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Technical Note - Bin urban areas, so they are likely to have lower proportions of rural women. Second, youngwomen at high risk from HIV infection do not visit antenatal clinics on account of stigma. Third,HIV seems to lead to lower fertility rates, so that visitors to antenatal clinics woulddisproportionately represent individuals with lower HIV prevalence, relative to the whole group.inally, most of the sentinel surveillance sites are located in public facilities, so that there wouldbe socio-economic differences between women whose blood is tested for HIV in the sentinelsurveillance sites, and those who visit private facilities, and are not covered. These caveatssuggest that sentinel surveillance data would underestimate HIV prevalence among women inreproductive age groups. The relatively greater ease with which HIV is transmitted to women,compared to men, and the increasing role of heterosexual sex in HIV transmission in developingcountries, suggests however, at least one factor leading to a bias in the other direction whenusing ante-natal clinic HIV data to assess HIV prevalence rates among all adults.10 UNDP, 200111 World Bank, 200112 UNAIDS/WHO, 2001, UNAIDS, 2000b and d13 Bloom et al., 199614 UNAIDS, 2002b15 The main advantages of the EPP over its predecessor, EPIMODEL, is its ability to make muchmore effective use of larger set of data points on HIV-prevalence, and to be able to work with amuch broader set of variables influencing HIV-prevalence (Chin and Lwanga 1990, UNAIDS2002b). In particular, EPP involves the estimation of four parameters that describe the timeprofile of HIV prevalence in a population – the initial year of the epidemic, the initial proportion ofthe population at risk for HIV infection, the distribution of the population into not at-risk and atriskcategories, and the rate at which the at-risk population gets infected with HIV. or a givenpattern of progression from HIV to AIDS, given death rate among individuals not infected withHIV, birth rates of HIV-negative children, survival rates to age-15 among HIV-infected children,fertility reduction due to HIV and the rate of perinatal transmission, the EPP finds the (four)parameter estimates and the resultant temporal pattern of HIV prevalence that “best fits” theobserved HIV-prevalence data from sentinel sites. Essentially, this amounts to choosing theparameters so as to minimise the error sum of squares of the fitted curve (UNAIDS 2002b,p.41). A particularly attractive element of EPP is its distinguishing rural and urban HIV surveillancedata to arrive at separate (and combined) HIV prevalence estimates for rural and urban regions.16 or additional details, see UNAIDS 2002b17 The model also used assumptions about declines in fertility rates owing to HIV infection amongreproductive age women.18 See, for instance, Anderson and May 1991; Kremer 199619 Chin and Lwanga, 199120 World Bank, 200021 Summers and Heston, 1991Regional Human Development ReportHIV/AIDS and Development in South Asia 2003 185
Statistical TablesStatistical TablesTable 1aHuman development indicators and indicesCountry HDI Life Adult Combined HPI 1 GDI GEMvalue expectancy literacy primary, Value(%) value Value2000 at birth rate (% secondary(years) age 15 and tertiary2000 and grossabove) enrolment2000 ratio(%)1999Afghanistan N.A. N.A. N.A. N.A. N.A. N.A. N.A.Bangladesh 0.478 59.4 41.3 37 42.4 0.468 0.223Bhutan 0.494 62 47 33 N.A. N.A. N.A.India 0.577 63.3 57.2 55 33.10.560 N.A.Iran (I.R.) 0.72168.9 76.3 73 17.0 0.703 N.A.Maldives 0.743 66.5 96.7 77 15.8 0.739 0.361Nepal 0.490 58.6 41.8 60 43.4 0.470 N.A.Pakistan 0.499 60 43.2 40 41.0 0.468 N.A.Sri Lanka 0.74172.191.6 70 17.6 0.737 0.274Note: N.A. indicates not availableSource: UNDP, 2002Table 1bTrends in HDICountry 1975 1980 1985 1990 1995 2000Afghanistan N.A. N.A. N.A. N.A. N.A. N.A.Bangladesh 0.335 0.353 0.386 0.416 0.445 0.478Bhutan N.A. N.A. N.A. N.A. N.A. 0.494India 0.407 0.434 0.473 0.511 0.545 0.577Iran (I.R.) 0.556 0.563 0.607 0.645 0.688 0.721Maldives N.A. N.A. 0.629 0.676 0.707 0.743Nepal 0.289 0.328 0.370 0.416 0.453 0.490Pakistan 0.345 0.372 0.404 0.442 0.473 0.499Sri Lanka 0.616 0.650 0.676 0.697 0.719 0.741Regional Human Development Report186 HIV/AIDS and Development in South Asia 2003
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It is now well accepted that HIV/AI
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© United Nations Development Progr
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OverviewGlobally, the Human Develop
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AcknowledgementsCombating HIV/AIDS
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The TeamHDRC: K. Seeta Prabhu, Sura
