A decade of modelling research yields considerable evidence for the importance of concurrency: a response to Sawers and Stillwaggon

Impact of post-incarceration care engagement interventions on HIV transmission among young Black men who have sex with men and their sexual partners: an agent-based network modeling study

Background

Understanding the impact of incarceration on HIV transmission among Black men who have sex with men is important given their disproportionate representation among people experiencing incarceration and the potential impact of incarceration on social and sexual networks, employment, housing, and medical care. We developed an agent-based network model (ABNM) of 10,000 agents representing young Black men who have sex with men in the city of Chicago to examine the impact of varying degrees of post-incarceration care disruption and care engagement interventions following release from jail on HIV incidence.

Methods

Exponential random graph models were used to model network formation and dissolution dynamics, and network dynamics and HIV care continuum engagement were varied according to incarceration status. Hypothetical interventions to improve post-release engagement in HIV care for individuals with incarceration (e.g., enhanced case management, linkage to housing and employment services) were compared to a control scenario with no change in HIV care engagement after release.

Finding

HIV incidence at 10 years was 4.98 [95% simulation interval (SI): 4.87, 5.09 per 100 person-years (py)] in the model population overall; 5.58 (95% SI 5.38, 5.76 per 100 py) among those with history of incarceration, and 12.86 (95% SI 11.89, 13.73 per 100 py) among partners of agents recently released from incarceration. Sustained post-release HIV care for agents with HIV and experiencing recent incarceration resulted in a 46% reduction in HIV incidence among post-incarceration partners [incidence rate (IR) per 100 py = 5.72 (95% SI 5.19, 6.27) vs. 10.61 (95% SI 10.09, 11.24); incidence rate ratio (IRR) = 0.54; (95% SI 0.48, 0.60)] and a 19% reduction in HIV incidence in the population overall [(IR per 100 py = 3.89 (95% SI 3.81-3.99) vs. 4.83 (95% SI 4.73, 4.92); IRR = 0.81 (95% SI 0.78, 0.83)] compared to a scenario with no change in HIV care engagement from pre-to post-release.

Interpretation

Developing effective and scalable interventions to increase HIV care engagement among individuals experiencing recent incarceration and their sexual partners is needed to reduce HIV transmission among Black men who have sex with men.

Funding

This work was supported by the following grants from the National Institutes of Health: R01DA039934; P20 GM 130414; P30 AI 042853; P30MH058107; T32 DA 043469; U2C DA050098 and the California HIV/AIDS Research Program: OS17-LA-003; H21PC3466.

Assessment of Bias in Estimates of Sexual Network Degree using Prospective Cohort Data

BACKGROUND

Sexual network degree, a count of ongoing partnerships, plays a critical role in the transmission dynamics of human immunodeficiency virus and other sexually transmitted infections. Researchers often quantify degree using self-reported cross-sectional data on the day of survey, which may result in bias because of uncertainty about future sexual activity.

METHODS

We evaluated the bias of a cross-sectional degree measure with a prospective cohort study of men who have sex with men (MSM). At baseline, we asked men about whether recent sexual partnerships were ongoing. We confirmed the true, ongoing status of those partnerships at baseline at follow-up. With logistic regression, we estimated the partnership-level predictors of baseline measure accuracy. With Poisson regression, we estimated the longitudinally confirmed degree as a function of baseline predicted degree.

RESULTS

Across partnership types, the baseline ongoing status measure was 70% accurate, with higher negative predictive value (91%) than positive predictive value (39%). Partnership exclusivity and racial pairing were associated with higher accuracy. Baseline degree generally overestimated confirmed degree. Bias, or number of ongoing partners different than predicted at baseline, was -0.28 overall, ranging from -1.91 to -0.41 for MSM with any ongoing partnerships at baseline. Comparing MSM of the same baseline degree, the level of bias was stronger for black compared with white MSM, and for younger compared with older MSM.

CONCLUSIONS

Research studies may overestimate degree when it is quantified cross-sectionally. Adjustment and structured sensitivity analyses may account for bias in studies of human immunodeficiency virus or sexually transmitted infection prevention interventions.

