No HIV stage is dominant in driving the HIV epidemic in sub-Saharan Africa

Understanding dynamics and overlapping epidemiologies of HIV, HSV-2, chlamydia, gonorrhea, and syphilis in sexual networks of men who have sex with men

Introduction

We aimed to investigate the overlapping epidemiologies of human immunodeficiency virus (HIV), herpes simplex virus type 2 (HSV-2), chlamydia, gonorrhea, and syphilis in sexual networks of men who have sex with men (MSM), and to explore to what extent the epidemiology of one sexually transmitted infection (STI) relates to or differs from that of another STI.

Methods

An individual-based Monte Carlo simulation model was employed to simulate the concurrent transmission of STIs within diverse sexual networks of MSM. The model simulated sexual partnering, birth, death, and STI transmission within each specific sexual network. The model parameters were chosen based on the current knowledge and understanding of the natural history, transmission, and epidemiology of each considered STI. Associations were measured using the Spearman's rank correlation coefficient (SRCC) and maximal information coefficient (MIC).

Results

A total of 500 sexual networks were simulated by varying the mean and variance of the number of partners for both short-term and all partnerships, degree correlation, and clustering coefficient. HSV-2 had the highest current infection prevalence across the simulations, followed by HIV, chlamydia, syphilis, and gonorrhea. Threshold and saturation effects emerged in the relationship between STIs across the simulated networks, and all STIs demonstrated moderate to strong associations. The strongest current infection prevalence association was between HIV and gonorrhea, with an SRCC of 0.84 (95% CI: 0.80-0.87) and an MIC of 0.81 (95% CI: 0.74-0.88). The weakest association was between HSV-2 and syphilis, with an SRCC of 0.54 (95% CI: 0.48-0.59) and an MIC of 0.57 (95% CI, 0.49-0.65). Gonorrhea exhibited the strongest associations with the other STIs while syphilis had the weakest associations. Across the simulated networks, proportions of the population with zero, one, two, three, four, and five concurrent STI infections were 48.6, 37.7, 11.1, 2.4, 0.3, and < 0.1%, respectively. For lifetime exposure to these infections, these proportions were 13.6, 21.0, 22.9, 24.3, 13.4, and 4.8%, respectively.

Conclusion

STI epidemiologies demonstrate substantial overlap and associations, alongside nuanced differences that shape a unique pattern for each STI. Gonorrhea exhibits an "intermediate STI epidemiology," reflected by the highest average correlation coefficient with other STIs.

A simple algorithm for selecting cases to investigate acute and early HIV infections in low- and middle-income countries

We documented the outcome of an over 10-year (2011-2021) effort to diagnose acute and early HIV infections (AEHI) in an Infectious Diseases Outpatient Clinic with limited resources. Of a total of 132, 119 HIV-RNA tests were performed from 2017 to 2020, 12 cases were identified, using a simple algorithm: risk exposure of 6 weeks or less before the visit and/or symptoms compatible with acute retroviral syndrome 7-30 days after exposure and/or undetermined 3rd generation rapid diagnostic test or serology. AEHI diagnoses varied from 2.4% among asymptomatic to 25% for undetermined serology cases using this simple screening applicable to different settings.

Analytic Characterization of the Herpes Simplex Virus Type 2 Epidemic in the United States, 1950-2050

Background

We analytically characterized the past, present, and future levels and trends of the national herpes simplex virus type 2 (HSV-2) epidemic in the United States.

Methods

A population-level mathematical model was constructed to describe HSV-2 transmission dynamics and was fitted to the data series of the National Health and Nutrition Examination Survey.

Results

Over 1950–2050, antibody prevalence (seroprevalence) increased rapidly from 1960, peaking at 19.9% in 1983 in those aged 15–49 years, before reversing course to decline to 13.2% by 2020 and 8.5% by 2050. Incidence rate peaked in 1971 at 11.9 per 1000 person-years, before declining by 59% by 2020 and 70% by 2050. Annual number of new infections peaked at 1 033 000 in 1978, before declining to 667 000 by 2020 and 600 000 by 2050. Women were disproportionately affected, averaging 75% higher seroprevalence, 95% higher incidence rate, and 71% higher annual number of infections. In 2020, 78% of infections were acquired by those 15–34 years of age.

