 

consumption expenditure. This suggests 

that the poor are put under greater stress 

due to the AIDS epidemic, including 

those members of the households who 

are not HIV-positive. 

On the whole, it may be stated that in 

order to bear the burden of expenditure 

on health, the households affected 

by HIV are reducing expenditure on 

other important items like education of 

children. Further, to meet this additional 

burden they are resorting to liquidation 

of assets and borrowings, which in turn 

affects their savings severely. While 

the burden of illness is being borne by 

all families whose members are HIVpositive, 

it is the poor among these who 

are worst hit. It appears that HIV and 

AIDS could increase the incidence as well 

as severity of poverty. 


Impact of HIV and AIDS on the 

Education of Children


Chapter 6 

Impact of HIV and AIDS on 

the Education of Children 

HIV and AIDS affects not only the life 

of the person afflicted by it, but the 

entire household. The economic impact 

of the burden is felt first since the 

infection affects mostly those in their 

most productive years and the illness has 

adverse effect on the earning capacity of 

the HIV-positive person, apart from the 

burden of treatment of opportunistic 

infections that they are generally prey 

to. Because of the stigma attached to the 

infection, the affected as well as the family 

have to bear with the discriminatory 

practices of society. The household is 

generally under the emotional strain of 

taking care of the sick. 

Apart from all these, another very important 

aspect which the infection can affect, is the 

education of children in the household. 

This can happen in various ways: 

a) The children could be forced to give 

up studies to earn and take the place 

of the breadwinner in the family. One 

of the case studies in the state of Tamil 

Nadu is about a household where the 

son is disgruntled because he has had 

to give up his studies and work since 

the family’s income has been affected 

because of their father’s being HIVpositive. 

b) In poor households, the expenses on 

the education of poor children could 

be curtailed to balance the increasing 

burden of illness of the HIV affected 

person. 

c) There could be instances where 

school going children have to act as 

caregivers in the family and look after 

their parents. 

d) Because of the stigma associated with 

the infection, children may not get 

access to education. 

Although education, which is a means of 

achieving skills and therefore a livelihood, 

is important to all, it is more important 

in the context of HIV and AIDS. Experts 

have coined the term ‘education vaccine’ 

to indicate that education is the first line 

of defence against the spread of HIV, 

and has been proved as an important 

means of preventing HIV and AIDS 

(World Bank, 2002; Boler Tania and Kate 

Carroll, undated; Vandermootele, Jan and 

Enrique Delamonica, 2000). However, 

it has also been assumed in literature 

that HIV and AIDS would result in lower 

investment in education of children (Bell, 

Devarajan and Gorbach, 2003). 

The focus of the present chapter is on the 

impact of HIV and AIDS on the demand 

for and access to education. The impact 

on the schooling of children in the state 

of Tamil Nadu is examined based on 

the results of the survey. The household 


77

impact is measured not only by asking 

whether the child goes to school, but 

also by observing the child’s school 

attendance, the type of school attended, 

the reasons for dropping out, etc. This 

data relates the presence of HIV and AIDS 

in a household to the ability to continue 

educating the children and tries to capture 

the gender differentials, if any. This study 

also tries to compare the enrolment rates 

and dropout rates of children belonging 

to two sets of households, i.e., households 

with the presence of an HIV-positive 

individual and households without any 

such individual. 

Table 6.1 

Ever and current enrolment of children in 

HIV and non-HIV households 


Age 6-14 years Boys Girls Total F/M 

Ever enrolled 

HIV households 97.3 97.4 97.4 1.00 

Non-HIV households 98.3 97.7 98.0 0.99 

Currently enrolled 



Number of children 

HIV households 148 154 302 

Non-HIV households 351 308 659 

Age 15-18 years 

Ever enrolled 

HIV households 100 100 100 1.00 

Non-HIVhouseholds 100 100 100 1.00 



Non-HIV households 86.6 8 6.6 86.6 1.00 

Number of children 

HIV households 30 29 59 

Non-HIV households 223 208 431 

Since the survey includes both HIVpositive 

households and non-HIV 

households, by keeping the socioeconomic 

characteristics of the two sets 

of households similar, a cross-sectional 

analysis of the differences in children’s 

education in the two sets of households 

has also been also attempted. This 

chapter concludes by drawing inferences 

about the future/higher education 

of the children based on the answers 

obtained for the open ended questions 

as well as on the focus group discussions 

conducted with the members of the 

Network of Positive People. 

6.1 Ever and current 

enrolment rates 

The ever and current enrolment rates for 

children in the age group of 6-14 years, 

which corresponds to class I-VIII, and 

age group 15-18 years which corresponds 

to classes IX to XII, are presented in 

Table 6.1. The gross enrolment rate is 

calculated as the number of children in 

the age group who were ever enrolled as 

a percentage of total number of children 

in that age group. The current enrolment 

rate is calculated by taking the number 

of children who are currently studying, 

as a percentage of the total number of 

children in that age group. 

In the age group of 6-14 years, the ever 

enrolled rates are slightly less than 100 

percent but are almost similar in both 

HIV and non-HIV households. Also, 

there is no noticeable difference between 

the enrolment rates of boys and girls. 

However, while almost all the enrolled 

children seem to be currently studying 

in non-HIV households, the current 

enrolment of children in HIV households 

is lesser than ever enrolled rates and 

noticeably so in the case of girls. 

In the age group of 15-18 years, there is 

100 percent enrolment of all children, 

HIV or non-HIV, boys or girls. The current 

enrolment rates in both categories of 


households have come down. However, 

while the current enrolment rate for non- 

HIV households has come down from 

100 percent to 86.6 percent for both boys 

and girls, in HIV households the current 

enrolment rates for boys has come down 

to 76.7 percent; but it has reduced to 

nearly half (51.7%) in the case of girls. The 

table clearly indicates that while most of 

the children from HIV households are 

enrolled in schools, the continuation of 

their studies is affected, more so for the 

girls and especially in the age group of 

15-18 years. 

6.2 Dropout rates and 

number of years of schooling 

Two observations are evident from Table 

6.2. Firstly, the dropout rates are lower for 

the non-HIV households as compared to 

HIV households. While the dropout rate 

for the children of HIV households is 4.8 

percent, the rate is lower, at 0.8 percent, 

for the children belonging to non-HIV 

households with reference to the age 

group of 6-14 years. 

The difference is more pronounced in 

children belonging to the age group of 

15-18 years. While the dropout rate for 

children from HIV households is 35.6 

percent, it is 12.5 percent for children 

from non-HIV households. 

Secondly, in non-HIV households the 

dropout rate for girls is slightly lower 

than that for boys in the age group of 

6-14 years and the reverse is true in the 

age group of 15-18 years. However, in 

the case of HIV households, the dropout 

rates are higher for girls in both age 

groups. Interestingly, the average number 

of years of schooling completed by the 

children who had dropped out of school 

has worked out to be more or less the 

same for the children of HIV and non-HIV 

households. 


enrolment rates by 

household income 

There is no clear trend as regards ever 

enrolment rates for children in the age 

The average 

number of years 

of schooling 

completed by the 

children who had 

dropped out of 

school has worked 

out to be more 

or less the same 

for the children of 

HIV and non-HIV 

households 

Table 6.2 

Dropout rates and number of years of schooling completed by dropout children 


Age 6-14 years Boys Girls Total F/M 

Percentage of children who have dropped out of school 



Average number of years of schooling completed by dropouts 




Percentage of children who have dropped put of school 



Average number of years of schooling completed by dropouts 




79

Annual household 

income (Rs) 


Ever enrolled 

group of 6-14 years whether they are 

from HIV or non-HIV households, with 

reference to the household income 

categories. On the other hand, for 

children belonging to the age group of 

15-18 years, it is seen that there is 100 

percent enrolment of both boys and 

girls in both types of households in all 

Table 6.3 

Ever & current enrolment rates for children 

by annual household income categories 


HIV households Non-HIV households 

Boys Girls All Boys Girls All 

Upto 20,000 95.7 96.8 96.4 96.6 100 98.1 

20,001-30,00 95.4 96.8 96.2 98.4 98.9 98.6 

30,001-41,00 100 100 100 100 98.5 99.3 

41001-84,000 97.6 97.1 97.4 96.6 96.0 96.3 

Above 84,000 100 100 100 100 96.0 97.9 


Upto 20,000 89.4 92.1 90.9 96.6 100.0 98.1 

20,001-30,00 95.5 90.3 92.5 96.0 98.9 97.2 

30,001-41,00 96.2 100 97.7 100 98.5 99.3 

41001-84,000 97.6 88.6 93.4 95.4 94.9 95.2 

Above 84,000 100 75.0 90.0 100 96.0 97.9 

N 148 154 302 351 308 659 


Ever enrolled 

Upto 20,000 100 100 100 100 100 100 

20,001-30,00 100 100 100 100 100 100 

30,001-41,00 100 100 100 100 100 100 

41001-84,000 100 100 100 100 100 100 

Above 84,000 100 100 100 100 100 100 


Upto 20,000 75.0 33.3 57.1 77.8 66.7 73.3 

20,001-30,00 75.0 37.5 50.0 94.4 97.7 95.7 

30,001-41,00 50.0 75.0 66.7 73.8 84.1 79.1 

41001-84,000 81.8 71.4 77.8 87.1 86.7 96.9 

Above 84,000 100 100 100 86.7 93.7 90.3 

N 30 29 59 223 208 431 

the different income groups. No clear 

trend is seen in the current enrolment 

rates of children from either HIV or non- 

HIV households in either of the two age 

groups. However, what is noticed is that 

the current enrolment rate of children 

in the age group of 15-18 years is very 

low in the case of children from HIV 

households, especially girls belonging to 

the first two income groups. This tallies 

with the existing perception that the 

burden of HIV is heavier on the poorer 

sections of society. It may probably be 

correct to assume that the burden of the 

diseases on households is responsible for 

such low rates of current enrolment. 

However, one surprising result is that the 

current enrolment is 100 percent, both 

for boys and girls, only in HIV households 

in the highest income category of Rs. 

84,000 and above, for the age group of 

15-18 years. 


enrolment rates by level of 

education of household head 

The relationship between the level of 

education of the household head and 

the enrolment of children in school 

has emerged clearly (Table 6.4). In the 

case of children in the age group of 6-14 

years, the ever enrolment as well as the 

current enrolment rates for both types of 

households mostly go up with the rise in 

the level of education of the household 

head. At lower levels of education, both 

the ever and current enrolment rates are 

generally lower for the children belonging 

to the HIV households as compared to 

non-HIV households. However, when the 

household head is a graduate/diploma 

holder, the ever enrolment rate and 

current enrolment rates are higher in 

HIV households and touch 100 percent. 

This could probably be because they 

realise the importance of educating their 


children, particularly in their situation, 

and think of it as an investment for the 

future. 

In the case of children in the age group 

of 15-18, ever enrolment rates are 100 

percent irrespective of the gender of the 

child or the type of household. However, 

from the current enrolment rates of both 

types of households, it is clearly seen that 

the rates go up with the level of education 

of the household heads. At the same 

time, at every level, the enrolment rate 

for children from HIV households is less 

than that for non-HIV households. No 

gender gap is noticed in either the ever 

enrolment rates or current enrolment 

rates in HIV and non-HIV households for 

children in the age group of 6-14 years. 

In the case of children in the age group 

of 15-18 years, the ever enrolment rates 

are 100 percent irrespective of gender 

and household. It is only in respect of 

the current enrolment rates of these 

Table 6.4 

Ever and current enrolment rates for children 

by level of education of household head 


Education of household head HIV households Non-HIV households 



Ever enrolment rate 

Illiterate 93.9 97.7 96.1 97.4 97.0 97.2 

Upto middle 93.9 98.1 96.6 98.4 97.0 97.8 

High school/higher secondary 100 100 98.4 98.7 98.6 98.7 

Graduate/diploma 100 100 100 96.6 96.8 96.7 

Current enrolment rate 

Illiterate 84.8 86.1 85.5 97.4 93.9 95.8 

Upto middle 90.9 96.3 94.2 95.3 97.0 96.0 

High school/higher secondary 100 88.5 95.1 98.7 96.6 98.7 

Graduate/diploma 100 100 100 96.6 96.8 96.7 

N 148 154 302 351 308 659 


Ever enrolment rate 

Illiterate 100 100 100 100 100 100 

Upto middle 100 100 100 100 100 100 

High school/higher secondary 100 100 92.9 100 100 100 

Graduate/diploma -- -- 100 100 100 100 

Current enrolment rate 

Illiterate 75.0 25.0 45.0 71.4 93.3 80.6 

Upto middle 66.7 50.0 61.5 88.1 81.2 84.6 

High school/higher secondary 84.6 76.9 75.0 87.4 91.7 89.4 

Graduate/diploma -- -- -- 93.8 93.7 93.7 

N 30 29 59 223 208 431 


81

The percentage 

of girls from HIV 

households going 

to government 

schools is much 

higher than that of 

girls from non-HIV 

households 

children from HIV households that a 

marked change in the rates for boys and 

girls is seen. 

When the household head is illiterate, the 

current enrolment rate for girls (25%) is 

one-third of that for boys (75%). However 

with increased level of education of the 

head of the household, the difference in 

the rates is seen to decrease and is 84.6 

percent for boys and 76.9 percent for 

girls when the head of the household is 

educated upto high school. The sample 

does not have any household where the 

head of the household having children 

within this age group is a graduate or a 

diploma holder. 

6.5 Type of school attended 

To a large extent, the type of school 

attended by children is indicative of the 

economic status of a household. In the 

present sample however, with reference 

to children of both the age groups, 

the percentage of children going to 

government schools is almost the same 

for both types of households. It is very 

marginally higher for HIV households; 

70.2 percent for HIV households & 68.6 

percent for non-HIV households in the 

6-14 years age group and 64.6 percent 

for HIV households & 64.2 percent for 

non-HIV households in the 15-18 years 

age group. 

Irrespective of the type of household, 

for children in the age group of 6-14 

years, the percentage of children going 

to government schools works out to be 

higher for girls as compared to boys, 

although the difference is marginal in 

non-HIV households. However, in the 

case of the children belonging to the 

age group of 15-18 years, the percentage 

of girls going to government schools 

is slightly higher than that of boys in 

HIV households, while the percentage 

of girls attending government schools 

is much lower than that of boys in 

non-HIV households. However, in 

both age groups, it is seen that the 

percentage of girls from HIV households 

going to government schools is much 

higher than that of girls from non-HIV 

households. 

6.6 School attendance 

Table 6.5 

Distribution of currently enrolled children 

by type of school attended 


Type of school HIV households Non-HIV households 

6-14 years Boys Girls All Boys Girls All 

Government 62.2 76.9 70.2 68.0 69.3 68.6 

Private • 36.7 23.1 29.3 31.7 30.3 31.1 

Informal/others 1.0 -- 0.5 0.3 0.3 0.3 

Total 100 100 100 100 100 100 

15 - 18 years 

Government 64.3 65.2 64.6 69.4 58.7 64.2 

Private • 35.7 34.8 35.4 30.6 41.3 35.8 

Informal/others -- -- -- -- -- -- 

Total 100 100 100 100 100 100 

The average number of days of absence 

from school during the last academic 

session is more for children belonging 

to HIV households, as compared to 

non-HIV households (Table 6.6), for 

children belonging to both age groups. 

