AIDS Communication Programs and HIV Prevention in South Africa

1. AIDS Communication Programs and HIV Prevention in South Africa

2. Advancing Health Communication, Saving Lives Four basic questions • Does HIV prevention behavior actually reduce HIV prevalence? • Do AIDS communication programs increase HIV prevention behavior? • Can the impact of individual programs be separated from others? • Are these interventions cost-effective?

3. Advancing Health Communication, Saving Lives That require appropriate theories and advanced methods to answer • Multivariate Causal Attribution Analysis (MCA) • 1. An intervention: a full-scale, population-level program with pre/post or follow-up sample survey, • An appropriate theory of communication and behavior change • A valid counter-factual condition to estimate the • net effects of the intervention • “What would have happened without it.”

4. Advancing Health Communication, Saving Lives MCA Analysis with Survey Data • Representative sample survey • Structural equation modeling (SEM) • to estimate causal relationships • Propensity score matching (PSM) • Approximates the conditions of a randomized experimental design by constructing a matched control group that is statistically equivalent to the treatment group external validity causal inference internal validity counter-factual condition

5. W X Z Advancing Health Communication, Saving Lives Causal Pathways: Communication Exposure to HIV Status Exogenous Socio-Demographic Controls Endogenous Variables 2 y2 Behavior 3 direct y3 HIV Status direct y1 Communication Direct or indirect effect? 1

6. Advancing Health Communication, Saving Lives South African National HIV Prevalence, HIV Incidence, Behaviour and Communication Survey, 2005 Commissioned by the Nelson Mandela Foundation Secondary statistical analysis by: D. Lawrence Kincaid (JHU) & Warren Parker (CADRE) Conducted by: Human Science Research Council (HSRC) Centre for AIDS Development Research & Evaluation (CADRE) Medical Research Council (MRC)

7. Advancing Health Communication, Saving Lives How would you rate yourself in terms of risk of becoming HIV positive? 63.6 % do not expect to get infected Percent N = 9,764 (weighted); Have had sex and HIV test

8. Advancing Health Communication, Saving Lives Reasons for believing one is not at risk of HIV infection 64.2 % reported one or more reasons Prevention Behavior Percent N = 9,764 (weighted); Have had sex and HIV test

9. Prevention behavior Tertiary education A student On a pension Not Black White Coloured Indian Single Female Ages 15-24 years Ages 25-43 years Poverty Frequency of 4-5 alcoholic drinks Ever used injectable drugs HIV prevalence in one’s cluster Negative but not stat. significant: No. of regular sex partners (12 mo.) No. of non-regular partners (1 mo.) Advancing Health Communication, Saving Lives Statistically Significant Predictors of HIV Negative Status South Africa, 2005 Positively Related Negatively Related to HIV Negative Status to HIV Negative Status N = 9,764; subsample that has had sex and HIV test; logistic regression analysis

10. Would have been HIV positive without prevention behavior Advancing Health Communication, Saving Lives Percent who are HIV positive by HIV prevention behavior Percent Treatment Group Matched Control Group Difference Using Prevention Behavior No Prevention Behavior N = 9,764; Have had sex and HIV test

11. Percent who are HIV negative by HIV prevention behavior Treatment Group Matched Control Group Difference 100 90.5 86.1 Would have been HIV positive without prevention behavior 80 60 Percent 40 20 4.4 0 Using Prevention Behavior No Prevention Behavior Difference p<0.001 Advancing Health Communication, Saving Lives

12. 16,702,263 Using prevention behavior x 4.4 % Difference in HIV negative status 734,890 Would have been HIV positive in 2005 without prevention behavior 3,990,876 HIV positive in 2005 + 734,890 Would have been HIV positive 4,725,776 Expected to be HIV positive in 2005 Advancing Health Communication, Saving Lives Percent Reduction in HIV Prevalence Due to Prevention Behavior 15.6 %Reduction in HIV infections due to HIV prevention behavior (734,890 / 4,725,776)

