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Concurrent partnerships and the spread of HIV

Morris, Martina1,3; Kretzschmar, Mirjam2

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1The Department of Sociology, Pennsylvania State University, University Park, Pennsylvania, USA

2The National Institute of Public Health and Environmental Protection, Bilthoven, The Netherlands.

3Requests for reprints to: Martina Morris, Department of Sociology, Pennsylvania State University, 614 Oswald Tower, University Park PA 16802–6211, USA.

Sponsorship: Supported by the Rockefeller Foundation, National Institutes of Health (1R29HD34957-01).

Date of receipt: 6 June 1996; revised: 22 November 1996; accepted: 15 January 1997.

[For editorial comment see pp681–683]

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Objective: To examine how concurrent partnerships amplify the rate of HIV spread, using methods that can be supported by feasible data collection.

Methods: A fully stochastic simulation is used to represent a population of individuals, the sexual partnerships that they form and dissolve over time, and the spread of an infectious disease. Sequential monogamy is compared with various levels of concurrency, holding all other features of the infection process constant. Effective summary measures of concurrency are developed that can be estimated on the basis of simple local network data.

Results: Concurrent partnerships exponentially increase the number of infected individuals and the growth rate of the epidemic during its initial phase. For example, when one-half of the partnerships in a population are concurrent, the size of the epidemic after 5 years is 10 times as large as under sequential monogamy. The primary cause of this amplification is the growth in the number of people connected in the network at any point in time: the size of the largest ‘component’. Concurrency increases the size of this component, and the result is that the infectious agent is no longer trapped in a monogamous partnership after transmission occurs, but can spread immediately beyond this partnership to infect others. The summary measure of concurrency developed here does a good job in predicting the size of the amplification effect, and may therefore be a useful and practical tool for evaluation and intervention at the beginning of an epidemic.

Conclusion: Concurrent partnerships may be as important as multiple partners or cofactor infections in amplifying the spread of HIV. The public health implications are that data must be collected properly to measure the levels of concurrency in a population, and that messages promoting ‘one partner at a time’ are as important as messages promoting fewer partners.

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There is now considerable variation in the timing and intensity of the HIV epidemic in different regions of the world [1]. Explanations for these differences, especially for the rapid and pervasive spread among heterosexual populations in sub-Saharan Africa, have focused on three factors: the rate of sexual partner acquisition [2–5], the impact of certain ‘core groups’ [6–12], and the presence of other sexually transmitted diseases (STD) that may amplify HIV transmission [13–16]. We investigate the potential impact of another factor: concurrent (or simultaneous) sexual partnerships. Concurrency need not change the rate of partner acquisition, it simply affects the overlap of partners over time. It represents an alternative to sequential monogamy, a different pattern in the general social organization of sexuality rather than a feature of ‘core groups’.

Intuition and exploratory work in mathematical disease models [17–20] suggest that concurrent partnerships will amplify the spread of an infectious agent such as HIV. From the viewpoint of the virus, there is less time lost after transmission occurs in waiting for the current partnership to dissolve, or between the end of one partnership and the beginning of another. In addition, the effect of partner sequence on exposure risk is reduced. Under serial monogamy each subsequent partner increases the risk of infection to a particular subject, so that earlier partners are less likely to be exposed to an infected subject than later partners. If partnerships are concurrent, much of the protective effect of the sequence is lost. Earlier partners remain connected to the subject, and can be exposed when the subject becomes infected by a later concurrent partner.

To formalize and quantify these intuitions we perform a simulation experiment of disease spread under different partnership scenarios. The simulations are based on a fully stochastic model, with a disease transmission process superimposed over a pair-formation and dissolution process in a heterosexual population. The scenarios are carefully structured to ensure that concurrency is not confounded with a simple increase in the number of partnerships. Comparisons across scenarios reflect the difference between, for example, having five partners in sequentially monogamous fashion, and five partners with some or all partnerships overlapping. Although HIV transmission is ultimately the topic of interest, we do not aim to capture the biological complexities of this particular disease (such as asymmetric or variable infectivity). Instead, we employ relatively simple biological assumptions and focus attention on the effects of concurrent partnerships. In the Discussion we will consider how the impact of concurrency might change under alternative assumptions.

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Measuring concurrency

While concurrency is simply defined at the individual level by the number of partnerships a person has at any moment in time, a summary of the amount of concurrency present in a population turns out to be more difficult. We will use a graph theoretic summary index to define and measure concurrency. Although the approach initially appears complicated and abstract, the measure that results ultimately turns out to be quite simple, both to understand, and to estimate from data that are easily collected.

In what follows, we use the terminology of graph theory to describe aspects of the partnership network. The network is called a ‘graph’, persons are ‘nodes’, and partnerships are ‘links’. The number of simultaneous partners a person has is called ‘the momentary degree of a node’, and the variation in degree is captured by the degree distribution, mean degree and degree variance in the graph.

The level of concurrency in a population clearly reflects some aspect of the momentary degree distribution. Degree mean alone is not a good measure when nodes can have degree 0, because averaging the links over isolates (persons without partners) and non-isolates obscures the simultaneity of interest in the partnerships. However, restricting the degree mean to non-isolates does not resolve this problem.

An example can be seen in Fig. 1a. The two contact graphs here both have five non-isolate nodes and four links; therefore, they have the same mean degree (whether the mean is based on all nodes, or on non-isolate nodes only). The pattern of concurrency, however, is critically different in the two graphs. One could argue that the second graph (graph II) has ‘more’ concurrency than graph I, as three nodes have concurrent partnerships in graph II, whereas only one node does in graph I. From an epidemiological perspective, however, graph I has the more efficient concurrency structure: transmission will be more rapid and less variable because the maximum distance between any two nodes in the network is only 2, compared with 4 in graph II.

Fig. 1
Fig. 1
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To distinguish the epidemiologically relevant aspect of concurrency we define a concurrency measure κ based on the ‘line graph’ of the original contact graph [21]. A node in the line graph transformation represents a partnership, and an link between two nodes indicates that they share a node in the original graph (i.e., they are concurrent partnerships). An example of the line graph, and how it varies with the different patterns of concurrency is given in Fig. 1b. The two panels are the line graphs of the original contact graphs in Fig. 1a. Every link in Fig. 1a becomes a node in Fig. 1b, and concurrent partnerships in Fig. 1a are connected by a link in Fig. 1b. The degree of a node in the line graph thus represents the number of partnerships that are adjacent to it. [Formally, let G(V, E) be the contact graph (as in Fig. 1a), where the set of nodes V describes the N individuals of the population and the set E (subset of V × V) describes the existing partnerships. The line graph L of G [21] has as nodes the set E. Two nodes of L are linked if they are adjacent edges in G (i.e., they share a node of V).] Under sequential monogamy, the line graph is made up of isolates because no partnership is concurrent with any other. For a star-shaped pattern in the original contact graph, the associated line graph is completely connected. Other patterns fall in between.

We define our population level measure of concurrency κ as the mean degree of the line graph. It represents the average number of concurrent partnerships per partnership in the population. The measure takes the value 0 under sequential monogamy, is equal to 1 when every partnership is concurrent to one other on average, and in general equals the line graph degree mean when the momentary degree distribution is Poisson. Because partnerships are discrete entities, when κ lies between 0 and 1, it has a very simple interpretation and indicates the fraction of partnerships that are concurrent. The measure also has the useful property in that it converges to a simple function of the variance (σ2) and the mean (µ) of the degree distribution of the original contact graph as the number of nodes grows large [22]:

The importance of this approximation is that it makes the measure easy to estimate from the available data. The approximation depends only on parameters from the original contact graph, so it can be estimated from local, rather than complete, network data [23]. Complete network data, that is, data on all nodes and links in a network, are both expensive and very difficult to collect. When dealing with sexual networks, such data would be virtually impossible to collect routinely. By contrast, local network data, that is, data on randomly selected respondents and their immediate partners only, are relatively easy and inexpensive to collect. One can rely on standard survey sampling techniques, and obtain information on the partner from the respondent so that no contact tracing is necessary. Local network data provide sufficient information for many epidemiological modeling purposes [24]. The fact that such data can also be used to estimate the epidemiologically relevant aspects of concurrency is fortunate, and it dramatically increases the usefulness of the measurement approach presented here.

It is interesting to note that the first two terms of the expression on the right hand side of equation 1 have been proposed as an approximation for the ‘effective’ mean contact rate when there is significant contact rate variability in the population [25]. This approximation was intended for the accumulation of sequentially monogamous partnerships, to measure variability in the number of partners per person over a period of time, rather than per person at a moment in time. There, as we also find here, variation amplifies the spread of infectious disease.

Equation 1
Equation 1
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Simulation model

We simulate the spread of a disease through a population under 10 different scenarios, where the first scenario represents sequential monogamy, and the remaining nine scenarios represent increasing levels of concurrency. We will briefly outline the main assumptions of the model; a complete description of the modeling framework has been published elsewhere [22].

The algorithm for producing the network and spreading the infection involves three separate processes: pair formation, pair dissolution, and disease transmission. Pair-formation and dissolution are controlled by a discrete-time Markov model. New partnerships form with a rate ρ, which depends on the number of partnerships already present, and existing partnerships separate with a constant rate σ, such that the total number of partnerships in the population fluctuates randomly around a constant average. This average is the same for all scenarios, and is held constant to ensure that concurrency is not confounded with a simple increase in the number of partnerships.

