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Epi Analysis Preliminary Findings Virginia Loo William K Bosu UNAIDS Conference Room - Prioritization Workshop, 18 August 2010.

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Presentation on theme: "Epi Analysis Preliminary Findings Virginia Loo William K Bosu UNAIDS Conference Room - Prioritization Workshop, 18 August 2010."— Presentation transcript:

1 Epi Analysis Preliminary Findings Virginia Loo William K Bosu UNAIDS Conference Room - Prioritization Workshop, 18 August 2010

2 Terms of Reference Update the epidemic profile, trends, key populations and geographical prioritization; Inform the evidence-based priorities for the NSP – Prevention – Treatment care and support – Surveillance, monitoring and evaluation Prepare epidemiological profiles of HIV by region

3 Methods Desktop reviews – General population – DHS, MICS – Pregnant women - HSS – MARPs surveys – Special studies – MOT, Synthesis Report, Estimates and projections – Administrative reports – health service data Re-analysis of HSS – age and urban standardization Web search – regional profiles

4 Framework for Analysis 1.Presence of MARP 2.Presence of casual heterosexual sex 3.Presence of high risk sexual activity 4.Presence of cases/infections

5 HIV SENTINEL SURVEILLANCE

6 Map Showing Location of HIV Sentinel Sites since 2005

7 Comparison of Adjusted and Crude Regional HIV Prevalence Overall, crude and adjusted HIV prevalence follow similar patterns Except for 2008, overall crude prevalence higher or similar to crude HIV prevalence Adjustment made no difference – GAR, WR, NR Crude consistently higher than adjusted vallues – UER, UWR, ER, VR Mixed pattenrs – AR, BAR, CR Widest disparities in UWR, VR

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11 Evidence of MARPS

12 Criteria for Evidence of MARPs Urban population size - census FSW intervention presence – WAPCAS report Presence of male clients – DHS 2008 MSM intervention presence % employed men

13 Key Findings on Evidence of MARPs AR, GAR, WR appear as regions with major MARPs activity based on criteria However, little correlation between size of urban population and – Number of FSW hotspots – % men engaging in paid sex Low prevalence of reported paid sex in men in DHS Prevalence in MARPs appears to be decreasing Little data on size and distribution of MARPs in Ghana Caveats: ecological fallacy (Correlation vs. Causality), reporting biases, considerations other than burden in selection of intervention sites

14 Multiple heterosexual sex

15 Multiple Sex Partnerships 2008 DHS2003 DHS2008 DHS 2003 DHS 2008 DHS 2009 DHS 2008 DHS % women with 2 or more partners in last 12 months (all women) % women with 2 or more partners in last 12 months (sex act women) % men with 2 or more partners in last 12 months (all men) % men with 2 or more partners in last 12 months (sex act men) % men with 2+ wives women: mean # lifetime partners men: mean # lifetime partners Western Central Greater Accra Volta Eastern Ashanti Brong Ahafo Northern Upper East Upper West National

16 Region 2008 DHS 2003 DHS 2008 DHS 2003 DHS 2008 DHS 2009 DHS 2008 DHS % women with 2 or more partners in last 12 months (all women) % women with 2 or more partners in last 12 months (sex act women) % men with 2 or more partners in last 12 months (all men) % men with 2 or more partner s in last 12 months (sex act men) % men with 2+ wives women : mean # lifetime partner s men: mean # lifetime partner s WR CR GAR VR ER AR BAR NR UER UWR Codes: Red=highest; Amber=above national average Ranking – Casual Sex Evidence

17 Key findings - Casual heterosexual sex Eastern, Greater Accra and Ashanti regions have the highest proportions of men and women with more than one partner and higher numbers of lifetime partners In both GAR and Ashanti regions, more than one fifth of men report having multiple partners, and the proportion with multiple wives is lower than the national average Three northern regions, BAR and CR have lowest rankings Caveats: polygamy, concurrency, reporting bias, protective sex