13. 15.6 % Reduction in HIV infections due to HIV prevention behavior 734,890 Additional HIV/AIDS cases x US $ 8,000 Lifetime costs for treatment (20 years)* Advancing Health Communication, Saving Lives Expected Life-Time Savings in ARV Treatment of HIV Positive Cases $ 5.9 Billion Estimated savings over 20 years due to HIV prevention as of 2005 * Source: Kahn, Marseille, & Auvert (2006)

14. National HIV/AIDS Communication Survey 2006 D. Lawrence Kincaid, Patrick Coleman, Van Pham JHBSPH & JHHESA Warren Parker, Benjamin Makhubele, Helen Hajiyiannis, Pumla Ntlabati, Cathy Connolly,CADRE A national sample of 6,998 (ages 15-65 yrs) representative of a population 29,315,622 South Africans, using the same sampling frame as the HSRC 2005 survey. A nationally representative sample of

15. Advancing Health Communication, Saving Lives • 1. Age • 2. Sex • 3. Single vs. ever married • 4. Level of education • 5. No children for whom you’re parent or guardian • 6. Level of Living Standard (Household Items) • Poverty: Lack of fuel, clean water, medicine, food • Knows someone who has died of AIDS • Owns one or more television sets • Frequency of watching television • Frequency of listening to radio • Listens to local community radio • Frequency of reading newspapers • Frequency of reading magazines • Frequency of internet use • Currently employed or student • Type of urban and rural residence • White, Indian, Colored versus Black • Province Socio-economic control variables used to estimate adjusted impact of communi-cation programs

16. Type of Communication Program Five Independent Television Programs 1. Tsha Tsha TV Drama 2. Soul City TV Drama 3, Khomanani Choice TV 4. Beat it Siyanqoba TV Program 5. loveLive TV Spots One Monthly Newspaper Supplement 6. S’camto Print (Sunday Times & loveLife) Percent Exposure 48 65 18 27 67 12 Advancing Health Communication, Saving Lives 19 Communication Programs in South Africa N= 6,998 (15-65 yrs.) Population (weighted) = 29,315,622

17. Type of AIDS Communication Program Khomanani Communication Campaign 7. TV Program or Spot 8. Radio Program or Spot 9. Leaflet 10. Newspaper Advertisement Khomanani Community Intervention 11. Participated organized event 12. Spoke to community action ambassador Percent Exposure 53 47 36 32 4 5 Advancing Health Communication, Saving Lives Communication Programs in South Africa N= 6,998 (15-65 yrs.) Population (weighted) = 29,315,622

18. Advancing Health Communication, Saving Lives Communication Programs in South Africa Percent Exposure 36 57 4 6 54 25 56 • Type of Communication Program • Two National Radio Programs • 13. Soul City Radio • 14. loveLive radio Advert • Two Community Radio Programs by ABC Ulwazi • 15. The Journey Community Radio Drama • 16. Body, Mind and Soul Community Radio Drama Three Programs for Children 17. Soul Buddyz TV Drama 18. Soul Buddyz Radio Program 19. Takalani Sesame TV Program N= 6,998 (15-65 yrs.) Population (weighted) = 29,315,622

19. Level of Exposure to 19 AIDS Communication Programs by Gender * Percent Number of Communication Programs N= 6,998 (15-65 yrs.) Population (weighted) = 29,315,622 (not stat. sig.) * About 2,197,454 out of 29,315,622 are not exposed to any programs

20. Advancing Health Communication, Saving Lives Measuring HIV Prevention Behavior • Have you ever had sex before? • Have you had sex in the past 12 mo.? • With the person you most recently had sex with, • did you do anything to prevent HIV infection? • What did you do? • [ DO NOT PROMPT. MULTIPLE RESPONSES. ] • Nothing, used condoms, faithful to partner…etc. N = 4,844 of 7,006

21. -19 Percent condom use by the cumulative exposure to 19 AIDS communication programs ADJUSTED for 19 socio-economic control variables Percent Number of AIDS Communication Programs Seen or Heard 18-point spread N= 4,844 (15-65 yrs.); if had sex in the last 12 months; p<0.001; logistic regression analysis