The momentary distribution of partnerships (Fig. 1) is independent of ρ and σ, and is varied over 10 levels to represent scenarios ranging from serial monogamy (individuals have no more than one partner at a time), to increasingly higher levels of concurrency (the momentary number of partners per individual is randomly distributed). This is accomplished by conditioning the probability of a new partnership on the current partnership status of each member of the pair. Under sequential monogamy, the probability of a partnership forming between two randomly selected persons is zero if either person has another partner. Under concurrency, this probability is (1 − ε) where ε ranges from [0–1] and is decreased to increase the level of concurrency. Mixing between the partnership classes under concurrency is random, that is, individuals with many partners are as likely to pair with monogamous individuals as they are with multipartnered individuals (the impact of assortative and disassortative mixing is analysed in Morris and Kretzschmar [26]). With the parameters chosen here, individuals have a momentary mean of just under one partner (range, 0–1 for monogamy, 0–4 for concurrency), accumulate an average of about 1.2 partners per year, and the typical partnership lasts about 6–7 months. As measured by κ, the fraction of partnerships that are concurrent ranges from 0 to 0.67. Because the total number of partnerships does not change, increasing the level of concurrency simply reallocates partnerships across the population, causing a change in distribution rather than in magnitude. The distributional change involves both an increase in the number of persons with concurrent partnerships, and a corresponding increase in the number of isolates.

The disease process begins by infecting a randomly selected person in a population with a stationary distribution of partnerships, defined as time t = 0. Disease transmission takes place within partnerships between susceptible and infected individuals at a constant rate of 0.05 per day. Each simulation is run for 5 years in a heterosexual population of 2000. For each of the 10 scenarios, 100 simulations are run with the same parameter values in order to observe variation in the epidemic outcomes. There are no vital dynamics or disease-related mortality.

Several aspects of this simulated network and associated epidemic outcomes are measured. The network structure is in dynamic equilibrium, so the summaries of this structure are calculated at the end of each 5-year run. The level of concurrency, κ, is calculated using equation 1 for each run, and the mean of the 100 runs is used for each scenario. The size of the largest component in the network is also recorded at the end of the run, as is the mean used for each scenario. Note that this is a measure of the momentary component size; additional nodes may have been connected over the course of the run but this is not measured here. The size of the epidemic is recorded at the end of the run; both the full distribution and the mean of the 100 runs for each scenario are presented (Figs 2 and 3, respectively). The growth rate is estimated as the change in the log of the mean number of infected persons per unit time during the phase of the epidemic, where the number of persons infected is below (N/2)1/2, about 22 in this population (compare Jacquez and O'Neill [27] and Ball and Donnely [28]). Here, again, the mean is taken over the 100 runs for each scenario.

Fig. 2
Fig. 2
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Fig. 3
Fig. 3
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Concurrency dramatically increases both the size and the variability of an epidemic, as can be seen in Fig. 2. Each panel in this figure represents the distribution of the number infected 5 years after the start of the epidemic for the 100 runs under the indicated value of concurrency. The 10 panels represent increasing levels of concurrency, starting with κ = 0 (serial monogamy) for panel 1, and rising to κ = 0.67 for panel 10. As concurrency rises, there are two corresponding shifts in the epidemic size distribution. First, the modal size increases. When one-quarter of the partnerships are concurrent (κ = 0.26, panel 5), the typical epidemic is three times as large by the end of 5 years as it is under sequential monogamy. When one-half of the partnerships are concurrent, the epidemic is about 10 times as large (panel 8). The variability in epidemic size also rises, as can be seen by the increasing spread in the distribution as one moves from panels 1 to 10. Thus, although the epidemic is typically larger, the outcome is also more variable, making it more difficult to predict.

A summary of the relationship between concurrency and epidemic size is shown in Fig. 3. The relationship is approximately linear on the log scale, so the impact of concurrency is quite large: the final number infected increases exponentially with κ. The regression estimate indicates that in this range of κ (i.e., 0–1, where it can be interpreted in percentage terms) for each 10% increase in the average number of concurrent partnerships the final epidemic size rises by a factor of roughly 40%. There are two things to keep in mind about this estimate. The first is that a full unit change in the average number of concurrent partnerships (κ) is a large change: for example, the increase from 0 to 1 represents the change from sequential monogamy to all partnerships being concurrent to one another (on average). Thus, the range examined here may represent most of the range that one would find in real populations. Second, one would expect this relationship to be valid only during the exponential growth phase of the epidemic, as in later phases saturation effects will prevail.

The initial amplification of spread is quite large, however: under the conditions here, it would take over 50 years for the epidemic under monogamy to reach the size observed in 5 years under the higher levels of concurrency (further analysis of changes in the evolutionary path of the epidemic can be found in Morris and Kretzschmar [26]).

Concurrency also increases the speed with which the epidemic spreads. Epidemic growth rate during the initial exponential phase of the epidemic is plotted against κ in Fig. 4. During this phase, the rate of growth also appears to be a exponentially increasing function of κ. The regression estimate indicates that each 10% increase in the average number of concurrent partnerships raises the growth rate by about 12%. This is close to a linear effect.

Fig. 4
Fig. 4
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Although these figures clearly demonstrate that concurrency has a large impact on transmission dynamics, they provide little insight into why. To understand the mechanism operating here, it is necessary to examine how concurrency changes the overall structure of the network. The key aspect of this change appears to be in the effect that concurrency has on increasing the size of the largest ‘connected component’: the number of nodes in the original graph that are directly or indirectly connected at any point in time. Under sequential monogamy, the maximum size of a connected component can not exceed 2. Under concurrency, by contrast, the maximum size of a connected component can become quite large: individuals have partners who are themselves connected to others, these others are again connected to additional persons, and so on.

The effect of concurrency on the average maximum component size are shown in Fig. 5. Maximum component size ranges here from 2 for κ = 0 to around 20 for κ = 0.67 (it rises much higher when partnerships are of longer duration), and the effect of concurrency is roughly linear. This order of magnitude increase in the size of the largest network component explains the dramatic changes in the course of the epidemics simulated: concurrency creates a large, loosely structured, constantly shifting web of connected nodes in a network, enabling an infectious agent to spread rapidly and pervasively.

Fig. 5
Fig. 5
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Compared with sequential monogamy, a pattern of concurrent partnerships can dramatically change the early course of an epidemic, increasing the growth rate and the number infected exponentially. These findings are consistent with other recent studies of sexual mixing [24,29] and core-group dynamics [30], which show that the distribution of partnerships, and not simply their mean, is a critical factor for infectious disease transmission. Together, these studies strongly suggest the need for network-oriented survey design and intervention in AIDS prevention efforts.

Although variable infectivity was not used in the models here, one can speculate that the effect of concurrency would be even stronger under that scenario. A short, early peak of infectivity would increase the likelihood that the virus would remain locked in an existing partnership after transmission under sequential monogamy. In contrast, under concurrency the virus can jump across each concurrent connection available during the peak infectious period. If the infectious window is quite short (e.g., a matter of weeks) then fairly high levels of partner change will be needed under sequential monogamy to reach the reproductive threshold and ensure continuing transmission. The larger momentary connected component created by concurrency, however, provides an ideal opportunity for spread, maximizing the use of the transmission window even, and perhaps especially, when partner change rates are low. For the kind of variable infectivity that is hypothesized to characterize HIV, then, the impact of concurrency is likely to be quite high.

The large impact of concurrent partnerships on both epidemic size and speed of spread has two important empirical implications. First, these results provide evidence that concurrent partnerships may partly explain the rapid heterosexual spread of HIV in sub-Saharan Africa and in other populations of the world. Most current research on variation in HIV epidemic intensity is currently focused on the impact of cofactor STD, a focus based on the STD-HIV association documented in observational studies [31,32]. It may be, however, that concurrent partnerships are the root cause of both STD and HIV, and that the STD-HIV correlation is simply an artifact of this process. Better estimates of the attributable risk of STD should become available, as a large, prospective, community-based case-control STD treatment study is now underway in Uganda with a behavioral component designed to measure concurrency [33]. Regardless of the STD effect, however, the simulations here show that concurrent partnerships are an important independent risk factor for HIV transmission. The intervention message is clear: one partner at a time.

The second implication is that patterns of concurrency in populations must be measured if accurate HIV/STD projection and effective intervention are desired. Simple measures of the rate of sexual partner acquisition are clearly inadequate for risk assessment; all of the simulations presented above were based on the same rate of partner acquisition, and the epidemic outcomes varied dramatically. Concurrency and other properties of partnership distribution should be among the core items required for HIV- and STD-related sexual behavior surveys. Such data are not difficult to collect. Many of the important features of the partnership distribution can be obtained using ‘egocentric’ or local network methods—a standard survey-based approach that relies on representatively sampled respondents to report on the attributes of their partners and relationships [23,34]. This approach is less expensive and intrusive than contact tracing, and thus more feasible for sensitive questions and large populations [24]. Local sexual network studies have now been carried out in several countries around the world, including Uganda [35], Thailand [36], and the United States [37]. The concurrency measure we have presented, κ, can be estimated from such local network data, as it depends only on the mean and variance of the momentary contact distribution.

Finally, there is much to be gained from additional simulation analyses of concurrency. Concurrent partnerships take many forms. The form examined here, of gender symmetric partnerships with relatively short-term partnerships and random mixing, is only loosely based on empirically observed patterns [38,39]. Polygamy features gender asymmetry and disassortative mixing, with women having one partner and men having multiple partners. Another common pattern is a combination of long- and short-term partners, with long-term partnerships formed in a sequential fashion (possibly overlapping during transition), and occasional concurrent short-term partnerships. Non-gender-based heterogeneity could also be modeled, with some persons sequentially monogamous, whereas others have concurrent partnerships. Each of these patterns represents culturally specific aspects of sexual network structure. Some of these structures are more efficient for transmission than others, certain network locations are more at risk than others, and each structure provides different ‘weak links’ in the chain of transmission that offer opportunities for intervention. HIV-related intervention efforts, whether targeted at risk groups or at overall transmission patterns, would be more effective if such dynamics were known and understood.

