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

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Demography

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.

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Notes

  1. The term “voluntary counseling and testing ” (VCT) is also used to describe HIV counseling and testing services.

  2. Detailed descriptions of the MLSFH sample selection, data collection, and data quality are provided on the project website (http://www.malawi.pop.upenn.edu/), in a Special Collection of the online journal Demographic Research that is devoted to the MLSFH (Watkins et al. 2003), and in a follow-up publication that incorporates the 2004 and 2006 rounds of the MLSFH data (Anglewicz et al. 2009).

  3. See Delavande et al. (2011) for an overview about expectations data in developing countries.

  4. The English questionnaire is translated and administered in Chichewa, Yao, or Tumbuka.

  5. The average distance to a clinic is 2 km, and more than 95% of those tested lived within 5 km. Distance to the clinic is calculated as a straight line.

  6. Because everybody received counseling, our analysis measures the impact of HCT rather than testing alone.

  7. HIV testing outside of the MLSFH is a possibility. When respondents were visited by the MLSFH VCT team for an HIV test in 2006, they were asked about all their previous HIV testing experiences. Note that 15% of our analytical sample were not found by the MLSFH HCT team in 2006. About 13% of the respondents who learned their HIV status in 2004 were retested in 2004, 2005, and 2006 outside the 2004 MLSFH. Because sero-conversion is rare (less than 2% between the waves), most of the individuals who were retested were still of the same HIV status, so for them, testing outside our study is unlikely to have an impact on our analysis. Of those who did not learn their HIV status in 2004, 14.9% reported being tested outside the MLSFH 2004 in 2004, 2005, and 2006 (46% of them in 2005 and 52% of them in 2006, but we do not know the exact month). As a result, we may wrongly classify some individuals as not knowing their HIV status when they engaged in the various behaviors in the past 12 months. This suggests that our estimates of the impact of testing on behavior are conservative.

  8. Using a t test, we can reject the hypothesis that the two means are equal (p < .001).

  9. We exclude two respondents of unknown gender.

  10. We maintain the assumption 17.2 of Wooldridge (2002) to ensure identification and consistency.

  11. Wooldridge (2002) pointed out that the hypothesis of selection should be tested with the uncorrected t statistics obtained from the IV estimation. Standard errors need to be corrected for the generated regressor problem when the hypothesis of no selection is rejected.

  12. Note also that only 97 respondents in the analytical sample are HIV positive.

  13. For this purpose, we allocated a 2006 HIV-positive status to respondents who were found to be HIV-positive in 2004, even for those who were not tested in 2006.

  14. We investigate later the impact of learning own and spouse’s HIV status simultaneously.

  15. Sherr et al. (2007) found that in rural Zimbabwe, testing negative for HIV was associated with increased risky behavior in terms of partner acquisition rates, although they could not address the selection issue of HIV testing.

  16. We focus on respondents who had never been married as of 2006, or who were divorced and separated in both 2004 and 2006. A female respondent is counted as having experienced a pregnancy in the past two years if she reports a higher number of children in 2004 than in 2006, or if (s)he reports being currently pregnant or having a partner currently pregnant.

  17. The incentive amounts were allocated independently on separate occasions to husbands and wives. Not all spouses of respondents were offered a test: men who divorced or were widowed and spouses of the newly sampled adolescents were ineligible for testing.

  18. We exclude from the couples’ analysis 19 respondents who were married in 2004 but whose spouse had died by 2006 because behaviors of widowed individuals may be quite different from those of married or separated respondents. Men in polygamous marriages are matched to their first wife.

  19. Distance between respondents’ home and the HCT clinic is the same for both spouses.

  20. A natural explanation for this behavior is altruism. However, given that the vast majority of people who previously tested positive actually report a low probability of being HIV positive, other motives may be responsible.

References

  • 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.

  • 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.

  • 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

    Article  Google Scholar 

  • Boozer, M. A., & Philipson, T. J. (2000). The impact of public testing for human immunodeficiency virus. Journal of Human Resources, 35, 419–446.

    Article  Google Scholar 

  • Chimbiri, A. (2007). The condom is an Intruder in Marriage: Evidence from rural Malawi. Social Science & Medicine, 64, 1102–1115.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

  • 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.

    Article  Google Scholar 

  • 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.

  • 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.

  • 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.

    Article  Google Scholar 

  • Manski, C. F. (2004). Measuring expectations. Econometrica, 72, 1329–1376.

    Article  Google Scholar 

  • 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.

  • Meijer, E., & Wansbeek, T. (2007). The sample selection model from a method of moments perspective. Econometric Reviews, 26, 25–51.

    Article  Google Scholar 

  • 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

  • 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 

  • 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.

  • Thornton, R. (2008). The demand for and impact of learning HIV status: Evidence from a field experiment. American Economic Review, 98, 1829–1863.

    Article  Google Scholar 

  • UNAIDS. (2001). The impact of voluntary counselling and testing. A global review of the benefits and challenges. Retrieved from http://www.unaids.org

  • UNAIDS. (2006). Report on the global HIV/AIDS epidemic. New York: World Health Organization and UNAIDS. Retrieved from http://www.unaids.org

  • UNAIDS. (2008). Report on the global HIV/AIDS epidemic. New York: World Health Organization and UNAIDS. Retrieved from http://www.unaids.org

  • 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.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • Wooldridge, J. (2002). Econometric analysis of cross section and panel data. Cambridge, MA: MIT Press.

    Google Scholar 

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Acknowledgments

We thank Chuck Manski, Pascaline Dupas, Erik Meijers, and seminar participants of the 2008 AEA meetings; Bocconi University; RAND Corporation; Universidade Nova de Lisboa; and UCL for comments. We gratefully acknowledge support for this research through the National Institute of Child Health and Development (Grant No. R03HD058976).

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Authors and Affiliations

  1. University of Essex and RAND Corporation, 1176 Main Street, Santa Monica, CA, 90407, USA

    Adeline Delavande

  2. University of Pennsylvania, 3718 Locust Walk (272 McNeil Bldg), Philadelphia, PA, 19104-6298, USA

    Hans-Peter Kohler

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  1. Adeline Delavande
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  2. Hans-Peter Kohler
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Correspondence to Adeline Delavande.

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Delavande, A., Kohler, HP. The Impact of HIV Testing on Subjective Expectations and Risky Behavior in Malawi. Demography 49, 1011–1036 (2012). https://doi.org/10.1007/s13524-012-0119-7

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