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Concurrent Partnerships, Acute Infection and HIV Epidemic Dynamics Among Young Adults in Zimbabwe

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Abstract

This paper explores the roles of acute infection and concurrent partnerships in HIV transmission dynamics among young adults in Zimbabwe using realistic representations of the partnership network and all published estimates of stage-specific infectivity. We use dynamic exponential random graph models to estimate partnership network parameters from an empirical study of sexual behavior and drive a stochastic simulation of HIV transmission through this dynamic network. Our simulated networks match observed frequencies and durations of short- and long-term partnerships, with concurrency patterns specific to gender and partnership type. Our findings suggest that, at current behavior levels, the epidemic cannot be sustained in this population without both concurrency and acute infection; removing either brings transmission below the threshold for persistence. With both present, we estimate 20–25% of transmissions stem from acute-stage infections, 30–50% from chronic-stage, and 30–45% from AIDS-stage. The impact of acute infection is strongly moderated by concurrency. Reducing this impact by reducing concurrency could potentially end the current HIV epidemic in Zimbabwe.

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References

  1. Coombs RW, Speck CE, Hughes JP, Lee W, Sampoleo R, Ross SO, et al. Association between culturable human immunodeficiency virus type 1 (HIV-1) in semen and HIV-1 RNA levels in semen and blood: Evidence for compartmentalization of HIV-1 between semen and blood. J Infect Dis. 1998;177(2):320–30.

    Article  PubMed  CAS  Google Scholar 

  2. Leynaert B, Downs AM, de Vincenzi I. Heterosexual transmission of human immunodeficiency virus—variability of infectivity throughout the course of infection. Am J Epidemiol. 1998;148(1):88–96.

    PubMed  CAS  Google Scholar 

  3. Little S, McLean A, Spina C, Richman D, Havlir D. Viral dynamics of acute HIV-1 infection. J Exp Med. 1999;190(6):841–50.

    Article  PubMed  CAS  Google Scholar 

  4. Quinn TC, Wawer MJ, Sewankambo N, Serwadda D, Li CJ, Wabwire-Mangen F, et al. Viral load and heterosexual transmission of human immunodeficiency virus type 1. N Engl J Med. 2000;343(13):921–9.

    Article  Google Scholar 

  5. Jacquez JA, Koopman J, Simon CP, Longini IMJ. Role of the primary infection in epidemics of HIV-infection in gay cohorts. J Acquir Immune Defic Syndr Hum Retrovirol. 1994;7(11):1169–84.

    CAS  Google Scholar 

  6. Koopman JS, Jacquez JA, Welch GW, Simon CP, Foxman B, Pollock SM, et al. The role of early HIV infection in the spread of HIV through populations. J Acquir Immune Defic Syndr Hum Retrovirol. 1997;14:249–58.

    Article  PubMed  CAS  Google Scholar 

  7. Longini IMJ, Clark WS, Haber M, Hosburgh RJ. The stages of HIV infection: waiting times and infection transmission probabilities. Lect Notes Biomath. 1989;83:111–37.

    Article  Google Scholar 

  8. Pilcher CD, Tien HC, Eron JJJ, Vernazza PL, Leu S-Y, Stewart PW, et al. Brief but efficient: acute HIV infection and the sexual transmission of HIV. J Infect Dis. 2004;189(10):1785–92.

    Article  PubMed  Google Scholar 

  9. Wawer MJ, Gray RH, Sewankambo NK, Serwadda D, Li XB, Laeyendecker O, et al. Rates of HIV-1 transmission per coital act, by stage of HIV-1 infection, in Rakai, Uganda. J Infect Dis. 2005;191(9):1403–9.

    Article  PubMed  Google Scholar 

  10. Pinkerton SD. Probability of HIV transmission during acute infection in Rakai, Uganda. AIDS Behav. 2008;12(5):677–84.

    Article  PubMed  Google Scholar 

  11. Abu-Raddad LJ, Longini IA. No HIV stage is dominant in driving the HIV epidemic in sub-Saharan Africa. AIDS. 2008;22(9):1055–61.

    Article  PubMed  Google Scholar 

  12. Hollingsworth TD, Anderson RM, Fraser C, editors. HIV-1 transmission, by stage of infection. Univ. Chicago Press; 2008.

  13. Cohen MS, Pilcher CD. Amplified HIV transmission and new approaches to HIV prevention. J Infect Dis. 2005;191(9):1391–3.

    Article  PubMed  Google Scholar 

  14. Eaton JW, Hallett TB, Garnett GP. Concurrent sexual partnerships and primary HIV infection: a critical interaction. AIDS Behav. 2010. doi:10.1007/s10461-010-9787-8.

  15. Hayes R, White R. Amplified HIV transmission during early-stage infection. J Infect Dis. 2005;193:604–5.

    Article  Google Scholar 

  16. Pinkerton SD. How many sexually-acquired HIV infections in the USA are due to acute-phase HIV transmission? AIDS. 2007;21(12):1625–9.

