The Effect of Systemic Racism and Homophobia on Police Enforcement and Sexual and Emotional Violence among Sex Workers in East London: Findings from a Cohort Study.

There is extensive qualitative evidence of violence and enforcement impacting sex workers who are ethnically or racially minoritized, and gender or sexual minority sex workers, but there is little quantitative evidence. Baseline and follow-up data were collected among 288 sex workers of diverse genders (cis/transgender women and men and non-binary people) in London (2018-2019). Interviewer-administered and self-completed questionnaires included reports of rape, emotional violence, and (un)lawful police encounters. We used generalized estimating equation models (Stata vs 16.1) to measure associations between (i) ethnic/racial identity (Black, Asian, mixed or multiple vs White) and recent (6 months) or past police enforcement and (ii) ethnic/racial and sexual identity (lesbian, gay or bisexual (LGB) vs. heterosexual) with recent rape and emotional violence (there was insufficient data to examine the association with transgender/non-binary identities). Ethnically/racially minoritized sex workers (26.4%) reported more police encounters partly due to increased representation in street settings (51.4% vs 30.7% off-street, p = 0.002). After accounting for street setting, ethnically/racially minoritized sex workers had higher odds of recent arrest (adjusted odds ratio 2.8, 95% CI 1.3-5.8), past imprisonment (aOR 2.3, 95% CI 1.1-5.0), police extortion (aOR 3.3, 95% CI 1.4-7.8), and rape (aOR 3.6, 95% CI 1.1-11.5). LGB-identifying sex workers (55.4%) were more vulnerable to rape (aOR 2.4, 95% CI 1.1-5.2) and emotional violence. Sex workers identifying as ethnically/racially minoritized (aOR 2.1, 95% CI 1.0-4.5), LGB (aOR 2.0, 95% CI 1.0-4.0), or who use drugs (aOR 2.0, 95% CI 1.1-3.8) were more likely to have experienced emotional violence than white-identifying, heterosexual or those who did not use drugs. Experience of any recent police enforcement was associated with increased odds of rape (aOR 3.6, 95% CI 1.3-8.4) and emotional violence (aOR 4.9, 95% CI 1.8-13.0). Findings show how police enforcement disproportionately targets ethnically/racially minoritized sex workers and contributes to increased risk of rape and emotional violence, which is elevated among sexual and ethnically/racially minoritized workers.

A Bayesian approach to estimate changes in condom use from limited human immunodeficiency virus prevalence data.

Evaluation of large-scale intervention programmes against human immunodeficiency virus (HIV) is becoming increasingly important, but impact estimates frequently hinge on knowledge of changes in behaviour such as the frequency of condom use over time, or other self-reported behaviour changes, for which we generally have limited or potentially biased data. We employ a Bayesian inference methodology that incorporates an HIV transmission dynamics model to estimate condom use time trends from HIV prevalence data. Estimation is implemented via particle Markov chain Monte Carlo methods, applied for the first time in this context. The preliminary choice of the formulation for the time varying parameter reflecting the proportion of condom use is critical in the context studied, because of the very limited amount of condom use and HIV data available. We consider various novel formulations to explore the trajectory of condom use over time, based on diffusion-driven trajectories and smooth sigmoid curves. Numerical simulations indicate that informative results can be obtained regarding the amplitude of the increase in condom use during an intervention, with good levels of sensitivity and specificity performance in effectively detecting changes. The application of this method to a real life problem demonstrates how it can help in evaluating HIV interventions based on a small number of prevalence estimates, and it opens the way to similar applications in different contexts.

Assortative mixing as a source of bias in epidemiological studies of sexually transmitted infections: the case of smoking and human papillomavirus.

For studies examining risk factors of sexually transmitted infections (STIs), confounding can stem from characteristics of partners of study subjects, and persist after adjustment for the subjects' individual-level characteristics. Two conditions that can result in confounding by the subjects' partners are: (C1) partner choice is assortative by the risk factor examined and, (C2) sexual activity is associated with the risk factor. The objective of this paper is to illustrate the potential impact of the assortativity bias in studies examining STI risk factors, using smoking and human papillomavirus (HPV) as an example. We developed an HPV transmission-dynamic mathematical model in which we nested a cross-sectional study assessing the smoking-HPV association. In our base case, we assumed (1) no effect of smoking on HPV, and (2) conditions C1-C2 hold for smoking (based on empirical data). The assortativity bias caused an overestimation of the odds ratio (OR) in the simulated study after perfect adjustment for the subjects' individual-level characteristics (adjusted OR 1·51 instead of 1·00). The bias was amplified by a lower basic reproductive number (R 0), greater mixing assortativity and stronger association of smoking with sexual activity. Adjustment for characteristics of partners is needed to mitigate assortativity bias.

