Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Curr Opin HIV AIDS. Author manuscript; available in PMC 2010 July 1.
Published in final edited form as:
PMCID: PMC2884281

HIV Transmission Networks

Richard Rothenberg, MD MPH, Professor


Purpose of Review

Over the past several years, one segment of the complex field of HIV transmission dynamics —heterosexual networks—has dominated theoretical and empirical investigation. This review provides an overview of recent work on HIV risks and networks, with a focus on recent findings in heterosexual network dynamics.

Recent findings

Qualitative (ethnographic) assessments have demonstrated the heterogeneity and complexity of heterosexual connections, particular in Africa where tradition, official polygamy, and unofficial multi-person arrangements lead to concurrency of sexual partnerships. A large, quantitative study on Likoma Island, Malawi, demonstrated the considerable, interlocking sexual connections that arise from a high-concurrency sexual setting, even with a low average number of partnerships (low-degree) of long duration. Such settings, as suggested by ethnographic studies, may be common in Africa and, coupled with newer information about transmissibility during acute and early infection, may provide a plausible explanation for endemic transmission and possibly for rapid HIV propagation.


Recognition of high- concurrency, low-degree networks is an important development for understanding HIV transmission dynamics. Their relevance to heterosexual transmission, and possible extension to other epidemiologic settings, reinforces the heterogeneity and complexity of HIV transmission dynamics.

Keywords: HIV, AIDS, heterosexual transmission, transmission dynamics, epidemiology

Now nearing the end of its third decade, the HIV/AIDS pandemic resists easy characterization. The major risk factors have been known for some time, but our understanding of how these risk factors mesh with human and viral dynamics continues to evolve. Though still referred to as epidemic, HIV/AIDS is now perceived as an endemic, chronic disease1 whose critical features are markedly heterogeneous.2 In any given setting, the complex mix of risk epidemiology, viral characteristics, host immunology, social networks, demographic phenomena, and social determinants influences transmission, incidence, prevalence, mortality, and the efficacy of interventions. HIV transmission networks provide an organizing principle for viewing these multifaceted issues, and networks have received substantial attention in this mix. One of the important concepts in the field has been that active transmission takes place in groups that have a disproportionate number of persons with many contacts (often referred to as “scale-free” networks, though this is probably a statistical misnomer3 in most instances). Recent work, predominantly focused on heterosexual networks that are dominated by persons with relatively few contacts (“low degree”) but a high level of simultaneity (“high concurrency”), suggests that some alternative network substrates may also underlie transmission.

Recent trends

Men continue to predominate in the notification of HIV/AIDS cases in the United States. From 2004–2007, the number of reported cases of HIV/AIDS in men who have sex with men increased from 17,898 to 22,472, and the number in male IDU was relatively constant at about 3,000.4 Nonetheless, the overall HIV/AIDS “endemic” is frequently described as having a disproportionate effect on women—in particular, those who are members of minority groups.4, 5 For both men and women, the number of reported cases of HIV/AIDS attributable to high risk heterosexual contact (defined as sexual contact with an infected person of the opposite sex, or sex with an injecting drug user [IDU] of the opposite sex, or, for a woman, with a man who has sex with men [MSM]) has remained constant or declined during the current decade. The proportion of such cases has risen, however, more dramatically for women than for men (Figure 1). These trends suggest that women now have an increasing share of a declining disease occurrence. A recent upward adjustment of the estimate of overall HIV/AIDS incidence,6 based on the emerging technology to detect recent infection, may change the perception of this disproportion.

Figure 1
Number of reported cases of HIV/AIDS attributed to heterosexual transmission and the proportion of heterosexual transmission cases out of the total cases reported, for men and women, United States, 1984–2006

MSM and IDU transmission networks

Investigations of male-to-male and IDU transmission during the past several years have focused on social network characteristics as risk factors.713 For example, in a study of men in Baltimore, MSM were more likely to be HIV positive than were heterosexual men, the networks of MSM were less dense, and those MSM who reported injection drug use also reported greater needle sharing than their heterosexual counterparts.13 Similarly, among IDU in Winnipeg, relationship to a risk network member, difficulty of access to syringes, and dyads who pooled resources were all at greater risk for syringe sharing.12 Though these investigations are important contributions to the epidemiology of risk, their primary concern was not with transmission dynamics.