18 Evidence of High Risk Sexual Activity

19 High Risk Sexual Activity 2008 DHS 2006 BSS men: % who had sex in the last 4 wks women: % who had sex in the last 4 wks men: sex before aged 18 (men yrs) women: sex before aged 18 (men yrs) men: % never married youth (15- 24) sex in past 12 mo women: % never married youth (15-24) sex in past 12 mo men: lifetime # of partner s wome n: lifetim e # of partner s men: % genital sore past 12 mo men: % genital sore or discha rge wome n: % genital sore past 12 mo women: % genital sore or dischar ge % adults genital ulcers past 12 mo % adults treate d for STIs in past 12 mo WR CR GAR VR ER AR BAR NR UER UWR National

20 High Risk Sexual Activity - Ranking Regn 2008 DHS 2006 BSS men: % who had sex in the last 4 wks women: % who had sex in the last 4 wks men: sex before aged 18 (men yrs) women: sex before aged 18 (men yrs) men: % never married youth (15-24) sex in past 12 mo women: % never married youth (15-24) sex in past 12 mo men: lifetime # of partner s wome n: lifetim e # of partne rs men: % genital sore past 12 mo men: % genital sore or discha rge wome n: % genital sore past 12 mo women : % genital sore or dischar ge % adults genital ulcers past 12 mo % adults treate d for STIs in past 12 mo WR CR GAR VR ER AR BAR NR UER UWR

21 Key findings – High risk sex A similar regional pattern appears for high risk sexual activity as for the evidence for multiple partner sex. ER, AR, CR have highest rankings in that order Three northern regions and WR have lowest rankings Surprisingly, the Northern region, which generally has lower levels of risk behaviour, shows relatively high levels of ulcers among men and women, than might otherwise be expected Caveats: reporting differences; does not distinguish commercial sex or spousal partners or regular partners; outcome of STI treatments

22 Regional Presence of Infections and Cases

23 Criteria New infections – Modes of Transmission modelling HIV sentinel surveillance Epidemic projection modelling Service outputs – PMTCT – HCT AIDS Surveillance

24 Presence of Cases - 1 AIDS case data HTC data Average AIDS cases Average AIDS deaths average Regional % of AIDS cases Regional % of AIDS deaths per capita AIDS cases (avg ) male # cases (HTC 2009) female # cases (HTC 2009) male % pos (HTC 2009) female % pos (HTC 2009) Ashanti %5.4%47 1, %27.1% Brong Ahafo %19.2% %23.9% Central %7.1%106 1, %5.0% Eastern %29.3%369 1, %12.3% GAR %23.0%102 1, %6.2% Northern %0.4% %1.1% Upper East %3.8% %10.7% Upper West %2.3% %1.8% Volta %6.8%77 1, %6.2% Western %2.6% %12.8% National ,067 1,9417.7%10.7%

25 Presence of Cases - 2 PMTCT data HSS data 2003 DHS data 2009 # PMTCT sites 2009 PMTCT uptake 2009 PMTCT % pos adjusted avg HSS ( ) avg HSS - rural ( ) avg HSS - urban ( ) women: HSS 2003 women: HIV prev (2003 DHS) men: HIV prev (2003 DHS) Ashanti5981.8%2.2% Brong Ahafo8386.4%2.0% Central7882.6%1.3% Eastern %2.8% GAR %1.8% Northern %0.4% Upper East4276.9%0.6% Upper West3988.6%1.2% Volta2893.3%2.2% Western3793.7%2.2% National 83.1%1.7%

26 Findings Similar pattern as before: ER, GAR, AR show evidence of highest HIV prevalence and share of AIDS cases ER and GAR account for 54% of AIDS; with BAR, account for 70% of AIDS in BAR contributes disproportionately to number of AIDS case. Lower levels of recent HSS measures, may suggest that BAR epidemic had been more severe in the past Wide variability in HIV infection from HTC. Ranges from 1.8% in NR to 24.5% in AR in PMTCT uptake in ranged from 60% in VR to 88% in VR; was 94% in KATH Regional HIV prevalence in PMTCT generally low – was 2% or less in 5 regions; <3% in 9 regions Caveats - Service availability; Diagnostic capacity; Service uptake behaviour; Completeness of reporting; HTC testing policy