Correlates of concurrent partnerships and patterns of condom use among men who have sex with men and transgender women in Peru

Background

In Peru, there is an ongoing high-incidence HIV epidemic among men who have sex with men (MSM) and transgender women (TW). Sexual concurrency, or having sex with a partner in between two acts of sex with another partner, may be a key factor in onward HIV transmission. In this study, we quantify concurrency, evaluate factors associated with concurrency, and assess condom use with concurrent partners among MSM and TW in Peru.

Methods

We conducted a secondary analysis of data from the 2011 Peruvian Biobehavioral Survey. Pearson’s Chi-squared test was used to identify individual-level characteristics associated with concurrency. We estimated the association between participant characteristics, concurrent partnerships, partnership type (stable vs. non-stable), and CLAI within the context of concurrent partnerships using multivariate and repeated-measure Poisson regression.

Results

3-month cumulative prevalence of concurrency was higher among TW compared to MSM (30.7% vs 25.2%, p = 0.014). Among those with concurrent stable and non-stable partners, 45% used condoms with both partners (95% CI: 40%-50%) and 30% preferentially had CLAI with the stable partner only (95%CI: 26%-35%). Factors associated with CLAI within the context of concurrent partnerships varied between MSM and TW.

Conclusions

Although concurrency is common among TW and MSM in Peru, patterns of concurrency and differential condom use may vary between TW and MSM. Future research may explore differential condom use with stable and non-stable partners to better understand behavioral factors that may alter vulnerability to HIV in TW compared to MSM.

EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks

Package EpiModel provides tools for building, simulating, and analyzing mathematical models for the population dynamics of infectious disease transmission in R. Several classes of models are included, but the unique contribution of this software package is a general stochastic framework for modeling the spread of epidemics on networks. EpiModel integrates recent advances in statistical methods for network analysis (temporal exponential random graph models) that allow the epidemic modeling to be grounded in empirical data on contacts that can spread infection. This article provides an overview of both the modeling tools built into EpiModel, designed to facilitate learning for students new to modeling, and the application programming interface for extending package EpiModel, designed to facilitate the exploration of novel research questions for advanced modelers.

The Human Immunodeficiency Virus Endemic: Maintaining Disease Transmission in At-Risk Urban Areas

OBJECTIVES

A study of network relationships, geographic contiguity, and risk behavior was designed to test the hypothesis that all 3 are required to maintain endemicity of human immunodeficiency virus (HIV) in at-risk urban communities. Specifically, a highly interactive network, close geographic proximity, and compound risk (multiple high-risk activities with multiple partners) would be required.

METHODS

We enrolled 927 participants from two contiguous geographic areas in Atlanta, GA: a higher-risk area and lower-risk area, as measured by history of HIV reporting. We began by enrolling 30 "seeds" (15 in each area) who were comparable in their demographic and behavioral characteristics, and constructed 30 networks using a chain-link design. We assessed each individual's geographic range; measured the network characteristics of those in the higher and lower-risk areas; and measured compound risk as the presence of two or more (of 6) major risks for HIV.

RESULTS

Among participants in the higher-risk area, the frequency of compound risk was 15%, compared with 5% in the lower-risk area. Geographic cohesion in the higher-risk group was substantially higher than that in the lower-risk group, based on comparison of geographic distance and social distance, and on the extent of overlap of personal geographic range. The networks in the 2 areas were similar: both areas show highly interactive networks with similar degree distributions, and most measures of network attributes were virtually the same.

CONCLUSIONS

Our original hypothesis was supported in part. The higher and lower-risk groups differed appreciably with regard to risk and geographic cohesion, but were substantially the same with regard to network properties. These results suggest that a "minimum" network configuration may be required for maintenance of endemic transmission, but a particular prevalence level may be determined by factors related to risk, geography, and possibly other factors.

