Modelling the expected Distribution of new HIV infections in Nigeria

1. Implications for data analysis, surveillance and incidence monitoring Modelling the expected Distribution of new HIV infections in Nigeria Dr Ogungbemi Kayode (NACA) Dr Oduwole Modupe (UNAIDS) Dr Nnorom Joseph (National Consultant) Dr Fajemisin Oluwole (National Consultant)  International consultants Dr. Stover John (Futures Institute) Borquez Annick (Imperial College London) With inputs from National M&E TWG and Supported by UNAIDS and the World Bank

2. Background on the Model • Developed by the UNAIDS Reference Group. • Used to calculate the expected short term incidence of HIV infections among the adult population . • Applied and piloted in several countries including Nigeria .

3. Process and Coordination • Country team constituted • Consensus building meeting held to agree on model assumptions • Draft shared with UNAIDS and international consultants for comments. • Final draft produced based on the comments from international consultants • Plan underway to update the model with recently available data.

4. Study Questions • What are the sources of new HIV infections in Nigeria? • Where are the bulk of new infections occurring in the next 12 months?. • What is the implication of this evidence for program planning, resource mobilization and distribution? • What is the implication for data analysis, surveillance and incidence monitoring?

5. Model Data sources • The spreadsheet model uses • the current prevalence of HIV infection • numbers of individuals with particular exposures, and • the rates of these exposures • No of partners and acts pe partner • No of acts protected • to calculate the expected incidence of HIV • The distribution of infection over the coming year by adult risk behaviour

6. Major modes of transmission of HIV in adults in Nigeria • Sexual contact • Commercial sex • Casual sex • Marital sex • Men who have sex with men • Injecting drug use • Blood transfusions • Medical injections

7. New infections from sexual transmission • New infections = f(HIV prevalence in partners, number of partners, acts per partner, transmission probability per act, STI co-factors, condom use) • Protection = condom use

8. Population Distribution of Risk in Nigeria Sources, NDHS 2003,NARHS 2005,IBBSS 2007, BSS 2005, expert opinion

9. HIV Prevalence by Risk Group

10. Partners and Acts Sources: NDHS, IBBSS,

11. Percentage of Acts Protected Source: IBBSS 2007, BSS 2005, NARHS 2005, NDHS 2003

13. Key Findings • About 25% of infections is attributable to high risk groups and their partners who together only constitute 3.3% of the adult population • More than 34% of infection will occur in persons reporting low risk sex practices • Condom use amongst low risk groups is dismally low. • About 39% of new infections will occur in CHS most of which involve the youths and mobile population

14. Data Use and Recommendations • Data Informed the finalization of National Prevention Plan and BCC Strategy. • Data informed the modification of World Bank MAP II PAD • Intensify efforts to target the assumed low risk groups and their partners with innovative, high impact prevention interventions including HCT • Preventive efforts among the high risk group and their partners should be intensified and sustained • High risk casual sex in youths and mobile populations requires special focus for prevention. • Emphasize the use of condoms • Couple counseling & testing

15. Model Limitations • Inputs • Variation in data between surveys • Few data inferred from regional estimates and default • Number of sexual partners and acts not available for some groups • Model Inherent Assumptions • Lack of heterogeneity within risk groups • Categorization according to the most risky behaviour

16. Thank you for your attention