27 Method of apportioning HIV infections by region, using EPP and HSS estimates a.2009 HSS prevalence X population size of region, adjusted for EPP estimated # infections vs total country estimate by HSS prev b avg adjusted HSS prevalence X population size of region, adjusted for EPP estimated # infections vs total country estimate by HSS prev c.DHS 2003 prev X population size of region, adjusted for EPP estimated # infections vs. total country estimate by DHS prev d.(DHS 2003/HSS 2003)*HSS 2009 prev *population size of region, adjusted for EPP estimated # infections vs. total country estimate by HSS prev

28 New HIV Infections - EPP a. % of HIV infections in region b. % of HIV infections in region c. % of HIV infections in region d. % of HIV infections in region Western10.0%11.8%15.1%14.6% Central8.0%8.2%5.5%4.0% Greater Accra15.5%18.9%15.2%14.8% Volta7.1%3.6%5.6%6.6% Eastern14.8%14.6%18.7%16.8% Ashanti23.5%22.8%18.9%20.5% Brong Ahafo8.8%9.3%13.9%13.2% Northern6.1%6.5%3.3%4.1% Upper East3.4%2.4%1.5%1.2% Upper West3.0%2.0%2.3%4.3% Total100.0%

29 Modes of Transmission Assesses relative contributions rather than estimating absolute numbers of new infections accurately Treats each risk group as mutually exclusive although it assigns the worst risk exposure to individuals with multiple exposure Depends heavily on quality of data inputs – Some changes in the original MOT model of 2008 – At national level, some missing data e.g. IDU – MOT applied to all regions and so missing data more serious e.g. MSM information only limited to Accra-Tema. Same input for all regions – Assumes the regional size of the sex workers, clients of FSW, MSM, and IDU population is proportional to the distribution of the 2000 urban population

30 ARBARCRERGARNRUERUWRVRWR Rev National Injecting Drug Use (IDU) Partners IDU Sex workers Clients Partners of Clients MSM Female partners of MSM Casual heterosexual sex Partners CHS Low-risk heterosexual No risk0.0 Medical injections Blood transfusions % to partners of high risk (IDU, FSW, MSM, CHS) % to sex work & MSM sex % to casual hetero sex Total # of incident cases2, ,0443, ,233 % of country's cases in region 24.5%7.4%5.9%9.8%30.8%4.8%2.0%1.5%3.9%9.3% % of country's pop in region 20.2%9.5%7.4%9.6%19.2%9.6%3.7%2.5%7.5%10.6% Regional pop size (15- 49) 2,106, ,886768,183 1,006,33 5 1,998,49 5 1,006, ,250263,792787, ,429,017

31 Rev NationalOrig National Injecting Drug Use (IDU) Partners IDU0.1 Sex workers Clients Partners of Clients MSM Female partners of MSM Casual heterosexual sex Partners CHS Low-risk heterosexual No risk0.00 Medical injections Blood transfusions0.1 Comparison between Original (2008) and Current (2010) MOT Models

32 MOT Preliminary Findings The regional models for MOT show large differences in the proportion of new infections attributed to FSW/MSM compared to casual heterosexual sex Note the contribution includes infections among regular partners of these risk groups 52% of new infections occur in MARPs and their partners The contribution of FSW/MSM is greater in Ashanti, Brong Ahafo, Central, Greater Accra, and Northern regions. While in Eastern and Volta regions, casual heterosexual sex appears to be a larger contributor. In the remaining regions, Upper East, Upper West, and Western regions, the contribution appears to be almost the same. The regions which contribute disproportionately to the national epidemic (i.e. the proportion of new infections is greater than the proportion of the population in the region) are Ashanti and Greater Accra.