Heterosexual transmission networks

In contrast, studies of heterosexual transmission have investigated both risk factors and dynamics. As noted, heterosexual transmission has increasing prominence in the epidemiology of HIV/AIDS in the United States, and has been of special importance in many other areas of the world for some time. Though their settings differ from that of the United States, several other countries—notably Russia,14 Brazil,15 and France16—have furnished data supporting the increasing prominence of heterosexual transmission. Current epidemiologic investigation continues to focus on risk factors for transmission in the heterosexual setting, including unsafe sex and history of STIs (Thailand),17 illicit drug use and migration (Caribbean),18 childhood sexual and physical abuse (Southeastern United States),5 and inadequate condom use (Southwestern United States).19 A meta-analytic review of 68 epidemiologic studies20 confirmed that the number of sex partners, history of paid sex, and infection with Herpes Simplex Virus type 2 or other STIs were significantly associated with HIV infection. The authors also found that these associations were present after stratification for high and low prevalence areas, suggesting that risk factors persist even as epidemics mature. This association of sexual risk factors with HIV is at odds with the findings of several large studies2124 conducted in Africa during the 1990s and the findings from a subsequent review.25 Some of the discrepancy may lie in the study approach. The earlier reports and review examined ecologic correlations between the level of sexual risk factors in multiple sites and the prevalence of HIV (though note was made as well of inconsistencies in the association of personal risk factors and HIV). The current meta-analytic review20 is a comprehensive assessment of the association between an individual’s risk factors and HIV. The underlying assumption of both the ecologic and cross-sectional approach is that current sexual activity reflects risk at the time that HIV was acquired, and is supported to some extent by the review’s finding that the associations were similar in high and low prevalence areas. None of the studies under consideration, however, was in a position to know the relationship of current HIV infection to sexual activity at the time of acquisition. The studies are markedly heterogeneous with regard to the level of risk variables,22 and two critical factors—frequency of sexual contact and time since acquisition (a surrogate for the transmission probability)—are missing, rendering interpretation of both ecologic and risk factor associations difficult. The emerging technology for identifying acute infection may clarify future inquiry, but is unlikely to resolve past inconsistencies.

Network assessment

Some important recent work has gone beyond risk factor assessment, and explored the role of network phenomenon in heterosexual propagation of HIV. At least two major factors—concurrency and bridging—have been studied extensively without the use of formal network designs.

Concurrency, originally proposed as an important factor in transmission in the early 1990s,26 is a prominent feature of heterosexual groups at risk. In Houston, TX, among a group of 553 women from high risk, high poverty, high HIV prevalence areas, 49% reported concurrent partnerships (and only 26% reported condom use at their last sexual contact).19 In the rural southern United States, 25% of women and 42% of men had multiple partnerships in the preceding year; 26% of such partnerships were concurrent, and 38% of partnerships in the preceding 5 years were concurrent.27 This sexual substrate, coupled with under-education and food insecurity, makes poverty a major factor in person’s taking on sexual risk,28 and economics in general a driving force in sexual reciprocity.29