Saturation effects and the concurrency hypothesis: Insights from an analytic model

Sexual partnerships that overlap in time (concurrent relationships) may play a significant role in the HIV epidemic, but the precise effect is unclear. We derive edge-based compartmental models of disease spread in idealized dynamic populations with and without concurrency to allow for an investigation of its effects. Our models assume that partnerships change in time and individuals enter and leave the at-risk population. Infected individuals transmit at a constant per-partnership rate to their susceptible partners. In our idealized populations we find regions of parameter space where the existence of concurrent partnerships leads to substantially faster growth and higher equilibrium levels, but also regions in which the existence of concurrent partnerships has very little impact on the growth or the equilibrium. Additionally we find mixed regimes in which concurrency significantly increases the early growth, but has little effect on the ultimate equilibrium level. Guided by model predictions, we discuss general conditions under which concurrent relationships would be expected to have large or small effects in real-world settings. Our observation that the impact of concurrency saturates suggests that concurrency-reducing interventions may be most effective in populations with low to moderate concurrency.

The Interaction of Risk Network Structures and Virus Natural History in the Non-spreading of HIV Among People Who Inject Drugs in the Early Stages of the Epidemic

This article explores how social network dynamics may have reduced the spread of HIV-1 infection among people who inject drugs during the early years of the epidemic. Stochastic, discrete event, agent-based simulations are used to test whether a "firewall effect" can arise out of self-organizing processes at the actor level, and whether such an effect can account for stable HIV prevalence rates below population saturation. Repeated simulation experiments show that, in the presence of recurring, acute, and highly infectious outbreaks, micro-network structures combine with the HIV virus's natural history to reduce the spread of the disease. These results indicate that network factors likely played a significant role in the prevention of HIV infection within injection risk networks during periods of peak prevalence. They also suggest that social forces that disturb network connections may diminish the natural firewall effect and result in higher rates of HIV.

Gender asymmetry in concurrent partnerships and HIV prevalence

The structure of the sexual network of a population plays an essential role in the transmission of HIV. Concurrent partnerships, i.e. partnerships that overlap in time, are important in determining this network structure. Men and women may differ in their concurrent behavior, e.g. in the case of polygyny where women are monogamous while men may have concurrent partnerships. Polygyny has been shown empirically to be negatively associated with HIV prevalence, but the epidemiological impacts of other forms of gender-asymmetric concurrency have not been formally explored. Here we investigate how gender asymmetry in concurrency, including polygyny, can affect the disease dynamics. We use a model for a dynamic network where individuals may have concurrent partners. The maximum possible number of simultaneous partnerships can differ for men and women, e.g. in the case of polygyny. We control for mean partnership duration, mean lifetime number of partners, mean degree, and sexually active lifespan. We assess the effects of gender asymmetry in concurrency on two epidemic phase quantities (R₀ and the contribution of the acute HIV stage to R₀) and on the endemic HIV prevalence. We find that gender asymmetry in concurrent partnerships is associated with lower levels of all three epidemiological quantities, especially in the polygynous case. This effect on disease transmission can be attributed to changes in network structure, where increasing asymmetry leads to decreasing network connectivity.

Estimation of the Overall Treatment Effect in the Presence of Interference in Cluster-Randomized Trials of Infectious Disease Prevention

An issue that remains challenging in the field of causal inference is how to relax the assumption of no interference between units. Interference occurs when the treatment of one unit can affect the outcome of another, a situation which is likely to arise with outcomes that may depend on social interactions, such as occurrence of infectious disease. Existing methods to accommodate interference largely depend upon an assumption of “partial interference” – interference only within identifiable groups but not among them. There remains a considerable need for development of methods that allow further relaxation of the no-interference assumption. This paper focuses on an estimand that is the difference in the outcome that one would observe if the treatment were provided to all clusters compared to that outcome if treatment were provided to none – referred as the overall treatment effect. In trials of infectious disease prevention, the randomized treatment effect estimate will be attenuated relative to this overall treatment effect if a fraction of the exposures in the treatment clusters come from individuals who are outside these clusters. This source of interference – contacts sufficient for transmission that are with treated clusters – is potentially measurable. In this manuscript, we leverage epidemic models to infer the way in which a given level of interference affects the incidence of infection in clusters. This leads naturally to an estimator of the overall treatment effect that is easily implemented using existing software.

