Demography

, Volume 49, Issue 3, pp 1011–1036

The Impact of HIV Testing on Subjective Expectations and Risky Behavior in Malawi

Article

Abstract

We investigate the causal impact of learning HIV status on HIV/AIDS-related expectations and sexual behavior in the medium run. Our analyses document several unexpected results about the effect of learning one’s own, or one’s spouse’s, HIV status. For example, receiving an HIV-negative test result implies higher subjective expectations about being HIV-positive after two years, and individuals tend to have larger prediction errors about their HIV status after learning their HIV status. If individuals in HIV-negative couples also learn the status of their spouse, these effects disappear. In terms of behavioral outcomes, our analyses document that HIV-positive individuals who learned their status reported having fewer partners and using condoms more often than those who did not learn their status. Among married respondents in HIV-negative couples, learning only one’s own status increases risky behavior, while learning both statuses decreases risky behavior. In addition, individuals in sero-discordant couples who learned both statuses are more likely to report some condom use. Overall, our analyses suggest that ensuring that each spouse learns the HIV status of the other, either through couple’s testing or through spousal communication, may be beneficial in high-prevalence environments.

Keywords

Subjective expectations HIV testing Risky behavior Malawi 

References

  1. Allen, S., Karita, E., Chomba, E., Roth, D. L., Telfair, J., Zulu, I., . . . Haworth, A. (2007). Promotion of couples’ voluntary counselling and testing for HIV through influential networks in two African capital cities. BMC Public Health, 7, 349.Google Scholar
  2. Allen, S., Meinzen-Derr, J., Kautzman, M., Zulu, I., Trask, S., Fideli, U., . . . Haworth, A. (2003). Sexual behavior of HIV discordant couples after HIV counseling and testing. AIDS, 17, 733–740.Google Scholar
  3. Anglewicz, P., Adams, J., Obare-Onyango, F., Kohler, H.-P., & Watkins, S. (2009). The Malawi diffusion and ideational change project 2004–06: Data collection, data quality and analyses of attrition. Demographic Research, 20(article 21), 503–540. doi:10.4054/DemRes.2009.20.21 CrossRefGoogle Scholar
  4. Boozer, M. A., & Philipson, T. J. (2000). The impact of public testing for human immunodeficiency virus. Journal of Human Resources, 35, 419–446.CrossRefGoogle Scholar
  5. Chimbiri, A. (2007). The condom is an Intruder in Marriage: Evidence from rural Malawi. Social Science & Medicine, 64, 1102–1115.CrossRefGoogle Scholar
  6. Corbett, E. L., Makamureb, B., Cheunga, Y. B., Dauyab, E., Matambob, R., Bandasonb, T., . . . Hayes, R. J. (2007). HIV incidence during a cluster-randomized trial of two strategies providing voluntary counselling and testing at the workplace, Zimbabwe. AIDS, 21, 483–489.CrossRefGoogle Scholar
  7. Delavande, A., Giné, X., & McKenzie, D. (2011). Measuring subjective expectations in developing countries: A critical review and new evidence. Journal of Development Economics, 94, 151–163.CrossRefGoogle Scholar
  8. Delavande, A., & Kohler, H.-P. (2009). Subjective expectations in the context of HIV/AIDS in Malawi. Demographic Research, 20(article 31), 817–875. doi:10.4054/DemRes.2009.20.31 CrossRefGoogle Scholar
  9. Denison, J., O’Reilly, K., Schmid, G., Kennedy, C., & Sweat, M. (2008). HIV voluntary counseling and testing and behavioral risk reduction in developing countries: A meta-analysis, 1990–2005. AIDS and Behavior, 12, 363–373.CrossRefGoogle Scholar
  10. De Paula, A., Shapira, G., & Todd, P. E. (2010). How beliefs about HIV status affect risky behaviors: Evidence from Malawi. Unpublished manuscript, Department of Economics, University of Pennsylvania.Google Scholar