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Althaus, CL; Heijne, JCM; Herzog, SA; Roellin, A; Low, N
Plos One, 7(): -.
ARTN e51438
Sexually Transmitted Infections
Concurrent sexual partnerships among female sex workers and their non-commercial male partners in Tijuana and Ciudad Juarez, Mexico
Robertson, AM; Syvertsen, JL; Rangel, MG; Staines, HS; Morris, M; Patterson, TL; Ulibarri, MD; Strathdee, SA
Sexually Transmitted Infections, 89(4): 330-332.
Plos One
Factors Associated with Risky Sexual Practices among Female Sex Workers in Karnataka, India
Mahapatra, B; Lowndes, CM; Mohanty, SK; Gurav, K; Ramesh, BM; Moses, S; Washington, R; Alary, M
Plos One, 8(4): -.
ARTN e62167
Plos One
Epidemics Scenarios in the "Romantic Network"
Carvalho, AM; Goncalves, S
Plos One, 7(): -.
ARTN e49009
European Physical Journal-Special Topics
Transmission of HIV in sexual networks in sub-Saharan Africa and Europe
van de Vijver, DAMC; Prosperi, MCF; Ramasco, JJ
European Physical Journal-Special Topics, 222(6): 1403-1411.
Plos One
HIV Prevalence by Race Co-Varies Closely with Concurrency and Number of Sex Partners in South Africa
Kenyon, C; Buyze, J; Colebunders, R
Plos One, 8(5): -.
ARTN e64080
Plos One
Understanding the Potential Impact of a Combination HIV Prevention Intervention in a Hyper-Endemic Community
Alsallaq, RA; Baeten, JM; Celum, CL; Hughes, JP; Abu-Raddad, LJ; Barnabas, RV; Hallett, TB
Plos One, 8(1): -.
ARTN e54575
Sexual Health
Concurrent sexual partnerships among young adults in Cape Town, South Africa: how is concurrency changing?
Maughan-Brown, B
Sexual Health, 10(3): 246-252.
Statistics in Medicine
Sampling biases and missing data in explorations of sexual partner networks for the spread of sexually transmitted diseases
Ghani, AC; Donnelly, CA; Garnett, GP
Statistics in Medicine, 17(): 2079-2097.

AIDS Research and Human Retroviruses
HIV type 1 transmission probabilities: Estimates from epidemiological studies
Mastro, TD; Kitayaporn, D
AIDS Research and Human Retroviruses, 14(): S223-S227.

Journal of Urban Health-Bulletin of the New York Academy of Medicine
Methods and measures for the description of epidemiologic contact networks
Riolo, CS; Koopman, JS; Chick, SE
Journal of Urban Health-Bulletin of the New York Academy of Medicine, 78(3): 446-457.

Journal of Acquired Immune Deficiency Syndromes
HIV-1 epidemic among female bar and hotel workers in northern Tanzania: Risk factors and opportunities for prevention
Kapiga, SH; Sam, NE; Shao, JF; Renjifo, B; Masenga, EJ; Kiwelu, IE; Manongi, T; Fawzi, W; Essex, M
Journal of Acquired Immune Deficiency Syndromes, 29(4): 409-417.

Epidemiologic Reviews
The social epidemiology of human immunodeficiency virus/acquired immunodeficiency syndrome
Poundstone, KE; Strathdee, SA; Celentano, DD
Epidemiologic Reviews, 26(): 22-35.
Journal of Infectious Diseases
Determinants and consequences of sexual networks as they affect the spread of sexually transmitted infections
Doherty, IA; Padian, NS; Marlow, C; Aral, SO
Journal of Infectious Diseases, 191(): S42-S54.

Demographic Research
The Likoma Network Study: Context, data collection, and initial results
Helleringer, S; Kohler, HP; Chimbiri, A; Chatonda, P; Mkandawire, J
Demographic Research, 21(): 428-+.
Journal of Theoretical Biology
Higher variability in the number of sexual partners in males can contribute to a higher prevalence of sexually transmitted diseases in females
Gouveia-Oliveira, R; Pedersen, AG
Journal of Theoretical Biology, 261(1): 100-106.
International Journal of Environmental Research and Public Health
When Do Sexual Partnerships Need to Be Accounted for in Transmission Models of Human Papillomavirus?
Muller, H; Bauch, C
International Journal of Environmental Research and Public Health, 7(2): 635-650.
Journal of Eastern African Studies
"Balinsalamu embawo?" AIDS and the context of sexual behaviour adjustment in Rakai, Uganda, c. 1975-90
Kuhanen, J
Journal of Eastern African Studies, 4(1): 20-43.
Public Health Reports
Economically Motivated Relationships and Transactional Sex Among Unmarried African American and White Women: Results from a US National Telephone Survey
Dunkle, KL; Wingood, GM; Camp, CM; DiClemente, RJ
Public Health Reports, 125(): 90-100.

Southern African Journal of HIV Medicine
'Differential Poverty Rates Are Responsible for the Racial Differentials in HIV Prevalence in South Africa': An Enduring and Dangerous Epidemiological Urban Legend?
Kenyon, C
Southern African Journal of HIV Medicine, (): 22-27.

Homosexual activity among rural Indian men: implications for HIV interventions
Verma, RK; Collumbien, M
AIDS, 18(): 1845-1847.

Journal of Urban Health-Bulletin of the New York Academy of Medicine
HIV knowledge and risk behaviors among women in law enforcement in Bogota, Colombia: Potential role as community educators
Miguez-Burbano, MJ; de Pool, I; Hadrigan, S; Jackson, J; Angarita, I; Then, EP; Burbano, X; Shor-Posner, G
Journal of Urban Health-Bulletin of the New York Academy of Medicine, 82(3): IV43-IV57.
Sexually Transmitted Infections
Declines in HIV prevalence can be associated with changing sexual behaviour in Uganda, urban Kenya, Zimbabwe, and urban Haiti
Hallett, TB; Aberle-Grasse, J; Boulos, LM; Cayemittes, MPA; Cheluget, B; Chipeta, J; Dorrington, R; Dube, S; Ekra, AK; Garcia-Calleja, JM; Garnett, GP; Greby, S; Gregson, S; Grove, JT; Hader, S; Hanson, J; Hladik, W; Ismail, S; Kassim, S; Kirungi, W; Kouassi, L; Mahomva, A; Marum, L; Maurice, C; Nolan, M; Rehle, T; Stover, J; Walker, N
Sexually Transmitted Infections, 82(): I1-I8.
European Addiction Research
Sexually transmitted infections, sexual risk behaviors and the risk of heterosexual spread of HIV among and beyond IDUs in St. Petersburg, Russia
Abdala, N; Krasnoselskikh, TV; Durante, AJ; Timofeeva, MY; Verevochkin, SV; Kozlov, AP
European Addiction Research, 14(1): 19-25.
Demographic Research
Polygyny and HIV in Malawi
Reniers, G; Tfaily, R
Demographic Research, 19(): 1811-1830.
AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV
Disassortative sexual mixing among migrant populations in the Netherlands: a potential for HIV/STI transmission?
van Veen, MG; Kramer, MA; de Coul, ELMO; van Leeuwen, AP; de Zwart, O; van de Laar, MJW; Coutinho, RA; Prins, M
AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV, 21(6): 683-691.
Journal of Theoretical Biology
Predicting epidemics on directed contact networks
Meyers, LA; Newman, MEJ; Pourbohloul, B
Journal of Theoretical Biology, 240(3): 400-418.
Annual Review of Sociology
Old inequalities, new disease: HIV/AIDS in sub-Saharan Africa
Heimer, CA
Annual Review of Sociology, 33(): 551-577.
Bulletin of the World Health Organization
An estimate of the global prevalence and incidence of herpes simplex virus type 2 infection
Looker, KJ; Gamett, GP; Schmid, GP
Bulletin of the World Health Organization, 86(): 805-812.
Bulletin of Mathematical Biology
Modeling the Population Level Effects of an HIV-1 Vaccine in an Era of Highly Active Antiretroviral Therapy
Rida, W; Sandberg, S
Bulletin of Mathematical Biology, 71(3): 648-680.
AIDS Patient Care and Stds
Initial Outcomes of Provider-Initiated Routine HIV Testing and Counseling During Outpatient Care at a Rural Ugandan Hospital: Risky Sexual Behavior, Partner HIV Testing, Disclosure, and HIV Care Seeking
Kiene, SM; Bateganya, M; Wanyenze, R; Lule, H; Nantaba, H; Stein, MD
AIDS Patient Care and Stds, 24(2): 117-126.
Epidemiologic Reviews
Social epidemiology in South Africa
Myer, L; Ehrlich, RI; Susser, ES
Epidemiologic Reviews, 26(): 112-123.
AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV
Consistent condom use in the heterosexual relationships of young adults who live in a high-HIV-risk neighbourhood and do not use "hard drugs"
Friedman, SR; Flom, PL; Kottiri, BJ; Neaigus, A; Sandoval, M; Curtis, R; Des Jarlais, DC; Zenilman, JM
AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV, 13(3): 285-296.

Evaluation Review
Probabilistic cost effectiveness analysis of HIV prevention - Comparing a Bayesian approach with traditional deterministic sensitivity analysis
Johnson-Masotti, AP; Laud, PW; Hoffmann, RG; Hayat, MJ; Pinkerton, SD
Evaluation Review, 25(4): 474-502.

Proceedings of the Royal Society of London Series B-Biological Sciences
An assessment of preferential attachment as a mechanism for human sexual network formation
Jones, JH; Handcock, MS
Proceedings of the Royal Society of London Series B-Biological Sciences, 270(): 1123-1128.
Annales Zoologici Fennici
Integrating association data and disease dynamics in a social ungulate: bovine tuberculosis in African buffalo in the Kruger National Park
Cross, PC; Lloyd-Smith, JO; Bowers, JA; Hay, CT; Hofmeyr, M; Getz, WM
Annales Zoologici Fennici, 41(6): 879-892.

Epidemiology and Infection
Risk factors of sexually transmitted infections among migrant and non-migrant sexual partnerships from rural South Africa
Zuma, K; Lurie, MN; Williams, BG; Mkaya-Mwamburi, D; Garnett, GP; Sturm, AW
Epidemiology and Infection, 133(3): 421-428.
Proceedings of the National Academy of Sciences of the United States of America
Critique of early models of the demographic impact of HIV/AIDS in sub-Saharan Africa based on contemporary empirical data from Zimbabwe
Gregson, S; Nyamukapa, C; Lopman, B; Mushati, P; Garnett, GP; Chandiwana, SK; Anderson, RM
Proceedings of the National Academy of Sciences of the United States of America, 104(): 14586-14591.
Samj South African Medical Journal
The burden of disease attributable to sexually transmitted infections in South Africa in 2000
Johnson, L; Bradshaw, D; Dorrington, R
Samj South African Medical Journal, 97(8): 658-662.

