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Sexual networks, partnership mixing, and the female-to-male ratio of HIV infections in generalized epidemics

Author

Listed:
  • Georges Reniers

    (London School of Hygiene and Tropical Medicine)

  • Benjamin Armbruster

    (Northwestern University)

  • Aaron Lucas

    (Harvard University)

Abstract

Background: Empirical estimates of the female-to-male ratio of infections in generalized HIV epidemics in sub-Saharan Africa range from 1.31 in Zambia to 2.21 in Ivory Coast. Inequalities in the gender ratio of infections can arise because of differences in exposure (to HIV-positive partners), susceptibility (given exposure), and survival (once infected). Differences in susceptibility have to date received most attention, but neither the relatively high gender ratio of infections nor the heterogeneity in empirical estimates is fully understood. Objective: Demonstrate the relevance of partnership network attributes and sexual mixing patterns to gender differences in the exposure to HIV-positive partners and the gender ratio of infections. Methods: Agent-based simulation model built in NetLogo. Results: The female-to-male ratio of infections predicted by our model ranges from 1.13 to 1.75. Gender-asymmetric partnership concurrency, rapid partnership turnover, elevated partnership dissolution in female-positive serodiscordant couples, and lower partnership re-entry rates among HIV-positive women can produce (substantial) differences in the gender ratio of infections. Coital dilution and serosorting have modest moderating effects. Conclusions: Partnership network attributes and sexual mixing patterns can have a considerable effect on the gender ratio of HIV infections. We need to look beyond individual behavior and gender differences in biological susceptibility if we are to fully understand, and remedy, gender inequalities in HIV infection in generalized epidemics.

Suggested Citation

  • Georges Reniers & Benjamin Armbruster & Aaron Lucas, 2015. "Sexual networks, partnership mixing, and the female-to-male ratio of HIV infections in generalized epidemics," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 33(15), pages 425-450.
    • Handle: RePEc:dem:demres:v:33:y:2015:i:15
    DOI: 10.4054/DemRes.2015.33.15
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    References listed on IDEAS

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    1. Nnko, Soori & Boerma, J.T.J Ties & Urassa, Mark & Mwaluko, Gabriel & Zaba, Basia, 2004. "Secretive females or swaggering males?: An assessment of the quality of sexual partnership reporting in rural Tanzania," Social Science & Medicine, Elsevier, vol. 59(2), pages 299-310, July.
    2. Georges Reniers & Benjamin Armbruster, 2012. "HIV Status Awareness, Partnership Dissolution and HIV Transmission in Generalized Epidemics," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-7, December.
    3. Susan Cotts Watkins, 2004. "Navigating the AIDS Epidemic in Rural Malawi," Population and Development Review, The Population Council, Inc., vol. 30(4), pages 673-705, December.
    4. Georges Reniers & Rania Tfaily, 2012. "Polygyny, Partnership Concurrency, and HIV Transmission in Sub-Saharan Africa," Demography, Springer;Population Association of America (PAA), vol. 49(3), pages 1075-1101, August.
    5. Laura Porter & Lingxin Hao & David Bishai & David Serwadda & Maria Wawer & Thomas Lutalo & Ronald Gray, 2004. "Hiv status and union dissolution in Sub-saharan Africa: The case of Rakai, Uganda," Demography, Springer;Population Association of America (PAA), vol. 41(3), pages 465-482, August.
    6. Georges Reniers, 2008. "Marital strategies for regulating exposure to HIV," Demography, Springer;Population Association of America (PAA), vol. 45(2), pages 417-438, May.
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    More about this item

    Keywords

    HIV/AIDS; marriage; sexual behavior; sexual networks; agent-based modeling; sex ratio; sub-Saharan Africa;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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