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1 Measuring the epidemic: 2 nd Generation Surveillance and the Asia Epidemic Model (AEM) USAID SOTA meeting Washington DC Oct. 7, 2002 Stephen Mills Family.

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Presentation on theme: "1 Measuring the epidemic: 2 nd Generation Surveillance and the Asia Epidemic Model (AEM) USAID SOTA meeting Washington DC Oct. 7, 2002 Stephen Mills Family."— Presentation transcript:

1 1 Measuring the epidemic: 2 nd Generation Surveillance and the Asia Epidemic Model (AEM) USAID SOTA meeting Washington DC Oct. 7, 2002 Stephen Mills Family Health International Asia Regional Office Bangkok, Thailand

2 2 Topics Update on 2 nd generation surveillance in Asia The role of modeling: the Asia Epidemic Model (AEM) - Examples: 1.Cambodia – various uses 2.The role of IDU HIV transmission in heterosexual epidemics

3 3 Increasing scrutiny of data showing prevention intervention effects

4 4 Number of countries with some level of quality surveillance, particularly behavioral surveillance, has increased Our understanding and resolution of some problems in design, sampling, analysis, etc. have improved Increasing examples where surveillance has helped to stimulate new and adjust old interventions The Good News

5 5 BangladeshRisk reduction in a low prevalence setting Examples of behavioral surveillance PlaceMajor uses and findings

6 6 % of IDU reporting ever sharing equipment in the past week – Bangladesh Overall HIV prevalence low among IDU (< 3%) Surveillance showed decreased sharing following introduction of needle exchange program (NEP) In Rajshahi, decreased sharing associated with NEP participation Needle exchange introduced Source: IEDCR, Gov of Bangladesh; Jenkins, Rahman, et al.

7 7 BangladeshRisk reduction in a low prevalence setting Cambodia Risk reduction linked to decreases in HIV and STIs Examples of behavioral surveillance PlaceMajor uses and findings

8 8 Condom use, HIV and STI prevalence - Brothel-based CSWs, Cambodia 1996-2001 Condom use HIV Source: NCHADS 2000-2002, Ryan et al 1998

9 9 BangladeshRisk reduction in a low prevalence setting Cambodia Risk reduction linked to decreases in HIV and STIs Tamil Nadu,Evaluation of large Indiaintervention program Examples of behavioral surveillance PlaceMajor uses and findings

10 10 % of truckers/helpers and factory workers reporting non-regular sex partners in the past year – Tamil Nadu, India Source: AIDS Prevention and Control Project (APAC), VHS, Chennai

11 11 % of FSWs, truckers/helpers, and factory workers reporting condom use with last non- regular sex partner – Tamil Nadu, India Source: AIDS Prevention and Control Project (APAC), VHS, Chennai

12 12 BangladeshRisk reduction in a low prevalence setting Cambodia Risk reduction linked to decreases in HIV and STIs Tamil Nadu,Evaluation of large Indiaintervention program Indonesia Difficulties in changing behaviors in a low prevalence setting Examples of behavioral surveillance PlaceMajor uses and findings

13 13 % of port workers and truckers reporting two ways or more of preventing HIV infection – various sites in Indonesia Source: University of Indonesia; FHI

14 14 % of port workers and truckers reporting condom use during last sex with FSW – various sites in Indonesia Source: University of Indonesia; FHI

15 15 BangladeshRisk reduction in a low prevalence setting Cambodia Risk reduction linked to decreases in HIV and STIs Tamil Nadu,Evaluation of large Indiaintervention program Indonesia Difficulties in changing behaviors in low prevalence setting Nepal Behavior change in a changing risk environment Examples PlaceWhat has BSS shown

16 16 % of transport workers and laborers reporting consistent ( “ Always ” ) use of condoms with FSWs in the past year – Terai area, Nepal Source: New Era; FHI

17 17 % of transport workers and male laborers reporting sex with a FSW in the past year – Terai area, Nepal Huge rise in number of sex establishments Source: New Era; FHI

18 18 What ’ s missing? Estimates of : –HIV trends in the future based on behavioral patterns –HIV infections averted from behavior change –HIV infections from various modes of transmission and their contribution to the overall epidemic Such estimates require modeling techniques

19 19 The Asian Epidemic Model A model focused on replicating the dynamics of Asian epidemics Developed by Tim Brown and Wiwat Peerapatanapokin, East-West Center Simple model - four transmission routes: –sex work; needle sharing; intramarital & pre- & extra-marital sex; mother to child –MSM in development Key inputs (variable by year) –sizes of important populations –behaviors over time Key output: epidemiological trends over time

20 20 Fitting an epidemic in the AEM Behavioral trends Epidemiological trends Transmission parameters Behavioral trends from existing data are given as inputs Transmission parameters are then varied until trends in HIV from the model are in reasonable agreement with observed HIV trends These transmission parameters include: - probability of HIV transmission - STD and circumcision cofactors