    Article  PubMed  Google Scholar 

  17. Prabhu VS, Hutchinson AB, Farnham PG, Sansom SL. Sexually acquired HIV infections in the United States due to acute-phase HIV transmission: an update. AIDS. 2009;23(13):1792–4.

    Article  PubMed  Google Scholar 

  18. Rapatski BL, Suppe F, Yorke JA. HIV epidemics driven by late disease stage transmission. J Acquir Immune Defic Syndr. 2005;38(3):241–53.

    PubMed  Google Scholar 

  19. Xiridou M, Geskus R, de Wit J, Coutinho R, Kretzschmar M. Primary HIV infection as source of HIV transmission within steady and casual partnerships among homosexual men. AIDS. 2004;18(9):1311–20.

    Article  PubMed  Google Scholar 

  20. Pao D, Fisher M, Hue S, Dean G, Murphy G, Cane PA, et al. Transmission of HIV-1 during primary infection: relationship to sexual risk and sexually transmitted infections. AIDS. 2005;19(1):85–90.

    Article  PubMed  Google Scholar 

  21. Yerly S, Vora S, Rizzardi P, Chave JP, Vernazza PL, Flepp M, et al. Acute HIV infection: impact on the spread of HIV and transmission of drug resistance. AIDS. 2001;15(17):2287–92.

    Article  PubMed  CAS  Google Scholar 

  22. Brenner BG, Roger M, Routy JP, Moisi D, Ntemgwa M, Matte C, et al., editors. High rates of forward transmission events after acute/early HIV-1 infection. Univ Chicago Press; 2007.

  23. Hudson CP. AIDS in rural Africa: a paradigm for HIV-1 prevention. Int J STD AIDS. 1996;7(4):236–43.

    Article  PubMed  CAS  Google Scholar 

  24. Morris M, Kretzschmar M. Concurrent partnerships and the spread of HIV. AIDS. 1997;11(5):641–83.

    Article  PubMed  CAS  Google Scholar 

  25. Gregson S, Nyamukapa CA, Garnett GP, Mason PR, Zhuwau T, Carael M, et al. Sexual mixing patterns and sex-differentials in teenage exposure to HIV infection in rural Zimbabwe. Lancet. 2002;359(9321):1896–903.

    Article  PubMed  Google Scholar 

  26. Sawers L, Stillwaggon E. Concurrent sexual partnerships do not explain the HIV epidemics in Africa: a systematic review of the evidence. J Int AIDS Soc. 2010;13:34.

    Google Scholar 

  27. NIMH Collaborative HIV/STD Prevention Trial Group. Methodological overview of a five-country community-level HIV/sexually transmitted disease prevention trial. AIDS. 2007;21 Suppl 2:S3–18.

    Google Scholar 

  28. Kasprzyk D, Montaño DE. Application of an integrated behavioral model to understand HIV prevention behavior of high-risk men in rural Zimbabwe. In: Ajzen I, Hornik R, editors. Prediction and change of health behavior: applying the reasoned action approach. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.; 2007.

  29. UNAIDS Reference Group on Estimates Modelling and Projections. Consultation on concurrent sexual partnerships: recommendations from a meeting of the UNAIDS reference group on estimates, modelling and projections held in Nairobi, Kenya, April 20–21 2009. http://www.epidem.org/Publications/Concurrency%20meeting%20recommendations_Final.pdf2009.

  30. Central Intelligence Agency. CIA World Factbook—Zimbabwe. 2009. https://www.cia.gov/library/publications/the-world-factbook/geos/zi.html Accessed 12 Dec 2009.

  31. Nnko S, Boerma JT, Urassa M, Mwaluko G, Zaba B. Secretive females or swaggering males? An assessment of the quality of sexual partnership reporting in rural Tanzania. Soc Sci Med. 2004;59(2):299–310.

    Article  PubMed  Google Scholar 

  32. Handcock MS, Hunter DR, Butts CT, Goodreau SM, Morris M. ERGM: a package to fit, simulate and diagnose exponential-family models for networks. 2.2-5 ed2010.

  33. Burington B, Hughes JP, Whittington WL, Stoner B, Garnett G, Aral SO, et al. Estimating duration in partnership studies: issues, methods and examples. Sex Transm Infect. 2010;86(2):84–9.

    Google Scholar 

  34. Frank O, Strauss D. Markov graphs. J Am Stat Assoc. 1986;81(395):832–42.

    Article  Google Scholar 

  35. Strauss D, Ikeda M. Pseudolikelihood estimation for social networks. J Am Stat Soc. 1990;85(409):204–12.

    Google Scholar 

  36. Wasserman S, Pattison P. Logit models and logistic regressions for social networks. I. An introduction to Markov graphs and p*. Psychometrika. 1996;60:401–25.