The latter studies are representative of the growing importance of qualitative contributions to the understanding of disease transmission. An ethnographic exploration of cohabitation suggests that marriage, or at least exclusivity, may be protective against transmission of HIV.30 Hattori and colleagues addressed this issue in detail31 using a sample of women drawn from the slums of Nairobi, Kenya. They stress the complexity of relationships, noting the different forms of formal (officially recognized) and informal pairing, and their varying social implications. They note that the 2003 Demographic Health Survey in Kenya reported a low prevalence of women with multiple partnerships in the preceding year (1.7%), but that the frequency of such reports varied with cohabiting status. In their sample from the Nairobi slums, more than twice the proportion of women reported two or more partners in the past year (4.6%), and there was important variation in this group as well. One percent of married, co-residing women (71% of the sample; representativeness is not discussed specifically, and the authors note that their study group is a selected subset) reported two or more partners, but 11.5% of co-residing women, 11.1% of widowed women, and 20.5% of divorced women reported two or more partners. Non-exclusivity was also a feature of older age, less education, and Catholic religion. Of special interest was the observation that women living with co-wives were more likely to have other male partners. Thus, the data suggest that in this impoverished group the overall population prevalence of 1-year non-monogamy was not high, but was strongly influenced by social, cultural, and demographic factors. These findings confirm those of a subsequent review and commentary32 that found wide-spread reporting of concurrent relationships embedded in complex social and sexual arrangements, and suggested that attention to such factors may be critical in the elucidation of transmission dynamics in Africa. Such thinking was underscored in a commentary by Dworkin and Ehrhardt,33 who pointed out the simple ABC approach (Abstinence, Be faithful, use Condoms) needs to amplified by a focus on GEM (Gender relations, Economics, Migration).

A formal network approach

Using a network design that incorporated both qualitative and quantitative elements, Helleringer and Kohler reported on 923 persons from Likoma Island, Malawi.34 They identified a network configuration characterized by long term relationships of low degree (3-year mean number of partners was 2.6 for men and 2.2 for women [IQR 1–3 for both]) and high concurrency. The concurrent relationships generated a giant connected component containing about half of the participants, with a large bicomponent (in which every member is connected to at least two others), containing approximately 25% of survey respondents. That such a component structure can emerge from a low-degree, high-concurrency sexual configuration was predicted theoretically and by simulation.35 This structure may be capable of supporting rapid transmission of HIV, particularly with new introduction of the virus, and a preponderance of acute infections.36, 37 In the Likoma group, HIV prevalence was 10.6% among women and 4.7% among men, with a greater concentration of HIV-positive persons in the periphery of the network (as opposed to the highly interactive bicomponent). In a letter, Brewer et al.38 assert that this finding undermines the likelihood that the described network configuration underlies HIV transmission, because prior network descriptions had placed a preponderance of HIV-positive persons centrally in a network of high prevalence, and peripherally in a network of low prevalence. Likoma, a setting substantially different from either of the two networks cited, lies between them on the prevalence spectrum, and appears to be past any period of rapid transmission that may have taken place, so that prior observations cited by Brewer et al. may not be predictive of Likoma’s HIV configuration.


In the United States, most of the recent work on bridging has focused on African American men who identify as heterosexual but also have sex with men without making their female partners aware of this activity (the so-called “down low”) as well as on the general population of men who have sex with both men and women (MSMW). For the former, several have written that the term is socially constructed and in many ways inappropriate,3941 since it “exoticizes” the activity and makes it qualitatively distinct from identical behavior in men who are not of African American ethnicity. In addition, Satcher et al.42 refer to U.S. national data to point out that the proportion of women who report having possibly contracted HIV because of sex with a bisexual man has remained constant in recent years, and was highest for African American women. Malebranche et al. review the issue in detail, and support the view that African American MSMW may be a “bisexual bridge” to African American women, and may account in part for their higher prevalence.43 Other recently described bridging populations include bisexual men in China,44 and transmission from IDU groups to non-IDUs through heterosexual contact,14, 45 Several authors have stressed the nuances of sexual activity in assessing bridging. Though official reporting systems are silent on the matter, heterosexual anal sex is common,46 and may be increasing.47 Bisexual men in China are reported to have anal intercourse with their female partners more often if they also have anal sex with their male partners.44 The variability of sexual behaviors among those with a high risk of transmitting HIV,48 however, reinforces the idea that the simple presence of possible sexual connections, in the absence of behavioral, biological, and network information, makes assessment of bridging difficult. Finally, investigations of bisexual bridging have focused on the origination, rather than the destination, of the bridge. Requisite studies, comparing women of differing ethnicities with regard to the sexual activity of their partners, appear to be lacking.