Studies in Family Planning
Behavioral Mechanisms in HIV Epidemiology and Prevention: Past, Present, and Future Roles
Bingenheimer, JB; Geronimus, AT
Studies in Family Planning, 40(3): 187-204.

AIDS and Behavior
Concurrent Partnerships as a Driver of the HIV Epidemic in Sub-Saharan Africa? The Evidence is Limited
Lurie, MN; Rosenthal, S
AIDS and Behavior, 14(1): 17-24.
Perspectives on Sexual and Reproductive Health
The Contexts of Sexual Involvement And Concurrent Sexual Partnerships
Paik, A
Perspectives on Sexual and Reproductive Health, 42(1): 33-42.
Statistical Methods in Medical Research
Mathematical biology and medical statistics: contributions to the understanding of AIDS epidemiology
Donnelly, CA; Cox, DR
Statistical Methods in Medical Research, 10(2): 141-154.

Sexually Transmitted Diseases
Stigmatized drug use, sexual partner concurrency, and other sex risk network and behavior characteristics of 18-to 24-year-old youth in a high-risk neighborhood
Flom, PL; Friedman, SR; Kottiri, BJ; Neaigus, A; Curtis, R; Des Jarlais, DC; Sandoval, M; Zenilman, JM
Sexually Transmitted Diseases, 28(): 598-607.

International Journal of Std & AIDS
High-risk behaviours in men from Bogota, Colombia and the spread of HIV
Miguez-Burbano, MJ; Page, JB; Angarita, I; Rodriguez, N; Baum, MK; Burbano, X; Shor-Posner, G
International Journal of Std & AIDS, 12(): 739-743.

Changing Face of Disease: Implications for Society
The evolution, transmission and geographic spread of infectious diseases in human populations - Questions and models
Sattenspiel, L
Changing Face of Disease: Implications for Society, 43(): 40-63.

Social Science & Medicine
Transactional sex among women in Soweto, South Africa: prevalence, risk factors and association with HIV infection
Dunkle, KL; Jewkes, RK; Brown, HC; Gray, GE; McIntryre, JA; Harlow, SD
Social Science & Medicine, 59(8): 1581-1592.
American Journal of Sociology
Dynamic network visualization
Moody, J; McFarland, D; Bender-deMoll, S
American Journal of Sociology, 110(4): 1206-1241.

Journal of Sex Research
Estimating sexual behavior parameters from routine sexual behavior data
Van Vliet, C; Van der Ploeg, CPB; Kidula, N; Malonza, IM; Tyndall, M; Nagelkerke, NJD
Journal of Sex Research, 35(3): 298-305.

International Journal of Std & AIDS
Network structural dynamics and infectious disease propagation
Potterat, JJ; Rothenberg, RB; Muth, SQ
International Journal of Std & AIDS, 10(3): 182-185.

Annals of Operations Research
Small world network models of the dynamics of HIV infection
Vieira, IT; Cheng, RCH; Harper, PR; de Senna, V
Annals of Operations Research, 178(1): 173-200.
Journal of Adolescent Health
The final word on HIV infection in American youth: Test!
Rogers, AS
Journal of Adolescent Health, 39(2): 147-149.
Sexually Transmitted Infections
Maintenance of endemicity in urban environments: a hypothesis linking risk, network structure and geography
Rothenberg, R
Sexually Transmitted Infections, 83(1): 10-15.
Revue D Epidemiologie Et De Sante Publique
Determinants of condom use and heterosexual multiple sexual partnership in French Antilles and French Guiana
Cobat, A; Halfen, S; Gremy, I
Revue D Epidemiologie Et De Sante Publique, 56(3): 143-157.
Proceedings of the National Academy of Sciences of the United States of America
Microdynamics in stationary complex networks
Gautreau, A; Barrat, A; Barthelemy, M
Proceedings of the National Academy of Sciences of the United States of America, 106(): 8847-8852.
Demographic Research
Extra-marital sexual partnerships and male friendships in rural Malawi
Clark, S
Demographic Research, 22(): -.
Harm Reduction Journal
Large sharing networks and unusual injection practices explain the rapid rise in HIV among IDUs in Sargodha, Pakistan
Khan, AA; Awan, AB; Qureshi, SU; Razaque, A; Zafar, ST
Harm Reduction Journal, 6(): -.
Computers and Biomedical Research
Sexual behavior, heterosexual transmission, and the spread of HIV in sub-Saharan Africa: A simulation study
Auvert, B; Buonamico, G; Lagarde, E; Williams, B
Computers and Biomedical Research, 33(1): 84-96.

Journal of Urban Health-Bulletin of the New York Academy of Medicine
The risk environment for HIV transmission: Results from the Atlanta and Flagstaff network studies
Rothenberg, R; Baldwin, J; Trotter, R; Muth, S
Journal of Urban Health-Bulletin of the New York Academy of Medicine, 78(3): 419-432.

Rationality and Society
A game theoretical analysis of sexually transmitted disease epidemics
Schroeder, KD; Rojas, FG
Rationality and Society, 14(3): 353-383.

International Journal of Std & AIDS
Once and future HIV treatment: a comparison of clinic and community groups
Rothenberg, R; Campos, PE; del Rio, C; Johnson, W; Arriola, KJ; Brown, M
International Journal of Std & AIDS, 14(7): 438-447.

Dynamic Social Network Modeling and Analysis
Local rules and global properties: Modeling the emergence of network structure
Morris, M
Dynamic Social Network Modeling and Analysis, (): 174-186.

Journal of Infectious Diseases
Reported sexually transmitted disease clinic attendance and sexually transmitted infections in britain: Prevalence, risk factors, and proportionate population burden
Fenton, KA; Mercer, CH; Johnson, AM; Byron, CL; McManus, S; Erens, B; Copas, AJ; Nanchahal, K; Macdowall, W; Wellings, K
Journal of Infectious Diseases, 191(): S127-S138.

Plos One
Sexual Seroadaptation: Lessons for Prevention and Sex Research from a Cohort of HIV-Positive Men Who Have Sex with Men
McConnell, JJ; Bragg, L; Shiboski, S; Grant, RM
Plos One, 5(1): -.
ARTN e8831
American Journal of Public Health
Rethinking Gender, Heterosexual Men, and Women's Vulnerability to HIV/AIDS
Higgins, JA; Hoffman, S; Dworkin, SL
American Journal of Public Health, 100(3): 435-445.
Microbes and Infection
Reasons for the increase in emerging and re-emerging viral infectious diseases
Hui, EKW
Microbes and Infection, 8(3): 905-916.
AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV
Modeling HIV transmission risk among Mozambicans prior to their initiating highly active antiretroviral therapy
Pearson, CR; Kurth, AE; Cassels, S; Martin, DP; Simoni, JM; Hoff, P; Matediana, E; Gloyd, S
AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV, 19(5): 594-604.
Plos Computational Biology
Social Contact Networks and Disease Eradicability under Voluntary Vaccination
Perisic, A; Bauch, CT
Plos Computational Biology, 5(2): -.
ARTN e1000280
AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV
Social networks and concurrent sexual relationships - a qualitative study among men in an urban South African community
Ragnarsson, A; Townsend, L; Thorson, A; Chopra, M; Ekstrom, AM
AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV, 21(): 1253-1258.
Ajar-African Journal of AIDS Research
A network-level explanation for the differences in HIV prevalence in South Africa's racial groups
Kenyon, C; Dlamini, S; Boulle, A; White, RG; Badri, M
Ajar-African Journal of AIDS Research, 8(3): 243-254.
Journal of Sexual Medicine
Sexually Transmitted Diseases and Sexual Function
Sadeghi-Nejad, H; Wasserman, M; Weidner, W; Richardson, D; Goldmeier, D
Journal of Sexual Medicine, 7(1): 389-413.
Sexually Transmitted Diseases
Influence of mathematical modeling of HIV and AIDS on policies and programs in the developing world
Stover, J
Sexually Transmitted Diseases, 27(): 572-578.

Sexually Transmitted Infections
The geographical and temporal evolution of sexually transmitted disease epidemics
Garnett, GP
Sexually Transmitted Infections, 78(): I14-I19.

Physica A-Statistical Mechanics and Its Applications
Sexual networks in contemporary Western societies
Liljeros, F
Physica A-Statistical Mechanics and Its Applications, 338(): 238-245.
Sexually Transmitted Infections
HIV surveillance data analytical tools - Maximising the global use of HIV surveillance data through the development and sharing of analytical tools
Garnett, GP; Grassly, NC; Boerma, JT; Ghys, PD
Sexually Transmitted Infections, 80(): -.
Perspectives on Sexual and Reproductive Health
Consistency of condom use among low-income hormonal contraceptive users
Sangi-Haghpeykar, H; Posner, SF; Poindexter, AN
Perspectives on Sexual and Reproductive Health, 37(4): 184-191.

Sexually Transmitted Infections
Behavioural data as an adjunct to HIV surveillance data
Garnett, GP; Garcia-Calleja, JM; Rehle, T; Gregson, S
Sexually Transmitted Infections, 82(): I57-I62.
Mathematical Biosciences
Cost-effective control of chronic viral diseases: Finding the optimal level of screening and contact tracing
Armbruster, B; Brandeau, ML
Mathematical Biosciences, 224(1): 35-42.
A tale of two-component generalised HIV epidemics
Shelton, JD
Lancet, 375(): 964-966.

International Journal of Std & AIDS
Type of partnership and heterosexual spread of HIV infection in rural Uganda: results from simulation modelling
Robinson, NJ; Mulder, D; Auvert, B; Whitworth, J; Hayes, R
International Journal of Std & AIDS, 10(): 718-725.