Sampling dynamic networks with application to investigation of HIV epidemic drivers

We propose a method for randomly sampling dynamic networks that permits isolation of the impact of different network features on processes that propagate on networks. The new methods permit uniform sampling of dynamic networks in ways that ensure that they are consistent with both a given cumulative network and with specified values for constraints on the dynamic network properties. Development of such methods is challenging because modifying one network property will generally tend to modify others as well. Methods to sample constrained dynamic networks are particularly useful in the investigation of network-based interventions that target and modify specific dynamic network properties, especially in settings where the whole network is unobservable and therefore many network properties are unmeasurable. We illustrate this method by investigating the incremental impact of changes in networks properties that are relevant for the spread of infectious diseases, such as concurrency in sexual relationships. Development of the method is motivated by the challenges that arise in investigating the role of HIV epidemic drivers due to the often limited information available about contact networks. The proposed methods for randomly sampling dynamic networks facilitate investigation of the type of network data that can best contribute to an understanding of the HIV epidemic dynamics as well as of the limitations of conclusions drawn in the absence of such information. Hence, the methods are intended to aid in the design and interpretation of studies of network-based interventions.

Self-reported sex partner dates for use in measuring concurrent sexual partnerships: correspondence between two assessment methods

Although prevalence of concurrent sexual partnerships is increasingly investigated as a driver of HIV epidemics, its measurement varies and its role in transmission dynamics remains contested. Relying on different methods of obtaining self-reported partnership histories may lead to significant differences in prevalence. This study examined the reliability of two methods for assessing dates of sex and the implications for measuring concurrent sexual partnerships. We conducted a cross-sectional reliability study using self-reported survey data from 650 women ages 18-65 years, recruited online nationwide for human papillomavirus natural history studies from 2007 to 2012. Intermethod reliability of first and last sex with the most recent partner was assessed using weighted kappa. Intraclass correlation coefficient was estimated for intramethod reliability across two consecutive questionnaires administered 4 months apart. Point prevalence of concurrent sexual partnerships at 6 months prior to the questionnaire date was similar between the two question formats (10.5 % for categorical and 10.9 % for continuous). The range between the minimum and maximum cumulative prevalence for 12 months was larger when using the categorical questions (17.0-29.6 % compared to 27.6-28.6 % using the continuous questions). Agreement between the two question formats was moderate for the date of first sex with the most recent partner (κ = 0.56, 95 % CI 0.48-0.64) and almost perfect for the date of last sex (κ = 0.93, 95 % CI 0.91-0.94). Longitudinal agreement for date of first sex was high for the continuous date question (ICC = 0.89, 95 % CI 0.86-0.92). Results of this reliability study can be used to inform the design of future studies of concurrent sexual partnerships and their association with HIV.

Impact of coverage-dependent marginal costs on optimal HPV vaccination strategies

The effectiveness of vaccinating males against the human papillomavirus (HPV) remains a controversial subject. Many existing studies conclude that increasing female coverage is more effective than diverting resources into male vaccination. Recently, several empirical studies on HPV immunization have been published, providing evidence of the fact that marginal vaccination costs increase with coverage. In this study, we use a stochastic agent-based modeling framework to revisit the male vaccination debate in light of these new findings. Within this framework, we assess the impact of coverage-dependent marginal costs of vaccine distribution on optimal immunization strategies against HPV. Focusing on the two scenarios of ongoing and new vaccination programs, we analyze different resource allocation policies and their effects on overall disease burden. Our results suggest that if the costs associated with vaccinating males are relatively close to those associated with vaccinating females, then coverage-dependent, increasing marginal costs may favor vaccination strategies that entail immunization of both genders. In particular, this study emphasizes the necessity for further empirical research on the nature of coverage-dependent vaccination costs.

What can mathematical models tell us about the relationship between circular migrations and HIV transmission dynamics?