Modeling heterosexual transmission

Mathematical consideration of the trajectory of HIV has for many years been dominated by sexual transmission between men, or by injecting drug use. Recently, considerable attention has been devoted, directly or indirectly, to models of heterosexual transmission.4963 Though the models are sophisticated, complex, and detailed, the major results for most of them are simply stated, and in some instances contradictory. Abbas and colleagues assert that antiretrovirals would not have a major impact on transmission, with only an 11.2% greater decline with their widespread use in 10 years compared to the decline in their absence.49 In contrast, Granich et al. present a model that finds that universal testing coupled with widespread use of antiretrovirals would successfully eliminate HIV.54

Several models have explored the complexity of simultaneous effects. A decline in prevalence attributed to a behavioral intervention may actually result from changes in immigration patterns and declines in mortality through treatment rather than from the intervention itself.63 In a similar vein, a decrease in cross-generational sex and limiting partner change may decrease individual risk but would have little effects on the overall epidemic trajectory.55 Hertog stressed that models must take into simultaneous consideration mixing patterns, pattern change, and infectiousness, since these factors interact and do not occur in isolation.56 Finally, Gouws et al. have stressed the importance of geographic area in assessing the proportion of HIV attributable to different routes of transmission.53

Models have been used recently to explore several contested areas of HIV/AIDS epidemiology. Dunkle et al. presented a construct to show that between 60% and 94% of heterosexual transmission occurs between (cohabiting) serodiscordant couples.51 (In an exhaustive review of the available empirical data, Guthrie et al. reach a similar, though non-quantified, conclusion about the importance of discordance.64 The default assumption in this work is that serodiscordant couples are monogamous, and missing from this discussion is a consideration of the potential interaction of serodiscordance and concurrency.) Deuchert and Brody report a model-based statistical analysis that questions whether parameters used in many models are in keeping with the extant empirical estimates for transmission probabilities or partner change.65 This conclusion might be reconsidered in light of changing concepts about the probability of transmission. Similar points were raised in an exchange in which Rapatski and colleagues assert that the bulk of transmission occurs during late-stage HIV disease, rather than during acute or early infection.61, 66

Modeling continues to be a fundamental tool for evaluating disease transmission. Recent theoretical advances in network modeling, based on a the family of exponential random graph models, have led to operational approaches and the development of practical tools for performing such analyses.67, 68 Such approaches offer considerable promise for amalgamating theoretical considerations and simulations with empirical observations, such as those made on Likoma Island.


Several themes motivate current investigation in HIV transmission networks. The simplistic sense of an epidemic as the sum of homogeneous events is giving way to the view of transmission as a complex and heterogeneous phenomenon, embedded in networks that may facilitate rapid propagation. Investigators are paying increasing attention to contextual issues, and qualitative tools are now being brought to bear more seriously on this complex system. These studies create some discordance between the frequent qualitative description of concurrent sexual arrangements and the survey reporting of infrequent multiple partnerships. An expanding view of HIV transmission heterogeneity will hopefully resolve some of the inconsistencies, create a more coherent picture of the interrelationship of elements, and ultimately lead to a setting-specific mix of appropriate interventions.


This review was supported in part by R01 DA019393 from the National Institute on Drug Abuse, National Institutes of Health.


Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Reference List

1. Chin J, Bennett A. Heterosexual HIV transmission dynamics: implications for prevention and control. Int J STD AIDS. 2007;18(8):509–513. [PubMed]
2. Beyrer C. HIV Epidemiology Update and Transmission Factors: Risks and risk contexts--16th International AIDS Conference Epidemiology Plenary. Clinical Infectious Diseases. 2007;44:981–987. [PubMed]
3. Hamilton DT, Handcock M, Morris M. Degree distributions in sexual networks: A framework for evaluating evidence. Sex Transm Dis. 2008;35(1):30–40. [PubMed]
4. Centers for Disease Control and Prevention. HIV/AIDS Statistics and Surveillance. 2008. [Accessed January 18, 2009]. (
5. Pence BW, Reif S, Whetten K, et al. Minorities, the poor, and survivors of abuse: HIV-infected patients in the US deep South. South Med J. 2007;100(11):1114–1122. [PubMed]
6. Hall HI, Song R, Rhodes P, et al. Estimation of HIV Incidence in the United States. JAMA. 2008;300(5):520–529. [PMC free article] [PubMed]
7. Aitken CK, Higgs P, Bowden S. Differences in the social networks of ethnic Vietnamese and non-Vietnamese injecting drug users and their implications for blood-borne virus transmission. Epidemiol Infect. 2008;136(3):410–416. [PubMed]
8. Choi KH, Ning Z, Gregorich SE, Pan QC. The influence of social and sexual networks in the spread of HIV and syphilis among men who have sex with men in Shanghai, China. J Acquir Immune Defic Syndr. 2007;45(1):77–84. [PubMed]
9. Gyarmathy VA, Li N, Tobin KE, et al. Injecting Equipment Sharing in Russian Drug Injecting Dyads. AIDS Behav. 2009 [PMC free article] [PubMed]
10. Peterson JL, Rothenberg R, Kraft JM, Beeker C, Trotter R. Perceived condom norms and HIV risks among social and sexual networks of young African American men who have sex with men. Health Educ Res. 2009;24(1):119–127. [PubMed]
11. Schneider JA, Saluja GS, Oruganti G, et al. HIV infection dynamics in rural Andhra Pradesh south India: a sexual-network analysis exploratory study. AIDS Care. 2007;19(9):1171–1176. [PubMed]
12. Shaw SY, Shah L, Jolly AM, Wylie JL. Determinants of injection drug user (IDU) syringe sharing: the relationship between availability of syringes and risk network member characteristics in Winnipeg, Canada. Addiction. 2007;102(10):1626–1635. [PubMed]
13. Tobin KE, Latkin CA. An examination of social network characteristics of men who have sex with men who use drugs. Sex Transm Infect. 2008;84(6):420–424. [PMC free article] [PubMed]
14. Burchell AN, Calzavara LM, Orekhovsky V, Ladnaya NN. Characterization of an emerging heterosexual HIV epidemic in Russia. Sex Transm Dis. 2008;35(9):807–813. [PubMed]
15. Fonseca MG, Bastos FI. Twenty-five years of the AIDS epidemic in Brazil: principal epidemiological findings, 1980–2005. Cad Saude Publica. 2007;23 Suppl 3:S333–S344. [PubMed]
16. Semaille C, Barin F, Cazein F, et al. Monitoring the dynamics of the HIV epidemic using assays for recent infection and serotyping among new HIV diagnoses: experience after 2 years in France. J Infect Dis. 2007;196(3):377–383. [PubMed]
17. Tunthanathip P, Lolekha R, Liesbeth BJ, et al. Indicators for Sexual HIV Transmission Risk among Thais attending HIV Care: The Importance of Positive Prevention. Sex Transm Infect. 2008 [PubMed]
18. Surratt H. Sex work in the Caribbean Basin: patterns of substance use and HIV risk among migrant sex workers in the US Virgin Islands. AIDS Care. 2007;19(10):1274–1282. [PubMed]