22. Advancing Health Communication, Saving Lives Impact on Other HIV/AIDS Outcomes Percentage HIV/AIDS Outcomes Point SpreadRange Used condom to prevent HIV 18 (41-59) Talked to partner about HIV test 24 (49-73) Talked to a friend about HIV test 26 (23-79) Ever had an HIV test 21 (36-57) HIV test within the last 12 months 19 (15-34) High reversed AIDS stigma 10 (37-47) Helped someone sick with AIDS 16 (6-22) Know ARV as treatment for AIDS 34 (60-26) Faithful to one’s partner 2 (1 - 3) Abstain from sex n. s. (4 - 4) One vs. multiple partners n. s. (87-87) One vs. multiple partners (last month) n. s. (97-97) Condom with non-regular partner n. s. (71-70)

23. Scatter plot of the correlation among 19 AIDS communication programs (Factor analysis of the tetrachoric correlation among 19 programs) KHOMANANI COMMUNITY PROGRAMS Khomanani organised event Khomanani leaflet Khomanani newspaper Khomanani community ambassador Khomanani TV advert TELEVISION PROGRAMS RADIO PROGRAMS loveLive S’Camtoprint Body Mind Soul radio drama Khomanani Choice TV Khomanani radio advert Journey radio drama Soul City TV Beat It Siyanqoba TV Soul Buddyz radio loveLife radio Takalani Sesame TV Soul Buddyz TV loveLife TV Tsha Tsha TV Soul City radio

24. Percent who watched the TV drama Tsha Tsha during the last 12 months by age and sex * Percent Age Group Advancing Health Communication, Saving Lives N= 6998; not stat. significant by sex

25. Advancing Health Communication, Saving Lives Impact of watching Tsha Tsha on Using Condoms to Prevent HIV/AIDS N = 4,844 who have had sex in last 12 months; p<0.001

26. Advancing Health Communication, Saving Lives Average Treatment Effects on Those Who Watched Tsha Tsha on Television HIV/AIDS Outcomes Average Treatment Effects (Percentage Point Difference) Used condom to prevent HIV 7.0 Used condom with nonregular partner 5.7 Discussed HIV test with partner 4.0 Ever tested for HIV 4.3 Aware of ARV as AIDS treatment 6.5 Attitude towards living with HIV/AIDS 3.0 Helped cared for person sick with AIDS 5.2 Abstinence from sex n.s. Faithful to one partner n.s. One versus multiple sex partners n.s.

27. Cost-Effectiveness analysis of the Tsha Tsha Television Serial Drama on Using Condoms to Prevent HIV

28. Estimation of the Cost-Effectiveness of Tsha Tsha on Using Condoms to Prevent HIV Additional condom users attributed to Tsha Tsha (7 % points): 724,971 Estimated production costs for 52 episodes broadcast before survey:1 US$ 2,272,000 Cost per additional condom user: $ 3.13 ($ 2,272,000 / 724,971) Cost per person reached: $ 0.16 ($ 2,272,000 / 14,132,107) 1 Joint funding by SABC-Education and USAID; broadcast costs are not included but are presumed to be offset by commercial advertising (R 14,768,000 / 6.5 = US $ 2,272,000).

29. Conclusions • HIV prevention behavior helps to • reduce HIV prevalence. • AIDS communication programs • increase HIV prevention behavior. • The impact of individual programs can • be separated from others. • HIV prevention communication • programs and HIV prevention behavior • are highly cost-effective.

30. Communicating Health … Saving Lives

31. Total population ages 15-65 years = 29,366,512 70% of 29,366,512 had sex in last year = 20,565,661 50% watched Tsha Tsha = 10,356,727 Used Condoms to Prevent HIV 58.2% who watched Tsha Tsha = 6,027,615 51.2% matched control group = − 5,302,644 Condom users attributed to Tsha Tsha 724,971 Advancing Health Communication, Saving Lives Estimation of the Cost-Effectiveness of Tsha Tsha * Also: net difference of 0.07 x 10,356,727 viewers = 724,971 condom adopters

32. The HIV Epidemic in South Africa • The HIV epidemic is severe, affecting all age groups • Large prevalence variations exist between sexes, age groups, race groups and communities • Most severely affected are females <20; females aged 20 - 40 and males aged 25 - 45 • Children and older age groups significantly affected HIV prevalence by age and gender, South Africa, 2005 (NM/HSRC)