The average number of days absent from 

school works out as 9.7 for the children of 

HIV households and 5.5 for the children 

belonging to non-HIV households in the 

age group of 6-14 years and 8.3 days for 

children from HIV households and 5.5 

for children from non-HIV households 

in the age group of 15-18 years. Except 

for children in the age group of 15-18 

years from HIV households, it is seen that 

girls are absent for lesser number of days 

than boys. 


Table 6.6 

School attendance of children In the last academic year by type of household 

6-14 Years HIV households Non-HIV households 


No. of days absent during last academic year (averages) 10.6 8.7 9.7 5.8 5.3 5.5 

Reasons for absence (%)* 

1. Child unwell 69.0 69.4 69.2 75.4 74.4 74.9 

2. Parent unwell 18.1 19.8 18.9 7.2 6.7 6.9 

3. Went out of station 39.7 33.3 36.6 37.7 36.5 37.1 

4. Not paid fees/not allowed to attend 6.0 5.4 5.7 1.3 1.8 1.5 

5. School environment not conducive 1.7 0.9 1.3 0.3 -- 0.2 

6. Child refused to attend 7.8 5.4 6.6 -- -- - 

7. Had to attend social function 18.1 6.3 12.3 -- -- -- 

8. Had to look after younger siblings/attend to HH chores 1.7 -- 0.9 -- -- -- 

9. Others 2.6 0.9 1.8 -- -- -- 

15-18 years 

No. of days absent during last academic year (averages) 7.9 9.0 8.3 6.3 6.1 6.2 

Reasons for absence (%)* 

1. Child unwell 58.8 50.0 54.8 75.7 72.9 74.3 

2. Parent unwell 35.3 21.4 29.0 20.6 16.6 18.6 

3. Went out of station 47.1 35.7 41.9 52.4 46.4 49.5 

4. Not paid fees/not allowed to attend 11.8 -- 6.5 0.5 2.2 1.4 

5. School environment not conducive -- -- -- 0.5 0.6 0.5 

6. Child refused to attend -- -- -- 2.1 0.6 1.4 

7. Had to attend social function 5.9 14.3 9.7 24.3 30.4 27.3 

8. Had to look after younger siblings/attend to HH chores 5.9 7.1 6.5 0.5 1.1 0.8 

9. Others -- -- -- 1.0 1.1 1.1 

* The percentages do not add to 100 due to multiple answers. 

There are interesting differences in the 

reasons for absence between the two 

types of households. The percentage of 

children not attending school due to ill 

health of the parents is obviously much 

higher for the children belonging to HIV 

households in both the age groups. The 

other reason is non-payment of fees/not 

being allowed to attend. In both types of 

households, another important reason 

for not attending school seems to be 

the ‘child himself/herself being unwell’, 

going out of station, or attending social 

functions. 

6.7 Reasons for 

discontinuation of schooling 

The survey results indicate that the 

presence of an HIV infected individual 

in a household does affect the children’s 

schooling. Though the enrolment of 

children in schools is affected only 

to a small extent, the continuation of 

schooling emerges as a greater problem. 

Generally, it is found that the reasons 

for children dropping out of school 

are similar for both HIV and non-HIV 

households. A number of children from 


83

In both HIV 

and non-HIV 

households, 

a significant 

percentage 

reported that the 

various incentives 

provided by the 

government have 

influenced their 

decision to enrol 

the children in 

school 

both households have dropped out 

because they are unable to afford the fees 

as they belong to the lower economic 

strata of society. While a higher number 

of children from HIV households have 

dropped out due to reasons like having 

to look after the sick at home, take care 

of younger siblings and to earn a living, 

in non-HIV households, the percentages 

under these categories are lower. In the 

15-18 years age group, a higher number 

of children in non-HIV households have 

dropped out because they have failed or 

because of lack of interest in studying 

or because education is considered 

unnecessary. A number of girls have also 

discontinued studying, as there are no 

separate schools for girls. 

In both HIV and non-HIV households, 

a significant percentage reported that 

the various incentives provided by 

the government have influenced their 

decision to enrol the children in school. 

The most popular scheme seems to be the 

‘Mid-day Meals Scheme’ and the other 

incentives mentioned include free books, 

hostel accommodation and free school 

uniform supplied by the government 

to children belonging to economically 

weaker sections of the society. 

Interestingly, no HIV household has 

reported stigma and discrimination 

as reasons for discontinuation of 

schooling. Does this mean there is no 

discrimination in the schools? The 

focus group discussions conducted with 

PLWHA provide some insight into this 

situation. Most of the parents mentioned 

that they did not have any problem in 

getting their wards admitted to school. 

In the case of children studying in public 

schools, teachers as well as parents of 

other students seemed to know about 

their status. However, one participant 

whose children were studying in an 

English-medium private school had not 

revealed his status to anybody, as he did 

not think that it was necessary to do so. 

Incidentally, in the present study, fifteen 

children (8 boys and 7 girls) in the age 

group of 6-14 years were HIV-positive. 

There were no HIV-positive children in 

the age group of 15-18 years. Of these 

fifteen children, fourteen were enrolled 

in school. One boy, however, could 

not get admission because of his HIVpositive 

status. One boy and two girls 

have dropped out, the boy, because he 

had to look after his parents (obviously 

in the later stages of the infection), and 

the girls, because there was no separate 

school for them. 


One of the genuine concerns of HIVpositive 

parents is about the future 

of their children. How long can they 

continue to educate their wards? 

Interestingly, most of the parents, even 

if they themselves were not very well 

educated, seem very keen on educating 

their children. They seem to have 

tremendous faith in education and 

think that education would improve the 

employment prospects of their children. 

They want to educate their children for 

as long as they can and most of them 

feel that in order to get employment, 

education upto graduation level is 

necessary. Although the parents may not 

live to reap the benefit of their children’s 

education, they are keen to educate 

them. However, not all can afford to do 

so. Only a small percentage mentioned 

that they could afford to educate their 

children beyond middle school. In the 

FGD conducted in Tamil Nadu, a number 

of parents who desired to educate their 

children had hopes that the Network or 

some other organisation would take care 

of the education of their children. In fact, 

two participants mentioned that they 


had enrolled their children in a boarding 

school run by an NGO specifically for the 

children of HIV-positive parents. 

Education is seen as the means to 

rise above one’s situation. With the 

curtailment of education, avenues 

of opportunities available to others 

become unavailable to children from 

families affected by HIV and AIDS. 

Hence, concerted efforts ought to be 

made to ensure that the education of 

these children is continued. This could 

either be in the form of monetary aid or 

by giving a helping hand in looking after 

the sick in these households. 


85

Impact of HIV and AIDS on 

Health


Chapter 7 

Impact of HIV and AIDS 

on Health 

There are several ways in which PLWHA 

and their households are likely to be 

affected by the infection. Economically, 

apart from the burden of medical 

treatment, since HIV affected individuals 

are in their most productive years, 

the affected households are also likely 

to suffer loss of income either due to 

absence from work because of illness or, 

in the worst case, by loss of employment. 

Socially, there is a stigma attached to the 

infection and households with a PLWHA 

are generally discriminated against. 

Taking care of an AIDS patient is also an 

emotional strain on the members of the 

household. In many cases the presence 

of HIV means that the household will 

dissolve, as parents die and children are 

sent to relatives for care and upbringing. 

In the health sector, the epidemic brings 

additional pressure. As the epidemic 

matures, the demand for care for PLWHA 

rises. Healthcare services may face 

different levels of strain depending on the 

number of people who seek services, the 

nature of their need, and the capacity to 

deliver that care. 

This chapter examines the pattern and 

burden of morbidity on the HIV affected 

households in the state of Tamil Nadu. 

The details about the opportunistic 

infections suffered, the type of treatment 

sought and the out-of-pocket expenditure 

incurred on the treatment were gathered 

from a sample of 478 PLWHA. In addition, 

the survey also collected information 

on the prevalence of non-hospitalised 

illnesses and the hospitalisation cases for 

all the members of HIV as well as non- 

HIV households (the controlled group), 

to compare the disease burden on the 

two types of households. The findings of 

the survey are presented in the following 

sections. 

7.1 Prevalence rate of illness 

7.1.1 Prevalence rates of 

illnesses – HIV and non-HIV 

households 

The prevalence rates are calculated for 

both non-hospitalised illnesses and 

hospitalised cases from the information 

collected from all the members of the HIV 

and non-HIV households. In all, there 

was a sample of 410 HIV and 1,203 non- 

HIV households and the total number 

of persons involved was 1,520 for HIV 

and 4,937 for non-HIV households. The 

prevalence rate of non-hospitalised 

illnesses is calculated on the basis of 

reports of illnesses by the households 

in the month preceding the date of 

interview. The non-hospitalised illnesses 

include acute as well as chronic illnesses 

that were prevalent during the onemonth 

reference period. The prevalence 

rate of hospitalisation is calculated based 

on the number of hospitalisation cases 

Impact of HIV and AIDS on the Health 

89

eported for the household members 

during the year preceding the date of 

interview. These are presented in the 

Tables 7.1 and 7.2. 

The tables clearly indicate that the 

burden of non-hospitalised as well as 

hospitalised illnesses is very heavy on 

HIV households in comparison with 

non-HIV households. In the case of nonhospitalised 

illnesses, the prevalence 

rate of illnesses in the age groups of 0-14 

and of 15-59 is high for HIV households; 

the prevalence rate in the age group of 

60 years and above is slightly higher 

in the case of non-HIV households. In 

the case of hospitalised illnesses, the 

reported number of cases is higher 

for HIV households for all age groups. 

What stands out is that in the age group 

of 15-59 which comprises the largest 

section of PLWHA, the burden on HIV 

households is nearly three and a half 

times that on non-HIV households with 

respect to non-hospitalised illness and 

is about five times greater in the case 

of hospitalised illnesses. On the whole, 

both, the rate of illness and the number 

of hospitalisation cases, are lesser for 

women than for men in both types of 

households, the exception being the age 

group of 0-14 in HIV households and 

that of 60+ in both HIV and non-HIV 

households. 

Table 7.1 

Prevalence rate of illness for the one-month reference period 

by type of households and age and sex 

(Per‘000 population) 

Age group HIV households Non-HIV households 

Male Female Total Male Female Total 

0-14 492.1 567.2 528.5 409.5 339.0 375.5 

15-59 1,442.3 963.1 1,177.2 354.3 325.8 340.7 

60+ 911.1 1,038.5 979.4 953.9 1,190.0 1,056.5 

All ages 1,071.3 850.9 954.6 396.6 365.5 381.8 

Number of persons 715 805 1,520 2,587 2,350 4,937 

Table 7.2 

Reported number of hospitalisation cases in the reference year 

by type of households and sex 

(Per‘000 population) 

Age group HIV households Non-HIV households 

Male Female Total Male Female Total 

0-14 90.6 84.0 87.4 43.9 41.4 42.7 

15-59 771.6 328.2 526.3 78.4 66.3 72.6 

60+ 488.9 365.4 422.7 230.8 310.0 265.2 

All ages 511.9 258.4 377.6 78.5 71.1 74.9 

Number of persons 715 805 1,520 2,587 2,350 4,937 


7.1.2 Prevalence rates of 

illnesses for PLWHA 

The prevalence rates for hospitalised and 

non-hospitalised illnesses are calculated 

for the PLWHA on the basis of the stage 

of their infection and the number of 

years since the infection was detected. 

The WHO classifies the HIV infection 

into four clinical stages based on the 

diseases and the performance scale. 

At stage I, it is asymptomatic and the 

individual would be able to carry on 

normal activities. At the clinical stage II, 

it is symptomatic (with symptoms like 

weight loss of 5 years 1,294 735 34 

All 1,743 906 478 


91

The manifestation 

of infections in 

AIDS patients 

depends on the 

level of immunity, 

which is reflected 

by the CD4 and T 

cell count 

prevalence rates seem to be decreasing 

as the number of years since the HIVpositive 

status was detected increases. 

The prevalence rates was the highest 

even for those who had tested HIVpositive 

in the last one year. It is possible 

that although they tested positive during 

the last year, they might have been 

infected earlier. 

While the stage-wise details have been 

given for 552 people, the rates on the 

basis of the number of years since 

detection of infection have been given 

only for 478 people. Of the 410 HIVpositive 

households interviewed, there 

emerged 552 cases of PLWHA. These 

also included children in the age group 

of 0-14, and between teenage and 

adulthood. The interviews, however, 

were held only with adult PLWHA. Also, 

not all of the adults came forward for the 

interview and hence information could 

be collected only from 478 persons. This 

explains the difference in the number of 

people for whom the results have been 

tabulated. 

The HIV virus causes chronic infection 

and the course of the infection would 

vary from individual to individual. 

Some persons may develop immuno 

deficiency within two to three years and 

others may remain AIDS free for 10-15 

years. The manifestation of infections 

in AIDS patients depends on the level of 

immunity, which is reflected by the CD4 

and T cell count. 

A sample of 478 PLWHA – 269 men and 

209 women – in Tamil Nadu were 

interviewed in detail to find out about the 

nature and frequency of illnesses suffered 

by them, their health seeking behaviour 

and the out-of-pocket expenditure 

incurred by the households in treating 

the OIs. These findings are presented 

below. 

Table 7.4 

Frequency of OIs reported by PLWHA by stage of HIV infection 

(non-hospitalised illness episodes) 

Number of times ill in the last one year 

Average 

number 

Frequently 

ill (%) 

Continuously 

ill (%) 

Number of times iII in the last one month 

Average 

number 

Frequently 

ill (%) 

Continuously 

ill (%) 

By sex 

Male 2.35 24.9 2.2 1.29 19.7 1.1 

Female 2.16 10.5 1.4 1.01 7.2 1.4 

By stage of infection 

Stage 1 1.60 21.7 -- 0.76 16.9 -- 

Stage 2 2.95 20.2 1.2 1.20 17.2 0.6 

Stage 3 1.96 19.6 2.4 1.20 12.9 1.8 

Stage 4 2.12 8.7 4.3 1.42 7.2 2.9 

No. of years back detected 

Last one year 1.68 21.0 1.54 1.17 16.9 1.0 

2-5 years 2.72 18.1 2.4 1.60 13.2 1.6 

>5 years 2.12 8.8 -- 1.09 5.9 -- 

All 2.26 18.6 1.9 1.16 14.2 1.3 


7.2 Details about nonhospitalised 

illness episodes 

7.2.1 Frequency of illnesses 

(Non-hospitalised) 

HIV weakens the body’s immune system 

i.e. the ability to fight diseases and as a 

result, PLWHA can get many infections, 

which are called opportunistic infections 

(OIs). This nomenclature emerges from 

the fact that they take advantage of the 

opportunity offered by the weakened 

immune system. The prevention 

and treatment of OIs is an important 

component of management of HIV. 

