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[19] Brewer DD, Rothenberg RB, Potterat JJ, et al. HIV epidemiology in sub-Saharan Africa: Rich in conjecture, poor in data. Int J STD AIDS 2004;15:63–5. [20] Brody S, Potterat JJ. Establishing valid AIDS monitoring and research in countries with generalized epidemics. Int J STD AIDS 2004; 15:1– 6. [21] Brewer DD, Hagan H, Sullivan DG, et al. Social structural and behavioral underpinnings of hyperendemic hepatitis C virus transmission in drug injectors. J Infect Dis 2006;194:764 –72.
To the Editors: Pettifor et al’s recent study concludes that “the remarkable prevalence of HIV in young people in South Africa cannot be ascribed to exceptional risk taking behavior” [1]. This and the accompanying editorial [2] argue that behavioral change campaigns have “failed,” and that more emphasis needs to be placed on biological interventions. This conclusion is based on their comparative study of sexual behaviors in representative survey samples of 18 –24-year-olds in the United States (Add Health) and South Africa (South African Youth Survey—SAYS). Their study found that all the risk factors evaluated (excluding couple age discordance) to be more prevalent in the United States—the low HIV prevalence area. We believe this conclusion is unwarranted for two reasons. First, their study ignores the literature that explores the reasons for the large differences in HIV prevalence by race within both these countries. Second, they do not evaluate any network-level risk factors. The Add Health Survey revealed that for every category of individual-level risk behavior, non-Hispanic blacks had considerably higher sexually transmitted infection rates (up to 28 times higher) compared with nonHispanic whites [3]. This does not however mean that behavioral factors do not determine these racial differences. It may just be that these differences are due to network-level factors that have not been assessed. Indeed, a further analysis of the Add Health and three other surveys from the United States showed that differences in rates of concurrency and assortative mixing explained a 2.6-fold difference by race in HIV prevalence [4]. Our group has shown a similar phenomenon in the Cape Area Panel Survey—a representative sample of 14 –22-yearolds in Cape Town, South Africa. HIV prevalence in South Africa differs by racial group by over an order of magnitude [5]. We found that individual-level risk factors were unable to explain these large differences in HIV spread, but that network-level factors could [6]. For example, the sexually active white respondents had had the greatest number of lifetime partners, but partner concurrency was more commonly reported by the black respondents— 41% of black men compared with 4% of white men stated that they had engaged in a concurrent sexual partnership. The SAYS study found that the biggest “risk factor” for HIV acquisition was race— black women, for example, had an adjusted odds ratio of 8.3 for being HIV-infected compared with white women [7]. However, they did not collect data on network parameters such as concurrency. In a separate study using the Cape Area Panel Survey data, we described that sexually transmitted infection symptom prevalence remained similarly associated with race when controlling for individual-level parameters only [8], but not when additionally adjusting for concurrency. These findings caution against concluding, on the basis of weak or absent associations between standard behavior metrics and HIV prevalence, whether individual or ecological, that nonbehavioral factors must be cofactors in transmission.
Many of the biological differences that Pettifor [1] and Jaspen [2] highlight as potential cofactors of transmission such as viral subtype and circumcision cannot be invoked as explanations for differences in HIV prevalence between demographic groups within country. In Cape Town, for example, all young adults are at threat from the same viral subtypes, and black men are the most likely to be circumcised [6]. We believe that the most plausible reason for the large differences in HIV prevalence between countries and between demographic groups within countries is differences in sexual behavior at the network level, factors which the authors readily identify they were unable to assess in their study. There is a danger, in the excitement of the recent advances in the development of biologically based HIV prevention technologies, that we may lose sight of important behavioral determinants of HIV transmission, which could be highly amenable to intervention if afforded the same investment that is being contemplated for some of these newer technologies. Behavioral campaigns have been responsible for the dramatic