  11. Desgrées-du-Loû, A., & Orne-Gliemann, J. (2008). Couple-centred testing and counselling for HIV serodiscordant heterosexual couples in sub-Saharan Africa. Reproductive Health Matters, 16, 151–161.CrossRefGoogle Scholar
  12. Goldstein, M., Zivin, J. G., Habyarimana, J., Pop-Eleches, C., & Thirumurthyk, H. (2008). Health worker absence, HIV testing and behavioral change: Evidence from western Kenya. Unpublished Working Paper, Department of Economics, Columbia University.Google Scholar
  13. Gong, E. (2010). HIV testing & risky behavior: The effect of being surprised by your HIV status. Unpublished manuscript, Department of Agricultural and Resource Economics, University of California, Berkeley.Google Scholar
  14. Granich, R. M., Gilks, C. F., Dye, C., De Cock, K., & Williams, B. G. (2009). Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission: A mathematical model. The Lancet, 373, 48–57.CrossRefGoogle Scholar
  15. Manski, C. F. (2004). Measuring expectations. Econometrica, 72, 1329–1376.CrossRefGoogle Scholar
  16. Matovu, J., Gray, R., Makumbi, F., Waver, M., Serwadda, D., Kigozi, G., . . . Nalugoda, F. (2005). Voluntary HIV counseling and testing acceptance, sexual risk behavior and HIV incidence in Rakai, Uganda. AIDS, 19, 503–511.Google Scholar
  17. Meijer, E., & Wansbeek, T. (2007). The sample selection model from a method of moments perspective. Econometric Reviews, 26, 25–51.CrossRefGoogle Scholar
  18. Obare, F., Fleming, P., Anglewicz, P., Thornton, R., Martinson, F., Kapatuka, A., . . . Kohler, H.-P. (2009). Acceptance of repeat population-based voluntary counseling and testing for HIV in rural Malawi. Sexually Transmitted Infections, 85, 139–144. Advance online publication. doi:10.1136/sti.2008.030320
  19. Santow, G., Bracher, M., & Watkins, S. (2008). Implications for behavioural change in rural Malawi of popular understandings of the epidemiology of AIDS (Working Paper CCPR-2008-045). Los Angles: California Center for Population Research, UCLA.Google Scholar
  20. Sherr, L., Lopman, G., Kakowa, M., Dube, S., Chawira, G., Nyamukapa, C., . . . Gregson, S. (2007). Voluntary counseling and testing: Uptake, impact on sexual behaviour, and HIV incidence in a rural Zimbabwean cohort. AIDS, 21, 851–860.Google Scholar
  21. Thornton, R. (2008). The demand for and impact of learning HIV status: Evidence from a field experiment. American Economic Review, 98, 1829–1863.CrossRefGoogle Scholar
  22. UNAIDS. (2001). The impact of voluntary counselling and testing. A global review of the benefits and challenges. Retrieved from http://www.unaids.org
  23. UNAIDS. (2006). Report on the global HIV/AIDS epidemic. New York: World Health Organization and UNAIDS. Retrieved from http://www.unaids.org
  24. UNAIDS. (2008). Report on the global HIV/AIDS epidemic. New York: World Health Organization and UNAIDS. Retrieved from http://www.unaids.org
  25. The Voluntary HIV-1 Counseling and Testing Efficacy Study Group. (2000). Efficacy of voluntary HIV-1 counselling and testing in individuals and couples in Kenya, Tanzania, and Trinidad: A randomised trial. Lancet, 356, 103–112.CrossRefGoogle Scholar
  26. Watkins, S., Behrman, J. R., Kohler, H.-P., & Zulu, E. M. (2003). Introduction to “Research on demographic aspects of HIV/AIDS in rural Africa”. Demographic Research Special Collection, 1(1), 1–30. doi:10.4054/DemRes.2003.S1.1 Google Scholar
  27. Weinhardt, L. S., Carey, M. P., Johnson, B. T., & Bickham, N. L. (1999). Effects of HIV counseling and testing on sexual risk behavior: A meta-analytic review of published research, 1985–1997. American Journal of Public Health, 89, 1397–1405.CrossRefGoogle Scholar
  28. Wooldridge, J. (2002). Econometric analysis of cross section and panel data. Cambridge, MA: MIT Press.Google Scholar

Copyright information

© Population Association of America 2012

Authors and Affiliations

  1. 1.University of Essex and RAND CorporationSanta MonicaUSA
  2. 2.University of PennsylvaniaPhiladelphiaUSA

Personalised recommendations