The sample PLWHA were asked the 

number of times they had fallen ill 

during the periods of a year and a 

month previous to the interview, and 

the same have been represented as 

last one year and last one month in 

Table 7.4. Nearly 19 percent reported 

that they were frequently ill during the 

one-year period and about 14 percent 

during the one-month period. A small 

percentage reported being continuously 

ill in the one-year period (2%) and in 

the one-month period (1%). For the 

remaining, i.e. those who were not 

either frequently or continuously ill, 

the average number of times that they 

had fallen ill during one year and one 

month have been calculated. It is seen 

that these percentages and the average 

numbers are generally lesser for women 

than for men. 

These calculations have also been made 

with reference to the stage of infection 

and the number of years since the 

HIV-positive status was detected. 

Although in the case of the number of 

times the PLWHA has been ill in the 

last one month, the average number of 

non-hospitalised illness episodes seem 

to be increasing with an increase in the 

stage of illness; no such trend is seen 

when the average number of illnesses 

in the last one year is considered. 

However, the percentage of PLWHA who 

are continuously ill is increasing with 

increasing stages of infection in both the 

last one month and the last one year. 

No trend seems to be emerging from 

these data when analysed on the basis 

of the number of years since the HIVpositive 

status was detected. More 

detailed information about the illnesses 

suffered by the PLWHA during the 

last one month prior to the date of 

interview was collected with regard to the 

nature of illness, the type of treatment 

sought and the amount of expenditure 

incurred on the treatment of these 

illnesses. 

7.2.2 Nature of illnesses 

(Non-hospitalised illness 

episodes) 

About sixty four percent of the men and 

one-fourth of the women had taken the 

HIV test because they had been suffering 

from prolonged illness. 

Table 7.5 shows that of the total number 

who went in for the HIV test after 

prolonged illness, nearly 34 percent men 

and 39 percent women have reported 

fever as the main cause. The other main 

illnesses are prolonged bouts of loose 

motion/diarrhoea and TB. 

The sample PLWHA were asked the 

number of times they had fallen ill (nonhospitalised 

illness) during the reference 

period of a month and details of upto 

two episodes per sample were collected. 

From the 478 PLWHA interviewed, 

there emerged 566 illness episodes. The 

percentage distribution of these 566 

illness episodes reported by the sample 

PLWHA in the one month reference 

period according to nature of illness is 

presented in Table 7.6. 

HIV weakens 

the body’s 

immune system 

ie, the ability to 

fight diseases 

and as a result, 

PLWHA can get 

many infections, 

which are called 

opportunistic 

infections (OIs) 


93

Table 7.5 

Distribution of PLWHA reporting prolonged 

illness as a reason for going in for HIV test 


Male Female 

Percent reporting prolonged illness 63.9 24.4 

Nature of illness 

1 Respiratory infection 7.6 2.0 

2 Malaria -- -- 

3 Fever 34.3 39.2 

4 Headache, bodyache etc. 0.6 3.9 

5 Weakness 1.2 2.0 

6 Typhoid 0.6 2.0 

7 Gynaecological problem 1.7 -- 

8 Loose motion/diarrhoea 29.6 11.8 

9 Jaundice 0.6 -- 

10 TB 12.2 11.8 

11 Skin diseases 7.0 7.8 

12 Sexually transmitted diseases 0.6 6.0 

13 Others 4.1 13.7 

All 100 100 

Table 7.6 


nature of illness reported 


Nature of illnesses Male Female Total 

1 Respiratory infection 15.2 18.9 16.6 

2 Malaria 0.3 0.5 0.4 

3 Fever 34.4 31.8 33.4 

4 Headache, bodyache 5.4 8.8 6.7 

5 Weakness 2.3 4.2 3.0 

6 Loose motion/diarrhoea 18.9 10.1 15.5 

7 Typhoid 0.3 0.9 0.5 

8 Jaundice 0.3 -- 0.2 

9 TB 8.9 4.6 7.2 

10 Skin diseases 4.6 2.8 3.9 

11 Sexually transmitted diseases/RTI 3.4 4.6 3.9 

12 Gynaecological problems -- 3.7 1.4 

13 Others 6.0 9.2 7.3 

Total 100 100 100 

Number of illness episodes 349 217 566 


Again, it is seen that fever remains the 

most highly reported illness (33%). 

Loose motion, diarrhoea, respiratory 

infections, TB and headache, bodyache 

and weakness are the other illnesses 

commonly experienced in the one month 

reference period. 

7.2.3 No treatment of illness 

The OIs result in more rapid decline in 

CD4 T-cells and hence treatment for 

opportunistic infections is required in 

order to reduce the suffering of the PLWHA 

and to allow them to lead an active life. 

The survey results show that not all illness 

episodes got treated. 

It is seen that generally treatment has 

been sought in all except 7.6 percent 

illness episodes. While nearly 6 percent 

of the illness episodes went untreated 

in the case of men, the percentage was 

higher, at 10.6 percent, for women. The 

number of illness episodes for which 

treatment was not taken was 20 in respect 

of male PLWHA and 23 in respect of 

female PLWHA. Among both men and 

women, the major reason for not taking 

treatment was that the illness was not 

considered serious. However, in the case 

of women, 13 percent of illness episodes 

did not get treated because of economic 

constraints; this has not been an issue in 

the case of men. This points out not only 

to the gender bias that is prevalent in 

society but also probably to the financial 

conditions being faced by HIV-positive 

women, many of whom are widows, and 

a few whom have been deserted. Further, 

in the case of women, there have been 

a couple of cases where no doctor was 

willing to treat the illness. 

7.2.4 Duration of illness 

episodes, treatment etc 

Of the 566 episodes (Table 7.6), treatment 

was sought for 523 episodes. For each 

of these illness episodes reported by 

the PLWHA during the one month 

reference period, information regarding 

the number of days each episode lasted, 

the duration of treatment, the number of 

days the patient was bedridden and the 

number of days the patient did not go to 

work were obtained. The same have been 

presented in Table 7.8 below. 

Among both men 

and women, the 

major reason 

for not taking 

treatment 

was that the 

illness was not 

considered serious 

Table 7.7 

Illness episodes receiving no treatment and reasons for no treatment for PLWHA 

Percentage of Illness episodes for which no treatment 

was sought 

Reasons for not seeking treatment (%) 


Male Female All 

5.7 10.6 7.6 

1 Illness not considered serious 90.0 73.9 81.4 

2 No medical facility nearby 5.0 -- 2.3 

3 No doctor was willing to treat -- 4.3 2.3 

4 Financial constraints -- 13.0 7.0 

5 Lack of time/long waiting 5.0 4.3 4.7 

6 No cooperation from the family -- -- -- 

7 Others -- 4.3 2.3 

Total 100 100 100 


95

Table 7.8 

Average number of days ill, bedridden and not going to work during each 

non-hospitalised illness episode in the last one month 

Number of days 

ill 

% reporting 

frequently/ 

continuously Ill 

Duration of 

treatment 

No. of days 

bedridden 


No. of days not 

going to work 


Stage 1 7.1 37.5 7.8 1.6 7.9 

Stage 2 7.7 38.7 6.2 2.5 7.5 

Stage 3 8.7 34.6 7.5 4.3 10.3 

Stage 4 8.9 31.3 6.7 4.6 9.5 

All 8.2 35.8 6.9 3.4 8.9 

As the household 

income increases, 

treatment is 

sought more and 

more from private 

health services 

Of the total episodes reported, 36 

percent of PLWHA were either frequently 

or continuously ill. In the case of the 

remaining episodes, on an average, 

the illness was of about eight days’ 

duration. Treatment was taken for seven 

days; the average number of days they 

were bedridden was about 3.4 and the 

number of days they were unable to go 

to work was around nine days for those 

who were employed at the time of the 

survey. 

The number of days the illness lasts, the 

number of days spent bedridden, and the 

number of days of absence from work 

have generally increased with increase 

in the stage of infection. The percentage 

reporting frequent/continuous illness 

decreases in the third and fourth stages 

of infection. One of the possible reasons 

could be that a number of respondents 

might have been hospitalised in stages 

three and four. 

7.2.5 Source of treatment 

The percentage distribution of illness 

episodes for which treatment was sought 

is presented in Table 7.9 with reference to 

the source of treatment. 

In nearly 54 percent of the illness 

episodes, treatment was taken from 

government health facilities while in 35 

percent of the episodes, private facilities 

were responsible for the treatment. In 

only about 10 percent of episodes, the 

treatment was taken from NGOs. While 

in about 74 percent of the episodes, 

women took treatment from government 

hospitals and NGOs, the percentage 

of men for such treatment has been 

lesser, at 57 percent. However, while 

only 25 percent of women have taken 

treatment from private health facilities, 

the percentage of men availing this 

facility is 41 percent. This could be either 

because in a family more importance is 

given to the man since he is generally 

the breadwinner or because many of 

these HIV-positive women do not have 

the support of their husband/family 

and hence lack the finances needed to 

go to private health facilities. The ‘other’ 

category includes episodes in which 

the affected persons directly purchased 

medicines from chemist shops or resorted 

to home remedies. 

An analysis of the source of treatment 

of non-hospitalised illness based on 

the annual household incomes of the 

PLWHA is given in Table 7.10. As can 

be seen, as the household income 

increases, treatment is sought more and 

more from private health services. 


Table 7.9 

Distribution of non-hospitalised illness episodes by source of treatment for male 

and female PLWHA 


Source of treatment Male Female All 

1. Government 49.5 60.8 53.7 

2. Private 40.7 24.7 34.8 

3 Charitable trust/NGO 7.6 12.9 9.6 

4. Faith healer/religious person -- -- -- 

5 Others 2.1 1.5 1.9 

Total 100 100 100 

Number of episodes 329 194 523 

Table 7.10 

Distribution of non-hospitalised illness episodes by source of treatment and 

by annual household income groups 

Source of treatment 

Upto 20,000 20,001- 

30,000 

Annual household income (Rs.) 

30,001- 

41,000 

41,001- 

84,000 


>84,000 All 

1 Government 54.6 56.9 59.4 51.6 28.0 53.7 

2 Private 25.4 31.9 31.9 45.3 72.0 34.8 

3 Charitable trust/NGO 17.3 9.5 5.8 2.3 -- 9.6 

4 Faith healer/religious 

-- -- -- -- -- -- 

person 

5 Others 2.7 1.7 2.9 0.8 -- 1.9 

Total 100 100 100 100 100 100 

It is seen that at the lowest level, 

treatment has been sought mostly from 

government facilities and NGOs (72% in 

toto). However, going upwards on the 

income scale, this percentage decreases 

and the percentage of episodes for 

which treatment has been received from 

private facilities increases. At the highest 

income stage level, only 28 percent 

of the episodes have been treated at 

government facilities, and the remaining 

72 percent have received treatment at 

private health facilities. 

7.2.6 Out-of-pocket expenses 

incurred on treatment 

In Table 7.11, the average expenditure 

incurred by the PLWHA on the treatment 

of illness episodes is presented with 

reference to the source of treatment. 

The expenditure incurred by households 

includes amount spent on fees, medicines 

and clinical tests, transport costs, as well 

as bribes and tips. It is seen from the table 

that whatever the source of treatment, 

the households have to make a certain 


97

Table 7.11 

Expenditure incurred by PLWHA for treatment of non-hospitalised illness 

episodes by source of treatment 


Source of treatment Rural Urban Total 

Male Female Male Female Male Female 

1 Government 251 266 674 157 435 228 

2 Private 790 458 810 886 799 556 

3 Charitable trust/NGO 67 24 75 54 70 30 

4 Faith healer/religious person -- -- -- -- -- -- 

5. Others 140 25 80 50 134 33 

All 440 279 684 284 549 281 

There is a gender 

difference in 

the average 

expenditure 

incurred per 

illness episode 

irrespective of 

the source of 

treatment 

minimum amount of expenditure. While 

the average expenditure per episode has 

been the least in the case of treatment 

from NGOs, it has been the highest for 

treatment from private doctors/clinics. 

As already seen in Table 7.10, none of 

the respondents have sought treatment 

from faith healers/religious persons and 

hence there is no expenditure shown 

against it. The expenditure in instances 

where home remedies have been used is 

also very small. 

In the case of the rural sample, the 

average cost per illness turns out to 

be much less for women than for men 

in private health facilities, and in the 

urban sample, the same thing is noticed 

with respect to government facilities. 

In the rural sample where treatment is 

taken from government facilities and in 

the urban sample where it is taken 

from private facilities, it is seen that 

there is very little difference in the 

cost per illness episode for men and 

women – in fact, it is slightly higher for 

women. In total, however, it is noticed 

that there is a gender difference in the 

average expenditure incurred per illness 

episode irrespective of the source of 

treatment with cost per treatment being 

less for female PLWHA than for male 

PLWHA. 

7.3 Details about 

hospitalisation cases 

7.3.1 Frequency of 

hospitalisation reported by 

PLWHA 

All the 478 sample PLWHA were asked 

details of how frequently they were 

hospitalised after testing HIV-positive and 

the number of times of hospitalisation 

during the year prior to the date of 

interview. These details are presented in 

Table 7.12. 

The percentage reporting hospitalisation 

since they were tested HIV-positive and 

the percentage reporting hospitalisation 

in the last one year is nearly the same for 

the both female and male samples of the 

PLWHA. A few important observations are 

worth mentioning. First, the percentage 

reporting hospitalisation is much 

higher for men as compared to women. 

While more than 65 percent men were 

hospitalised, both during the time since 

detection and during the reference one 

year period; in the case of women this 

percentage was much lower at 37 percent. 

Secondly, the percentage of PLWHA who 

were hospitalised as well as the average 

number of times they were hospitalised 

has increased with the advance in the 

stage of infection. Thirdly, no instance 


Table 7.12 

Frequency of hospitalisation reported by PLWHA by stage of HIV infection and 

number of years back HIV was detected 

Percent 

reporting 

hospitalisation 

Hospitalisation since detected 

HIV-positive 

Average 

number of 

times 

Frequently 

hospitalised 

(%) 

Percent 

reporting 


Number of times hospitalised 

in the last one year 

Average 

number of 

times 


Frequently 

hospitalised 

(%) 

By sex 

Male 66.2 2.14 1.7 65.1 1.77 -- 

Female 37.8 2.37 -- 37.3 1.63 -- 


Stage 1 24.1 1.75 -- 24.1 1.35 -- 

Stage 2 41.7 1.93 -- 41.1 1.32 -- 

Stage 3 64.4 2.11 1.9 62.6 1.66 -- 

Stage 4 92.7 2.84 1.6 92.7 2.40 -- 

By no. of years back HIV status detected 

Upto 1 year 46.7 1.83 -- 46.2 1.67 -- 

2-5 years 59.8 2.45 2.0 59.0 1.80 -- 

> 5 years 50.0 2.24 -- 47.1 1.56 -- 

All 53.8 2.21 1.2 52.9 1.73 -- 

of frequent/continuous hospitalisation 

has been reported during the one year 

reference period. However, while 1.7 

percent of men have reported frequent 

hospitalisation since the detection of 

their HIV-positive status, these have been 

reported in stages three and four of the 

infection. Finally, this table once again, 

reiterates the point that the number of 

years since testing HIV-positive may not 

be indicative of the stage of infection. 