declines in HIV incidence in Uganda [9]; in both Uganda and Zimbabwe, reductions in partner concurrency were instrumental in bringing down HIV incidence [9,10]. Chris Kenyon, MbChB., M.A., M.P.H. Department of Medicine University of Cape Town Cape Town, South Africa Andrew Boulle, MbChB., M.P.H. Centre for Infectious Disease Epidemiology and Research University of Cape Town Cape Town South Africa Robert Colebunders, MBChB. Professor of Infectious Diseases University of Antwerpen Sipho Dlamini, MBChB., F.C.P. Senior Registrar Infectious Diseases Groote Schuur Hospital South Africa Saul Johnson, MBChB. Managing Director Health & Development Africa References [1] Pettifor AE, Levandowski BA, Macphail C, et al. A Tale of two countries: Rethinking sexual risk for HIV among young people in South Africa and the United States. J Adolesc Health 2011;49:237– 43. [2] Jaspan H. The wrong place at the wrong time: Geographic disparities in young people’s HIV risk. J Adolesc Health 2011;49:227–9. [3] Hallfors DD, Iritani BJ, Miller WC, Bauer DJ. Sexual and drug behavior patterns and HIV and STD racial disparities: The need for new directions. Am J Public Health 2007;97:125–32. [4] Morris M, Kurth AE, Hamilton DT, et al. Concurrent partnerships and HIV prevalence disparities by race: linking science and public health practice. Am J Public Health 2009;99:1023–31. [5] Shisana O, Rehle T, Simbayi L, et al. South African National HIV Prevalence, HIV Incidence, Behaviour and Communication Survey. Human Sciences, Research Council, Pretoria, South Africa; 2005. [6] Kenyon C, Dlamini S, Boulle A, et al. A network level explanation for the differences in HIV prevalence in South Africa’s racial/ethnic groups. Afr J AIDS Res 2009;8:243–54.
J.J. Potterat et al. / Journal of Adolescent Health 50 (2012) 207–210
[7] Pettifor AE, Rees HV, Kleinschmidt I, et al. Young people’s sexual health in South Africa: HIV prevalence and sexual behaviors from a nationally representative household survey. AIDS 2005;19:1525–34. [8] Kenyon C, Badri M. The role of concurrent sexual relationships in the spread of Sexually Transmitted Infections in young South Africans. South Afr J HIV Med 2009:10:29 –36. [9] Kirby D. Changes in sexual behaviour leading to the confirmation from multiple sources of evidence decline in the prevalence of HIV in Uganda. Sex Transm Infect 2008;84:ii35– 41. [10] Daniel T, Halperin DT, Mugurungi O, et al. A surprising prevention success: Why did the HIV epidemic decline in Zimbabwe? PLoS Med 2011; 8;e1000414.
The Authors reply: In their letter, Potterat et al raise the question of whether the high prevalence of HIV observed among young people in South Africa is the result of parenteral HIV exposure. Although we found that young people in South Africa did not report more sexual risk behaviors than their U.S. peers, current evidence suggests that the vast majority of infections in sub-Saharan Africa, including South Africa, are the result of sexual transmission [1,2]. Several studies have documented that unclean needles contribute only a small proportion of new HIV infections in sub-Saharan Africa [3–7]. Although measuring all exposures is important when trying to determine the etiology of infection, in a setting such as South Africa, the dominant modifiable risk factor for HIV is sexual behavior. Measuring sexual behavior well is important to understanding transmission and for developing interventions. We do not believe that the combination of high HIV prevalence and the lack of high-risk behavior among South African youth means that they are being significantly exposed through routes other than sexual intercourse. Rather, we hypothesize that a combination of sexual mixing in a high-prevalence setting, structural factors that put young people at increased risk of exposure and unique biological factors, such as the predominance of clade C HIV [8,9], is driving the epidemic in subSaharan Africa over and above individual sexual behaviors. Kenyon et al assert that we dismiss the role of behavior, in particular concurrency, and also race in explaining differences in the epidemics observed in South Africa and the United States. The debate on the role of concurrency as a driver of the HIV epidemic in sub-Saharan Africa continues [10 –14]. We believe it plays a role and is likely one of several factors contributing to the on-going epidemic. In our South African youth survey, we found that close to 25% of men and 5% of women reported concurrent partners in the past 12 months [15]. We found it to be associated with HIV infection among women but not men. The question of whether South African young people practice concurrency more than their U.S. peers is unclear. Morris et al report a point prevalence of concurrency