Conclusions

The epidemic has undergone a major transition over a century, with the greatest impact in those 15–34 years of age. In addition to 47 million prevalent infections in 2020, high incidence will persist over the next 3 decades, adding >600 000 new infections every year.

Acute and early HIV infection screening among men who have sex with men, a systematic review and meta-analysis

INTRODUCTION

Screening for acute and early HIV infections (AEHI) among men who have sex with men (MSM) remains uncommon in sub-Saharan Africa (SSA). Yet, undiagnosed AEHI among MSM and subsequent failure to link to care are important drivers of the HIV epidemic. We conducted a systematic review and meta-analysis of AEHI yield among MSM mobilized for AEHI testing; and assessed which risk factors and/or symptoms could increase AEHI yield in MSM.

METHODS

We systematically searched four databases from their inception through May 2020 for studies reporting strategies of mobilizing MSM for testing and their AEHI yield, or risk and/or symptom scores targeting AEHI screening. AEHI yield was defined as the proportion of AEHI cases among the total number of visits. Study estimates for AEHI yield were pooled using random effects models. Predictive ability of risk and/or symptom scores was expressed as the area under the receiver operator curve (AUC).

RESULTS

Twenty-two studies were identified and included a variety of mobilization strategies (eight studies) and risk and/or symptom scores (fourteen studies). The overall pooled AEHI yield was 6.3% (95% CI, 2.1 to 12.4; I2  = 94.9%; five studies); yield varied between studies using targeted strategies (11.1%; 95% CI, 5.9 to 17.6; I2  = 83.8%; three studies) versus universal testing (1.6%; 95% CI, 0.8 to 2.4; two studies). The AUC of risk and/or symptom scores ranged from 0.69 to 0.89 in development study samples, and from 0.51 to 0.88 in validation study samples. AUC was the highest for scores including symptoms, such as diarrhoea, fever and fatigue. Key risk score variables were age, number of sexual partners, condomless receptive anal intercourse, sexual intercourse with a person living with HIV, a sexually transmitted infection, and illicit drug use. No studies were identified that assessed AEHI yield among MSM in SSA and risk and/or symptom scores developed among MSM in SSA lacked validation.

CONCLUSIONS

Strategies mobilizing MSM for targeted AEHI testing resulted in substantially higher AEHI yields than universal AEHI testing. Targeted AEHI testing may be optimized using risk and/or symptom scores, especially if scores include symptoms. Studies assessing AEHI yield and validation of risk and/or symptom scores among MSM in SSA are urgently needed.

A novel Bayesian approach to predicting reductions in HIV incidence following increased testing interventions among gay, bisexual and other men who have sex with men in Vancouver, Canada

Increasing HIV testing rates among high-risk groups should lead to increased numbers of cases being detected. Coupled with effective treatment and behavioural change among individuals with detected infection, increased testing should also reduce onward incidence of HIV in the population. However, it can be difficult to predict the strengths of these effects and thus the overall impact of testing. We construct a mathematical model of an ongoing HIV epidemic in a population of gay, bisexual and other men who have sex with men. The model incorporates different levels of infection risk, testing habits and awareness of HIV status among members of the population. We introduce a novel Bayesian analysis that is able to incorporate potentially unreliable sexual health survey data along with firm clinical diagnosis data. We parameterize the model using survey and diagnostic data drawn from a population of men in Vancouver, Canada. We predict that increasing testing frequency will yield a small-scale but long-term impact on the epidemic in terms of new infections averted, as well as a large short-term impact on numbers of detected cases. These effects are predicted to occur even when a testing intervention is short-lived. We show that a short-lived but intensive testing campaign can potentially produce many of the same benefits as a campaign that is less intensive but of longer duration.