19. Richards JE, Risser JM, Padgett PM, Rehman HU, Wolverton ML, Arafat RR. Condom use among high-risk heterosexual women with concurrent sexual partnerships, Houston, Texas, USA. Int J STD AIDS. 2008;19(11):768–771. [PubMed]. *Though the focus is on condom use by a group of at-risk women, of note is the fact that 49% of the respondents were engaged in concurrent sexual relationships.
20. Chen L, Jha P, Stirling B, et al. Sexual risk factors for HIV infection in early and advanced HIV epidemics in sub-Saharan Africa: systematic overview of 68 epidemiological studies. PLoS ONE. 2007;2(10):e1001. [PubMed]. **An exhaustive review of the association of sexual risk factors for HIV, comparing low and high prevalence areas as surrogates for early and mature epidemics. The data support the association of risk factors with current HIV, placing a different perspective on earlier reports of a disconnect between risks and infection. The real extent of prior associations is hampered by the absence of several critical factors: frequency of sexual contact and time since HIV infection. These factors have taken on new importance in light of the emerging information about early infection, viral load, and infectivity.
21. Buve A, Lagarde E, Carael M, et al. Interpreting sexual behaviour data: validity issues in the multicentre study on factors determining the differential spread of HIV in four African cities. AIDS. 2001;15 suppl 4:S117–S126. [PubMed]
22. Carael M, Cleland J, Deheneffe JC, Ferry B, Ingham R. Sexual behaviour in developing countries: implications for HIV control. AIDS. 1995;9(10):1171–1175. [PubMed]
23. Lagarde E, Auvert B, Carael M, et al. Concurrent sexual partnerships and HIV prevalence in five urban communities of sub-Saharan Africa. AIDS. 2001;15(7):877–884. [PubMed]
24. Auvert B, Buve A, Ferry B, et al. Ecological and individual level analysis of risk factors for HIV infection in four urban populations in sub-Saharan Africa with different levels of HIV infection. AIDS. 2001;15 Suppl 4:S15–S30. [PubMed]
25. Brewer DD, Brody S, Drucker E, et al. Mounting anomalies in the epidemiology of HIV in Africa: cry the beloved paradigm. Int J STD AIDS. 2003;14(3):144–147. [PubMed]
26. Hudson CP. Concurrent partnerships could cause AIDS epidemics. Int J STD AIDS. 1993;4(5):249–253. [PubMed]
27. Adimora AA, Schoenbach VJ, Doherty IA. HIV and African Americans in the southern United States: sexual networks and social context. Sex Transm Dis. 2006;33(7 Suppl):S39–S45. [PubMed]
28. Adimora AA, Schoenbach VJ, Martinson FE, et al. Heterosexually transmitted HIV infection among African Americans in North Carolina. J Acquir Immune Defic Syndr. 2006;41(5):616–623. [PubMed]
29. Stratford D, Ellerbrock TV, Chamblee S. Social organization of sexual-economic networks and the persistence of HIV in a rural area in the USA. Cult Health Sex. 2007;9(2):121–135. [PubMed]
30. Reniers G. Marital strategies for regulating exposure to HIV. Demography. 2008;45(2):417–438. [PMC free article] [PubMed]
31. Hattori MK, Dodoo FN. Cohabitation, marriage, and 'sexual monogamy' in Nairobi's slums. Soc Sci Med. 2007;64(5):1067–1078. [PubMed]. **An extensive consideration of the ethnographic and cultural factors in which heterosexual sex is embedded in Nairobi, Kenya. The authors describe the multiple types of relations, both formal and informal, which creates concurrency and may facilitate HIV transmission
32. Mah TL, Halperin DT. Concurrent Sexual Partnerships and the HIV Epidemics in Africa: Evidence to Move Forward. AIDS Behav. 2008 [PubMed]
33. Dworkin SL, Ehrhardt AA. Going beyond "ABC" to include "GEM": critical reflections on progress in the HIV/AIDS epidemic. Am J Public Health. 2007;97(1):13–18. [PubMed]