in the United States of between 5% and 13% for African American young men and 4% for African American young women [10]. As this estimate is a point prevalence, it likely underestimates concurrency over a longer period (i.e., in past 6 or 12 months). Doherty et al found among Latino youth in the United States that 27% of males and 14% of females reported having concurrent partners in the past 6 months [16]. Manhart et al in a random digit-dial survey of 18 –39 years olds in Seattle found that between 21% and 35% of males and 12%–24% of females reported concurrent partners depending on the way concurrency was measured [17]. Although multiple partners, concurrency, network characteristics, and the prevalence of infection within given networks are important to the spread of epidemics—we do not believe they are the sole driver of the epidemic observed in sub-Saharan Africa. With regard to race,
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we found race to be strongly associated with HIV in the data used in the SA-US comparison; in fact, young black South African women were almost eight times more likely to be infected compared with young women of other races [18]. However, as noted above, there are a host of biological, behavioral, and contextual/ structural factors that likely explain this increased risk, not concurrency alone. We previously reported that young black South African women with one lifetime partner experience a remarkable risk of acquiring HIV, a phenomena not easily explained via sexual behavior alone [19]. Addressing sexual behavior is important to the control of the spread of HIV. However, the recognition that unique but poorly understood biological factors likely contribute to the spread of HIV in South Africa is also important for HIV prevention and to inspire greater compassion for the young people so greatly affected. Accordingly, we believe that addressing behavior alone will not be sufficient to eliminating the epidemic in sub-Saharan Africa. Combination HIV prevention, which addresses multiple risk factors at multiple levels at which risk occurs, seems like the most reasonable way forward [20]. Audrey E. Pettifor, Ph.D., M.P.H. William C. Miller, M.D., Ph.D. Myron Cohen, M.D. Department of Epidemiology University of North Carolina Chapel Hill, North Carolina Catherine MacPhail, Ph.D. Helen Rees, M.D. Wits Reproductive Health and HIV Institute (WRHI) University of the Witwatersrand Johannesburg, South Africa References [1] Pettifor AE, Levandowski BA, Macphail C, et al. A tale of two countries: Rethinking sexual risk for HIV among young people in South Africa and the United States. J Adolesc Health 2011;49:237– 43. [2] Joint United Nations Programme on HIV/AIDS (UNAIDS). UNAIDS report on the global AIDS epidemic 2010. Geneva, Switzerland: UNAIDS, 2010. [3] Thoma M, Gray RH, Kiwanuka N, et al. Unsafe injections and transmission of HIV-1 in sub-Saharan Africa. Lancet 2004;363:1650 –1. [4] Schmid GP, BuvÊ A, Mugyenyi P, et al. Transmission of HIV-1 infection in sub-Saharan Africa and effect of elimination of unsafe injections. Lancet 2004;363:482– 8. [5] White RG, Ben SC, Kedhar A, et al. Quantifying HIV-1 transmission due to contaminated injections. Proc Natl Acad Sci USA 2007;104:9794 –9. [6] Walker PR, Worobey M, Rambaut A, et al. Epidemiology: Sexual transmission of HIV in Africa. Nature 2003;422:679. [7] French K, Riley S, Garnett G. Simulations of the HIV epidemic in sub-Saharan Africa: Sexual transmission versus transmission through unsafe medical injections. Sex Transm Dis 2006;33:127–34. [8] Novitsky V, Ndung’u T, Wang R, et al. Extended high viremics: A substantial fraction of individuals maintain high plasma viral RNA levels after acute HIV-1 subtype C infection. AIDS Lond Engl 2011;25:1515–22. [9] Cohen MS, Eron J, Soderberg K, Jr., McMichael A. High clade C HIV-1 viremia: How did we get here and where are we going? AIDS Lond Engl 2011;25: 1543–5. [10] Morris M, Kurth AE, Hamilton DT, et al. Concurrent partnerships and HIV prevalence disparities by race: Linking science and public health practice. Am J Public Health 2009;99:1023–31. [11] Lurie MN, Rosenthal S. The concurrency hypothesis in sub-Saharan Africa: Convincing empirical evidence is still lacking. Response to Mah and Halperin, Epstein, and Morris. AIDS Behav 2010;14:34. [12] Epstein H, Morris M. Concurrent partnerships and HIV: An inconvenient truth. J Int AIDS Soc 2011;14:13. [13] Padian NS, Manian S. The concurrency debate: Time to put it to rest. Lancet 2011;378:203– 4. [14] Tanser F, Barnighausen T, Hund L, et al. Effect of concurrent sexual partnerships on rate of new HIV infections in a high-prevalence, rural South African population: A cohort study. Lancet 2011;378:247–55.