Who mixes with whom among men who have sex with men? Implications for modelling the HIV epidemic in southern India.

In India, the identity of men who have sex with men (MSM) is closely related to the role taken in anal sex (insertive, receptive or both), but little is known about sexual mixing between identity groups. Both role segregation (taking only the insertive or receptive role) and the extent of assortative (within-group) mixing are known to affect HIV epidemic size in other settings and populations. This study explores how different possible mixing scenarios, consistent with behavioural data collected in Bangalore, south India, affect both the HIV epidemic, and the impact of a targeted intervention. Deterministic models describing HIV transmission between three MSM identity groups (mostly insertive Panthis/Bisexuals, mostly receptive Kothis/Hijras and versatile Double Deckers), were parameterised with behavioural data from Bangalore. We extended previous models of MSM role segregation to allow each of the identity groups to have both insertive and receptive acts, in differing ratios, in line with field data. The models were used to explore four different mixing scenarios ranging from assortative (maximising within-group mixing) to disassortative (minimising within-group mixing). A simple model was used to obtain insights into the relationship between the degree of within-group mixing, R0 and equilibrium HIV prevalence under different mixing scenarios. A more complex, extended version of the model was used to compare the predicted HIV prevalence trends and impact of an HIV intervention when fitted to data from Bangalore. With the simple model, mixing scenarios with increased amounts of assortative (within-group) mixing tended to give rise to a higher R0 and increased the likelihood that an epidemic would occur. When the complex model was fit to HIV prevalence data, large differences in the level of assortative mixing were seen between the fits identified using different mixing scenarios, but little difference was projected in future HIV prevalence trends. An oral pre-exposure prophylaxis (PrEP) intervention was modelled, targeted at the different identity groups. For intervention strategies targeting the receptive or receptive and versatile MSM together, the overall impact was very similar for different mixing patterns. However, for PrEP scenarios targeting insertive or versatile MSM alone, the overall impact varied considerably for different mixing scenarios; more impact was achieved with greater levels of disassortative mixing.

Differences between seven measures of self-reported numbers of clients of female sex workers in southern India: implications for individual- and population-level analysis.

Quantifying sexual activity of sub-populations with high-risk sexual behaviour is important in understanding HIV epidemiology. This study examined inconsistency of seven outcomes measuring self-reported clients per month (CPM) of female sex workers (FSWs) in southern India and implications for individual/population-level analysis. Multivariate negative binomial regression was used to compare key social/environmental factors associated with each outcome. A transmission dynamics model was used to assess the impact of differences between outcomes on population-level FSW/client HIV prevalence. Outcomes based on 'clients per last working day' produced lower estimates than those based on 'clients per typical day'. Although the outcomes were strongly correlated, their averages differed by approximately two-fold (range 39.0-79.1 CPM). The CPM measure chosen did not greatly influence standard epidemiological 'risk factor' analysis. Differences across outcomes influenced HIV prevalence predictions. Due to this uncertainty, we recommend basing population-based estimates on the range of outcomes, particularly when assessing the impact of interventions.

Men who have sex with men and women in Bangalore, South India, and potential impact on the HIV epidemic.

OBJECTIVE: The aim of this study was to quantify differences in patterns of sexual behaviour among men who have sex with men and women (MSMW) compared with men who have sex with men only (MSMO), and to examine the extent to which bisexual behaviour may act as a bridge for introducing HIV infection into the general population. METHODS: A cross-sectional survey in Bangalore city in 2006, which sampled men seeking sex with men in public places and hammams (bath houses where transgender individuals sell sex to men). RESULTS: Among a sample of 357 men reporting same-sex behaviour; 41% also reported sex with a woman in the past year and 14% were currently married to a woman, only two of whom had informed their wives about having sex with men. Condom use was very inconsistent with all male partners, while 98% reported unprotected vaginal sex with their wives. MSMW reported lower rates of risky behaviour with other men than MSMO: fewer reported selling sex (17% vs 58%), or receptive anal sex with known (28% vs 70%) or unknown (30% vs 59%) non-commercial partners. CONCLUSION: Bisexual behaviour was common among men seeking sex with men sampled in this survey. Although MSMW reported lower rates of risky sexual behaviour with male partners than MSMO, inconsistent condom use with both male and female partners indicates a potential means of HIV transmission into the general population. HIV prevention programmes and services should reach bisexual men who potentially expose their male and female partners to HIV.