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ContentsCHAPTER 1Introduction1.1 Th
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Contents3.2 African AIDS is not a s
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GlossaryAIDSAcquired Immuno-deficie
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Introduction2Regional Human Develop
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Introductioncases, the region has t
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IntroductionAlthough theHIV/AIDS in
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IntroductionBox 1.2Human developmen
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IntroductionBox 1.3Millennium Devel
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Nexus between Human Development and
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The HIV/AIDS Epidemics of South Asi
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Human Rights and HIV/AIDS“An impo
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Human Rights and HIV/AIDSincrease t
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Human Rights and HIV/AIDSsupport an
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Human Rights and HIV/AIDSBox 4.3Sti
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Human Rights and HIV/AIDSBox 4.5Bad
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Human Rights and HIV/AIDSnumber of
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Human Rights and HIV/AIDSnegotiate
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Human Rights and HIV/AIDSBox 4.6Ind
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Human Rights and HIV/AIDSTable 4.2I
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Human Rights and HIV/AIDSsociety in
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Human Rights and HIV/AIDSReforms co
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Human Rights and HIV/AIDSSource: WH
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Human Rights and HIV/AIDSBox 4.12Me
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Human Rights and HIV/AIDSclients an
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Human Rights and HIV/AIDSand develo
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Human Rights and HIV/AIDSTable 4.5S
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Human Rights and HIV/AIDSBox 4.16Th
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Human Rights and HIV/AIDSBox 4.17Hu
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Human Rights and HIV/AIDSnuisance.
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Human Rights and HIV/AIDSand autono
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The Way orwardRegional Human Develo
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The Way orward“The social andpoli
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The Way orwardis not a desirable on
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The Way orwarddevelopment, divert s
Page 140 and 141: The Way orwardProviding ARV treatme
Page 142 and 143: The Way orward5.5 Adolescent Sexual
Page 144 and 145: The Way orwardwomen’s lives are t
Page 146 and 147: The Way orwardcomprehensive guidanc
Page 148 and 149: The Way orwardInvolving religious l
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Page 157 and 158: Endnotes17 Bandhu, 200218 UNAIDS/WH
Page 159 and 160: Endnotes56 Pradhan, 199857 Malla, 2
Page 161 and 162: Endnoteson Economic, Social and Cul
Page 163 and 164: Annexure IRegional Human Developmen
Page 165 and 166: Annexure ICountry Treaty Concluding
Page 167 and 168: Annexure IAnnexure IIInternational
Page 169 and 170: Technical Note - ATechnical Note -
Page 171 and 172: Technical Note - A(EDEP) is calcula
Page 173 and 174: Technical Note - Bvalue is to the u
Page 175 and 176: Technical Note - Bsubstantial degre
Page 177 and 178: Technical Note - Bthe rate of growt
Page 179 and 180: Technical Note - BThe full list of
Page 181 and 182: Technical Note - B(13) H =(α∗ρ
Page 183 and 184: Technical Note - BTable T1Human dev
Page 185 and 186: Technical Note - BTable T3(b)HIV/AI
Page 187 and 188: Technical Note - BTable T7HIV/AIDS
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Page 193 and 194: Statistical TablesTable 3Profile of
Page 195 and 196: Statistical TablesRegional Human De
Page 197 and 198: Country act SheetsRegional Human De
Page 199 and 200: Country act SheetsBANGLADESHIndicat
Page 201 and 202: Country act SheetsINDIAIndicator Ye
Page 203 and 204: Country act SheetsMALDIVESIndicator
Page 205 and 206: Country act SheetsPAKISTANIndicator
Page 207: Country act SheetsRegional Human De
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