Human Biologists in the Archives
Infectious diseases in the historical archives: A modeling approach
Sattenspiel, L
Human Biologists in the Archives, 34(): 234-265.

Social Science & Medicine
Secretive females or swaggering males? An assessment of the quality of sexual partnership reporting in rural Tanzania
Nnko, S; Boerma, JT; Urassa, M; Mwaluko, G; Zaba, B
Social Science & Medicine, 59(2): 299-310.
Sexually Transmitted Infections
Surveillance and modelling of HIV, STI, and risk behaviours in concentrated HIV epidemics
Mills, S; Saidel, T; Magnani, R; Brown, T
Sexually Transmitted Infections, 80(): 57-62.
Culture Health & Sexuality
Cultural politics and masculinities: Multiple-partners in historical perspective in KwaZulu-Natal
Hunter, M
Culture Health & Sexuality, 7(3): 209-223.
Health Education Research
Male heterosexual crack smokers with multiple sex partners: between- and within-person predictors of condom use intention
Bowen, A; Williams, M; Dearing, E; Timpson, S; Ross, M
Health Education Research, 21(4): 549-559.
Demographic Research
Sexual behaviour patterns in South Africa and their association with the spread of HIV: Insights from a mathematical model
Johnson, LF; Dorrington, RE; Bradshaw, D; Pillay-Van Wyk, V; Rehle, TM
Demographic Research, 21(): 289-339.
Clinical Infectious Diseases
Developing and Evaluating Comprehensive HIV Infection Control Strategies: Issues and Challenges
DeGruttola, V; Smith, DM; Little, SJ; Miller, V
Clinical Infectious Diseases, 50(): S102-S107.
American Journal of Clinical Nutrition
HIV and hepatocellular and esophageal carcinomas related to consumption of mycotoxin-prone foods in sub-Saharan Africa
Williams, JH; Grubb, JA; Davis, JW; Wang, JS; Jolly, PE; Ankrah, NA; Ellis, WO; Afriyie-Gyawu, E; Johnson, NM; Robinson, AG; Phillips, TD
American Journal of Clinical Nutrition, 92(1): 154-160.
International Journal of Std & AIDS
HIV infection among patients with sexually transmitted diseases in rural South Africa
Wilkinson, D; Wilkinson, N
International Journal of Std & AIDS, 9(): 736-739.

Sexual behaviour in Britain: partnerships, practices, and HIV risk behaviours
Johnson, AM; Mercer, CH; Erens, B; Copas, AJ; McManus, S; Wellings, K; Fenton, KA; Korovessis, C; Macdowall, W; Nanchahal, K; Purdon, S; Field, H
Lancet, 358(): 1835-1842.

Sexually Transmitted Infections
Determinants of STD epidemics: implications for phase appropriate intervention strategies
Aral, SO
Sexually Transmitted Infections, 78(): I3-I13.

Journal of Urban Health-Bulletin of the New York Academy of Medicine
The next generation of HIV prevention for adolescent females in the United States: Linking behavioral and epidemiologic sciences to reduce incidence of HIV
Ellen, JM
Journal of Urban Health-Bulletin of the New York Academy of Medicine, 80(4): 40-49.

Quarterly Journal of Economics
Sexually transmitted infections, sexual behavior, and the HIV/AIDS epidemic
Oster, E
Quarterly Journal of Economics, 120(2): 467-515.

Lancet Infectious Diseases
Intravaginal practices, bacterial vaginosis, and women's susceptibility to HIV infection: epidemiological evidence and biological mechanisms
Myer, L; Kuhn, L; Stein, ZA; Wright, TC; Denny, L
Lancet Infectious Diseases, 5(): 786-794.

Annual Review of Public Health
Network analysis in public health: History, methods, and applications
Luke, DA; Harris, JK
Annual Review of Public Health, 28(): 69-93.
Lancet Infectious Diseases
Testing the limits of case finding for HIV prevention
Cassell, MM; Surdo, A
Lancet Infectious Diseases, 7(7): 491-495.

HIV, sexually transmitted infections and sexual behaviour of male clients of female sex workers in Andhra Pradesh, Tamil Nadu and Maharashtra, India: results of a cross-sectional survey
Subramanian, T; Gupte, MD; Paranjape, RS; Brahmam, GNV; Ramakrishnan, L; Adhikary, R; Kangusamy, B; Thomas, BE; Kallam, S; Girish, CPK
AIDS, 22(): S69-S79.

AIDS and Behavior
Gay Men Who Engage in Group Sex are at Increased Risk of HIV Infection and Onward Transmission
Prestage, GP; Hudson, J; Down, I; Bradley, J; Corrigan, N; Hurley, M; Grulich, AE; McInnes, D
AIDS and Behavior, 13(4): 724-730.
HIV: consensus indicators are needed for concurrency
Lancet, 375(): 621-622.
Mathematical Biosciences
Analysis and simulation of a stochastic, discrete-individual model of STD transmission with partnership concurrency
Chick, SE; Adams, AL; Koopman, JS
Mathematical Biosciences, 166(1): 45-68.

The Atlanta Urban Networks Study: a blueprint for endemic transmission
Rothenberg, RB; Long, DM; Sterk, CE; Pach, A; Potterat, JJ; Muth, S; Baldwin, JA; Trotter, RT
AIDS, 14(): 2191-2200.

Evaluation and Program Planning
HIV risk networks and HIV transmission among injecting drug users
Neaigus, A; Friedman, SR; Kottiri, BJ; Jarlais, DCD
Evaluation and Program Planning, 24(2): 221-226.

Sexually Transmitted Diseases
The epidemiological and control implications of HIV transmission probabilities within partnerships
Rottingen, JA; Garnett, GP
Sexually Transmitted Diseases, 29(): 818-827.

Sexually Transmitted Infections
Investigating ethnic inequalities in the incidence of sexually transmitted infections: mathematical modelling study
Turner, KME; Garnett, GP; Ghani, AC; Sterne, JAC; Low, N
Sexually Transmitted Infections, 80(5): 379-385.
Jaids-Journal of Acquired Immune Deficiency Syndromes
Mathematical models for HIV transmission dynamics - Tools for social and behavioral science research
Cassels, S; Clark, SJ; Morris, M
Jaids-Journal of Acquired Immune Deficiency Syndromes, 47(): S34-S39.

Vulnerability of women in southern Africa to infection with HIV: biological determinants and priority health sector interventions
Chersich, MF; Rees, HV
AIDS, 22(): S27-S40.

Sexual Health
Cultural scripts for multiple and concurrent partnerships in southern Africa: why HIV prevention needs anthropology
Leclerc-Madlala, S
Sexual Health, 6(2): 103-110.
Journal of Womens Health
Gender and Poverty in South Africa in the Era of HIV/AIDS: A Quantitative Study
Shisana, O; Rice, K; Zungu, N; Zuma, K
Journal of Womens Health, 19(1): 39-46.
Scandinavian Journal of Public Health
The socioeconomic characteristics of risky sexual behaviour among reproductive-age women in St Petersburg
Regushevskaya, E; Dubikaytis, T; Nikula, M; Kuznetsova, O; Hemminki, E
Scandinavian Journal of Public Health, 36(2): 143-152.
Culture Health & Sexuality
Intensive sex partying amongst gay men in Sydney
Hurley, M; Prestage, G
Culture Health & Sexuality, 11(6): 597-610.
International Journal of Epidemiology
Commentary: The social pathology of the HIV/AIDS pandemic
Myer, L; Morroni, C; Susser, ES
International Journal of Epidemiology, 32(2): 189-192.
Mathematical Biosciences
Monogamous networks and the spread of sexually transmitted diseases
Eames, KTD; Keeling, MJ
Mathematical Biosciences, 189(2): 115-130.
Journal of Urban Health-Bulletin of the New York Academy of Medicine
Men, multiple sexual partners, and young adults' sexual relationships: Understanding the role of gender in the study of risk
O'Sullivan, LF; Hoffman, S; Harrison, A; Dolezal, C
Journal of Urban Health-Bulletin of the New York Academy of Medicine, 83(4): 695-708.
Sexual network structure and the spread of HIV in Africa: evidence from Likoma Island, Malawi
Helleringer, S; Kohler, HP
AIDS, 21(): 2323-2332.

Mathematical Population Studies
Networks in epidemiology
Kretzschmar, M; Wallinga, J
Mathematical Population Studies, 14(4): 203-209.
Characteristics of external/bridge relationships by partner type and location where sexual relationship took place
Helleringer, S; Kohler, HP; Chimbiri, A
AIDS, 21(): 2560-2561.

International Journal of Epidemiology
Measuring effectiveness in community randomized trials of HIV prevention
Hallett, TB; Garnett, GP; Mupamberiyi, Z; Gregson, S
International Journal of Epidemiology, 37(1): 77-87.
Womens Health Issues
Partnership concurrency status and condom use among women diagnosed with Trichomonas vaginalis
Lichtenstein, B; Desmond, RA; Schwebke, JR
Womens Health Issues, 18(5): 369-374.
Southern African Journal of HIV Medicine
The Role of Concurrent Sexual Relationships in the Spread of Sexually Transmitted Infections in Young South Africans
Kenyon, C; Badri, M
Southern African Journal of HIV Medicine, (): 29-+.

Revisiting the Foundations of Network Analysis
Butts, CT
Science, 325(): 414-416.
Social Science & Medicine
The social ecology of syphilis
Thomas, JC; Clark, M; Robinson, J; Monnett, M; Kilmarx, PH; Peterman, TA
Social Science & Medicine, 48(8): 1081-1094.

AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV
Consistent condom use among drug-using youth in a high HIV-risk neighbourhood
Friedman, SR; Flom, PL; Kottiri, BJ; Neaigus, A; Sandoval, M; Fuld, J; Curtis, R; Zenilman, JM; Des Jarlais, DC
AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV, 14(4): 493-507.
International Journal of Tuberculosis and Lung Disease
Contact tracing: comparing the approaches for sexually transmitted diseases and tuberculosis
Rothenberg, RB; McElroy, PD; Wilce, MA; Muth, SQ
International Journal of Tuberculosis and Lung Disease, 7(): S342-S348.