33 HIV Prevalence in MARPs Declining? MARPSHARP 2006SHARP 2009 Female Sex workers in Accra, Kumasi Male clients of FSWsWAPCAS 2001WAPCAS 2009 Paying clients Non-paying clients Total17.4 -

34 2008 MOT Model with Revised HIV Prevalence in FSW and Their Clients Risk Group Incidence per 100,000 % of incidence Incidence per 100,000 % of incidence Injecting Drug Use (IDU) Sex workers Clients MSM Casual heterosexual sex Low-risk heterosexual No risk0.0 Partners of IDU,FSW clients, MSM Medical injections Blood transfusions Total

35 Summary of MOT and EPP Consistent with the other assessment criteria, EPP shows ER, GAR, AR are regions in which highest proportion of new infections are occurring Regional MOT models do not fit well with data and so will be refined Reducing HIV prevalence in MARPs (FSWs and their clients) from 2006 to current levels reduces HIV incidence rate by 18% and significantly re- distributes the share of infection between low risk heterosexuals and MARPs

36 General Recommendations Need for epidemiological data on MARPs Some discrepancies in sexual behaviour in BSS Need for some more innovative ways to obtain accurate sexual behaviour data Need for more bio-behavioural data in priority regions such as ER, GAR, AR Different epidemiological profiles suggest one size fits all not appropriate; more targeted approaches needed

37 Recommendations for Prevention The available data are relatively limited, but still suggest the need for prioritization of prevention interventions to address MARPs Targeting prevention programmes – Impending mapping and size estimation studies should be implemented – In the many towns with no MARP intervention or information, a rapid initial assessment starting with largest towns is advised using local field personnel – Invest in PLACE (Priorities for Local AIDS Control Efforts) to identify hotspots Review social marketing approaches to increase condom availability and use Mixture of approaches often needed

38 Prevention - MARPs The most effective approach to prevention to regular partners, is to reduce the prevalence among those at risk by effective targeted interventions for MARP. Efforts needed to increase the proportion of MARP who know their HIV status, get early care and treatment, and to encourage testing among their regular partners

39 Prevention – Casual Heterosexual Sex Casual heterosexual sex appears to be an important mode of transmission in some areas, and requires specific targeting of interventions. The population which engages in this behaviour is likely to be small and must be characterized more precisely to better target and design appropriate interventions. Broad based education and awareness campaigns are unlikely to be effective with this group

40 Prioritizing Care, Support and Treatment 1 Allocating care and treatment resources can be based on the estimated number of infected live in each region of the country. Current models to estimate the burden of disease (e.g. through EPP) are done at the national level. However, the total number of infections estimated can be apportioned regionally through different methods, for example, by using a measure of HIV prevalence, applied to the population size of the region, and calibrating it against the number of infections estimated through EPP. Applying this formula, the Ashanti region is allocated the largest portion of infections, followed by GAR and ER

41 Prioritizing Care, Support and Treatment 2 Important to focus diagnostic services in efficient case finding, to ensure that people who are infected know their status and can access services. Proper forecasting for care and treatment needs requires understanding where those who are infected are, and what proportion of them are likely to be diagnosed. Recent scale up of testing services has been dramatic in most regions. However, the key objectives of testing and counseling must drive the way services are scaled up. Case finding, and referral/linkages to care and treatment is a primary measure of the effectiveness of HTC. HTC must continue to focus on those groups which are most likely to be at risk, rather than to test large numbers of people who are not likely to be infected. Case finding efficiency through HTC should be a core indicator of this programme. Regions where the positivity of HTC has dropped below the estimated HIV prevalence of the region suggests poorly focused and inefficient HTC services.

42 HIV Surveillance through PMTCT As PMTCT services scale up and uptake reaches >90% these data become valuable and inexpensive measures of HIV prevalence in more districts/towns, helping regions to further identify where cases are found and where both prevention and care/treatment services can be targeted. Optimal use of these data will improve the effectiveness of the programme

43 Summary HIV prevalence generally low but high in some sub-populations Adjusting HIV by age and urban distribution does not significantly affect trends in most regions Different bio-behavioural and service data point to ER, GAR and AR as priority regions for HIV interventions MARPs contributes disproportionately to HIV but there are indications that HIV infection in FSWs and their clients in Ghana may be dropping Need to identify, map and estimate the size of MARPs More targeted interventions are needed based on epidemiology and demography Identifying cases for treatment could be based on more selective HTC programme scale up As PMTCT coverage and uptake improves, it would be a better source of HIV surveillance than the current annual HSS


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