There is no trend in the percentage 

hospitalised according to the number of 

years since testing positive. 

7.3.2 Nature of illness 

(Hospitalisation cases) 

As in the case of non-hospitalised illness 

episodes, in the case of hospitalisation 

also, fever (20%), loose motion/diarrhoea 

(34%) and tuberculosis (11.5%) emerge 

as the common health problems 

suffered by PLWHA as can be seen from 

Table 7.13. 

While calculating the average number 

of days hospitalised, cases in which 

the PLWHA were in the hospital at the 

time of interview have been excluded. 

The average number of days of being 

admitted in a hospital at one time is 

nearly ten days for men and 13 days for 

women and 11 days on the whole. Among 

the common diseases, an average of 

around 11.5 days has been reported for 

respiratory infections, headache, body 

ache, jaundice and tuberculosis. 

7.3.3 Source of treatment 

(Hospitalisation) 

The percentage distribution of the 

hospitalised cases according to the 

source of treatment indicates that 

while nearly 59 percent seek treatment 


99

Table 7.13 

Distribution of hospitalisation cases by nature of illness suffered by HIV-positive men and women and 

number of days hospitalised 


Nature of illness Male Female All Avg. no. of days hospitalised 

Male Female All 

1 Respiratory infection 6.4 7.3 6.7 16.8 8.6 14.2 

2 Malaria -- - -- -- -- -- 

3 Fever 23.7 12.2 20.3 9.0 21.1 11.1 

4 Headache, bodyache etc. 2.4 6.5 3.6 8.7 19.6 14.5 

5 Weakness 2.0 1.6 1.9 8.7 17.5 10.9 

6 Typhoid 2.0 0.8 -- 7.7 25.0 10.1 

7 Jaundice 0.3 -- 0.2 15.0 -- 15.0 

8 Sexually transmitted diseases 2.0 3.2 2.4 10.5 12.7 11.4 

9 Loose motion/diarrhoea 36.8 27.6 34.1 8.9 9.6 9.1 

10 TB 11.1 12.2 11.5 12.8 21.0 15.4 

11 Skin diseases 4.1 4.1 4.1 6.1 12.8 8.1 

12 Gynaecological/reproductive 

-- 6.5 1.9 -- 5.9 5.9 

problems 

13 Meningitis and viral encephalitis 0.3 -- -- -- -- 3.0 

14 Others 8.9 18.0 11.7 9.5 9.3 9.5 

All Illness 100 100 100 9.8 13.2 10.8 

from government hospitals, about 26.5 

percent seek treatment from private 

nursing homes and the rest (nearly 

14%) from NGOs and charitable trusts. 

The percentages are somewhat similar 

to those in non-hospitalised illness 

episodes although the percentage seeking 

treatment from government hospitals and 

NGOs has increased by around 5 percent 

each, and that from private hospitals 

has decreased by around 9 percent 

in comparison with non-hospitalised 

illness. Generally for hospitalisation, 

people, especially poor/low-income 

households prefer government health 

facilities since hospitalisation could 

be prohibitively expensive in a private 

nursing home. 

Table 7.14 

Distribution of hospitalisation cases by source of treatment for PLWHA by 

rural/urban break-up 


Source of treatment Rural Urban Total 


1. Government hospital 59.4 67.1 48.5 73.1 54.6 69.6 

2. Private nursing home 23.0 23.3 37.1 15.4 29.3 20.0 

3 Charitable trust/NGO 17.6 9.6 13.6 11.5 15.8 10.4 

4. Faith healer/religious -- -- 0.2 -- 0.2 -- 

person 

Total 100 100 100 100 100 100 


It is seen that both in rural and urban 

areas, more women than men take 

treatment in government hospitals. While 

in the rural areas, a similar percentage 

of men and women take treatment 

from private hospitals, in urban areas 

more men take treatment from private 

hospitals than women. In totality, it is 

seen that while 30 percent men take 

treatment in private hospitals, the figure 

is only 20 percent in the case of women. 

Table 7.15 below gives the distribution 

of hospitalisation cases with reference to 

annual household income groups. 

Once again, it is seen that as in the 

case of non-hospitalised illnesses, the 

percentage of PLWHA seeking treatment 

in private hospitals generally increases 

with increased income. In the lowest 

income group, while 60 percent of the 

cases have been treated in government 

hospitals and 21 percent through NGOs, 

only 18 percent have received treatment 

from private hospitals. However, at 

the highest income level, 83 percent 

of the cases have received treatment 

in private health facilities with only 

the remaining 17 percent going to 

government hospitals. 

7.3.4 Household expenditure 

on hospitalisation 

The direct cost of hospitalisation includes 

amount paid as room rent, doctor’s 

fee and cost of medicine, clinical test, 

surgery and transport. In addition, there 

could be expenses like a special diet 


Table 7.15 

Distribution of hospitalisation cases by source of treatment 

and by annual household income groups 

Upto 

20000 

20001- 

30000 

Annual household income (Rs) 

30001- 

41000 

41001- 

84000 


Above 

84000 

1 Government 60.0 58.3 71.2 58.5 16.7 59.0 

2 Private 18.1 27.1 20.3 33.0 83.3 26.5 

3 Charitable trust/NGO 21.3 14.6 8.5 8.5 -- 14.2 

4 Faith healer/religious 0.6 -- -- -- -- -- 

person 

Total 100 100 100 100 100 100 

All 

Table 7.16 

Average expenditure incurred per hospitalisation case 

by PLWHA by source of treatment 


Source of treatment Male Female All 

1. Government 811 768 796 

2. Private 3,996 4,544 4,119 

3. Charitable trust/NGO 373 326 363 

4. Faith healer/religious person -- -- -- 

5. Others 600 -- 600 

Total 1,674 1,477 1,616 


101

Irrespective of the 

income level, all 

the households 

had borrowed 

to meet the 


expenses 

for the patients and lodging, food and 

travel costs for the caregivers. At times, 

the households may have to pay tips/ 

bribes to the hospital staff to get better 

care and attention. Table 7.16 shows the 

average amount spent by the household 

per hospitalisation case according to the 

source of treatment. 

T h e a v e r a g e e x p e n d i t u r e p e r 

hospitalisation is Rs. 1,674 for men, 

Rs. 1,477 for women and Rs. 1,616 on 

the whole. While the expenditure per 

episode is higher for men in the case 

of government facilities and NGOs, it 

is higher for women in private health 

facilities. The average expenditure per 

hospitalisation is the highest for private 

hospitals/nursing homes and the lowest 

for treatment from NGOs/charitable 

trusts. Although the expenditure per 

episode in government hospitals is only 

Rs. 796, it could still be a big burden 

on the households which belong to the 

lowest economic strata. The difference 

in expenditure per episode between 

hospitalisation in private and government 

hospitals clearly indicates why a higher 

percentage of PLWHA go to government 

hospitals for treatment. 

T h e e x p e n d i t u r e i n c u r r e d p e r 

hospitalisation case analysed on the basis 

of the annual household income shows 

that generally the average expenditure 

per hospitalisation case increases with 

an increased annual income. Analysed 

source-wise, it has shown extremely 

surprising results. It is seen that as the 

income increases, the expenditure on 

government hospitals also increases. This 

is not the case when the hospitalisation is 

either in a private hospital or a charitable 

trust. The average expenditure in the 

lowest income group considering all 

sources is Rs. 1,055, and is Rs. 517 for 

government hospitals. The survey also 

tried to find out how the HIV affected 

households bear the burden of illness 

and expenditure. 

7.3.5 Source of financing 


Tables 7.18 and 7.19 examine the sources 

of financing of hospitalisation cases 

based on annual household income 

( Table 7.18) and stage of infection 

(Table 7.19). 

On the whole, the households could 

manage the expenses with their past 

Table 7.17 

Expenditure incurred per hospitalisation case by PLWHA 

by source of treatment and annual household income groups 



Annual household income (Rs.) 

Upto 

20,000 

20,001- 

30,000 

30,001- 

41,000 

41,001- 

84,000 

Above 

84,000 

Total 

1 Government (codes1&2)* 517 795 775 1287 2137 813 

2 Private (codes3) 3,998 2,881 4,870 4,122 5,882 4,119 

3 Charitable trust/NGO (codes5) 86 771 742 557 363 363 

4 Faith healer/religious person (codes 7) -- -- -- -- -- -- 

5 Others 600 -- -- -- -- 600 

Total 1,055 1,365 1,605 2,160 5,258 1,626 


Table 7.18 

Distribution of hospitalisation cases by source of financing hospitalisation and 

annual household income groups 


Source of financing 

Annual household income 

Upto 

20,000 

20,001- 

30,000 

30,001- 

41,000 

41,001- 

84,000 

Above 

84,000 

Total 

Past savings 19.2 22.5 7.7 19.2 25.0 18.4 

Liquidation of assets 12.8 15.0 26.9 23.1 -- 16.7 

Borrow from money lender/ 

other financial institution 

32.1 15.0 34.6 23.1 25.0 27.0 

Loan from employer -- 5.0 -- -- 25.0 1.7 

Borrow from friends and 

relatives 

19.2 30.0 30.8 19.2 25.0 23.6 

NGO support 16.7 12.5 -- 15.4 -- 12.6 

Others -- -- -- -- -- -- 

Total 100 100 100 100 100 100 

Table 7.19 

Distribution of hospitalisation cases by source of financing hospitalisation 

and stage of infection 


Source of financing Stage 1 Stage 2 Stage 3 Stage 4 All 

Past savings -- 30.0 16.0 17.7 18.4 

Liquidation of assets 42.9 23.3 12.0 16.1 16.7 

Borrow from money lender/ 

other financial institution 

57.1 20.0 28.0 25.8 27.0 

Loan from employer -- -- 2.7 1.6 1.7 

Borrow from friends and 

relatives 

-- 23.3 30.7 17.7 23.6 

NGO support -- 3.3 10.7 21.0 12.6 

Others -- -- -- -- -- 

Total 100 100 100 100 100 

savings only for 18 percent of the 

hospitalisation cases. Except the highest 

income households, all the others had 

resorted to liquidation of assets to 

finance hospitalisation. Irrespective of 

the income level, all the households had 

borrowed to meet the hospitalisation 

expenses. 

Although the source of financing 

hospitalisation with reference to the stage 

of infection does not show any clear trend, 

except that at stage 4, the households seem 

to rely on all the sources to finance the 

hospitalisation expenses. The dependence 

on NGOs also increases with the increase 

in the stage of infection 


103


• The prevalence rates of both nonhospitalised 


are higher for HIV households as 

compared to non-HIV households, 

indicating a heavy burden of diseases 

on HIV households. 

• A good number of the sample PLWHA 

had gone in for the HIV test after 

suffering from prolonged illness like 

undiagnosed fever, tuberculosis or 

diarrhoea. 

• The burden of diseases generally 

increases with the advance of stage 

of infection and the PLWHA have to 

spend a lot of money even when they 

undergo treatment from government 

hospitals. 

• In order to meet this burden, they not 

only have to dip into their savings 

but also have to borrow money. In 

the worst-case scenario, they have 

to resort to liquidation of assets. In 

fact, except for households in the 

highest income group, all the rest 

have resorted to it. 


Stigma and Discrimination, 

Knowledge and Awareness 

about HIV and AIDS


Chapter 8 

Stigma and Discrimination, 

Knowledge and Awareness 

about HIV and AIDS 

8.1 Introduction 

HIV is an infection that preys on social, 

economic and community vulnerabilities. 

From the beginning, the infection has 

been accompanied by social responses 

of widespread stigma and discrimination. 

Because of its association with lifestyle 

choices that are considered socially 

unacceptable by many, HIV infection is 

widely stigmatised. People living with 

the virus are discriminated against. 

Equally responsible for this attitude is 

the lack of proper knowledge among 

people about the infection and the many 

misconceptions that exist around it. 

Stigmatisation and discrimination not 

only affect the rights of the people living 

with this condition, it discourages them 

from disclosing their status, in many 

cases, even to their spouses and hence 

contributes to others getting infected. 

This chapter analyses the stigma and 

discrimination faced by the sample 

PLWHA in four different settings in 

the state of Tamil Nadu, namely their 

family, the community in which they 

live, their workplace and the healthcare 

facilities where they seek treatment. 

This chapter also includes the views 

and attitude of the general population 

about HIV and AIDS, since stigma and 

discrimination against PLWHA arise 

mostly due to lack of knowledge and 

awareness and misconceptions about 

the infection. Before discussing the 

stigma and discrimination faced by 

PLWHA, details about the ways in which 

the sample PLWHA discovered their HIV 

status and the disclosure of their status 

to their family members and others are 

presented. 

8.2 Discovering HIV status 

An HIV infected person would not know 

his/her HIV status unless he/she goes in 

for a blood test after a prolonged illness 

or at the time of donating blood or during 

pregnancy. Health counsellors also 

recommend the spouses of those who 

test HIV-positive to go in for voluntary 

testing. Table 8.1 shows that while 

nearly 64 percent of the men who had 

tested HIV-positive had gone in for 

a test after prolonged illness, only 24 

percent of women had gone in for testing 

after prolonged illness. A number of 

women, as high as 64 percent, had 

gone in for voluntary testing and a large 

percentage of such women had done 

so after discovering the HIV status of 

their husbands. Around 9 percent of 

the women discovered their HIV status 

during pregnancy and a few men also 

discovered their status when their wives 

tested positive during pregnancy. 

Stigma and Discrimination 

107

Table 8.1 

Distribution of PLWHA by ways of discovering their HIV status 


Characteristics Rural Urban Total 


Discovering HIV status 

Voluntary testing 28.2 62.7 30.6 66.3 29.4 64.1 

After prolong illness 66.7 23.8 61.2 25.3 63.9 24.4 

During pregnancy-spouse/self 0.7 11.9 -- 3.6 0.4 8.6 

Blood test at the time of joining 1.5 0.8 3.7 -- 2.6 0.5 

a job 

Others 3 0.8 4.5 4.8 3.7 2.4 

No. of years back HIV was detected 

Less than a year 48.9 48.4 32.1 30.1 40.5 41.2 

1-3 years 31.9 28.6 51.5 44.6 41.6 34.9 

3--5 years 12.6 15.1 11.2 15.7 11.9 15.3 

5+ 6.7 7.9 5.2 9.6 6 8.6 

Place of testing 

Government hospital 54.1 65.9 58.2 65.1 56.1 65.6 

Private hospital/clinic 45.9 34.1 41.8 34.9 43.9 34.4 

Mode of infection 

Sexual contact (heterosexual) 85.9 88.1 85.8 92.8 85.9 89.9 

Sexual contact (homosexual) 0.7 1.6 1.5 -- 1.1 1 

Blood transfusion/donation 5.2 6.3 3 2.4 4.1 4.8 

Needle sharing 3.7 0.8 6 -- 4.8 0.5 

Others 4.4 3.2 3.7 4.8 4.1 3.8 

N (Number of persons) 135 126 134 83 269 209 

The sample consists mostly of those who 

had tested positive in the last three years; 

they account for around three-fourths of 

the sample PLWHA. Most of them had 

gone to government hospitals for the 

HIV test. About 56 percent of the men 

and 66 percent of the women had got the 

test done in government hospitals, and 

the remaining 44 percent men and 34 

percent women had it done from private 

hospitals/clinics. 

