1. Monitoring the effects of ARV treatment programmes on prevention Gabriel Mwaluko 1, Mark Urassa,2, John Changalucha,2, Ties Boerma 3 1 TANESA Project, Mwanza, Tanzania 2 National Institute for Medical Research, Mwanza, Tanzania 3 University of North Carolina at Chapel Hill

2. The effect of treatment on prevention / HIV transmission Positive –more HIV testing & counselling, –stigma reduction, –behavioural change, –reduction in infectiousness of people on treatment Negative : –behavioural disinhibition, –more STIs, –resources diverted from prevention –longer period of infectiousness because of longer life

3. Monitoring of prevention interaction: levels and methods At the individual level - among those who are on treatment –in the context of treatment visits –information from partners At the population / community level - among those living in communities with access to treatment –through local studies –through national surveys –qualitative and quantitative data

4. Sources of data on knowledge, attitude, risk behaviour General population surveys: reproductive ages (15- 49, 15-59) Youth / adolescents surveys (12-19, 15-24, 10-17) Target group surveys: sex workers, clients of sex workers, MSM, IDU Qualitative data; participatory research, qualitative data

5. Monitoring at the community / population level: indicators HIV Testing and Counselling uptake –Routine data from centres - include reason for testing –Population survey: ever had a test, wants a test, knows where to get a test etc. Stigma /discrimination –Survey: Willingness to care for household member with AIDS; buy food from shopkeeper with HIV/AIDS; female teacher with HIV/AIDS not sick allowed to continue teaching; member of family infected, want it to remain a secret –Qualitative data Risk perception

6. Indicators of Stigma, Kisesa 1996-2000 (both sexes combined)

7. Trends in Sexual Behaviour Abstinence/ first sex Multiple partnerships Condom use

8. Trends in median age at first sex (years) among young people, Kisesa, Tanzania* *Based on current status data among 15-19 year olds

9. Indicators - Sexual behaviour: general  Proportion reporting a non-marital non-cohabiting partner in the last 12 months - cohabitation is considered lower risk  Proportion who used a condom during the last sex with a non- cohabiting partner Condom use at last sex is good measure of consistency of use at the population level

10. Condoms: Used a condom at last sex with non-regular partner, men, Tanzania, 1994-1999

11. Multiple partnerships, Lusaka, Zambia, 1990-98

12. Trends in number of partners in the last year among sexually active MEN, Kisesa

13. Trends in condom use among MEN15-44, Kisesa, Tanzania

14. ABC and more.. studies How accurate is self reported sexual behaviour? Extensive comparison of levels and trends in Uganda, Thailand, Zambia and Kenya, Cameroon and Zimbabwe Four city study UNAIDS Rural Kisesa - Manicaland comparison Difficult to assess validity but certainly multiple issues

15. Trends in HIV/STI Transmission HIV prevalence by sex and age HIV incidence STI as a proxy

16. Trends in sexual behaviour and STIs in industrialized countries STIs: Infection rates of early syphilis, rectal gonorrhoea Sexual behaviour: unprotected anal intercourse among HIV negative men, number of partners HIV incidence? Caution - role HIV optimism

17. HIV prevalence among MEN and WOMEN 15-44 in three sero-surveys, Kisesa, Tanzania* *All prevalence rates are age-standardized

18. Concluding thoughts Monitoring of effect of treatment programmes on prevention is a necessity - regular monitoring or research or both? Individual behaviours - condom use? STD incidence probably best bet (HIV incidence in partners?) Measurement of trends over time in behaviour is difficult and one needs to look for opportunities at both national and local levels, supplemented by qualitative research Need for better STI surveillance HIV surveillance - multiple methods will have to be employed