    Article  Google Scholar 

  37. Handcock MS. Statistical models for social networks: degeneracy and inference. In: Breiger RL, Carley KM, Pattison P, editors. Dynamic social network modeling and analysis: workshop summary and papers. Washington: National Academies Press; 2003. p. 229–40.

    Google Scholar 

  38. Snijders TAB, Pattison PE, Robins GL, Handcock MS. New specifications for exponential random graph models. Sociol Methodol. 2006;36(1):99–153.

    Article  Google Scholar 

  39. Robins G, Morris M. Advances in exponential random graph (p*) models. Soc Networks. 2007;29(2):169–72.

    Article  Google Scholar 

  40. Handcock MS, Hunter DR, Butts CT, Goodreau SM, Morris M. Statnet: software tools for the representation, visualization, analysis and simulation of social network data. J Stat Softw. 2008;24(1):1–11.

    PubMed  Google Scholar 

  41. Hunter DR, Goodreau SM, Handcock MS. Goodness of fit of social network models. J Am Stat Assoc. 2008;103(481):248–58.

    Article  CAS  Google Scholar 

  42. Krivitsky PN. Statistical models for social network data and processes. Seattle: University of Washington; 2009.

    Google Scholar 

  43. Handcock MS, Hunter DR, Butts CT, Goodreau SM, Morris M. Statnet: software tools for the statistical modeling of network data. 2.0 ed2003.

  44. The World Bank. World development indicators. Washington: The World Bank; 2010.

    Google Scholar 

  45. Gregson S, Gonese E, Hallett TB, Taruberekera N, Hargrove JW, Lopman B, et al. HIV decline in Zimbabwe due to reductions in risky sex? Evidence from a comprehensive epidemiological review. Int J Epidemiol. 2010;39(5):1311–23.

    Article  PubMed  Google Scholar 

  46. Joint United Nations Programme on HIV/AIDS. AIDS epidemic update. Geneva: UNAIDS, World Health Organization; 2009.

  47. Jacquez JA, Simon CP. The stochastic SI model with recruitment and deaths. 1. Comparison with the closed SIS model. Math Biosci. 1993;117(1–2):77–125.

    Article  PubMed  CAS  Google Scholar 

  48. May RM. Population biology of microparasite infections. In: Hallam TG, Levin SA, editors. Mathematical ecology: an introduction. Berlin: Springer-Verlag; 1986. p. 405–42.

    Google Scholar 

  49. Morris M, Kurth AE, Hamilton DT, Moody J, Wakefield S, The Network Modeling Group. Concurrent partnerships and HIV prevalence disparities by race: linking science and public health practice. Am J Public Health. 2009;99(6):1023–31.

    Article  PubMed  Google Scholar 

  50. Morris M, Epstein H, et al. Timing is everything: international variations in historical sexual partnership concurrency and HIV prevalence. PLoS One e14092. 2010. doi:10.1371/journal.pone.0014092.

  51. Moody J. The importance of relationship timing for diffusion. Soc Forces. 2002;81(1):25–56.

    Article  Google Scholar 

  52. Hallett TB, Singh K, Smith JA, White RG, Abu-Raddad LJ, Garnett GP. Understanding the impact of male circumcision interventions on the spread of HIV in southern Africa. PLoS One. 2008;3(5):e2212.

    Article  PubMed  Google Scholar 

  53. Deuchert E, Brody S. Plausible and implausible parameters for mathematical modeling of nominal heterosexual HIV transmission. Ann Epidemiol. 2007;17(3):237–44.

    Article  PubMed  Google Scholar 

  54. Gisselquist D, Rothenberg R, Potterat J, Drucker E. HIV infections in sub-Saharan Africa not explained by sexual or vertical transmission. Int J STD AIDS. 2002;13:657–66.

    Article  PubMed  Google Scholar 

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Acknowledgments

The authors would like to thank the study participants as well as Mark Handcock, David Hunter, Pavel Krivitsky, Carter Butts, and the entire statnet development team. We are also grateful for the helpful comments from people who read earlier drafts, including Jim Shelton and Helen Epstein. SMG and SC were supported in part by the Puget Sound Partners for Global Health (Research and Technology Project Award 26145). NIH provided support for the data collection (U10-MH061544, R2I-AA014802), the methodology and software development (R01-HD041877 and R01-DA12831), and the analysis (K99-HD057553 and P30-AI27757).

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Correspondence to Steven M. Goodreau.

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Goodreau, S.M., Cassels, S., Kasprzyk, D. et al. Concurrent Partnerships, Acute Infection and HIV Epidemic Dynamics Among Young Adults in Zimbabwe. AIDS Behav 16, 312–322 (2012). https://doi.org/10.1007/s10461-010-9858-x

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