In India, the main route of HIV transmission 

is through sexual contact and this route 

accounts for approximately 86 percent 

of the HIV infections in the country. The 

remaining 14 percent are by other routes 

such as blood transfusion, parent-tochild-transmission 

and through injecting 

drugs, particularly in north eastern states 

and in some metropolitan cities (NACO, 

2005). The present sample also shows that 

the main mode of transmission of HIV 

infection is through sexual contact, that 

too heterosexual contact. For as many as 

90 percent of women and 86 percent of 

men, the mode of transmission of HIV 

is reported to be through heterosexual 

contact. 


8.3 Reaction to HIV status 

8.3.1 Initial reaction 

The survey tried to find out how the 

affected/infected persons and their 

family members reacted as soon as the 

HIV status was discovered and Table 8.2 

presents these findings. 

As expected, in more than 65 percent of 

the cases, the initial reaction had been 

one of shock. Many of them could not 

believe it and there were those who felt 

embarrassed. A few of them did not 

want to face their family members and 

a small percentage decided to stay away 

from their family and spouse. Around 

Table 8.2 

Distribution of sample PLWHA by reaction to their HIV status 




Initial reaction (self)* 

Shocked 61.4 70.6 64.9 69.9 63.2 70.3 

Embarrassed 43.7 43.6 33.6 39.8 38.7 42.1 

Could not believe 28.9 24.4 32.8 21.7 30.9 23.4 

Didn’t want to face the family 8.9 4.8 26.1 9.6 17.5 6.7 

Decided to stay away from the 

3 1.6 3.7 3.6 3.3 2.4 

family & spouse 

Decided to keep HIV status secret 14.1 10.3 17.9 9.6 16 10 

Others 0.7 1.6 -- 4.8 0.4 2.9 

Initial Reaction of spouse/family members* 

Shocked 54.1 30.9 62.7 39.8 58.4 34.4 

Denied/disappointed 8.9 6.3 17.9 7.2 13.4 6.7 

Empathised 9.6 25.4 9 15.7 9.3 21.5 

Embarrassed 22.2 15.9 23.9 19.3 23 17.2 

Supportive 50.4 46 38.1 37.3 44.2 42.6 

Disowned by the family 0.7 7.1 2.2 8.4 1.5 7.7 

Spouse deserted 5.9 4 2.2 1.2 4.1 2.9 

Not informed anybody 9.6 12.7 11.2 16.9 10.4 14.3 

Others 1.5 3.2 5.2 12 3.5 6.7 

Current attitude of spouse/family members* 

Neglected, isolated, verbally/ 

6.7 16.7 11.9 20.5 9.3 18.2 

physically teased 

All are supportive 66.7 58.7 64.9 57.8 65.8 58.4 

Family is not but spouse is 

15.6 8.7 13.4 7.2 14.5 8.1 

supportive 

Initial hesitation, but then supportive 7.4 10.3 22.4 22.9 14.9 15.3 

Others (deprived of using basic 5.9 5.6 4.5 7.2 5.2 6.2 

amenities at home, asked to leave 

home) 

Total number 135 126 134 83 269 209 

*Multiple Responses 


109

In cases where 

the family is not 

supportive but 

the spouse is, it 

is noticed that 

more women are 

supportive of 

their HIV-positive 

husbands (14.5%) 

than men of their 

HIV-positive wives 

13 percent had initially decided to keep 

their HIV status as a secret on account of 

perceived discrimination or rejection. 

As far as the initial reaction of the 

spouse/family members is concerned, it 

is seen that quite a large percentage were 

shocked and disappointed. However, 

in about 43 percent of the cases they 

were supportive and here no gender 

divide is noticed. Surprisingly, in a larger 

percentage of cases the family/spouse 

sympathised with the female PLWHA 

(21.5%) rather than the male PLWHA 

(9.3%). Again, surprisingly, in 4.1 percent 

cases male PLWHA were deserted 

by their spouses while in the case of 

female PLWHA this figure was lower 

at 2.9 percent. However, 7.7 percent of 

female PLWHA were disowned by their 

family in comparison with 1.5 percent 

male PLWHA who were subjected to this 

treatment. 

8.3.2 Current attitude of 

spouse/family members 

The current attitude of the family 

members is quite encouraging, as 80 

percent of the male and 74 percent of 

the female PLWHA have reported that 

their families are quite supportive in 

spite of there being a slight hesitation for 

a few in the beginning. This speaks for 

the strong family ties in India. However, 

here again, there is a gender gap in the 

percentage receiving support from the 

family, although there is no rural/urban 

divide. Also, in cases where the family 

is not supportive but the spouse is, it is 

noticed that more women are supportive 

of their HIV-positive husbands (14.5%) 

than men of their HIV-positive wives 

(8.1%). Again, the percentage reporting 

problems like “deprived of using basic 

amenities” and being asked to leave the 

home etc, is more in the case of women 

than for men and this gender difference 

is more marked in urban areas. 

For both men and women, the contexts 

and forms of HIV and AIDS related 

discrimination and stigmatisation would 

appear to be similar but it is the context 

of ‘relationship’ that sets apart the 

experience of women from that of men. 

Discrimination like neglect, isolation, 

verbal teasing was reported by a higher 

percentage of women in both urban and 

rural areas. 

In the FGD that was conducted at 

Cambam in the Theni district, there were 

participants who had been treated well 

by their families as well as those who 

had faced discrimination. One of the 

participants informed the group that his 

mother, brothers and sisters were taking 

extra care of him since they felt that he 

was not going to live for long. However, in 

case of a woman participant her brother’s 

family supported her after she became a 

widow but they asked her to keep her bed 

and vessels separately and were always 

scared of catching the infection from 

her to the extent that they would not 

even allow her to kiss her daughter who 

was HIV-negative. The majority of the 

participants in the FGD did not complain 

of discrimination within the family. 

8.3.3 Coping with the 

situation 

As seen earlier, when their HIV-positive 

status was detected, most of the people 

were initially shocked, embarrassed or 

could not believe it. The survey tried 

to find out from the PLWHA how they 

managed to cope with the situation and 

how they got over the initial shock. Table 

9.3 presents the percentage distribution 

of the PLWHA with reference to various 

types of coping mechanisms adopted by 

them and the nature of moral support 

received by them from various people. 

Around 48 percent of the HIV-positive 

men and 44 percent of the women 

reported that the counselling received 


from counsellors helped them to come 

to terms with the situation. 

Table 8.3 

Distribution of PLWHA by coping 

mechanism adopted to get over initial 

shock/disbelief etc 


Characteristics Male Female 

Counselling 47.6 43.5 

Confidently 3.7 6.2 

Family support 13.4 10.1 

Friend support 0.4 1 

Became alcoholic -- -- 

Decided to keep HIV -- -- 

status secret 

Help others 0.4 -- 

NGO support 1.6 -- 

Wanted to know how 33.1 39.2 

to live with HIV status 

Total 100 100 

A higher percentage of women (6.2%) as 

compared to men (3.7%) decided to face 

the situation boldly. Some of them did 

receive moral and emotional support 

from their family and friends and also 

from NGOs. It is interesting to note that 

after testing positive, nearly 35 percent 

of the respondents wanted to know more 

about the infection and the ways and 

means of leading a quality life in spite of 

their HIV status. 

8.4 Disclosure of HIV status 

Whether an individual who is infected 

by HIV would disclose his/her status to 

others would depend upon the kind of 

reaction that the individual expects from 

them. As seen in the table, around 13 

percent of the PLWHA’s initial reaction, i.e. 

as soon as they were tested positive, was 

not to disclose their status to anyone. It is 

seen from Table 8.4 that while 88 percent 

of women in the sample informed their 

spouses immediately, the percentage 

of men who did the same is lower at 

69.3 percent. But of those who have not 

informed their spouses even after one 

year, the percentage sample of women is 

slightly higher at 5.2 percent as against 3.5 

percent for the men. This could probably 

be because if the woman is HIV-positive 

without her husband being the same, her 

perception would probably be that her 

husband/family would not support her 

or keep her. Hence, this refusal to make 

Table 8.4 

Distribution of PLWHA by disclosure of status 




Percentage who initially decided to keep 14.1 10.3 17.9 9.6 16 10 

HIV status a secret 

Percentage who informed their spouse 

Immediately 75.2 91.9 63.2 83.6 69.3 88.3 

Within six months 11.2 3.5 24.6 8.9 17.7 5.8 

Within one year 6.8 1.1 7.9 -- 7.4 0.7 

After one year 3.4 -- 0.8 -- 2.1 -- 

Not informed their spouse 3.4 3.5 3.5 7.5 3.5 5.2 

Not disclosed to anyone in the community 65.9 50 75.4 65.1 70.6 56 

N (Number of persons) 135 126 134 83 269 209 



111

Around 20 

percent of the 

households had 

changed their 

place of residence 

after one of 

their household 

members was 

detected HIVpositive 

a disclosure could be for the security of 

her future life. 

The fact that so many of the respondents 

informed their spouses immediately 

after the diagnosis is an encouraging 

sign since this would reduce the chances 

of their transmitting the infection to 

their spouses. A high percentage of 

the sample, nearly 71 percent of men 

and 56 percent of women have not 

disclosed their HIV-positive status in the 

community, fearing, in all probability, 

the stigma and discrimination they will 

fall victim to. 

8.5 Migration 

The survey tried to find out whether 

the households changed their place of 

residence after one of their household 

members was detected HIV-positive. It 

is clear from Table 8.5 that around 20 

percent of the households had changed 

their place of residence. Of the total 

number of households that had changed 

the place of residence, more than 40 

percent of them had shifted within the 

same village/city. It is interesting to 

observe that the percentage of households 

moving from rural to urban and urban to 

rural is similar. Inter-state migration has 

been very marginal. 

Nearly 12 percent of the households had 

to change their place of residence since 

they were asked to vacate the house by 

the owner because of the HIV status of 

one of the family members, and around 

15 percent shifted their residence, as they 

did not want their status to be known to 

others. While 12 percent have changed 

their residence because they could no 

longer afford the earlier one, 3.7 percent 

had to move away as they had lost 

property, indicating the financial burden 

the illness and its treatment brings on 

the household. About 10 percent had 

Table 8.5 

Distribution of PLWHA reporting 

change of residence and reasons 

to migrate in order to seek medical 

treatment. 

8.6 Stigma and 

discrimination faced by 

PLWHA 


Characteristics 

Percentage of household 19.8 

reporting changing of residence 

after deducting HIV 

Type of movement 

Within the same city/village 42 

From city to village 8.6 

From village to city 11.1 

From one city to another city 22.2 

From one village to another 14.8 

village 

One state to another state 1.2 

Reasons for changing the 

residence* 

Search of employment 18.5 

Could not afford earlier place of 12.3 

residence 

To seek medical treatment 9.9 

Loss property 3.7 

Reasons of anonymity 14.8 

Asked to vacate the house 12.3 

because of HIV status 

Others 28.4 


Stigma and discrimination faced by the 

PLWHA at different settings, namely 

family, community, workplace and the 

healthcare facilities are presented in this 

section. 

8.6.1 Discrimination in family 

& community 

In most developing countries, the 

families and communities generally 


provide supportive environment for 

illness management and treatment 

(Bharat, 1996). However, the same study 

found that although majority of those 

who disclosed their HIV status to their 

families received care and support, it was 

generally men rather than women who 

qualified for such care. Gender seems to 

be a strong determinant of the type of 

response one receives from the family: 

daughters, wives and daughters-in-law 

experience higher levels of discrimination 

than men (Bharat et al 2001). 

The community’s perception about the 

epidemic also influences the family’s 

responses to the infected individual. If 

the family expects isolation and ostracism 

from the community, then the family may 

not include the HIV-positive individual 

in the family. Table 8.6 presents stigma 

and discrimination faced by PLWHA in 

the community and neighbourhood. 

It is seen in Table 8.4 that many of the 

PLWHA have not disclosed their status 

in the community. Of those who have 

disclosed their status, about 10 percent 

have reported discrimination in the 

form of neglect, abuse, social boycott 

of family and children. Other studies 

also give the evidence of reactions like 

ostracism, differential treatment at death, 

and discrimination in schools towards 

children of infected parents (Bharat et al 

2001; ILO 2003). 

The presence of an HIV-positive individual 

does seem to affect the marriage and 

job prospects of other family members 

to some extent. Here again, there is 

a difference in the attitude of society 

towards men and women. While only 0.4 

percent of HIV-positive men reported that 

their HIV status was affecting the marriage 

prospects of their siblings, 2.4 percent of 

positive women reported this problem. 

Similarly, a small percentage of PLWHA 

complained that their HIV status was 

Table 8.6 

Stigma and discrimination faced 

by PLWHA in the community/ 

neighbourhood by sex 


Percentage reporting 

that they are treated 

differently or badly 

Type of discrimination 

faced by those reporting 

stigma/discrimination* 

Total 

Male Female 

10 10.5 

Neglected, isolated 35.2 34.2 

Verbally abused, teased 16.7 9.8 

Children not allowed to 20.4 14.6 

play with other children/ 

anganwadi centre 

Socially boycotted or 16.7 22 

debarred from public 

amenities 

Refused house for 1.8 4.9 

renting 

Others 9.3 14.6 

Percentage of PLWHA 0.4 2.4 

whose siblings’ marriage 

prospect was affected 

Percentage of PLWHA 

whose family members’ 

job prospects was 

affected 

0.7 2.4 


affecting the job prospects of other family 

members and this percentage reporting 

discrimination is surprisingly higher for 

women. 

8.6.2 Discrimination at 

workplace 

Every person has a right to gainful 

employment and the right to earn 

a living. However, for a number of 

HIV infected persons, getting gainful 

employment could become a problem 

due to stigma and discrimination against 

such persons. In a workplace, stigma 

and discrimination against PLWHA can 

manifest itself through discriminatory 


113

hiring and promotion practices and 

work allocation, establishment of unfair 

benefit packages and negative attitude of 

employers, co-workers and managers. In 

the present study, details about the type 

of discrimination faced by the PLWHA 

in the workplace, attitude of employers 

and their colleagues were gathered from 

those who were currently employed. 