J.J. Potterat et al. / Journal of Adolescent Health 50 (2012) 207–210
[19] Brewer DD, Rothenberg RB, Potterat JJ, et al. HIV epidemiology in sub-Saharan Africa: Rich in conjecture, poor in data. Int J STD AIDS 2004;15:63–5. [20] Brody S, Potterat JJ. Establishing valid AIDS monitoring and research in countries with generalized epidemics. Int J STD AIDS 2004; 15:1– 6. [21] Brewer DD, Hagan H, Sullivan DG, et al. Social structural and behavioral underpinnings of hyperendemic hepatitis C virus transmission in drug injectors. J Infect Dis 2006;194:764 –72.
To the Editors: Pettifor et al’s recent study concludes that “the remarkable prevalence of HIV in young people in South Africa cannot be ascribed to exceptional risk taking behavior” [1]. This and the accompanying editorial [2] argue that behavioral change campaigns have “failed,” and that more emphasis needs to be placed on biological interventions. This conclusion is based on their comparative study of sexual behaviors in representative survey samples of 18 –24-year-olds in the United States (Add Health) and South Africa (South African Youth Survey—SAYS). Their study found that all the risk factors evaluated (excluding couple age discordance) to be more prevalent in the United States—the low HIV prevalence area. We believe this conclusion is unwarranted for two reasons. First, their study ignores the literature that explores the reasons for the large differences in HIV prevalence by race within both these countries. Second, they do not evaluate any network-level risk factors. The Add Health Survey revealed that for every category of individual-level risk behavior, non-Hispanic blacks had considerably higher sexually transmitted infection rates (up to 28 times higher) compared with nonHispanic whites [3]. This does not however mean that behavioral factors do not determine these racial differences. It may just be that these differences are due to network-level factors that have not been assessed. Indeed, a further analysis of the Add Health and three other surveys from the United States showed that differences in rates of concurrency and assortative mixing explained a 2.6-fold difference by race in HIV prevalence [4]. Our group has shown a similar phenomenon in the Cape Area Panel Survey—a representative sample of 14 –22-yearolds in Cape Town, South Africa. HIV prevalence in South Africa differs by racial group by over an order of magnitude [5]. We found that individual-level risk factors were unable to explain these large differences in HIV spread, but that network-level factors could [6]. For example, the sexually active white respondents had had the greatest number of lifetime partners, but partner concurrency was more commonly reported by the black respondents— 41% of black men compared with 4% of white men stated that they had engaged in a concurrent sexual partnership. The SAYS study found that the biggest “risk factor” for HIV acquisition was race— black women, for example, had an adjusted odds ratio of 8.3 for being HIV-infected compared with white women [7]. However, they did not collect data on network parameters such as concurrency. In a separate study using the Cape Area Panel Survey data, we described that sexually transmitted infection symptom prevalence remained similarly associated with race when controlling for individual-level parameters only [8], but not when additionally adjusting for concurrency. These findings caution against concluding, on the basis of weak or absent associations between standard behavior metrics and HIV prevalence, whether individual or ecological, that nonbehavioral factors must be cofactors in transmission.