Characterizing the transitioning epidemiology of herpes simplex virus type 1 in the USA: model-based predictions

BACKGROUND

Herpes simplex virus type 1 (HSV-1) is a prevalent lifelong infection that appears to be undergoing an epidemiologic transition in the United States (US). Using an analytical approach, this study aimed to characterize HSV-1 transitioning epidemiology and estimate its epidemiologic indicators, past, present, and future.

METHODS

An age-structured mathematical model was developed to describe HSV-1 transmission through oral and sexual modes of transmission. The model was fitted to the National Health and Nutrition Examination Surveys, 1976-2016 data series.

RESULTS

HSV-1 seroprevalence was projected to decline from 61.5% in 1970 to 54.8% in 2018, 48.5% in 2050, and 42.0% in 2100. In < 3 decades, seroprevalence declined by > 30% for those aged 0-19 years, but < 5% for those aged > 60. Meanwhile, the number of new infections per year (oral and genital) was persistent at 2,762,000 in 1970, 2,941,000 in 2018, 2,933,000 in 2050, and 2,960,000 in 2100. Of this total, genital acquisitions contributed 252,000 infections in 1970, 410,000 in 2018, 478,000 in 2050, and 440,000 in 2100-a quarter of which are symptomatic with clinical manifestations. For those aged 15-49 years, nearly 25% of incident infections are genital. Most genital acquisitions (> 85%) were due to oral-to-genital transmission through oral sex, as opposed to genital-to-genital transmission through sexual intercourse.

CONCLUSION

HSV-1 epidemiology is undergoing a remarkable transition in the US, with less exposure in childhood and more in adulthood, and less oral but more genital acquisition. HSV-1 will persist as a widely prevalent infection, with ever-increasing genital disease burden.

Use of routine HIV testing data for early detection of emerging HIV epidemics in high-risk subpopulations: A concept demonstration study

Introduction

HIV epidemics in hard-to-reach high-risk subpopulations are often discovered years after epidemic emergence in settings with poor surveillance infrastructure. Using hypothesis-generation modeling, we aimed to investigate and demonstrate the concept of using routine HIV testing data to identify and characterize hidden epidemics in high-risk subpopulations. We also compared this approach to surveillance based on AIDS case notifications.

Methods

A deterministic mathematical model was developed to simulate an emerging HIV epidemic in a high-risk subpopulation. A stochastic Monte Carlo simulation was implemented on the total population to simulate the sampling process of generating routine HIV testing data. Epidemiological measures were estimated on the simulated epidemic and on the generated testing sample. Sensitivity analyses were conducted on the results.

Results

In the simulated epidemic, HIV prevalence saturated at 32% in the high-risk subpopulation and at 0.33% in the total population. The epidemic started its emerging-epidemic phase 28 years after infection introduction, and saturated 67 years after infection introduction. In the simulated HIV testing sample, a significant time trend in prevalence was identified, and the generated metrics of epidemic emergence and saturation were similar to those of the simulated epidemic. The epidemic was identified 4.0 (95% CI 3.4–4.6) years after epidemic emergence using routine HIV testing, but 29.7 (95% CI 15.8–52.1) years after emergence using AIDS case notifications. In the sensitivity analyses, none of the sampling biases affected the conclusion of an emerging epidemic, but some affected the estimated epidemic growth rate.

Conclusions

Routine HIV testing data provides a tool to identify and characterize hidden and emerging epidemics in high-risk subpopulations. This approach can be specially useful in resource-limited settings, and can be applied alone, or along with other complementary data, to provide a meaningful characterization of emerging but hidden epidemics.

Does infection with Chlamydia trachomatis induce long-lasting partial immunity? Insights from mathematical modelling

OBJECTIVES

To explore whether existence of long-lasting partial immunity against reinfection with Chlamydia trachomatis is necessary to explain C. trachomatis prevalence patterns by age and sexual risk, and to provide a plausible estimate for the effect size, defined here as a reduction in susceptibility to reinfection.