American Journal of Epidemiology
Defining core gonorrhea transmission utilizing spatial data
Bernstein, KT; Curriero, FC; Jennings, JM; Olthoff, G; Erbelding, EJ; Zenilman, J
American Journal of Epidemiology, 160(1): 51-58.
Factors affecting HIV concordancy in married couples in four African cities
Freeman, EE; Glynn, JR; Lagarde, E; Ferry, B; Lydie, N; Hayes, R; Morison, L; Weiss, H; Glynn, J; Robinson, N
AIDS, 18(): 1715-1721.

Lancet Infectious Diseases
Containing HIV/AIDS in India: the unfinished agenda
Chandrasekaran, P; Dallabetta, G; Loo, V; Rao, S; Gayle, H; Alexander, A
Lancet Infectious Diseases, 6(8): 508-521.

AIDS and Behavior
"A bull cannot be contained in a single kraal": Concurrent sexual partnerships in Botswana
Carter, MW; Kraft, JM; Koppenhaver, T; Galavotti, C; Roels, TH; Kilmarx, PH; Fidzani, B
AIDS and Behavior, 11(6): 822-830.
Perspectives on Sexual and Reproductive Health
Predictors of STDs among Asian and Pacific Islander young adults
Hahm, HC; Lee, JH; Ozonoff, A; Amodeo, M
Perspectives on Sexual and Reproductive Health, 39(4): 231-239.
Development and Change
Understanding the Southern African 'Anomaly': Poverty, Endemic Disease and HIV
Sawers, L; Stillwaggon, E
Development and Change, 41(2): 195-224.

Microbes and Infection
Magic bullets need accurate guns - syphilis eradication, elimination, and control
Garnett, GP; Brunham, RC
Microbes and Infection, 1(5): 395-404.

HIV prevalence, sexual risk behaviour and sexual mixing patterns among migrants in Amsterdam, the Netherlands
Gras, MJ; Weide, JF; Langendam, MW; Coutinho, RA; van den Hoek, A
AIDS, 13(): 1953-1962.

Sexually Transmitted Diseases
Sexual network structure and sexually transmitted disease prevention - A modeling perspective
Kretzschmar, M
Sexually Transmitted Diseases, 27(): 627-635.

Social Science & Medicine
Voluntary counseling and testing for couples: a high-leverage intervention for HIV/AIDS prevention in sub-Saharan Africa
Painter, TM
Social Science & Medicine, 53(): 1397-1411.

AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV
Sex partner support, drug use and sex risk among HIV-negative non-injecting heroin users
Miller, M; Neaigus, A
AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV, 14(6): 801-813.
Sexually Transmitted Infections
The impact of the phase of an epidemic of sexually transmitted infection on the evolution of the organism
Turner, KME; Garnett, GP
Sexually Transmitted Infections, 78(): I20-I30.

Journal of Urban Health-Bulletin of the New York Academy of Medicine
Feminization of the HIV epidemic in the United States: Major research findings and future research needs
Wingood, GM
Journal of Urban Health-Bulletin of the New York Academy of Medicine, 80(4): 67-76.

Bmc Public Health
Body mass index, sexual behaviour, and sexually transmitted infections: an analysis using the NHANES 1999-2000 data
Nagelkerke, NJD; Bernsen, RMD; Sgaier, SK; Jha, P
Bmc Public Health, 6(): -.
ARTN 199
Sexually Transmitted Infections
Fewer partners or more condoms? Modelling the effectiveness of STI prevention interventions
Garnett, GP; White, PJ; Ward, H
Sexually Transmitted Infections, 84(): II4-II11.
Sexually Transmitted Infections
Reported number of sexual partners: comparison of data from four African longitudinal studies
Todd, J; Cremin, I; McGrath, N; Bwanika, JB; Wringe, A; Marston, M; Kasamba, I; Mushati, P; Lutalo, T; Hosegood, V; Zaba, B
Sexually Transmitted Infections, 85(): I72-I80.
Plos One
Fitting the HIV Epidemic in Zambia: A Two-Sex Micro-Simulation Model
Leclerc, PM; Matthews, AP; Garenne, ML
Plos One, 4(5): -.
ARTN e5439
Annals of Epidemiology
Plausible and implausible parameters for mathematical modeling of nominal heterosexual HIV transmission
Deuchert, E; Brody, S
Annals of Epidemiology, 17(3): 237-244.
Sexually Transmitted Infections
Biological and demographic causes of high HIV and sexually transmitted disease prevalence in men who have sex with men
Goodreau, SM; Golden, MR
Sexually Transmitted Infections, 83(6): 458-462.
Lancet Infectious Diseases
Concurrency and HIV: 15 years and counting
Hudson, C
Lancet Infectious Diseases, 7(): 773.

International Journal of Std & AIDS
Denialism undermines AIDS prevention in sub-Saharan Africa
Gissequist, D
International Journal of Std & AIDS, 19(): 649-655.
Social Psychology Quarterly
The (re)Presentation of an Epidemic in Everyday Life
Mcdonnell, TE
Social Psychology Quarterly, 71(4): 321-323.

Sexual networks and HIV
Morris, M
AIDS, 11(): S209-S216.

International Journal of Std & AIDS
All STDs are not created equal: an analysis of the differential effects of sexual behaviour changes on different STDs
Pinkerton, SD; Layde, PM; DiFfranceisco, W; Chesson, HW
International Journal of Std & AIDS, 14(5): 320-328.

International Journal of Std & AIDS
Running on empty: sexual co-factors are insufficient to fuel Africa's turbocharged HIV epidemic
Gisselquist, D; Potterat, JJ; Brody, S
International Journal of Std & AIDS, 15(7): 442-452.

American Journal of Sociology
Chains of affection: The structure of adolescent romantic and sexual networks
Bearman, PS; Moody, J; Stovel, K
American Journal of Sociology, 110(1): 44-91.

AIDS Education and Prevention
Psychosocial correlates of HIV protection motivation among black adolescents in Venda, South Africa
Boer, H; Mashamba, MT
AIDS Education and Prevention, 17(6): 590-602.

International Family Planning Perspectives
Protecting young women from HIV/AIDS: The case against child and adolescent marriage
Clark, S; Bruce, J; Dude, A
International Family Planning Perspectives, 32(2): 79-88.

Journal of Sex Research
Young urban adults' heterosexual risk encounters and perceived risk and safety: A structured diary study
O'Sullivan, LF; Udell, W; Patel, VL
Journal of Sex Research, 43(4): 343-351.

AIDS and Behavior
Concurrent Sexual Partnerships and the HIV Epidemics in Africa: Evidence to Move Forward
Mah, TL; Halperin, DT
AIDS and Behavior, 14(1): 11-16.
AIDS and Behavior
The Mathematics of Concurrent Partnerships and HIV: A Commentary on Lurie and Rosenthal, 2009
Epstein, H
AIDS and Behavior, 14(1): 29-30.
Health & Place
Sexualised space, sexual networking & the emergence of AIDS in Rakai, Uganda
Kuhanen, J
Health & Place, 16(2): 226-235.
Studies in Family Planning
Men's Multiple Sexual Partnerships in 15 Sub-Saharan African Countries: Sociodemographic Patterns and Implications
Bingenheimer, JB
Studies in Family Planning, 41(1): 1-17.

Back to behavior: prevention priorities in countries with low HIV prevalence
Mills, S
AIDS, 14(): S267-S273.

Social Science & Medicine
Networks, resources and risk among women who use drugs
Miller, M; Neaigus, A
Social Science & Medicine, 52(6): 967-978.

Journal of Urban Health-Bulletin of the New York Academy of Medicine
Incarceration and High-Risk Sex Partnerships among Men in the United States
Khan, MR; Doherty, IA; Schoenbach, VJ; Taylor, EM; Epperson, MW; Adimora, AA
Journal of Urban Health-Bulletin of the New York Academy of Medicine, 86(4): 584-601.
Journal of Urban Health-Bulletin of the New York Academy of Medicine
Differences in Sexual Identity, Risk Practices, and Sex Partners between Bisexual Men and Other Men among a Low-Income Drug-Using Sample
Williams, CT; Mackesy-Amiti, ME; McKirnan, DJ; Ouellet, LJ
Journal of Urban Health-Bulletin of the New York Academy of Medicine, 86(): S93-S106.
AIDS and Behavior
Poverty, Sex and HIV
Nattrass, N
AIDS and Behavior, 13(5): 833-840.
AIDS and Behavior
Prevalence and Correlates of Concurrent Sexual Partnerships in Zambia
Sandoy, IF; Dzekedzeke, K; Fylkesnes, K
AIDS and Behavior, 14(1): 59-71.
Plos One
Gender Differences in the Risk of HIV Infection among Persons Reporting Abstinence, Monogamy, and Multiple Sexual Partners in Northern Tanzania
Landman, KZ; Ostermann, J; Crump, JA; Mgonja, A; Mayhood, MK; Itemba, DK; Tribble, AC; Ndosi, EM; Chu, HY; Shao, JF; Bartlett, JA; Thielman, NM
Plos One, 3(8): -.
ARTN e3075
International Journal of Std & AIDS
Political determinants of variable aetiology resonance: explaining the African AIDS epidemics
Hunsmann, M
International Journal of Std & AIDS, 20(): 834-838.
Journal of Mathematical Sociology
Concurrency and commitment: Network scheduling and its consequences for diffusion
Gibson, DR
Journal of Mathematical Sociology, 29(4): 295-323.
Sexually Transmitted Diseases
Factors associated with self-risk perception for sexually transmitted diseases among adolescents
Gurvey, JE; Adler, N; Ellen, JM
Sexually Transmitted Diseases, 32(): 742-744.
Assessing the effects of human mixing patterns on human immunodeficiency virus-1 interhost phylogenetics through social network simulation
Goodreau, SM
Genetics, 172(4): 2033-2045.
Jaids-Journal of Acquired Immune Deficiency Syndromes
Examining racial disparities in HIV - Lessons from sexually transmitted infections research
Kraut-Becher, J; Eisenberg, M; Voytek, C; Brown, T; Metzger, DS; Aral, S
Jaids-Journal of Acquired Immune Deficiency Syndromes, 47(): S20-S27.