Incremental role of male circumcision on a generalised HIV epidemic through its protective effect against other sexually transmitted infections: from efficacy to effectiveness to population-level impact.

BACKGROUND: Male circumcision (MC) can reduce HIV acquisition. However, a better understanding of the indirect protective effect of MC on sexually transmitted infections (STIs) is required. OBJECTIVE: To assess the incremental benefits conferred by MC on HIV infection at the individual level in circumcision trials (no herd immunity effect) and at the population level (with herd immunity effect) owing to its protective effect against other STIs. METHODS: A dynamic stochastic model of HIV and STI infections in a Kenyan population was used to simulate the impact of MC offered to a few trial participants or to a large proportion of men in order to study the protective role of MC on HIV infection at the individual and population levels. RESULTS: Fewer than 20% of the HIV infections prevented in the circumcised arm of the circumcision trials (individual level) could be attributable to the efficacy of MC against STIs rather than against HIV. At the population level, MC can significantly reduce the prevalence of HIV, especially among men and women in the longer term. However, even at the population level, the long-term incremental impact of MC on HIV due to the protection against STI is modest (even if MC efficacy against the STI and STI prevalence was high). CONCLUSIONS: The protection of MC against STI contributes little to the overall effect of MC on HIV. Additional work is needed to determine whether, and under what conditions, the protective effect of MC efficacy against STIs can have a significant incremental benefit on the HIV epidemic.

Sexual identity and its contribution to MSM risk behavior in Bangaluru (Bangalore), India: the results of a two-stage cluster sampling survey.

In India, there are categories of MSM (hijras, kothis, double-deckers, panthis and bisexuals), which are generally associated with different HIV-risk behaviors. Our objective was to quantify differences across MSM identities (n = 357) and assess the extent they conform to typecasts that prevail in policy-orientated discourse. More feminine kothis (26%) and hijras (13%) mostly reported receptive sex, and masculine panthis (15%) and bisexuals (23%) insertive anal sex. However, behavior did not always conform to expectation, with 25% and 16% of the sample reporting both insertive and receptive anal intercourse with known and unknown noncommercial partners, respectively (p < 0.000). Although behavior often complied with stereotyped role and identity, male-with-male sexual practices were fluid. Reification of these categories in an intervention context may hinder our understanding of the differential HIV risk among MSM.

Evaluating large-scale HIV prevention interventions: study design for an integrated mathematical modelling approach.

BACKGROUND: There is an urgent need to evaluate HIV prevention interventions, thereby improving our understanding of what works, under what circumstances and what is cost effective. OBJECTIVES: To describe an integrated mathematical evaluation framework designed to assess the population-level impact of large-scale HIV interventions and applied in the context of Avahan, the Indian AIDS Initiative, in southern India. The Avahan Initiative is a large-scale HIV prevention intervention, funded by the Bill & Melinda Gates Foundation, which targets high-risk groups in selected districts of the six states most affected by the HIV/AIDS epidemic (Maharashtra, Karnataka, Tamil Nadu, Andhra Pradesh, Nagaland and Manipur) and along the national highways. METHODS: One important component of the monitoring and evaluation of Avahan relies on an integrated mathematical framework that combines empirical biological and behavioural data from different subpopulations in the intervention areas, with the use of tailor-made transmission dynamics models embedded within a Bayesian framework. RESULTS: An overview of the Avahan Initiative and the objectives of the monitoring and evaluation of the intervention is given. The rationale for choosing this evaluation design compared with other possible designs is presented, and the different components of the evaluation framework are described and its advantages and challenges are discussed, with illustrated examples. CONCLUSIONS: This is the first time such an approach has been applied on such a large scale. Lessons learnt from the CHARME project could help in the design of future evaluations of large-scale interventions in other settings, whereas the results of the evaluation will be of programmatic and public health relevance.

What is the achievable effectiveness of the India AIDS Initiative intervention among female sex workers under target coverage? Model projections from southern India.