Table 8.7 

Distribution of the PLWHA according 

to their work status 

Characteristics Number Percent 

Currently working 363 76.0 

Never employed 57 11.9 

Stopped working 58 12.1 

at the time of 

survey 

Total 478 100 

Table 8.8 

Distribution of PLWHA by disclosure of status and 

discrimination faced at workplace 


Percentage of PLWHA who changed the 

job after testing HIV-positive 

Percentage of PLWHA who disclosed 

their HIV status to the employer 

Percentage of PLWHA who faced 

discrimination 

Percentage of PLWHA receiving support 

from employer 

About 12 percent of the respondents 

were never employed. The workplace, 

which is considered to be the second 

home and where an individual spends 

his maximum time, is a microcosm of 

the whole community, which mirrors 

societal attitudes. 


HIV household 


11.3 13.4 12.2 

18.5 27.5 22.6 

14.3 8.6 11.1 

75.0 85.7 81.0 

The PLWHA who were currently employed 

were asked whether they changed their 

job after they were tested positive. As 

seen in Table 8.8, only about 12 percent 

had changed jobs and this percentage 

is more or less the same for urbanites 

as well as rural folk. Only 23 percent of 

the PLWHA who are currently employed 

have disclosed their HIV status to their 

employers and the main reason for not 

disclosing their HIV status is the fear 

of losing the job. It may be surprising 

to know that only a small percentage 

of those who have disclosed their HIV 

status have reported that they have 

faced discrimination and in fact many of 

them, especially in the urban areas, have 

reported that they are receiving support 

from their employers. This could be due to 

the fact that a number of them are working 

in a protective environment with NGOs 

and institutes which are in the field of HIV 

and AIDS. These employees are receiving 

support in the form of reimbursement of 

medical expenditure and paid leave. 

In the FGD, many of the participants 

informed that they had not disclosed their 

HIV-positive status to their employers 

fearing discrimination. However, some 

women working as labourers mentioned 

that neither those who were working with 

them nor their employers treat them 

badly or differently although they are 

unable to attend to work on many days 

due to ill health. 

8.6.3 Discrimination at health 

facilities 

The healthcare setting has emerged as 

the most frequently encountered place of 

discrimination, followed by familial and 

community contexts. The various forms of 

discrimination in a health facility include 

refusal of treatment, discriminatory 

precautions and lack of confidentiality. 

Doctors often refuse to aid in the delivery 

of a positive pregnant woman, despite 


minimal risk of contracting the infection 

(ILO 2003). The discrimination can also 

appear in the form of refusal to touch 

a patient, levying additional charges, 

and agreeing to treat only if the mode 

of infection was not sexual. In a study 

conducted in Mumbai and Bangalore, 

many healthcare providers and facilities 

were found to deny care, treat patients 

poorly, and stipulate conditions for 

agreeing to treat HIV patients (Bharat et 

al 2001). Table 8.9 presents percentage 

distribution of PLWHA reporting 

discrimination at health facilities in Tamil 

Nadu. 

About 17 percent of male and 11 percent 

of female PLWHA in Tamil Nadu reported 

that they had faced discrimination at 

healthcare facilities although there is 

no urban/rural divide. Among those 

reporting discrimination at health 

Table 8.9 

Distribution of PLWHA reporting discrimination at health facilities 




PLWHA reporting discrimination at health 17 11.1 17.2 10.8 17.1 11 

facilities 

Place of discrimination 

PHC/CHC 17.4 14.3 -- 11.1 8.7 13 

Government hospital 56.5 64.3 82.6 77.8 69.6 69.6 

Private doctor/hospital 26.1 21.4 17.4 11.1 21.7 17.4 

Type of discrimination* 

1 Neglected, isolated 16.7 16.7 31.7 23.5 24.7 19.5 

2 Verbally or physical abused, teased 22.2 20.9 9.8 23.5 15.6 21.9 

3 Refused medical treatment 19.4 16.7 12.2 17.6 15.6 17.1 

4 Referred to another health facility 22.2 16.7 21.9 23.5 22.1 19.5 

5 Refused access to basic facilities -- 4.2 2.4 -- 1.3 2.4 

6 Unnecessary use of protective gear 11.1 16.7 12.2 5.9 11.7 12.2 

7 Others** 8.3 8.3 9.8 5.9 9.1 7.3 

Attitude of other patients 

1 Neglected, isolated 11.5 21.4 40.7 25 26.4 23.1 

2 Verbally or physically abused, teased 3.8 -- 3.7 8.3 3.8 3.8 

3 Refused to seek treatment with HIV -- -- 14.8 8.3 7.5 3.8 

4 Restrictions on movement in ground -- 7.1 3.7 -- 1.9 3.8 

5 Status not known to others 19.2 14.3 14.8 25 17 19.2 

6 Not discriminated 53.8 50 22.2 16.7 37.7 34.6 

7 Others (refused to seek treatment along 11.5 7.1 -- 16.7 5.7 11.5 

with PLWHA) 

Reporting denial of admission at health 

facility 

3 4 8.2 3.6 5.6 3.8 


**Others include refused access to facilities like toilets and common eating and drinking utensils, non 

admission, shunting between wards/hospitals, doctor did not touch/gave wrong information 


115

Discrimination 

forces people to 

hide their status 

and may well lead 

to further spread 

of infection but 

the fact that it is 

happening at the 

hands of doctors 

and other health 

officials is very 

discouraging 

facilities, more than three-fourths have 

had bad experiences at government 

healthcare facilities. This was confirmed 

by the participants of the FGD. The 

general view was that although there is 

a government hospital (maybe a PHC) 

near Kandamkoil, the personnel were 

afraid of treating these PLWHA. A lady 

participant mentioned that although her 

husband was vomiting continuously and 

was taken to the hospital, he was refused 

treatment and had to be taken to the 

district hospital at night. 

Another young woman, presently a widow, 

narrated her experience during her child’s 

birth in 2000. She and her husband had 

been diagnosed as HIV-positive when 

she was five months pregnant. When the 

doctor at the nursing home came to know 

of this, he refused to take up her case. As a 

result, she went to a government hospital 

for delivery but because of her previous 

bitter experience did not disclose her 

status. A similar incident was recounted 

by another woman where her fatherin-law’s 

status was not disclosed while 

seeking treatment for his heart attack as 

they feared that treatment would have 

been refused if his HIV-positive status 

was known. Discrimination forces people 

to hide their status and may well lead 

to further spread of infection but the 

fact that it is happening at the hands of 

doctors and other health officials is very 

discouraging. 

The fact that only 22 percent of men and 17 

percent of women among those reporting 

discrimination, had mentioned that they 

were discriminated against at private 

health facilities, may give an impression 

that there is less discrimination in the 

private set up. But it has already been 

seen in the chapter on profile that the 

economic background of the PLWHA 

is very bad. Hence one can reasonably 

assume that only a small proportion of 

the PLWHA are likely to go to private 

health facilities. 

Of those PLWHA who had reported 

discrimination, about 37 percent were 

either refused medical treatment or were 

referred to another health facility; nearly 

40 percent felt that they were neglected 

and isolated or abused at the health 

facilities and about 4 percent complained 

that they were denied admission in a 

hospital. 

It is heartening to note that 38 percent 

of men and 35 percent of women did 

not face any discriminatory or hostile 

behaviour from other patients who were 

being treated along with them. However, 

in some cases their HIV status was not 

known to other patients, hence the 

question of discriminatory treatment 

does not arise. About 25 percent of 

PLWHA complained that they were 

isolated and neglected by other patients. 

In some of the cases, HIV-negative 

patients refused to get treatment along 

with PLWHA. 

8.7 Knowledge and 

awareness about 

HIV and AIDS and attitude 

towards PLWHA 

Stigma, negative responses and attitude 

towards PLWHA are generally the result 

of lack of knowledge about HIV and 

AIDS and in particular about the routes 

of transmission. Hence in this study, 

through a survey of non-HIV households, 

an attempt was made to find out about the 

general level of knowledge and awareness 

about HIV and AIDS. Both men and 

women in the age group of 20 to 60 years 

were asked a series of questions to judge 

their knowledge about the infection, and 

also to know their attitude towards 

PLWHA. In all, 1,203 persons – 559 men 

and 643 women – were interviewed in 


Table 8.10 

Distribution of respondents according to their knowledge and awareness 

about HIV and AIDS 




People reporting ever heard about HIV and AIDS 

Source of information* 99 97.1 100 99.3 99.5 98.1 

Radio 33.3 34.3 25.5 25.9 29.8 30.2 

TV 36.8 37.2 38.5 40.5 37.5 38.8 

Cinema hall 2 0.9 2.8 5 2.3 2.9 

Newspapers/books/magazines 11 5.9 9.5 6 10.3 5.9 

Posters/hoarding/drama/puppet show 5.4 3.2 6.3 5.8 5.8 4.5 

School/workplace 3.1 0.9 3.6 1.7 3.3 1.3 

Doctor/health workers 2.6 4.6 3.6 5.6 3.1 5.1 

Relatives/friends 5.9 11.6 9.9 9.4 7.7 10.6 

Others -- 1.2 0.2 0.2 0.1 0.7 

People who think HIV and AIDS can be 74.3 60.5 66.9 40.5 71 51 

prevented 

People who know where to go for 47.6 31.9 56.8 36.5 51.7 34.1 

voluntary testing for HIV and AIDS 

People willing to go for testing for HIV 47.6 31.9 56.8 36.5 51.7 34.1 

and AIDS 

People who know someone suffering 37.9 26.2 23.8 19.4 31.7 23 

from HIV and AIDS 

People who know anyone who died of 

AIDS 

43.4 40.4 26.6 22.7 36 32 


Tamil Nadu. The results of this survey 

show interesting facts. 

Almost everyone in the sample seems to 

have heard about HIV and AIDS and the 

media, especially, radio and television 

seem to have played a role in creating this 

awareness. While about 38 percent have 

come to know about the infection through 

various television channels, around 30 

percent have become aware of it through 

programmes or announcements on the 

radio. This is not surprising considering 

that a very high proportion of sample men 

and women are in the habit of watching 

television and listening to the radio quite 

regularly (Table 8.11). Interestingly, for 

about 8 percent men and 11 percent 

women, the source of information has 

turned out to be friends/relatives. 

Although everyone has heard about 

HIV and AIDS, not all of the respondents 

seem to have knowledge about other details 

like whether HIV and AIDS transmission 

could be prevented and where to go 

for voluntary testing etc. Only about 50 

percent of the women and 70 percent of 

the men knew that HIV and AIDS could 

be prevented, less than one-third of the 

women and 50 percent of men knew 

where to go for voluntary testing. Men 

appear to be more knowledgeable about 

information related to HIV and AIDS. 


117

Table 8.11 

Distribution of respondents by exposure to media 




Listen to radio 

Daily/weekly 85.5 82.3 74.2 71.1 80.5 77 

Occasionally/monthly 7.7 12.4 20.2 22.4 13.2 16.9 

Never 6.7 5.3 5.6 6.6 6.3 5.9 

Watch TV 

Daily/weekly 90.7 84.9 88.7 93.1 89.8 88.8 

Occasionally/monthly 6.7 10 8.9 5.3 7.7 7.8 

Never 2.6 5 2.4 1.6 2.5 3.4 

Go to cinema 

Weekly/daily 6.7 6.2 8.1 7.9 7.3 7 

Monthly 23.5 17.1 17.7 13.8 20.9 56.4 

Occasionally 53.4 54.6 58.1 58.5 55.5 21 

Never 16.4 22.1 16.1 19.7 16.3 15.5 

Read newspaper/magazines 

Daily 44.1 20.3 51.2 22.7 47.2 21.5 

Weekly/monthly 10.3 7.4 6.4 6.2 8.6 6.8 

Occasionally 35.7 50.4 27 35.2 31.8 43.2 

Never 10 21.8 15.3 35.9 12.3 28.5 

Total 100 100 100 100 100 100 

8.7.1 Knowledge about modes 

of transmission 

Table 8.12 presents percentage distribution 

of respondents according to their 

knowledge about the various modes of 

transmission. More than 50 percent of 

women and about 75 percent of men 

could mention all the right modes of 

transmission of HIV, which includes sexual 

contact, sharing a needle with an infected 

person, transfusion of infected blood and 

transmission from mother to child. 

It a p p e a r s t h a t m e n a re m o re 

knowledgeable than women regarding the 

right modes of transmission of the virus. 

There is, however, no urban/rural divide. 

However, the percentage of respondents 

not knowing even a single mode of 

transmission is almost negligible. 

Although a fairly high percentage of 

respondents knew the various modes 

of transmission, many of them also 

had misconceptions about the modes 

of transmission. Such myths and 

misconceptions accentuate the stigma 

and discrimination against HIV infected 

persons. Many of them seem to have a 

misconception that sharing shaving kits 

and razors (40%) as also mosquito bites 

(27%) could spread AIDS. A few of believe 

that hugging and kissing a PLWHA or 

sharing food and utensils and touching or 

shaking hands with PLWHA could infect 

them as well. 


Table 8.12 

Distribution of respondents according to their knowledge about mode of 

transmission of HIV and AIDS 




Reporting right mode of transmission 

All modes 73.9 58.4 73.4 52 73.7 55.4 

Some modes 24.8 37.8 25.4 46.7 25.1 42 

Not at all 0.3 0.9 1.2 0.7 0.7 0.8 

Others 1 2.9 -- 0.7 0.5 1.9 

People who had misconception that HIV and AIDS can spread through 

Hugging/kissing AIDS 14.2 10 10.2 5.7 12.5 8.2 

Sharing food/utensils 6.7 6.8 6.2 5.7 6.5 6.4 

Mosquito bite 24.8 24.6 29 31.2 26.6 27.4 

Touching/shaking hands 4.4 5.2 4.2 7.2 4.3 6.1 

Sharing toilet 11.1 13.8 8.2 8.5 9.9 11.6 

Sharing shaving kits/razors 38.9 39.5 42.1 41.5 40.2 40.3 

Who have heard of any other disease 49.2 42.2 64.1 37.5 55.8 40 

transmitted through sexual contact 

Who know that a person suffering from 

STI has greater chance of getting HIV 

and AIDS 

47 35.7 65.3 32.9 55.1 34.4 

As compared to women, men seem to 

know more about sexually transmitted 

infections. While more than 50 percent 

of the male respondents knew about 

STI, only 40 percent of women seem to 

have knowledge about this infection. A 

similar percentage of men and of women 

knew that a person suffering from STI 

has greater chances of getting HIV and 

AIDS. The knowledge about STI seems 

to be more among urban men and rural 

women as compared to rural men and 

urban women. 

Knowledge and awareness about 

condom assumes significance in the 

context of avoiding the spread of HIV 

infection. Unprotected sex with multiple 

partners and non-regular partners is an 

important mode of HIV transmission. In 

the present study, an equal percentage 

of men and women (49%) reported 

being aware of the uses of condoms in 

preventing pregnancy. While a higher 

percentage of men were aware that 

it could be used for HIV and AIDS 

prevention, a higher percentage of 

women knew that it could be used for 

prevention of STIs. However, on the 

whole, the level of knowledge seems 

very low. The percentage of people 

who reported the use of condoms was 

low. This knowledge regarding usage of 

condom for preventing transmission 

of HIV and AIDS is higher among the 

rural population as compared to urban 

population. In spite of various efforts 

being taken to promote the use of 

condoms, only a small percentage i.e. 

one-third of men and nearly one-fourth 

of women seem to know that condoms 

can be used to prevent HIV and AIDS. 