34. Helleringer S, Kohler HP. Sexual network structure and the spread of HIV in Africa: evidence from Likoma Island, Malawi. AIDS. 2007;21(17):2323–2332. [PubMed]. **A large network study of sexual activity on the island community of Likoma in Malawi. The authors demonstrate the presence of a large connected group, containing a smaller, more highly connected group, that arises from high levels of concurrency but modest numbers of long duration partnerships. The study provides initial empirical evidence for the potential importance of such network configurations.
35. Morris M, Goodreau S, Moody J. Sexual networks, Concurrency, and STD/HIV. In: Holmes KK, Sparling P, Stamm W, Piot P, Wasserheit J, Corey L, et al., editors. Sexually Transmitted Diseases. 4th Edition. McGraw-Hill; 2008. pp. 109–126.. *An excellent chapter that explores the network epidemiology of HIV and STDs. The authors demonstrate that complex networks that arise from low-degree, high concurrency relationships.
36. Hollingsworth TD, Anderson RM, Fraser C. HIV-1 transmission, by stage of infection. J Infect Dis. 2008;198(5):687–693. [PubMed]
37. Powers KA, Poole C, Pettifor AE, Cohen MS. Rethinking the heterosexual infectivity of HIV-1: a systematic review and meta-analysis. Lancet Infect Dis. 2008;8(9):553–563. [PMC free article] [PubMed]
38. Brewer DD, Potterat JJ, Muth SQ, Gisselquist D, Brody S. Disconnects in presumed heterosexual HIV transmission in Malawi. AIDS. 2008;22(11):1377–1379. [PubMed]
39. Ford CL, Whetten KD, Hall SA, Kaufman JS, Thrasher AD. Black sexuality, social construction, and research targeting 'The Down Low' ('The DL') Ann Epidemiol. 2007;17(3):209–216. [PubMed]
40. Saleh LD, Operario D. Moving beyond "the Down Low": A critical analysis of terminology guiding HIV prevention efforts for African American men who have secretive sex with men. Soc Sci Med. 2008;68(2):390–395. [PubMed]
41. O'Leary A, Jones KT. Bisexual men and heterosexual women: how big is the bridge? How can we know? Sex Transm Dis. 2006;33(10):594–595. [PubMed]
42. Satcher AJ, Durant T, Hu X, Dean HD. AIDS cases among women who reported sex with a bisexual man, 2000–2004--United States. Women Health. 2007;46(2–3):23–40. [PubMed]
43. Malebranche DJ. Bisexually active Black men in the United States and HIV: acknowledging more than the "Down Low". Arch Sex Behav. 2008;37(5):810–816. [PubMed]
44. Lau JT, Wang M, Wong HN, et al. Prevalence of bisexual behaviors among men who have sex with men (MSM) in China and associations between condom use in MSM and heterosexual behaviors. Sex Transm Dis. 2008;35(4):406–413. [PubMed]
45. Abdala N, Krasnoselskikh TV, Durante AJ, Timofeeva MY, Verevochkin SV, Kozlov AP. Sexually transmitted infections, sexual risk behaviors and the risk of heterosexual spread of HIV among and beyond IDUs in St. Petersburg, Russia. Eur Addict Res. 2008;14(1):19–25. [PubMed]
46. Stadler JJ, Delany S, Mntambo M. Sexual coercion and sexual desire: ambivalent meanings of heterosexual anal sex in Soweto, South Africa. AIDS Care. 2007;19(10):1189–1193. [PubMed]
47. Leichliter JS. Heterosexual anal sex: part of an expanding sexual repertoire? Sex Transm Dis. 2008;35(11):910–911. [PubMed]
48. Aidala AA, Lee G, Howard JM, Caban M, Abramson D, Messeri P. HIV-positive men sexually active with women: sexual behaviors and sexual risks. J Urban Health. 2006;83(4):637–655. [PMC free article] [PubMed]
49. Abbas UL, Anderson RM, Mellors JW. Potential impact of antiretroviral chemoprophylaxis on HIV-1 transmission in resource-limited settings. PLoS ONE. 2007;2(9):e875. [PMC free article] [PubMed]