Many of the biological differences that Pettifor [1] and Jaspen [2] highlight as potential cofactors of transmission such as viral subtype and circumcision cannot be invoked as explanations for differences in HIV prevalence between demographic groups within country. In Cape Town, for example, all young adults are at threat from the same viral subtypes, and black men are the most likely to be circumcised [6]. We believe that the most plausible reason for the large differences in HIV prevalence between countries and between demographic groups within countries is differences in sexual behavior at the network level, factors which the authors readily identify they were unable to assess in their study. There is a danger, in the excitement of the recent advances in the development of biologically based HIV prevention technologies, that we may lose sight of important behavioral determinants of HIV transmission, which could be highly amenable to intervention if afforded the same investment that is being contemplated for some of these newer technologies. Behavioral campaigns have been responsible for the dramatic declines in HIV incidence in Uganda [9]; in both Uganda and Zimbabwe, reductions in partner concurrency were instrumental in bringing down HIV incidence [9,10]. Chris Kenyon, MbChB., M.A., M.P.H. Department of Medicine University of Cape Town Cape Town, South Africa Andrew Boulle, MbChB., M.P.H. Centre for Infectious Disease Epidemiology and Research University of Cape Town Cape Town South Africa Robert Colebunders, MBChB. Professor of Infectious Diseases University of Antwerpen Sipho Dlamini, MBChB., F.C.P. Senior Registrar Infectious Diseases Groote Schuur Hospital South Africa Saul Johnson, MBChB. Managing Director Health & Development Africa References [1] Pettifor AE, Levandowski BA, Macphail C, et al. A Tale of two countries: Rethinking sexual risk for HIV among young people in South Africa and the United States. J Adolesc Health 2011;49:237– 43. [2] Jaspan H. The wrong place at the wrong time: Geographic disparities in young people’s HIV risk. J Adolesc Health 2011;49:227–9. [3] Hallfors DD, Iritani BJ, Miller WC, Bauer DJ. Sexual and drug behavior patterns and HIV and STD racial disparities: The need for new directions. Am J Public Health 2007;97:125–32. [4] Morris M, Kurth AE, Hamilton DT, et al. Concurrent partnerships and HIV prevalence disparities by race: linking science and public health practice. Am J Public Health 2009;99:1023–31. [5] Shisana O, Rehle T, Simbayi L, et al. South African National HIV Prevalence, HIV Incidence, Behaviour and Communication Survey. Human Sciences, Research Council, Pretoria, South Africa; 2005. [6] Kenyon C, Dlamini S, Boulle A, et al. A network level explanation for the differences in HIV prevalence in South Africa’s racial/ethnic groups. Afr J AIDS Res 2009;8:243–54.
J.J. Potterat et al. / Journal of Adolescent Health 50 (2012) 207–210
[7] Pettifor AE, Rees HV, Kleinschmidt I, et al. Young people’s sexual health in South Africa: HIV prevalence and sexual behaviors from a nationally representative household survey. AIDS 2005;19:1525–34. [8] Kenyon C, Badri M. The role of concurrent sexual relationships in the spread of Sexually Transmitted Infections in young South Africans. South Afr J HIV Med 2009:10:29 –36. [9] Kirby D. Changes in sexual behaviour leading to the confirmation from multiple sources of evidence decline in the prevalence of HIV in Uganda. Sex Transm Infect 2008;84:ii35– 41. [10] Daniel T, Halperin DT, Mugurungi O, et al. A surprising prevention success: Why did the HIV epidemic decline in Zimbabwe? PLoS Med 2011; 8;e1000414.
The Authors reply: In their letter, Potterat et al raise the question of whether the high prevalence of HIV observed among young people in South Africa is the result of parenteral HIV exposure. Although we found that young people in South Africa did not report more sexual risk behaviors than their U.S. peers, current evidence suggests that the vast majority of infections in sub-Saharan Africa, including South Africa, are the result of sexual transmission [1,2]. Several studies have documented that unclean needles contribute only a small proportion of new HIV infections in sub-Saharan Africa [3–7]. Although measuring all exposures is important when trying to determine the etiology of infection, in a setting such as South Africa, the dominant modifiable risk factor for HIV is sexual behavior. Measuring sexual behavior well is important to understanding transmission and for developing interventions. We do not believe that the combination of high HIV prevalence and the lack of high-risk behavior among South African youth means that they are being significantly exposed through routes other than sexual intercourse. Rather, we hypothesize that a combination of sexual mixing in a high-prevalence setting, structural factors that put young people at increased risk of exposure and unique biological factors, such as the predominance of clade C HIV [8,9], is driving the epidemic in subSaharan Africa over and above individual sexual behaviors. Kenyon et al assert that we dismiss the role of behavior, in particular concurrency, and also race in explaining differences in the epidemics observed in South Africa and the United States. The debate on the role of