BACKGROUND: The India AIDS Initiative (Avahan) prevention programme funded by the Bill and Melinda Gates Foundation aims to reduce HIV prevalence in high risk groups such as female and male sex workers and their clients, to limit HIV transmission in the general population. OBJECTIVES: To assess the potential effectiveness of the Avahan intervention at the level of coverage targeted, in different epidemiological settings in India. METHODS: A deterministic compartmental model of the transmission dynamics of HIV and two sexually transmitted infections, and sensitivity analysis techniques, were used, in combination with available behavioural and epidemiological data from Mysore and Bagalkot districts in the Indian state of Karnataka, to evaluate the syndromic sexually transmitted infection (STI) management (STI treatment), periodic presumptive treatment of STI (PPT), and condom components of the Avahan intervention targeted to female sex workers (FSW). RESULTS: If all components of the intervention reach target coverage (that is, PPT, STI treatment and condom use), the intervention is expected to prevent 22-35% of all new HIV infections in FSW and in the total population over 5 years in a low transmission setting like Mysore, and to be half as effective in high transmission settings such as Bagalkot. The results were sensitive to small variations in intervention coverage. The condom component alone is expected to prevent around 20% of all new HIV infections over 5 years in Mysore and around 6% for the STI component alone; compared with 7%-14% for the PPT component alone. Multivariate sensitivity analyses suggested that interventions may be more effective in settings with low FSW HIV prevalence and small FSW populations, whereas HIV prevalence was most influenced by sexual behaviour and condom use parameters for FSW. CONCLUSION: The Avahan intervention is expected to be effective. However, to be able to demonstrate effectiveness empirically in the different settings, it is important to achieve target coverage or higher, which in the case of PPT could take a number of years to achieve. These preliminary model predictions need to be validated with more detailed mathematical models, as better data on sexual behaviour, condom use, STI and HIV trends over time, and intervention coverage data accumulate over the course of the programme.

The impact of needle-exchange programs on the spread of HIV among injection drug users: a simulation study.

OBJECTIVE: To determine the impact of the implementation of a needle-exchange program (NEP) on the spread of human immunodeficiency virus (HIV) in an injection drug user (IDU) community. We conducted a Monte Carlo simulation study of a theoretical population of 10000 IDUs. The population was followed monthly from 1984 to 2000. HIV was assumed to be transmitted only by needle sharing. The NEP was introduced in 1989 and evaluated over a period of 11 years. The impacts of the proportion of the population attending the NEP, the risk level of IDUs attending the NEP, the reduction in needle-sharing frequency, and the number of new needle-sharing partners acquired at the NEP on prevalence and incidence of HIV were determined. Increasing the proportion of the population who always attend the NEP and eliminating needle-sharing incidents among IDUs who always attended the NEP were the most effective ways of reducing the spread of HIV. Attracting high-risk users instead of lower risk users to the NEP also reduced the spread of HIV, but to a lesser extent. NEPs are effective at reducing the spread of HIV; even under the worst case scenario of low risk users more likely to attend the NEP, one additional partner per month as a result of attending the NEP, and poor NEP attendance, the estimated prevalence was still less than that from the scenario without an NEP. Under our model, NEPs were shown to reduce the spread of HIV significantly. Efforts should be focused on getting as many IDUs as possible to become regular NEP attenders and stop sharing needles rather than partially reducing the frequency of sharing by a larger number of IDUs.

The impact of HIV epidemic phases on the effectiveness of core group interventions: insights from mathematical models.

Mathematical models have highlighted the disproportionate contribution of core group transmitters to the spread of sexually transmitted diseases. Because the effectiveness of interventions varies with time, it has been suggested that epidemic phases should be considered in the design of prevention strategies. This study aimed to examine the impact of HIV epidemic phases on the effectiveness of HIV interventions based on gonorrhoea screening and condom use, targeted to core groups. The results are based on a mathematical model of gonorrhoea and HIV transmission in a relatively slow spreading HIV epidemic using Cotonou (Benin) as an example. For epidemics with a low reproductive potential modest core group interventions can significantly reduce HIV incidence and prevalence. As the epidemic matures, effective interventions should also incorporate core and non-core populations. For epidemics with a high reproductive potential, core group interventions are necessary but not sufficient to have a rapid and large scale impact. A more general population approach is also needed early in the epidemic. Epidemic phases are also important in the evaluation of prevention strategies.

Prevalence of Chlamydia trachomatis and Neisseria gonorrhoeae among at-risk women, young sex workers, and street youth attending community organizations in Quebec City, Canada.