Circular migrations are the periodic movement of individuals between multiple locations, observed in parts of sub-Saharan Africa. Relationships between circular migrations and HIV are complex, entailing interactions between migration frequency, partnership structure, and exposure to acute HIV infection. Mathematical modeling is a useful tool for understanding these interactions. Two modeling classes have dominated the HIV epidemiology and policy literature for the last decade: one a form of compartmental models, the other network models. We construct models from each class, using ordinary differential equations and exponential random graph models, respectively. Our analysis suggests that projected HIV prevalence is highly sensitive to the choice of modeling framework. Assuming initial equal HIV prevalence across locations, compartmental models show no association between migration frequency and HIV prevalence or incidence, while network models show that migrations at frequencies shorter than the acute HIV period predict greater HIV incidence and prevalence compared to longer migration periods. These differences are statistically significant when network models are extended to incorporate a requirement for migrant men's multiple partnerships to occur in different locations. In settings with circular migrations, commonly-used forms of compartmental models appear to miss key components of HIV epidemiology stemming from interactions of relational and viral dynamics.

SI infection on a dynamic partnership network: characterization of R0

We model the spread of an SI (Susceptible → Infectious) sexually transmitted infection on a dynamic homosexual network. The network consists of individuals with a dynamically varying number of partners. There is demographic turnover due to individuals entering the population at a constant rate and leaving the population after an exponentially distributed time. Infection is transmitted in partnerships between susceptible and infected individuals. We assume that the state of an individual in this structured population is specified by its disease status and its numbers of susceptible and infected partners. Therefore the state of an individual changes through partnership dynamics and transmission of infection. We assume that an individual has precisely n 'sites' at which a partner can be bound, all of which behave independently from one another as far as forming and dissolving partnerships are concerned. The population level dynamics of partnerships and disease transmission can be described by a set of (n +1)(n +2) differential equations. We characterize the basic reproduction ratio R0 using the next-generation-matrix method. Using the interpretation of R0 we show that we can reduce the number of states-at-infection n to only considering three states-at-infection. This means that the stability analysis of the disease-free steady state of an (n +1)(n +2)-dimensional system is reduced to determining the dominant eigenvalue of a 3 × 3 matrix. We then show that a further reduction to a 2 × 2 matrix is possible where all matrix entries are in explicit form. This implies that an explicit expression for R0 can be found for every value of n.

Gender inequality and HIV transmission: a global analysis

Introduction

The HIV pandemic disproportionately impacts young women. Worldwide, young women aged 15–24 are infected with HIV at rates twice that of young men, and young women alone account for nearly a quarter of all new HIV infections. The incommensurate HIV incidence in young – often poor – women underscores how social and economic inequalities shape the HIV epidemic. Confluent social forces, including political and gender violence, poverty, racism, and sexism impede equal access to therapies and effective care, but most of all constrain the agency of women.

Methods

HIV prevalence data was compiled from the 2010 UNAIDS Global Report. Gender inequality was assessed using the 2011 United Nations Human Development Report Gender Inequality Index (GII). Logistic regression models were created with predominant mode of transmission (heterosexual vs. MSM/IDU) as the dependent variable and GII, Muslim vs. non-Muslim, Democracy Index, male circumcision rate, log gross national income (GNI) per capita at purchasing power parity (PPP), and region as independent variables.

Results and discussion

There is a significant correlation between having a predominantly heterosexual epidemic and high gender inequality across all models. There is not a significant association between whether a country is predominantly Muslim, has a high/low GNI at PPP, has a high/low circumcision rate, and its primary mode of transmission. In addition, there are only three countries that have had a generalized epidemic in the past but no longer have one: Cambodia, Honduras, and Eritrea. GII data are available only for Cambodia and Honduras, and these countries showed a 37 and 34% improvement, respectively, in their Gender Inequality Indices between 1995 and 2011. During the same period, both countries reduced their HIV prevalence below the 1% threshold of a generalized epidemic. This represents limited but compelling evidence that improvements in gender inequality can lead to the abatement of generalized epidemics.

Conclusions

Gender inequality is an important factor in the maintenance – and possibly in the establishment of – generalized HIV epidemics. We should view improvements in gender inequality as part of a broader public health strategy.