METHODS

A population-based mathematical model was constructed to describe C. trachomatis natural history and transmission dynamics by age and sexual risk. The model was parameterised using natural history, and epidemiological and sexual behaviour data, and applied for UK and US data. Sensitivity analyses were conducted to assess the robustness of predictions to variations in model structure and to examine the impact of alternative assumptions for the mechanism underlying partial immunity.

RESULTS

Partial immunity against reinfection was found necessary to explain observed C. trachomatis prevalence patterns by age and sexual risk. The reduction in susceptibility to reinfection was estimated at 93% using UK data (95% uncertainty interval (UI)=88%-97%) and at 67% using US data (95% UI=24%-88%). The model-structure sensitivity analyses affirmed model predictions. The immunity-mechanism sensitivity analyses suggested a mechanism of susceptibility reduction against reinfection or a mechanism of infectious-period duration reduction upon reinfection.

CONCLUSIONS

A strong long-lasting partial immunity against C. trachomatis reinfection should be present to explain observed prevalence patterns. The mechanism of immunity could be either a reduction in susceptibility to reinfection or a reduction in duration of infection on reinfection. C. trachomatis infection appears to naturally elicit a strong long-lasting immune response, supporting the concept of vaccine development.

Counting Down the 2020 Goals for 9 Neglected Tropical Diseases: What Have We Learned From Quantitative Analysis and Transmission Modeling?

The control of neglected tropical diseases (NTDs) has received huge investment in recent years, leading to large reductions in morbidity. In 2012, the World Health Organization set ambitious targets for eliminating many of these diseases as a public health problem by 2020, an aspiration that was supported by donations of treatments, intervention materials, and funding committed by a broad partnership of stakeholders in the London Declaration on NTDs. Alongside these efforts, there has been an increasing role for quantitative analysis and modeling to support the achievement of these goals through evaluation of the likely impact of interventions, the factors that could undermine these achievements, and the role of new diagnostics and treatments in reducing transmission. In this special issue, we aim to summarize those insights in an accessible way. This article acts as an introduction to the special issue, outlining key concepts in NTDs and insights from modeling as we approach 2020.

Temporal evolution of HIV sero-discordancy patterns among stable couples in sub-Saharan Africa

INTRODUCTION

Objective was to examine the temporal variation of HIV sero-discordancy in select representative countries (Kenya, Lesotho, Mali, Niger, Tanzania, and Zimbabwe) in sub-Saharan Africa at different HIV epidemic scales. A sero-discordant couple is defined as a stable couple (SC) in which one partner is HIV-positive while the other is HIV-negative.

METHODS

A deterministic compartmental mathematical model was constructed to describe HIV transmission dynamics. The model was pair-based, that is explicitly modeling formation of SCs and infection dynamics in both SCs and in single individuals. The model accommodated for different forms of infection statuses in SCs. Using population-based nationally-representative epidemiologic and demographic input data, historical (1980-2014) and future (2015-2030) trends of sero-discordancy and other demographic and epidemiologic indicators were projected throughout HIV epidemic phases.

RESULTS

As the epidemics emerged, about 90% of SCs affected by HIV were sero-discordant. This proportion declined to 45%-88% at epidemic peak and stabilized as the epidemics started their natural decline. The largest reductions in sero-discordancy were in high HIV-prevalence countries. As the epidemics further declined with antiretroviral therapy (ART) scale-up, the proportion of sero-discordant couples among HIV-affected couples was projected to increase to 70%-92% by 2030. The proportion of sero-discordant couples among all SCs increased as the epidemics emerged and evolved, then peaked at 2%-20% as the epidemics peaked, and then declined as the epidemics declined to reach 0.3%-16% by 2030.

CONCLUSIONS

Sero-discordancy patterns varied with the evolution of the epidemics, and were affected by both epidemic phase and scale. The largest variations were found in high HIV-prevalence countries. The fraction of stable couples that are sero-discordant, as opposed to being sero-concordant positive, was projected to increase with ART scale-up and further HIV incidence decline over the coming two decades. These findings inform strategic planning and resource allocation for interventions among sero-discordant couples.