21 21 Key Inputs and Assumptions Models are only as good as their inputs and assumptions –careful analysis of existing data is needed to ensure inputs are realistic to validate outputs –transparency is essential Important role of 2 nd generation surveillance The model should fit the historical patterns observed in HIV infections

22 22 The Cambodian HIV Epidemic - a History Highest national HIV prevalence in Asia Epidemic initially fueled by men and commercial sex partners Recent data however, shows prevention is having an impact, and HIV prevalence is falling in sentinel groups HIV among direct sex workers peaked at 41% in 1996 and by 2000 had fallen to 31% HIV has reached into the general population –Prevalence among antenatal clinic attendees peaked at 3.2% in 1997 and had declined to 2.3% by 2000 But while the epidemic is slowing, better understanding of past and future trends is required to better direct the response

23 23 Key behavioral inputs and trends The percentage of men having sex with sex workers has fallen –27% in 1996 to 11% of adult males in 2000 Condom use –Increased from 15% to 86% in brothel sites –Low between husband/wife – 0.6% –Extramarital sex - 35% (estimated) Brothel-based sex workers have 3.2 clients/night STDs among sex workers fell from 39% in 1996 to 23% in 2001

24 24 Direct and indirect sex workers General population males General population females White lines are HIV trends from observed data Colored lines are AEM generated HIV trends AEM Fit for Cambodia

25 25 HIV Infection in Cambodia over time New, cumulative and current HIV infections

26 26 Prevention efforts in Cambodia have paid huge benefits Red line represents what might have been if behaviors had not changed Infections prevented

27 27 Sustaining past successes in sex work is essential to keeping HIV under control. If condom use in direct sex work were to fall to 60% in 2002, the epidemic would re- establish itself. Supposing condom use drops to 60% starting 2002

28 28 Changing Routes of Transmission The Cambodian HIV epidemic is dynamic –As one route is controlled others assume importance –Dominance of sex work has now shifted to dominance of husband-to-wife infections –Over the next 3 to 4 years, mother-to-child transmission will become dominant

29 29 The routes of transmission are changing rapidly in 2002: Spousal transmission is 42% Children are now 35% The response should adapt to address these changes

30 30

31 31 Shifts in New Infection Patterns Infection route1990199520002005 Males from sex workers 79%61%15%20% Males from wives 0%1%6%9% Females sex workers 10%8%4%7% Females from husbands 10%26%48%19% Children from mothers 1%4%27%45% TOTAL New infections2,89538,82210,5534,014

32 32 Implications Current prevention efforts must be sustained The epidemic has changed dynamically over the last decade New initiatives are needed to address –Husband wife infections –Continuing infections in sex work –Pediatric infections –MSM (not included in model)

33 33 Other applications of AEM Exploring the impact of IDU and MSM sexual networks on more “ generalized ” transmission of HIV Recent application looked at how many HIV infections would be averted by keeping HIV among injecting drug users at low levels To be published in the International Journal of Drug Policy by Tobi Saidel/FHI and others

34 34 Role of IDUs in heterosexual epidemics Parameters needed Size of IDU population Sexual behavior of IDU population, including commercial sex and non-regular sex partners Time of HIV entrance into IDU population Parameters were taken from research conducted in several settings in India

35 35 Proposed IDU Scenarios Scenario I (Early commercial sex epidemic) High volume of commercial sex Low prevalence among sex workers Look at low, medium and high prevalence among IDUs Scenario II (Advanced commercial sex epidemic already underway) Assume high prevalence among sex workers Look at low, medium and high prevalence among IDUs Scenario III (“Controlled” commercial sex epidemic) Assume reducing epidemic among sex workers Look at low, medium and high prevalence among IDUs

36 36

37 37 Total Infections 1995-2010 Early Commercial Sex Epidemic IDU HIV Prevalence # of infections % increase 5 %187,000 90%506,000271%

38 38 Conclusions and policy implications of the IDU analysis Spread of HIV among IDUs can lead to large-scale heterosexual spread Early interventions to IDU have the greatest impact on the entire population

39 39 Hard-to-reach populations or hard-to-change governments? Population groups which are first affected and fuel the HIV epidemics of Asia continue to be “ unappealing ” for governments: –Injection drug users –Men who have sex with men –Migrating individuals of other nationalities or ethnic groups Double whammy: –Lack of interventions PLUS –Lack of surveillance and monitoring which indicates an epidemic Asia’s unappealing population groups in need

40 40 HIV prevalence among 3 MSM groups in Jakarta, Indonesia

41 41

42 42 HIV prevalence among injection drug users in Kathmandu, Nepal, 1991-2001 Percent

43 43 Most countries still do not have adequate coverage of surveillance in appropriate population groups and geographic areas Epidemics are sometimes missed because of concentration of surveillance in donor-covered intervention areas Support for national surveillance critical –Stimulates appropriate intervention coverage, not only by USAID but other donors as well –Feeds into modelling programs which provide estimates of impact Looking towards the future


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