119

Table 8.13 

Distribution of respondents according to their knowledge about usage of condom 



People reporting right usage of condom 


Avoiding preg/FP method 48.7 49 47.9 49.7 48.4 49.3 

STI prevention 13.4 20.3 21.3 27.2 17 23.7 

HIV and AIDS prevention 37 29.9 30 22.6 33.8 26.3 

Others 0.8 0.8 0.8 0.5 0.8 0.7 

Percentage of people reporting using 

condom 

14.8 13.3 14.9 11.8 14.8 12.6 

8.7.2 Attitude of people 

towards PLWHA 

Stigma and discrimination contribute 

to the socio-economic vulnerability 

of PLWHA. Existing misconceptions 

regarding the spread of the infection have 

led to high-prevalence of discrimination 

and negative responses and attitudes of 

people towards PLWHA. 

Table 8.14 presents the percentage 

distribution of respondents according 

to their attitude towards PLWHA. The 

table clearly shows that people do have 

a negative attitude towards PLWHA and 

as compared to men, women are more 

prejudiced and have more of a negative 

attitude towards such persons. People are 

generally more hesitant to share food with 

PLWHA and even to allow their children 

Table 8.14 

Distribution of respondents according to their attitude towards PLWHA 



Reporting that they would Male Female Male Female Male Female 

Interact with the family having HIV patients 60.1 59.6 59.3 56.9 59.7 58.3 

Share food with the PLWHA 35.7 29.8 33.9 23.4 34.9 26.7 

Avail the health facility used by the PLWHA 30.2 23.0 28.2 17.8 29.3 20.5 

Allow their children to play with the children from a family 27.6 22.4 41.9 27.3 34.0 24.7 

having a PLWHA 

Send their children to a school where HIV-positive children 27.6 24.2 43.5 29.9 34.7 26.9 

study 

Purchase fruits vegetables etc from a shop keeper who is 34.7 33.0 49.2 45.7 41.1 39.0 

HIV-positive 

Accept a PLWHA as a teacher 30.5 24.2 29.4 22.0 30.1 23.2 

Their community would allow PLWHA to live in the same 41.2 37.8 48.0 39.1 44.2 38.4 

community 

N (Number of respondents) 311 339 248 304 559 643 


to mingle with children belonging to HIV 

households. These negative responses 

arise mainly due to misconceptions 

about the modes of transmission of HIV. 

Thus, creating greater awareness among 

people would go a long way in accepting 

the PLWHA in the family and society at 

large. 


1. For a person suffering from HIV, 

treatment of any opportunistic illness 

becomes very important. Steps 

should be taken to see that such 

people get access to treatment 

from both government and private 

health facilities. In fact, their right 

to treatment should be ensured, or 

else their status may be withheld, 

increasing the chances of spreading 

the infection. 

2. Efforts should be made to create 

greater awareness about HIV and 

AIDS, especially about the modes of 

transmission of the infection. 

3. Campaigns to change the attitude of 

the people towards PLWHA are highly 

recommended. 

4. Popular television channels and 

radio stations could be utilised for 

creating greater awareness as well 

as for changing the attitude of the 

people, since radio and television 

seem to be effective means of mass 

communication. 

5. Pre and post-test counselling for HIV 

and AIDS should be emphasised. 

6. Proper awareness and information 

about the infection and a change in 

the attitude of the people towards 

those suffering from it could go a long 

way in curtailing the spread of this 

infection. 

The negative 

responses arise 

mainly due to 

misconceptions 

about the modes 

of transmission 

of HIV 


121


Conclusion and Policy 

Implications

124 Socio-Economic Impart of HIV and AIDS in Tamil Nadu, India

Chapter 9 

Conclusion and Policy 

Implications 

The results of the study in Tamil Nadu 

indicate that although the impact of 

the epidemic is mainly on the working 

members of the household, the entire 

household gets affected economically, 

physically, emotionally and to some 

extent socially. The education of the 

children in these families is also being 

affected. 

The percentage of widows in the sample is 

much higher than that of widowers. Also, 

while 64 percent of the men discovered 

their HIV status after prolonged illness, 

the same percentage of women discovered 

their status after voluntary testing, and 

that too mostly after their husbands had 

tested positive. One may infer from this 

that in the household set up, there is a 

possibility that in a higher percentage 

of the cases, the infection is being 

transmitted from men to women. Also, as 

seen from the profile, many of the PLWHA 

have been forced to withdraw from the 

labour force due to ill health. 

C o m p a r i s o n o f t h e w o r k f o rc e 

participation rates of HIV and non-HIV 

households shows that the infection 

has indeed put an additional burden 

of earning on the children and more so 

on the elderly in the household. This 

is in spite of the fact that work force 

participation in the sample is higher for 

PLWHA. It would be another matter to 

assess what would be the impact when 

the presently working PLWHA are unable 

to continue working. Not only has the 

infection forced a few PLWHA to change 

their occupation after being detected 

HIV-positive, but some have even had 

to give up their jobs. Most of the PLWHA 

who had to give up work had to do this 

due to ill health. The HIV households were 

seen to suffer income loss in three ways: 

(a) Currently working PLWHA forced to 

take leave or be absent from work due 

to ill health, (b) PLWHA dropping out 

of work force with worsening physical 

condition, and (c) An employed caregiver 

in the family had to take leave to look 

after the PLWHA. Although the aggregate 

economic impact did not appear to be 

much at the macro level, it was serious, 

particularly in households where the 

number of PLWHA was more than one 

or where the family suffered loss in more 

than one of the above mentioned ways. 

There was also no mechanism in place to 

support those who lost their jobs and the 

issue is more serious in the case of wage 

earners who lack social security. 

While the annual per capita income of 

HIV households in the sample is lesser 

than that of the non-HIV households, 

their per capita expenditure is higher, 

mainly because of higher levels of 

Conclusion and Policy Implications 

125

The income of 


needs to be 

supplemented 

either by finding 

employment for 

some unemployed 

person of the 

household or 

depending on 

the situation, by 

finding suitable 

employment 

for the affected 

PLWHA 

expenditure on medical care (more than 

double) and house rent. To cope with 

this additional burden, these households 

are undercutting expenditure on other 

items including food essentials for their 

continued good health and education 

of the children which may later have 

repercussions on the household income. 

Also, the HIV households are seen 

resorting to borrowings and liquidation 

of assets which is affecting their savings 

adversely. The movement away from fixed 

assets to relatively liquid assets, observed 

in sample HIV households indicates loss 

of wealth and also capacity to deal with 

exogenous shocks in the future. The 

long-term consequences of HIV and 

AIDS on total and household savings can 

be disastrous. The impact may not be 

visible yet in the Indian scene given the 

fact that the proportion of households 

affected by HIV is still quite low. The wellto-do 

among the HIV households seem 

to be managing quite well even with the 

burden of additional expenditure/loss 

of income, while the poor among these 

households are the worst hit. It appears 

that HIV and AIDS could increase the 

incidence as well as severity of poverty. 

Since the PLWHA can work as long as 

they are fit, it is essential to see that they 

have good food and get the required 

supply of ARV. Health facilities must be 

made affordable. The income of HIV 

households needs to be supplemented 

either by finding employment for some 

unemployed person of the household or 

depending on the situation, by finding 

suitable employment for the affected 

PLWHA. 

Education is a must for a person to be 

independent and lead a reasonably 

good life. The results of the survey 

show that one HIV-positive child was 

refused admission in school in view of 

his condition. More importantly, the 

enrolment and continuation of schooling 

of non-HIV children from HIV households 

is being affected either because they are 

forced to take up some job or have to 

look after the sick. Public in general and 

school authorities in particular need 

to be educated about HIV and AIDS. 

Education of children must be ensured 

either by giving them financial help or 

better still by making arrangements for 

treatment and care of the affected. 

The results reveal that many of the 

sample PLWHA had gone in for an HIV 

test after suffering prolonged illness. 

The prevalence rates of both nonhospitalised 


are much higher in HIV households 

compared to their non-HIV counterparts; 

thus indicating a heavy financial burden 

on them and putting the strain of looking 

after the affected on the household. The 

burden is generally seen to increase 

with increasing stages of infection. 

The expenditure on illness is the least 

when treatment is taken from NGOs, 

higher when taken from government 

facilities and the highest when they go 

to private doctors or hospitals, in case of 

both non-hospitalised and hospitalised 

illness. Even when treatment is taken 

from NGOs and government hospitals, 

they are forced to incur a minimum 

expenditure, which itself is a huge burden 

on these households, belonging to a low 

economic strata of society. At least the 

poor among the HIV households – those 

below poverty line – should be provided 

free healthcare. 

The results of the survey show that 

though a large majority of the PLWHA 

are informing their spouses immediately 

after learning of their positive status, 

there are a few who have kept it a secret 

from them. This may not only spread 

the virus to the spouse but also to any 

children that might be born. They are 


also reluctant to divulge their status in 

the community and workplace for fear 

of discrimination and loss of job, but 

this stigma can create an environment 

in which people may avoid HIV-related 

services. 

Although most families have been 

supportive, there are also cases of 

discrimination by the family itself. Lack 

of awareness or misconceptions about 

the infection as well as the negative 

attitude of people towards PLWHA has 

led discrimination in the community 

workplace and even in healthcare 

facilities. It may be emphasised that 

women are being discriminated against 

more in families even though they take 

care of the sick husband and are also 

at times forced to take up a job apart 

from attending to household chores 

even when they are themselves sick. 

Their knowledge and awareness levels 

about the infection are also low, which 

makes it difficult for them to protect 

themselves from the infection. Another 

important point noticed is that while 

the prevalence rate of illness is generally 

lower for women, the expenditure per 

illness episode is also less for women 

PLWHA, irrespective of the source from 

which the treatment has been taken. Also, 

the percentage of untreated illnesses is 

higher for women, mainly due to lack of 

money. Responses from non-HIV adults 

interviewed indicate that women are 

more prejudiced as compared to men 

and have more of a negative attitude 

towards PLWHA. Special efforts need to 

be made to educate women. 

It is imperative that people, especially 

women be made fully aware of the 

different aspects of the infection, both 

through education and through the 

media to bring about a change in the 

attitude towards PLWHA. Special efforts 

need to be made to sensitise people 

working in healthcare facilities. The fear 

and prejudice that lies at the core of such 

discrimination needs to be tackled by 

creating a more enabling environment 

to assimilate HIV affected people within 

society. 

The fact that families have been supportive 

to a large extent in India reflects the 

strong family ties that exist in the system. 

Many of the widows thrown out of their 

in-law’s house have taken shelter with 

their parents and brothers. Some of the 

PLWHA who attended the FGD were of the 

view that their families would take care 

of their children eventually. This would 

also be much better for the children 

than being sent to orphanages. Hence, 

it is possible that the future witnesses 

many grandparents not only fending 

for themselves, but also taking care of 

their orphaned grandchildren. Hence, it 

is essential that a support system be in 

place to help them. The support could be 

financial, physical or moral depending on 

the merits of each case. 

It is imperative 

that people, 

especially women 

be made fully 

aware of the 

different aspects 

of the infection, 

both through 

education and 

through the media 

to bring about 

a change in the 

attitude towards 

PLWHA 


127


Annexures 


129


Annexures 

Annexure I 

Summary of focus group 

discussion 

The focus group discussion on the 

socio-economic impact study of HIV 

and AIDS was conducted in Cambum, in 

Theni district, on 5 January, 2005 at the 

Cambum Network of Positive People. 

• There was a total of 21 participants, of 

whom 13 were women (including two 

CSWs). The participants were either in 

stage one or two of the infection. The 

women were in the age group 20-45 

years, and men in the age group 30- 

37 years. Except for two participants, 

all the others belonged to the OBC 

category. All the participants were 

from a very poor socio-economic 

background. While four of the female 

participants and one male participant 

were illiterate, only two female and 

two male participants had completed 

their school education. The remaining 

had only completed primary or were 

below primary level of education. 

Most of the male participants were 

working as wage labourers and had 

been earning more before they tested 

HIV-positive. Many of the female 

participants were widows. These 

were women who were not working 

initially, but were forced to take up 

some job to earn their livelihood after 

the death of their husbands, and in 

effect mostly after they realised that 

they had become HIV-positive. Most 

of them were working as counsellors/ 

outreach workers with the network 

or as wage-labourers. The income 

of most of the participants was very 

meagre, as low as Rs. 800 per month, 

with the exception being participants 

who were working with the network 

and whose salary was in the range of 

Rs. 1,500-2,500 per month. 

About the network at 

Cambum 

Prevalence of HIV is very high in Cambum. 

Hence, though there is already a network 

at Theni, (the district headquarters) the 

one at Cambum was formed so that the 

PLWHA of Cambum area need not travel 

to Theni for monthly meetings. The 

objectives of the monthly meetings are to 

share each other’s experiences, circulate 

information about any new development 

like newly introduced/available ARV, 

NGOs working for the positive people, 

NGOs supplying Sathuma as well as 

giving guidance in general. The Cambum 

network has links with Sewanilayam, 

an NGO which runs a care and support 

home and also the government hospital 

at Theni. Sewanilayam has bed facilities 

for PLWHA along with a separate ward 

for TB patients. 

Annexures 

131

Reasons for high HIV 

prevalence in Cambum 

Cambum is near the Kerala-Tamil Nadu 

border, and there is heavy movement 

of trucks/lorries in this region. It is also 

very close to the tourist spot of Thekadi, 

which is a sanctuary. Prostitution is 

widespread in this area. Due to poverty 

and lack of any other source of income, 

even housewives and positive women, 

who have become widows are involved 

in the flesh trade. Although many of the 

participants did not seem to understand 

the word HIV-positive, they all know 

about AIDS. 

The participants were asked if they 

had experienced any discrimination in 

their homes, workplace, health facilities 

etc. and were told that they could 

freely share their experiences. These 

subjects were taken up one by one. 

Many of the participants narrated their 

experiences. 

Discrimination at health 

facilities 

1. One of the women participants 

narrated her case. Once when her 

husband was very ill (vomiting 

continuously) he was taken to the 

nearest government hospital (maybe 

a PHC) at Kandamkoil, but he was 

refused treatment there; and at 

night, he had to be taken to the 

district government hospital. The 

general feeling was that, except at 

the district hospital, the HIV-positive 

are generally refused treatment in 

all government health facilities. It is 

possible that the government health 

facilities at the lower level are neither 

equipped nor trained to handle 

PLWHA, and are afraid of treating 

them. 

2. A young HIV-positive widow narrated 

her experience. She and her husband 

were both diagnosed HIV-positive 

when she was five months pregnant 

(in the year 2000). When the doctor 

at the private nursing home, where 

she was going for check-ups, came 

to know that she was positive, he 

refused to continue her treatment. 