Marital concurrency and HIV risk in 16 African countries

Research has identified sexual concurrency as a potential underlying driver of high HIV infection levels in sub-Saharan Africa, though few studies have explicitly examined the contribution of marital concurrency. Utilizing a multi-level model of Demographic and Health Surveys with HIV-biomarkers for sixteen African countries, this study assessed the relationship between an individual's HIV serostatus and rates of formal and informal marital concurrency (% polygamous unions, % extramarital partner past year) among married men and women. Mutually exclusive regional-level variables were constructed and modeled to test the contextual risk posed by living in a region with higher levels of formal and informal marital concurrency controlling for individual sexual partnerships and other covariates. Compared with regions where monogamous unions were more prevalent, the odds of having HIV were higher among individuals living in regions with more informal marital concurrency, but lower in regions with more polygamy, even accounting for individual-level sexual behavior. These results can help inform prevention policy and practice in sub-Saharan Africa.

A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks

We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey.

Prevalence and correlates of sexual partner concurrency among Australian gay men aged 18-39 years

Mathematical models predict higher rates of HIV and sexually transmitted infections (STIs) in populations with higher rates of concurrent sexual partnerships. Although gay men and other men who have sex with men (MSM) have disproportionately high rates of HIV/STIs, little is known about the prevalence and correlates of sexual concurrency in these populations. This paper reports findings from a national community-based survey of 1,034 Australian gay-identified men aged 18-39 years, who gave detailed information about their sexual partners over the past 12 months. In all, 237 (23 %) reported two or more concurrent sexual partners. For their most recent period of concurrency, 44 % reported three or more partners and 66 % reported unprotected sex with one or more of their partners. A multivariate logistic regression found sexual concurrency was significantly more likely among men on higher incomes (P = 0.02), who first had anal sex at a relatively young age (P = 0.03), and who reported a large number of partners in the past 12 months (P < 0.001). Age, education, HIV status, and other sociodemographic and sexual behavior variables were not significant correlates. However, men who reported sexual concurrency were significantly more likely to have been diagnosed with an STI in the past 12 months (P = 0.04). Findings from this study suggest sexual concurrency is common among younger Australian gay men. With many of these men not always using condoms, health agencies should consider the potential impact of concurrency on HIV/STI epidemics among gay men and other MSM.

Measuring and modelling concurrency

This article explores three critical topics discussed in the recent debate over concurrency (overlapping sexual partnerships): measurement of the prevalence of concurrency, mathematical modelling of concurrency and HIV epidemic dynamics, and measuring the correlation between HIV and concurrency. The focus of the article is the concurrency hypothesis - the proposition that presumed high prevalence of concurrency explains sub-Saharan Africa's exceptionally high HIV prevalence. Recent surveys using improved questionnaire design show reported concurrency ranging from 0.8% to 7.6% in the region. Even after adjusting for plausible levels of reporting errors, appropriately parameterized sexual network models of HIV epidemics do not generate sustainable epidemic trajectories (avoid epidemic extinction) at levels of concurrency found in recent surveys in sub-Saharan Africa. Efforts to support the concurrency hypothesis with a statistical correlation between HIV incidence and concurrency prevalence are not yet successful. Two decades of efforts to find evidence in support of the concurrency hypothesis have failed to build a convincing case.

Dynamic concurrent partnership networks incorporating demography

We introduce a population model that incorporates From a mathematical point of view we deal with continuous-time Markov chains at the individual level, with the interaction between individuals captured by a global variable describing opportunities for new partnerships. We show that for large time a stationary distribution is attained and we deduce various statistical features of that distribution, with particular attention for concurrency, i.e. the overlap in time of multiple partnerships of one and the same individual. Our ultimate motivation is to model the spread of sexually transmitted infections in the population, for which the present paper serves as a prelude.

Risk behaviours by type of concurrency among young people in three STI clinics in the United States

BACKGROUND

Concurrent sexual partnerships can increase sexually transmissible infections (STI) transmission on a population level. However, different concurrency types may be associated with differential risks for transmission. To investigate this, we describe the prevalence and correlates of four specific concurrency types.