concurrency as a driver of the HIV epidemic in sub-Saharan Africa continues [10 –14]. We believe it plays a role and is likely one of several factors contributing to the on-going epidemic. In our South African youth survey, we found that close to 25% of men and 5% of women reported concurrent partners in the past 12 months [15]. We found it to be associated with HIV infection among women but not men. The question of whether South African young people practice concurrency more than their U.S. peers is unclear. Morris et al report a point prevalence of concurrency in the United States of between 5% and 13% for African American young men and 4% for African American young women [10]. As this estimate is a point prevalence, it likely underestimates concurrency over a longer period (i.e., in past 6 or 12 months). Doherty et al found among Latino youth in the United States that 27% of males and 14% of females reported having concurrent partners in the past 6 months [16]. Manhart et al in a random digit-dial survey of 18 –39 years olds in Seattle found that between 21% and 35% of males and 12%–24% of females reported concurrent partners depending on the way concurrency was measured [17]. Although multiple partners, concurrency, network characteristics, and the prevalence of infection within given networks are important to the spread of epidemics—we do not believe they are the sole driver of the epidemic observed in sub-Saharan Africa. With regard to race,
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we found race to be strongly associated with HIV in the data used in the SA-US comparison; in fact, young black South African women were almost eight times more likely to be infected compared with young women of other races [18]. However, as noted above, there are a host of biological, behavioral, and contextual/ structural factors that likely explain this increased risk, not concurrency alone. We previously reported that young black South African women with one lifetime partner experience a remarkable risk of acquiring HIV, a phenomena not easily explained via sexual behavior alone [19]. Addressing sexual behavior is important to the control of the spread of HIV. However, the recognition that unique but poorly understood biological factors likely contribute to the spread of HIV in South Africa is also important for HIV prevention and to inspire greater compassion for the young people so greatly affected. Accordingly, we believe that addressing behavior alone will not be sufficient to eliminating the epidemic in sub-Saharan Africa. Combination HIV prevention, which addresses multiple risk factors at multiple levels at which risk occurs, seems like the most reasonable way forward [20]. Audrey E. Pettifor, Ph.D., M.P.H. William C. Miller, M.D., Ph.D. Myron Cohen, M.D. Department of Epidemiology University of North Carolina Chapel Hill, North Carolina Catherine MacPhail, Ph.D. Helen Rees, M.D. Wits Reproductive Health and HIV Institute (WRHI) University of the Witwatersrand Johannesburg, South Africa References [1] Pettifor AE, Levandowski BA, Macphail C, et al. A tale of two countries: Rethinking sexual risk for HIV among young people in South Africa and the United States. J Adolesc Health 2011;49:237– 43. [2] Joint United Nations Programme on HIV/AIDS (UNAIDS). UNAIDS report on the global AIDS epidemic 2010. Geneva, Switzerland: UNAIDS, 2010. [3] Thoma M, Gray RH, Kiwanuka N, et al. Unsafe injections and transmission of HIV-1 in sub-Saharan Africa. Lancet 2004;363:1650 –1. [4] Schmid GP, BuvÊ A, Mugyenyi P, et al. Transmission of HIV-1 infection in sub-Saharan Africa and effect of elimination of unsafe injections. Lancet 2004;363:482– 8. [5] White RG, Ben SC, Kedhar A, et al. Quantifying HIV-1 transmission due to contaminated injections. Proc Natl Acad Sci USA 2007;104:9794 –9. [6] Walker PR, Worobey M, Rambaut A, et al. Epidemiology: Sexual transmission of HIV in Africa. Nature 2003;422:679. [7] French K, Riley S, Garnett G. Simulations of the HIV epidemic in sub-Saharan Africa: Sexual transmission versus transmission through unsafe medical injections. Sex Transm Dis 2006;33:127–34. [8] Novitsky V, Ndung’u T, Wang R, et al. Extended high viremics: A substantial fraction of individuals maintain high plasma viral RNA levels after acute HIV-1 subtype C infection. AIDS Lond Engl 2011;25:1515–22. [9] Cohen MS, Eron J, Soderberg K, Jr., McMichael A. High clade C HIV-1 viremia: How did we get here and where are we going? AIDS Lond Engl 2011;25: 1543–5. [10] Morris M, Kurth AE, Hamilton DT, et al. Concurrent partnerships and HIV prevalence disparities by race: Linking science and public health practice. Am J Public Health 2009;99:1023–31. [11] Lurie MN, Rosenthal S. The concurrency hypothesis in sub-Saharan Africa: Convincing empirical evidence is still lacking. Response to Mah and Halperin, Epstein, and Morris. AIDS Behav 2010;14:34. [12] Epstein H, Morris M. Concurrent partnerships and HIV: An inconvenient truth. J Int AIDS Soc 2011;14:13. [13] Padian NS, Manian S. The concurrency debate: Time to put it to rest. Lancet 2011;378:203– 4. [14] Tanser F, Barnighausen T, Hund L, et al. Effect of concurrent sexual partnerships on rate of new HIV infections in a high-prevalence, rural South African population: A cohort study. Lancet 2011;378:247–55.