Her in-laws were forcing her to 

go in for an abortion. Fearing that 

she would be denied admission 

even in a government hospital if 

her status were known, she went to 

the government hospital without 

revealing her status. 

3. A similar incident was narrated by 

another woman, where they sought 

treatment for her father-in-law 

when he had a heart attack, without 

divulging his status since they feared 

refusal of treatment were the true 

status known. 

Thus discrimination forces people to hide 

their HIV-positive status and this might in 

fact lead to spread of the infection. 

The participants were also asked if 

they were taking medicines from faith 

healers and others or any other system 

of medicine. One of the participants 

said that he was getting medicines from 

an ashram in Thiruvananthapuram. He 

was given tablets and told that he would 

be cured of the infection. Although he 

took the medicine for about ten days, 

he did not find any improvement. He 

later went to the government hospital at 

Periyakulam. 

The general opinion was that people used 

to believe in faith healers till recently. 

However, now the awareness level of the 

people has improved and they do not 

get carried away by the words of such 

persons. 


Discrimination at workplace 

Many of the participants had not revealed 

their status at their workplace fearing 

discrimination. However, a number 

of women who were working as wagelabourers 

mentioned that since they were 

unable to go to work regularly because of 

their ill health, the others were probably 

aware of their status. In their case, neither 

their employers nor their co-workers 

treated them badly or any differently 

from the others. 

One of the participants, a construction 

worker, had a different story to narrate. 

The contractor with whom he was working 

had stopped giving him work when he 

came to know about the participant’s 

HIV status, since he was afraid that a 

PLWHA may not be able to come to work 

regularly. Because of this, he had decided 

not to reveal his HIV status to his current 

employer. 

Discrimination in the 

community 

The general perception was that in the 

last two years, a lot of changes have taken 

place in the attitude of people towards 

PLWHA. An incident that took place 

about four years ago was narrated by one 

of the participants. When a man died of 

AIDS in their village, nobody went for his 

cremation, and the community isolated 

the family. His widow got married to 

another PLWHA. Now the attitude of 

the people has changed due to the 

awareness campaign undertaken by 

the Network activists. People have now 

realised that HIV does not spread by 

touching those who are HIV-positive. 

Discrimination in the family 

Most of the participants did not complain 

about any discrimination in the family 

circle. They do get visitors and are 

invited for social functions. However, 

one of them mentioned that his relatives 

were not interacting freely with him. It 

is interesting to note that stigma and 

discrimination seem more of an urban 

and middle-class phenomenon. The rural 

poor seem to accept the HIV-positive 

more easily. This was corroborated by the 

experience of a woman participant who 

was somewhat educated and belonged 

to the lower middle class. Although her 

brother’s family supported her after she 

became a widow, they told her to keep her 

bed and vessels separately and not to kiss 

her daughter, who is HIV-negative. They 

were always scared that they might catch 

the infection from her. Her parents were 

worried that it would be difficult for them 

to get her younger sister married. Hence, 

they immediately arranged the younger 

sister’s marriage even though she was 

only 16. However, another participant 

had a very different experience. In his 

house, his mother, brothers and sisters 

were taking special care of him since 

they felt that he was not going to live for 

long. 


had any problem in getting houses on 

rent. None of them seemed to have 

faced any such problem. This shows 

that discrimination can be much less 

in rural areas. 

Children’s education 

Generally, the participants mentioned 

that they did not have any problem 

in getting their wards admission in 

schools and all of them were sending 

their children to school. In the case of 

children who were studying in public 

schools, the teachers as well as the 

parents of other students seemed to 

know about their HIV status. However, 

one of the participants whose children 

Annexures 

133

Annexures 

were studying in an English medium 

private school had not revealed his HIV 

status to anyone, since he felt that it was 

not necessary. 

Though they themselves were not 

well educated and many of them were 

working as labourers, all of them wanted 

to educate their children as much as 

possible, most of them at least till the 

10 th standard. However, when they 

were asked whether they would be 

able to educate their children upto 

tenth class given their health status, 

the response of the participants varied 

greatly. For instance, the participants 

who were daily wage earners were very 

clear in their minds that their children 

would go to school as long as they (the 

parents) could earn and the day they 

would stop working, their children 

would start working. Other participants 

who desired to educate their children 

expressed the hope that the Network 

or some other organisation would 

take care of the education of their 

children. Two participants mentioned 

that they had enrolled their children 

in a boarding school run by an NGO 

specifically for the children of HIVpositive 

parents. 

Impact of HIV status on 

employment 

The next topic for discussion was the 

impact of the infection on their earnings. 

Most of the participants were of the view 

that the infection had indeed affected 

their earning capacity. 

1. One of the participants who was a 

construction worker mentioned that 

while he could work continuously for 

about 40-45 days before the onset of 

the infection, he could no longer do 

so, and needs to take leave for about 

four-five days in between as he falls 

sick. His earnings have come down 

because of this. 

2. Another participant who was working 

as a local lorry driver with a transport 

company was earning Rs. 1500 per 

month. He has not been able to work 

for the last three years as he had been 

suffering from various opportunistic 

infections including TB and has 

now been forced to give up his job 

because of ill health. 

3. There were four female participants 

who had a different story to tell. 

These women were not working 

earlier and had started working only 

after the death of their husbands. 

They are working with the network 

and other NGOs. Although these 

women take up assignments with 

the network as volunteers since it 

gives them some income, they seem 

to have a larger interest as well. They 

want to provide moral support to 

other PLWHA and show that they 

can continue to lead a productive 

life even after becoming positive. 

It was seen that a number of HIVpositive 

women, especially widows, 

have come out into the open and 

started speaking out. Some of the 

men have also given up their jobs and 

joined the network to do voluntary 

work. 

Coping with the financial 

problems 

Next, they were asked as to how they 

were coping with the financial loss. 

There were a number of answers that 

came up, the most common being that 

they resorted to borrowing. In the case 

of the participant who had to give up 

his job as a driver, his wife had started 

earning as a wage labourer. Some of 

the participants mentioned that they 

used to wear good clothes and eat good 

food earlier, but have had to give up all 


that now. One of the participants who 

had a few acres of land had given it 

on lease. 

Gender issues 

The participants were then asked whether 

they perceived any discrimination in 

the treatment of HIV-positive men and 

women. The general opinion was that 

society looks down upon HIV-positive 

women as bad characters whereas 

it is more tolerant when it comes to 

HIV-positive men. When the women 

were asked whether they were aware 

of their husband’s positive status from 

the beginning, a participant narrated 

her story. Her husband, a truck driver, 

was an AIDS patient and used to get 

opportunistic infections like loose 

motions and mouth ulcers. He was 

even admitted to a hospital. However, 

her husband and in-laws kept his HIV 

status a secret from her and she also 

got infected as a result. In fact, some of 

the female participants came to know of 

their HIV status only after the death of 

their husbands. 

Though most of the widows did mention 

that they were annoyed and frustrated 

since, owing to their husband’s behaviour, 

they had to work and take care of their 

children, one of them had a very different 

attitude. In her own words, “Anybody can 

get ill and die, so why should I blame my 

husband”. According to her, he got the 

infection by going to prostitutes. She also 

justified this behaviour of her husband 

saying that before she married him, he 

was married to a sick woman and in her 

opinion, any man in such a situation 

would seek pleasure outside wedlock. 

It was rather surprising that even the 

participant who is currently working with 

the Network said that she never got angry 

with her husband for not having revealed 

his HIV status to her. 

In another incident, the wife left her 

husband and went to her parent’s 

house when she came to know of his 

HIV status. But her parents advised her 

to take care of the ailing husband. She 

stayed with her in-laws till her husband’s 

death. 

According to the male participants, many 

men do not divulge their status to their 

wives since they fear that their wives may 

not look after them. However, two of the 

male participants mentioned that they 

had divulged their status to their wives 

and the wives have accepted them and 

have a very sympathetic attitude towards 

them. 

It was generally seen that widows are 

living either with their parents or by 

themselves. 

Future plans 


had made any plans for the future 

security of their children. Two of the 

male participants who were working as 

counsellors said that they were saving 

for their children and their aim was to 

save as much as possible for the future 

of their children and their wives, who 

were not HIV-positive. They wanted 

to educate their children as much as 

possible and till such time that their 

health permits them to earn. Some of 

the women who were educated only 

upto primary or middle school seemed 

very keen to educate their children 

rather than simply save money for them. 

They felt that they were suffering as 

they were uneducated and did not want 

their children to face the same situation. 

Their arrangements for the future of 

the children seemed to vary a lot. In 

a number of cases, the HIV-positive 

women were confident that their mother 

or brothers would take care of their 

Annexures 

135

children. However, a few of them did not 

have such expectations. Those who had 

got married without the consent of their 

parents, especially in the case of intercaste 

marriages, do not seem to get any 

support from the family and they do not 

seem to have any hopes of their children 

looked after by their grandparents after 

their death. 

The discussion ended by thanking the 

participants for their cooperation. 


Annexure II 

Box 1 

Case study 1: Tamil Nadu: Lend a helping hand 

This is the story of a family in Trichy 

in Tamil Nadu. Mr. X married Miss X 

about 11 years ago when she was a 

girl of about 17 years. Mr. X had many 

relationships with women before 

marriage, and marriage did not deter 

him from continuing to have relations 

with other women. The couple had 

two daughters. Eventually, Mr. X’s 

continued relationships with other 

women became the cause of Mrs. X’s 

separation from her husband. Mrs. X 

got employment as a quality control 

checker, earning Rs. 400 p.m. in a 

textile mill in her native town, with her 

daughters studying in a government 

school there. About three years ago, 

the couple decided to reunite: Mrs. 

X gave up her job, the children, their 

schooling, and all three returned to Mr. 

X’s place – Manaparai. Although Mrs. 

X and her daughters are interested in 

education, it has been discontinued 

since Mr. X is of the opinion that 

there is nothing much to be gained in 

educating women. 

Meanwhile, the elder daughter used to 

get continuous fever, cough and cold 

and had to get a blood test last year. 

She was found to be HIV-positive and 

affected by TB. Later, after tests, it 

was found that both Mr. and Mrs. X 

are HIV-positive. The younger daughter 

has not yet been tested. 

Mr. X, the only earner in the family, 

earns about Rs. 300 per day but 

spends it all on gambling, wine, and 

women claiming that he’s addicted to 

liquor out of depression as he wants 

to forget the family’s difficulties and 

drown his sorrows. He also beats 

them in a drunken state. He gives 

very little money to his wife for 

household necessities. The family 

has absolutely no assets: they live in 

a one room rented accommodation, 

cook on a kerosene stove, and appear 

undernourished. The parents of both 

Mr. and Mrs. X who are aware of their 

children’s HIV-positive status have 

forsaken them. Their neighbours seem 

to be unaware of their health status. 

The family had already borrowed 

money from all sources possible when 

the elder daughter was unwell and 

needed to be hospitalised. 

Although this appears to be the 

common story of all women in 

the lower income group in society 

who are burdened with family 

problems and get no help from their 

husbands and are instead abused 

by them, the situation of Mrs. X 

is a little worse than that of other 

women from her income group: she 

Annexures 

137

has to look after three people who 

are ill and whose condition is likely 

to deteriorate without good, healthy 

food. As she was already working in 

a textile mill and had studied upto the 

twelth class, she is ready to work and 

feels that she can earn by tailoring and 

can work from home where she can 

also keep an eye on her sick daughter. 

However, she does not have a sewing 

machine. She is scared of even hiring 

a machine fearing that her husband, 

in a state of drunkenness, might 

dispose of the machine to be able to 

buy alcohol. The children do not want 

to live with their father and wish that 

at least the VCTC counsellors could 

look after them. 

It is time that somebody – the 

government, an NGO or us – lends the 

lady a hand before it is too late, so that 

she can engage herself in an income 

earning activity. 


Box 2 

Case Study 2: From riches to rags physically, 

financially and emotionally 

This is the story of one Mr. X, a resident 

of Trichy in Tamil Nadu. He was a hard 

worker engaged as a truck driver and 

earned, on an average, about Rs. 500 

per day, for 15-18 days a month. He 

was able to maintain his family i.e. 

his wife and two sons comfortably. 

However, about four to five years ago 

he became addicted to wine, women 

and smoking and finally ended up with 

HIV infection. 

Thereafter, within a short span 

of time he became ill and started 

suffering from fever, cough and 

diarrhoea continuously and lost a lot 

of weight. When he underwent the 

recommended blood test he came 

to know he was HIV-positive. His 

immediate reaction was to end his 

life. However, he controlled himself, 

thinking of others who survived the 

epidemic. Later, he decided to live as 

long as possible for the sake of his 

family, resolving to take the doctor’s 

advice, stay on the medicines given 

and keep himself fit. 

However, in the last three years he 

has been hospitalised three times. Not 

only were all his savings spent on the 

hospital charges and medicines, but 

he also had to dispose of his wife’s 

jewellery and in addition, had to borrow 

money from others. He was also 

forced to change his accommodation 

twice for he could not afford the rent 

and is presently living in a semi-pucca 

one room accommodation with no 

separate kitchen or water tap and for 

which he is paying a rent of Rs. 550 

per month. Water is fetched from a 

common tap for which they have to 

pay an additional sum of Rs. 50 per 

month. They have now shifted to using 

a kerosene stove; his wife cooks for 

her sister’s family and in return, shares 

their food. They share a toilet with 

another family. 

Mr. X’s wife and children are not HIVpositive. 

During the last three years 

of financial struggle, his eldest son 

had to give up his studies after twelth 

class, and had to take up a job to earn 

money and help support the family. 

He feels that he has been denied his 

education and that his future is bleak 

because of his father’s mistakes. 

He always questions in what way 

he is responsible for his father’s 

infection and inability to work when 

all his friends are going to college and 

getting an education. Because of this 

his relation with his father is strained. 

He seldom talks to his father but still 

manages to convey his lack of respect 

and displeasure very often. 

The second son who is also a good 

student and is presently studying in 

class X also wants to study further. 

The two sons and Mr. X’s wife feel 

that Mr. X alone is responsible for 

all the misfortunes that the family is 

facing and give vent to their feelings. 

Mr. X has changed in the last three 

years since he came to know about 

his HIV-positive status. He has given 

up liquor, smoking and sex. Although 

he is presently in the 3 rd stage of the 

infection, he realises his responsibility 

to his family and is trying his best to 

earn his keep. He is now employed 

as a driver with someone and earns 

about Rs. 1,500 per month. He is 

ever ready to do overtime and is also 

involved in a small side business of 

buying and selling of two wheelers for 

commission. 

Mr. X tries to remain calm and unruffled 

by his family’s behaviour. He leaves the 

house at 7:30 in the morning, returns 

only after 8:30, has his dinner and 

goes to bed. For all his repentance and 

changed way of life, it is now too late 

to turn back the clock. 

Annexures 

139

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United Nations Development Programme 

55, Lodi Estate, New Delhi-110003 

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