50. Deuchert E, Brody S. The role of health care in the spread of HIV/AIDS in Africa: evidence from Kenya. Int J STD AIDS. 2006;17(11):749–752. [PubMed]
51. Dunkle KL, Stephenson R, Karita E, et al. New heterosexually transmitted HIV infections in married or cohabiting couples in urban Zambia and Rwanda: an analysis of survey and clinical data. Lancet. 2008;371(9631):2183–2191. [PubMed]
52. Gomez-Gardenes J, Latora V, Moreno Y, Profumo E. Spreading of sexually transmitted diseases in heterosexual populations. Proc Natl Acad Sci U S A. 2008;105(5):1399–1404. [PubMed]
53. Gouws E, White PJ, Stover J, Brown T. Short term estimates of adult HIV incidence by mode of transmission: Kenya and Thailand as examples. Sex Transm Infect. 2006;82 Suppl 3:iii51–iii55. [PMC free article] [PubMed]
54. Granich RM, Gilks CF, Dye C, De Cock KM, Williams BG. Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission: a mathematical model. Lancet. 2008 [PubMed]
55. Hallett TB, Gregson S, Lewis JJ, Lopman BA, Garnett GP. Behaviour change in generalised HIV epidemics: impact of reducing cross-generational sex and delaying age at sexual debut. Sex Transm Infect. 2007;83 Suppl 1:i50–i54. [PubMed]
56. Hertog S. Heterosexual behavior patterns and the spread of HIV/AIDS: the interacting effects of rate of partner change and sexual mixing. Sex Transm Dis. 2007;34(10):820–828. [PubMed]
57. Merli MG, Hertog S, Wang B, Li J. Modelling the spread of HIV/AIDS in China: the role of sexual transmission. Popul Stud (Camb ) 2006;60(1):1–22. [PubMed]
58. Modjarrad K, Chamot E, Vermund SH. Impact of small reductions in plasma HIV RNA levels on the risk of heterosexual transmission and disease progression. AIDS. 2008;22(16):2179–2185. [PMC free article] [PubMed]
59. Mukandavire Z, Garira W. Effects of public health educational campaigns and the role of sex workers on the spread of HIV/AIDS among heterosexuals. Theor Popul Biol. 2007;72(3):346–365. [PubMed]
60. Mukandavire Z, Garira W. Sex-structured HIV/AIDS model to analyse the effects of condom use with application to Zimbabwe. J Math Biol. 2007;54(5):669–699. [PubMed]
61. Rapatski BL, Suppe F, Yorke JA. Reconciling different infectivity estimates for HIV-1. J Acquir Immune Defic Syndr. 2006;43(3):253–256. [PubMed]
62. Sani A, Kroese DP, Pollett PK. Stochastic models for the spread of HIV in a mobile heterosexual population. Math Biosci. 2007;208(1):98–124. [PubMed]
63. Walker PT, Hallett TB, White PJ, Garnett GP. Interpreting declines in HIV prevalence: impact of spatial aggregation and migration on expected declines in prevalence. Sex Transm Infect. 2008;84 Suppl 2:ii42–ii48. [PubMed]
64. Guthrie BL, de BG, Farquhar C. HIV-1-discordant couples in sub-Saharan Africa: explanations and implications for high rates of discordancy. Curr HIV Res. 2007;5(4):416–429. [PubMed]
65. Deuchert E, Brody S. Plausible and implausible parameters for mathematical modeling of nominal heterosexual HIV transmission. Ann Epidemiol. 2007;17(3):237–244. [PubMed]
66. Koopman JS, Simon CP, Response to Rapatski BL, Suppe F, Yorke JA. HIV edpidemics driven by late disease stage transmission. JAIDS. 2006;41(5):677. [PubMed]
67. Handcock MS, Hunter DR, Butts CT, Goodreau SM, Morris M. statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data. J Stat Softw. 2008;24(1):1548–7660. [PMC free article] [PubMed]
68. Morris M, Handcock MS, Hunter DR. Specification of Exponential-Family Random Graph Models: Terms and Computational Aspects. J Stat Softw. 2008;24(4):1548–7660. [PMC free article] [PubMed]