BACKGROUND: Despite a relatively recent decline in the global incidence of Chlamydia trachomatis and Neisseria gonorrhoeae it seems that some segments of the population such as street youth, sex workers, and individuals with social problems or delinquent behavior could be part of a core group for STDs. These persons may be reluctant to undergo STD diagnosis in traditional medical settings. GOALS: To determine the prevalence of C trachomatis and N gonorrhoeae infection using polymerase chain reaction on urine samples among subjects attending an anonymous HIV testing clinic and four community organizations in Quebec City, and to identify associated risk factors. STUDY DESIGN: A cross-sectional study of 626 street youth, sex workers, and women with social problems or delinquent behavior was conducted. RESULTS: The prevalences of N gonorrhoeae and C trachomatis were, respectively, 1.1% (95% CI, 0.5%--2.3%) and 5.8% (95% CI, 4.1%--7.9%). No significant difference was found between men and women, but the sexually transmitted disease (STD) prevalence was much higher in subjects younger than 20 years: 11.4% versus 3.6% (P < 0.01). In a logistic regression model, factors independently associated with STD infection were age younger than 20 years (OR, 2.6; P = 0.007), occasional sex partners (OR, 2.9; P = 0.007), and injection of drugs (OR, 2.8; P = 0.002) in the preceding 6 months. CONCLUSIONS: A moderate STD prevalence was found in the study population. The prevalence, however, can be considered high (>10%) among street youth and young sex workers. Providing community-based STD screening and treatment services appear to be an efficient method for reaching these high-risk groups.

Some methodological issues in the study of sexual networks: from model to data to model.

BACKGROUND: Mixing between sexual activity classes is an important determinant of sexually transmitted disease transmission. However, attempts to estimate sexual mixing patterns in the field remain limited partly because of practical and methodological difficulties. GOAL: To evaluate and identify appropriate sampling schemes to estimate the mixing pattern between sexual activity classes from large population networks with one or more components. STUDY DESIGN: The study is based on simulations of large population networks with various structural characteristics. A variety of snowball sampling schemes are applied to these networks and are evaluated by the quality of the mixing matrix estimates that they produce. RESULTS AND CONCLUSIONS: Unbiased estimation of mixing patterns (global assortativity, within-group mixing of the lowest activity classes, within-group mixing of the highest activity classes) from large population networks is possible with a snowball sampling design in which the initial sample of index cases is drawn from the general population, all partners of the index case are recruited, and only one generation of partners are traced (one cycle). Simulation techniques proved useful in addressing complex methodological issues in situations where analytic results are difficult to obtain.

Complementary hypothesis concerning the community sexually transmitted disease mass treatment puzzle in Rakai, Uganda.

OBJECTIVES: To study the dynamics of a mass treatment programme for sexually transmitted diseases (STD) on prevalence of STD and HIV incidence in order to help explain the results of the STD mass treatment community trial in Rakai, Uganda. METHODS: The analysis is based on simulations of STD mass treatment interventions using a deterministic model describing the course of STD and HIV transmission over time and incorporating demographic, biological and behavioural parameters. The mass intervention modelled mimics that used in the Rakai community trial. RESULTS: Mass treatment decreases STD prevalence to a very low level compared with baseline but is unsuccessful at eradicating the infection. STD prevalences return to baseline fairly rapidly after each round of mass treatment. Under different realistic scenarios, the fraction of HIV cases prevented by STD mass treatment assuming uniform 80% coverage of high- and low-risk groups, over the 20-month period following the first round of treatment, was greater than 35%. If, however, differential coverage is assumed, for example that while the total coverage is still 80%, only 40 or 25% of those at high risk are treated, the HIV preventable fraction is reduced, to 19 and 15% respectively (undetectable given the statistical power of the study). The tremendous impact of differential coverage can also be observed even in the early stage of the HIV epidemic. CONCLUSIONS: In the Rakai trial, mass treatment may have had an effect, although transient, on all STD prevalences, which could have had positive repercussions for HIV incidence. This modelling exercise suggests that although an 80% coverage appears high, the differential coverage of low- and high-risk populations may seriously impair our ability to test the STD-HIV interaction hypothesis.

Simulation studies of phase III clinical trials to test the efficacy of a candidate HIV-1 vaccine.

One question of particular importance in phase III HIV vaccine trials is the choice of efficacy measure (EM) to validly and precisely estimate the true vaccinal efficacy. Traditional EMs, based on hazard rate ratio (HRR) or cumulative incidence ratio (CIR) are time-sensitive to mode of vaccine action and population heterogeneities. Through Monte-Carlo simulation, the performance of HRR and CIR based EMs are examined across different trial designs and vaccine and population characteristics. A new EM based on log-spline hazard regression (HARE) is proposed. Given that vaccinal properties (mode of action, time-lag, waning) are unknown a priori, appropriate selection of EM is problematic, and HRR and CIR can be unreliable to estimate the true maximum efficacy of candidate products. Non-random sexual mixing can exacerbate biases in HRR and CIR. HARE can offer valid estimation across different modes of vaccine action and in presence of frailty effects, contrary to its traditional counterparts. Our simulation studies highlight the weaknesses of widely used EMs while offering guidelines for trial design and suggesting new avenues for statistical analysis.