International Journal of Drug Policy
Sexual health risk among dance drug users: Cross-sectional comparisons with nationally representative data
Mitcheson, L; McCambridge, J; Byrne, A; Hunt, N; Winstock, A
International Journal of Drug Policy, 19(4): 304-310.
Ciencia & Saude Coletiva
Networks: epidemiology of transmissible diseases from a systemic perspective
Codeco, CT; Coelho, FC
Ciencia & Saude Coletiva, 13(6): 1767-1774.

Bulletin of the World Health Organization
Focusing strategies of condom use against HIV in different behavioural settings: an evaluation based on a simulation model
van Vliet, C; Meester, EI; Korenromp, EL; Singer, B; Bakker, R; Habbema, JDF
Bulletin of the World Health Organization, 79(5): 442-454.

American Journal of Epidemiology
Subtype-specific transmission probabilities for human immunodeficiency virus type 1 among injecting drug users in Bangkok, Thailand
Hudgens, MG; Longini, IM; Vanichseni, S; Hu, DJ; Kitayaporn, D; Mock, PA; Halloran, ME; Satten, GA; Choopanya, K; Mastro, TD
American Journal of Epidemiology, 155(2): 159-168.

Sexually Transmitted Diseases
Spatial bridges for the importation of gonorrhea and chlamydial infection
Kerani, RP; Golden, MR; Whittington, WLH; Handsfield, HH; Hogben, M; Holmes, KK
Sexually Transmitted Diseases, 30(): 742-749.
American Journal of Health Behavior
Condom use among low-income African American males attending an STD clinic
Grimley, DM; Hook, EW; DiClemente, RJ; Lee, PA
American Journal of Health Behavior, 28(1): 33-42.

AIDS and Behavior
Using the Internet to recruit rural MSM for HIV risk assessment: Sampling issues
Bowen, A; Williams, M; Horvath, K
AIDS and Behavior, 8(3): 311-319.

Journal of Sex Research
Risky sexual Behavior in low-income African American women: The impact of sexual health variables
Robinson, BBE; Scheltema, K; Cherry, T
Journal of Sex Research, 42(3): 224-237.

International Migration Review
Male Migration, Women Left Behind, and Sexually Transmitted Diseases in Armenia
Sevoyan, A; Agadjanian, V
International Migration Review, 44(2): 354-375.
Simulations to evaluate HIV vaccine trial designs
Adams, AL; Barth-Jones, DC; Chick, SE; Koopman, JS
Simulation, 71(4): 228-241.

Social Science & Medicine
Sexually transmitted diseases in Morocco: gender influences on prevention and health care seeking behavior
Manhart, LE; Dialmy, A; Ryan, CA; Mahjour, J
Social Science & Medicine, 50(): 1369-1383.

Effectiveness of HIV prevention interventions in developing countries
Merson, MH; Dayton, JM; O'Reilly, K
AIDS, 14(): S68-S84.

Sexually Transmitted Diseases
Mathematical modeling as a tool in STD prevention and control - A decade of progress, a millennium of opportunities
Aral, SO; Roegner, R
Sexually Transmitted Diseases, 27(): 556-557.

International Journal of Health Services
Nation in pain: Why the HIV/AIDS epidemic is out of control in Zimbabwe
Sibanda, A
International Journal of Health Services, 30(4): 717-738.

Sexually Transmitted Infections
Prevention strategies for sexually transmitted infections: importance of sexual network structure and epidemic phase
Ward, H
Sexually Transmitted Infections, 83(): I43-I49.
Sexually Transmitted Infections
Recent multiple sexual partners and HIV transmission risks among people living with HIV/AIDS in Botswana
Kalichman, SC; Ntseane, D; Nthomang, K; Segwabe, M; Phorano, O; Simbayi, LC
Sexually Transmitted Infections, 83(5): 371-375.
Health Affairs
Tackling HIV in India: Evidence-based priority setting and programming
Claeson, M; Alexander, A
Health Affairs, 27(4): 1091-1102.
Studies in Family Planning
Young People's Sexual Partnerships in KwaZulu-Natal, South Africa: Patterns, Contextual Influences, and HIV Risk
Harrison, A; Cleland, J; Frohlich, J
Studies in Family Planning, 39(4): 295-308.
Studies in Family Planning
A Framework of Sexual Partnerships: Risks and Implications for HIV Prevention in Africa
Green, EC; Mah, TL; Ruark, A; Hearst, N
Studies in Family Planning, 40(1): 63-70.
Tropical Medicine & International Health
Do behavioural differences help to explain variations in HIV prevalence in adolescents in sub-Saharan Africa?
Chapman, R; White, RG; Shafer, LA; Pettifor, A; Mugurungi, O; Ross, D; Pascoe, S; Cowan, FM; Grosskurth, H; Buve, A; Hayes, RJ
Tropical Medicine & International Health, 15(5): 554-566.
Social Science & Medicine
Polygyny and women's health in sub-Saharan Africa
Bove, R; Valeggia, C
Social Science & Medicine, 68(1): 21-29.
Sexually Transmitted Diseases
Evidence undermining the adequacy of the HIV reproduction number formula
Potterat, JJ; Muth, SQ; Brody, S
Sexually Transmitted Diseases, 27(): 644-645.

Sexually Transmitted Infections
An introduction to mathematical models in sexually transmitted disease epidemiology
Garnett, GP
Sexually Transmitted Infections, 78(1): 7-12.

Journal of Urban Health-Bulletin of the New York Academy of Medicine
Transmission of STIs/HIV at the partnership level: Beyond individual-level analyses
Gorbach, PM; Holmes, KK
Journal of Urban Health-Bulletin of the New York Academy of Medicine, 80(4): 15-25.

Sexually Transmitted Infections
Population contextual associations with heterosexual partner numbers: a multilevel analysis
Smith, AMA; Subramanian, SV
Sexually Transmitted Infections, 82(3): 250-254.
American Journal of Public Health
Prevalence of HIV infection among young adults in the United States: Results from the Add Health Study
Morris, M; Handcock, MS; Miller, WC; Ford, CA; Schmitz, JL; Hobbs, MM; Cohen, MS; Harris, KM; Udry, JR
American Journal of Public Health, 96(6): 1091-1097.
Sexually Transmitted Diseases
Commentary - Gonorrhea surveillance: The missing links
Rothenberg, R; Potterat, JJ
Sexually Transmitted Diseases, 29(): 806-810.

Sexual contacts and epidemic thresholds
Jones, JH; Handcock, MS
Nature, 423(): 605-606.
Annual Review of Public Health
Modeling infection transmission
Koopman, J
Annual Review of Public Health, 25(): 303-326.
Theoretical Population Biology
Likelihood-based inference for stochastic models of sexual network formation
Handcock, MS; Jones, JH
Theoretical Population Biology, 65(4): 413-422.
International Journal of Epidemiology
Modelling the impact on Hepatitis C transmission of reducing syringe sharing: London case study
Vickerman, P; Hickman, M; Judd, A
International Journal of Epidemiology, 36(2): 396-405.
British Medical Journal
AIDS and the irrational
Epstein, H
British Medical Journal, 337(): -.
ARTN a2638
Genitourinary Medicine
Syndromic management of sexually transmitted diseases in developing countries: what role in the control of the STD and HIV epidemics?
Wilkinson, D
Genitourinary Medicine, 73(6): 427-428.

Journal of the Royal Statistical Society Series A-Statistics in Society
Measuring sexual partner networks for transmission of sexually transmitted diseases
Ghani, AC; Garnett, GP
Journal of the Royal Statistical Society Series A-Statistics in Society, 161(): 227-238.

Sexually Transmitted Diseases
Modeling contact networks and infection transmission in geographic and social space using GERMS
Koopman, JS; Chick, SE; Riolo, CS; Adams, AL; Wilson, ML; Becker, MP
Sexually Transmitted Diseases, 27(): 617-626.

Sexually Transmitted Infections
A pilot study of a rapid assessment method to identify places for AIDS prevention in Cape Town, South Africa
Weir, SS; Morroni, C; Coetzee, N; Spencer, J; Boerma, JT
Sexually Transmitted Infections, 78(): I106-I113.

Sexually Transmitted Infections
Sexual network structure as an indicator of epidemic phase
Potterat, JJ; Muth, SQ; Rothenberg, RB; Zimmerman-Rogers, H; Green, DL; Taylor, JE; Bonney, MS; White, HA
Sexually Transmitted Infections, 78(): I152-I158.

Sexual mixing patterns and sex-differentials in teenage exposure to HIV infection in rural Zimbabwe
Gregson, S; Nyamukapa, CA; Garnett, GP; Mason, PR; Zhuwau, T; Carael, M; Chandiwana, SK; Anderson, RM
Lancet, 359(): 1896-1903.

Culture Health & Sexuality
Cultural politics and masculinities: Multiple-partners in historical perspective in KwaZulu-Natal
Hunter, M
Culture Health & Sexuality, 7(4): 389-403.
Infectious Disease Clinics of North America
Global epidemiology of HIV-AIDS
Karim, SSA; Karim, QA; Gouws, E; Baxter, C
Infectious Disease Clinics of North America, 21(1): 1-+.
HIV infection does not disproportionately affect the poorer in sub-Saharan Africa
Mishra, V; Assche, SRV; Greener, R; Vaessen, M; Hong, R; Ghys, PD; Boerma, JT; Van Assche, A; Khan, S; Rutstein, S
AIDS, 21(): S17-S28.

Plos One
Understanding the Impact of Male Circumcision Interventions on the Spread of HIV in Southern Africa
Hallett, TB; Singh, K; Smith, JA; White, RG; Abu-Raddad, LJ; Garnett, GP
Plos One, 3(5): -.
ARTN e2212
Birds of A Feather, or Friend of A Friend? Using Exponential Random Graph Models to Investigate Adolescent Social Networks
Goodreau, SM; Kitts, JA; Morris, M
Demography, 46(1): 103-125.

