Guidelines for second generation HIV surveillance - World Health ...

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Programmes may need to be updated based on new information about the epidemic. As you process feedback (findings/data) from the last round of surveillance activities, your data priorities may need to shift. An example can be provided by data analysis of the Honduras HIV epidemic (Figure 4.8). The HIV notification rates per 100 000 population are higher in the coastal regions compared with the rest of the country. At the same time, the male-to-female (M:F) ratio of people infected with HIV in the north is close to 1, whereas in the rest of the country the M:F ratio is 3:1. This characteristic has been constant over time, which implies that two different epidemics are evolving in the country. 4.3.3. Indentify where new infections are occurring Epidemiological information can contribute to indentifying where new infections are coming from. For instance, this information is key to using the UNAIDS Modes of Transmission model (MOT). It uses national prevalence and behavioural data to model the distribution of incidence in key populations at increased risk. It is therefore an important tool in supporting country programmes to “Know the HIV Epidemic” and therefore modify programmes. The epidemiological synthesis preceding the modelling exercise is a key requirement for developing a clear explanation of the dynamics of HIV infection, assessing the degree of alignment between programme and resource efforts, and the priority areas identified through the modelling exercise. By developing an understanding of the national epidemic and context (gaps, risks, service coverage and resources), the country is able to make better decisions on prioritization and definition of goals and targets for effective scale up of the national response. As an example, Figure 4.9 presents the results of the Modes of Transmission study in selected African countries and where it was evident that key populations at higher risk played a major role in transmission of new HIV infections. Figure 4.8. Taux de cas d’infection à VIH notifiés pour 100 000 habitants, stratifiés par situation géographique et par sexe, Honduras, 1997–2009 Tasa por 100,000 habitantes 70.0 60.0 50.0 40.0 30.0 20.0 10.0 CN (1,2,5,11) - Mujer Resto - Mujer CN(1,2,5,11) - Hombre Resto - Hombre 0.0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Año CN: North Coast H: men and M: women Resto: rest of the country, mujer: women, hombre: men Source : Honduras National AIDS Programme: triangulation of national data, 2011. 52
Figure 4.9. Results from Modes of Transmission in selected countries of sub-Saharan Africa Percent new infections 100% 80% 60% 40% 20% Distribution of new infections by surce of risk Modes of Transmission South, East and West Africa, 2008–2009 Evaluating a National Surveillance System 0% Lesotho Kenya Swaziland Uganda Zambia Benin Burkina Faso Cote d’Ivoire Ghana Nigeria Senegal Southern and East Africa West Africa ■ Other ■ Sex Work ■ IDU ■ Prison population (measured only in Kenya ■ MSM ■ Multiple partners ■ Stable heterosexual couples The results of these studies were the basis for undertaking several new prevention programmes that addressed key populations. 53
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UNAIDS/WHO Working Group on Global
Page 3 and 4:
UNAIDS/WHO Working Group on Global
Page 5 and 6: Contents Acknowledgements 1. Introd
Page 7 and 8: 1. Introduction 1.1. What is second
Page 9 and 10: 1.4. What this update includes This
Page 11 and 12: • Data from interventions or prog
Page 13 and 14: Epidemic categories Low-level epide
Page 15 and 16: If data from proxy groups have been
Page 17 and 18: 2.2.2. Step 2: Estimate the size of
Page 19 and 20: Table 2.3. Summary of methods for e
Page 21 and 22: In generalized epidemics, distingui
Page 23 and 24: Figure 2.2. Stratification by regio
Page 25 and 26: Figure 2.4. HIV prevalence among AN
Page 27 and 28: 3. Design a comprehensive surveilla
Page 29 and 30: Tips for developing a national surv
Page 31 and 32: Low-level epidemic: brief explanato
Page 33 and 34: Surveillance activities for general
Page 35 and 36: Track key events where the burden o
Page 37 and 38: 3.1.4. Understand mortality trends
Page 39 and 40: • Prepare annual reports of the e
Page 41 and 42: As much as possible, this type of e
Page 43 and 44: Figure 4.2. Using HIV prevalence tr
Page 45 and 46: • Individuals may migrate to urba
Page 47 and 48: Probability surveys are the most ri
Page 49 and 50: Trends among young people or recent
Page 51 and 52: Figure 4.6. Asian Epidemic Model pr
Page 53 and 54: More precise risk behaviour data th
Page 55: Using data to plan programmes in In
Page 59 and 60: How to deal with data aggregation i
Page 61 and 62: Figure A.3. HIV sentinel surveillan
Page 63 and 64: Initiating second generation HIV su
Page 65 and 66: Networks (social, sexual) Outcome P
Page 67 and 68: 17. Patel SV et al. Filling a gap:
Page 69 and 70: Notes .............................
Page 72: For more information, contact: Worl
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