Some important issues in the planning of phase III HIV vaccine efficacy trials.

Given that interesting HIV vaccine candidates, including live preparations and DNA plasmids, exist and that the first phase III vaccine (AIDSVAX) testing is due to begin this summer, 1998, in the U.S., adequately addressing trial preparedness is a pressing issue. Despite double-blind randomized controlled clinical trial design, there may be difficulties with interpretation and use of the usual measures of vaccinal efficacy and calculation of sample size. Difficulties arise from vaccine characteristics (e.g. mode of action, time-lag, waning) and population heterogeneities (e.g. differences in susceptibility, sexual behaviour, mixing preferences) causing frailty effects that can exacerbate bias and time-dependent effects already known to exist in simple cases. Since vaccine properties, particularly mode of action, are unlikely to be known before the onset of clinical trials, choosing an efficacy measure and the associated analyses and sample size calculations will be problematic. Interim analyses designed to decide whether a study will be prolonged may be tenuous if based on a time-dependent measure and will influence sample size determination. Despite shortcomings, general recommendations can be made to minimise pernicious effects. The objectives of this paper are principally to review the current state of knowledge of the different stages in the preparation of large phase III HIV vaccine efficacy trials, the methodological difficulties related to their design, and the analysis of data collected from them. Mathematical models and trial simulations are used to demonstrate that further research is necessary to study the behaviour of vaccine efficacy measures under heterogeneous conditions of population, vaccine action, and trial design and identify a time-independent efficacy measure. Alternative methods to validate sample size calculations have to be developed in older to reduce the chances of unnecessary economic and human cost in phase III HIV vaccine trials.

Highlights of the sexual activity of the heterosexual population in the province of Quebec.

OBJECTIVES: To describe and quantify the level of sexual activity of the heterosexually active population of Quebec. METHODS: The data analysed included 2889 heterosexually active individuals aged 15-60 (agemed = 32) from a 1996-7 survey on the sexual lifestyles of the general population of Quebec. Various probability distributions were studied to assess their capacity to describe and quantify the lifetime and yearly numbers of sexual partners of the sampled population. To estimate the annual rates of new partner acquisition, a generalised linear model was fitted to the number of lifetime sexual partners as a function of age, years of sexual activity, and sex. RESULTS: The mean and variance of the number of lifetime sexual partners for men (mean = 11, s2 = 163) is higher than for women (mean = 6, s2 = 72). The negative binomial and lognormal probability distributions give the most adequate fit to the lifetime number of partners for both agglomerated and stratified (by sex and age) data. The estimated annual rates of new partner acquisition provide two important results for prevention: (1) the first year of sexual activity represents the highest annual rate of new partner acquisition independent of age, (2) annual rates of new partner acquisitions increase through mid-life (ages 40-50) combined with a decrease in condom use. CONCLUSION: Problems caused by the use of large categories in the estimation of mean and variance cannot totally be overcome by fitting probability distributions to the empirical data despite good fits. Furthermore, we believe that adequate estimates of the annual rate of new partner acquisition should be a better measure of the risk of HIV infection than the number of partners since the first is a measure of incidence while the second is a measure of prevalence.

Mathematical models of disease transmission: a precious tool for the study of sexually transmitted diseases.

This paper is an introduction to the mathematical epidemiology of sexually transmitted diseases (STDs) and its application to public health. After a brief introduction to transmission dynamics models, the construction of a deterministic compartmental mathematical model of HIV transmission in a population is described. As a background to STD transmission dynamics, basic reproductive rate, intergroup mixing, rate of partner change, and duration of infectivity are discussed. Use of the models illustrates the effect of sexual mixing (proportionate to highly assortative), of preventive intervention campaigns, and of HIV-chlamydia interaction on HIV prevalence in the different population groups. In particular, planned prevention campaigns can benefit the targeted intervention group but surprisingly can be disadvantageous for the general population. Through examples, mathematical models are shown to be helpful in our understanding of disease transmission, in interpretation of observed trends, in planning of prevention strategies, and in guiding data collection.