American Journal of Public Health
Concurrent Partnerships and HIV Prevalence Disparities by Race: Linking Science and Public Health Practice
Morris, M; Kurth, AE; Hamilton, DT; Moody, J; Wakefield, S
American Journal of Public Health, 99(6): 1023-1031.
AIDS Education and Prevention
Developing Concurrency Messages for the Black Community in Seattle, Washington
Andrasik, MP; Chapman, CH; Clad, R; Murray, K; Foster, J; Morris, M; Parks, MR; Kurth, AE
AIDS Education and Prevention, 24(6): 527-548.

Sexually Transmitted Infections
Bringing it home: community survey of HIV risks to primary sex partners of men and women in alcohol-serving establishments in Cape Town, South Africa
Kalichman, SC; Pitpitan, E; Eaton, L; Cain, D; Carey, KB; Carey, MP; Harel, O; Mehlomakhulu, V; Simbayi, LC; Mwaba, K
Sexually Transmitted Infections, 89(3): 231-236.
Polygyny and the spread of HIV in sub-Saharan Africa: a case of benign concurrency
Reniers, G; Watkins, S
AIDS, 24(2): 299-307.
PDF (698) | CrossRef
Concurrency is more complex than it seems
Kretzschmar, M; White, RG; Caraël, M
AIDS, 24(2): 313-315.
PDF (257) | CrossRef
Herpes simplex 2 risk among women in a polygynous setting in rural West Africa
Halton, K; Ratcliffe, AA; Morison, L; West, B; Shaw, M; Bailey, R; Walraven, G
AIDS, 17(1): 97-103.

PDF (98)
Examining the promise of HIV elimination by ‘test and treat’ in hyperendemic settings
Dodd, PJ; Garnett, GP; Hallett, TB
AIDS, 24(5): 729-735.
PDF (429) | CrossRef
Treatment with antiretroviral therapy is not associated with increased sexual risk behavior in Kenyan female sex workers
McClelland, RS; Graham, SM; Richardson, BA; Peshu, N; Masese, LN; Wanje, GH; Mandaliya, KN; Kurth, AE; Jaoko, W; Ndinya-Achola, JO
AIDS, 24(6): 891-897.
PDF (323) | CrossRef
Model-based evaluation of single-round mass treatment of sexually transmitted diseases for HIV control in a rural African population
Korenromp, EL; Van Vliet, C; Grosskurth, H; Gavyole, A; Van der Ploeg, CP; Fransen, L; Hayes, RJ; Habbema, JD
AIDS, 14(5): 573-593.

PDF (351)
Condom acceptance is higher among travelers in Uganda
Morris, M; Wawer, MJ; Makumbi, F; Zavisca, JR; Sewankambo, N
AIDS, 14(6): 733-741.

PDF (154)
Do needle exchange programmes increase the spread of HIV among injection drug users?: an investigation of the Vancouver outbreak
Schechter, MT; Strathdee, SA; Cornelisse, PG; Currie, S; Patrick, DM; Rekart, ML; O‚Shaughnessy, MV
AIDS, 13(6): F45-F51.

PDF (150)
Emerging future issues in HIV/AIDS social research
Friedman, SR; Kippax, SC; Phaswana-Mafuya, N; Rossi, D; Newman, CE
AIDS, 20(7): 959-965.
PDF (155) | CrossRef
Coining a new term in epidemiology: concurrency and HIV
Garnett, GP; Johnson, AM
AIDS, 11(5): 681-683.

PDF (188)
Concurrent sexual partnerships and HIV prevalence in five urban communities of sub-Saharan Africa
Lagarde, E; Auvert, B; Caraël, M; Laourou, M; Ferry, B; Akam, E; Sukwa, T; Morison, L; Maury, B; Chege, J; N'Doye, I; Buvé, A; Cities, tS
AIDS, 15(7): 877-884.

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What role does HIV-1 subtype play in transmission and pathogenesis? An epidemiological perspective
Hu, DJ; Buvé, A; Baggs, J; van der Groen, G; Dondero, TJ
AIDS, 13(8): 873-881.

PDF (194)
The association of HIV serodiscordance and partnership concurrency in Likoma Island (Malawi)
Helleringer, S; Kohler, H; Kalilani-Phiri, L
AIDS, 23(10): 1285-1287.
PDF (155) | CrossRef
Current Opinion in Infectious Diseases
Sexual networks and the transmission of drug-resistant HIV
Drumright, LN; Frost, SD
Current Opinion in Infectious Diseases, 21(6): 644-652.
PDF (179) | CrossRef
Risk of HIV-1 in Rural Kenya: A Comparison of Circumcised and Uncircumcised Men
Agot, KE; Ndinya-Achola, JO; Kreiss, JK; Weiss, NS
Epidemiology, 15(2): 157-163.
PDF (261) | CrossRef
Concurrent Sexual Partnerships Among Women in the United States
Stancil, TR; Adimora, AA; Schoenbach, VJ; Bonas, DM; Martinson, FE; Donaldson, KH
Epidemiology, 13(3): 320-327.

PDF (771)
Contextual Factors and the Black-White Disparity in Heterosexual HIV Transmission
Adimora, AA; Schoenbach, VJ
Epidemiology, 13(6): 707-712.

PDF (243)
JAIDS Journal of Acquired Immune Deficiency Syndromes
Rectal Gonorrhea and Chlamydia Reinfection Is Associated With Increased Risk of HIV Seroconversion
Bernstein, KT; Marcus, JL; Nieri, G; Philip, SS; Klausner, JD
JAIDS Journal of Acquired Immune Deficiency Syndromes, 53(4): 537-543.
PDF (161) | CrossRef
JAIDS Journal of Acquired Immune Deficiency Syndromes
The Unexpected Movement of the HIV Epidemic in the Southeastern United States: Transmission Among College Students
Hightow, LB; MacDonald, PD; Pilcher, CD; Kaplan, AH; Foust, E; Nguyen, TQ; Leone, PA
JAIDS Journal of Acquired Immune Deficiency Syndromes, 38(5): 531-537.

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JAIDS Journal of Acquired Immune Deficiency Syndromes
Estimating HIV Prevalence and Risk Behaviors Among High-Risk Heterosexual Men With Multiple Sex Partners: Use of Respondent-Driven Sampling
Chopra, M; Townsend, L; Johnston, L; Mathews, C; Tomlinson, M; O'Bra, H; Kendall, C
JAIDS Journal of Acquired Immune Deficiency Syndromes, 51(1): 72-77.
PDF (83) | CrossRef
JAIDS Journal of Acquired Immune Deficiency Syndromes
Increasing Uptake of HIV Testing and Counseling Among the Poorest in Sub-Saharan Countries Through Home-Based Service Provision
Helleringer, S; Kohler, H; Frimpong, JA; Mkandawire, J
JAIDS Journal of Acquired Immune Deficiency Syndromes, 51(2): 185-193.
PDF (175) | CrossRef
JAIDS Journal of Acquired Immune Deficiency Syndromes
Sex With Older Partners Is Associated With Primary HIV Infection Among Men Who Have Sex With Men in North Carolina
Hurt, CB; Matthews, DD; Calabria, MS; Green, KA; Adimora, AA; Golin, CE; Hightow-Weidman, LB
JAIDS Journal of Acquired Immune Deficiency Syndromes, 54(2): 185-190.
PDF (207) | CrossRef
JAIDS Journal of Acquired Immune Deficiency Syndromes
Utility of Behavioral Changes as Markers of Sexually Transmitted Disease Risk Reduction in Sexually Transmitted Disease/HIV Prevention Trials
Pinkerton, SD; Chesson, HW; Layde, PM; the National Institute of Mental Health Multisite HIV Prevention Trial Group,
JAIDS Journal of Acquired Immune Deficiency Syndromes, 31(1): 71-79.

PDF (2940)
JAIDS Journal of Acquired Immune Deficiency Syndromes
Sexual Mixing Patterns and Heterosexual HIV Transmission Among African Americans in the Southeastern United States
Doherty, IA; Schoenbach, VJ; Adimora, AA
JAIDS Journal of Acquired Immune Deficiency Syndromes, 52(1): 114-120.
PDF (129) | CrossRef
JAIDS Journal of Acquired Immune Deficiency Syndromes
Group Sex Events and HIV/STI Risk in an Urban Network
Friedman, SR; Bolyard, M; Khan, M; Maslow, C; Sandoval, M; Mateu-Gelabert, P; Krauss, B; Aral, SO
JAIDS Journal of Acquired Immune Deficiency Syndromes, 49(4): 440-446.
PDF (277) | CrossRef
Sexually Transmitted Diseases
Establishing Efficient Partner Notification Periods for Patients With Chlamydia
Zimmerman-Rogers, H; Potterat, JJ; Muth, SQ; Bonney, MS; Green, DL; Taylor, JE; White, HA
Sexually Transmitted Diseases, 26(1): 49-54.

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Sexually Transmitted Diseases
A New Scale for Measuring Dynamic Patterns of Sexual Partnership and Concurrency: Application to Three French Caribbean Regions
Sexually Transmitted Diseases, 30(1): 6-9.

PDF (155)
Sexually Transmitted Diseases
Discord, Discordance, and Concurrency: Comparing Individual and Partnership-Level Analyses of New Partnerships of Young Adults at Risk of Sexually Transmitted Infections
Gorbach, PM; Drumright, LN; Holmes, KK
Sexually Transmitted Diseases, 32(1): 7-12.

PDF (332)
Sexually Transmitted Diseases
Sexual Risk Among Injection Drug Users Recruited From Syringe Exchange Programs in California
Bluthenthal, RN; Bogart, LM; Kral, AH; Scott, A; Anderson, R; Flynn, N; Gilbert, ML
Sexually Transmitted Diseases, 32(1): 27-34.

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Sexually Transmitted Diseases
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HIV; networks; sexual behavior; transmission

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