METHODS

Between 2001 and 2004, 1098 young adults attending three STI clinics were interviewed and tested for STIs. Characteristics associated with concurrency types were identified using logistic regression.

RESULTS

Approximately one-third of respondents reported reactive (34%), transitional (36%), compensatory (32%) and experimental (26%) concurrency. Among men, reactive concurrency was associated with not identifying as heterosexual, drug use and having sex the same day as meeting a partner. Among women, reactive concurrency was associated with African-American race and having >3 lifetime partners. Transitional concurrency was associated with >3 lifetime partners for men and women. Among men, compensatory concurrency was associated with African-American race; among women, there were no associations with compensatory concurrency. Among men, experimental concurrency was associated with >3 lifetime partners and having sex the same day as meeting a partner. Among women, experimental concurrency was associated with not identifying as heterosexual, drug use and having sex the same day as meeting a partner.

CONCLUSIONS

All concurrency types were common in this population and each was associated with a set of demographic and risk factors. Reactive and experimental concurrency types were associated with other high-risk behaviours, such as drug use.

Determinants of sexual network structure and their impact on cumulative network measures

There are four major quantities that are measured in sexual behavior surveys that are thought to be especially relevant for the performance of sexual network models in terms of disease transmission. These are (i) the cumulative distribution of lifetime number of partners, (ii) the distribution of partnership durations, (iii) the distribution of gap lengths between partnerships, and (iv) the number of recent partners. Fitting a network model to these quantities as measured in sexual behavior surveys is expected to result in a good description of Chlamydia trachomatis transmission in terms of the heterogeneity of the distribution of infection in the population. Here we present a simulation model of a sexual contact network, in which we explored the role of behavioral heterogeneity of simulated individuals on the ability of the model to reproduce population-level sexual survey data from the Netherlands and UK. We find that a high level of heterogeneity in the ability of individuals to acquire and maintain (additional) partners strongly facilitates the ability of the model to accurately simulate the powerlaw-like distribution of the lifetime number of partners, and the age at which these partnerships were accumulated, as surveyed in actual sexual contact networks. Other sexual network features, such as the gap length between partnerships and the partnership duration, could-at the current level of detail of sexual survey data against which they were compared-be accurately modeled by a constant value (for transitional concurrency) and by exponential distributions (for partnership duration). Furthermore, we observe that epidemiological measures on disease prevalence in survey data can be used as a powerful tool for building accurate sexual contact networks, as these measures provide information on the level of mixing between individuals of different levels of sexual activity in the population, a parameter that is hard to acquire through surveying individuals.

HIV and concurrent sexual partnerships: modelling the role of coital dilution

BACKGROUND

The concurrency hypothesis asserts that high prevalence of overlapping sexual partnerships explains extraordinarily high HIV levels in sub-Saharan Africa. Earlier simulation models show that the network effect of concurrency can increase HIV incidence, but those models do not account for the coital dilution effect (non-primary partnerships have lower coital frequency than primary partnerships).

METHODS

We modify the model of Eaton et al (AIDS and Behavior, September 2010) to incorporate coital dilution by assigning lower coital frequencies to non-primary partnerships. We parameterize coital dilution based on the empirical work of Morris et al (PLoS ONE, December 2010) and others. Following Eaton et al, we simulate the daily transmission of HIV over 250 years for 10 levels of concurrency.

RESULTS

At every level of concurrency, our focal coital-dilution simulation produces epidemic extinction. Our sensitivity analysis shows that this result is quite robust; even modestly lower coital frequencies in non-primary partnerships lead to epidemic extinction.

CONCLUSIONS

In order to contribute usefully to the investigation of HIV prevalence, simulation models of concurrent partnering and HIV epidemics must incorporate realistic degrees of coital dilution. Doing so dramatically reduces the role that concurrency can play in accelerating the spread of HIV and suggests that concurrency cannot be an important driver of HIV epidemics in sub-Saharan Africa. Alternative explanations for HIV epidemics in sub-Saharan Africa are needed.