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.

Estimating the annual risk of HIV transmission within HIV sero-discordant couples in sub-Saharan Africa

OBJECTIVE

To estimate the annual risk of HIV transmission (ϕ) within HIV sero-discordant couples in 23 countries in sub-Saharan Africa (SSA), by utilizing newly available national population-based data and accounting for factors known to potentially affect this estimation.

METHODS

We used a recently developed pair-based mathematical model that accommodates for HIV-dynamics temporal variation, sexual risk-behavior heterogeneity, and antiretroviral therapy (ART) scale-up.

RESULTS

Estimated country-specific ϕ (in absence of ART) ranged between 4.2% (95% uncertainty interval (UI): 1.9%-6.3%) and 47.4% (95% UI: 37.2%-69.0%) per person-year (ppy), with a median of 12.4%. ϕ was strongly associated with HIV prevalence, with a Pearson correlation coefficient of 0.92, and was larger in high- versus low-HIV-prevalence countries. ϕ increased by 1.31% (95% confidence interval: 1.00%-1.55%) ppy for every 1% increase in HIV prevalence.

CONCLUSIONS

ϕ estimates were similar to earlier estimates, and suggested considerable heterogeneity in HIV infectiousness across SSA. This heterogeneity may explain, partly, the differences in epidemic scales.

Sexual network drivers of HIV and herpes simplex virus type 2 transmission

OBJECTIVES

HIV and herpes simplex virus type 2 (HSV-2) infections are sexually transmitted and propagate in sexual networks. Using mathematical modeling, we aimed to quantify effects of key network statistics on infection transmission, and extent to which HSV-2 prevalence can be a proxy of HIV prevalence.

DESIGN/METHODS

An individual-based simulation model was constructed to describe sex partnering and infection transmission, and was parameterized with representative natural history, transmission, and sexual behavior data. Correlations were assessed on model outcomes (HIV/HSV-2 prevalences) and multiple linear regressions were conducted to estimate adjusted associations and effect sizes.

RESULTS

HIV prevalence was one-third or less of HSV-2 prevalence. HIV and HSV-2 prevalences were associated with a Spearman's rank correlation coefficient of 0.64 (95% confidence interval: 0.58-0.69). Collinearities among network statistics were detected, most notably between concurrency versus mean and variance of number of partners. Controlling for confounding, unmarried mean/variance of number of partners (or alternatively concurrency) were the strongest predictors of HIV prevalence. Meanwhile, unmarried/married mean/variance of number of partners (or alternatively concurrency), and clustering coefficient were the strongest predictors of HSV-2 prevalence. HSV-2 prevalence was a strong predictor of HIV prevalence by proxying effects of network statistics.

CONCLUSION

Network statistics produced similar and differential effects on HIV/HSV-2 transmission, and explained most of the variation in HIV and HSV-2 prevalences. HIV prevalence reflected primarily mean and variance of number of partners, but HSV-2 prevalence was affected by a range of network statistics. HSV-2 prevalence (as a proxy) can forecast a population's HIV epidemic potential, thereby informing interventions.

Modelling infectious diseases with relapse: a case study of HSV-2

Background

Herpes Simplex Virus Type 2 (HSV-2) is one of the most common sexually transmitted diseases. Although there is still no licensed vaccine for HSV-2, a theoretical investigation of the potential effects of a vaccine is considered important and has recently been conducted by several researchers. Although compartmental mathematical models were considered for each special case in the previous studies, as yet there are few global stability results.

Results

In this paper, we formulate a multi-group SVIRI epidemic model for HSV-2, which enables us to consider the effects of vaccination, of waning vaccine immunity, and of infection relapse. Since the number of groups is arbitrary, our model can be applied to various structures such as risk, sex, and age group structures. For our model, we define the basic reproduction number ℜ₀ and prove that if ℜ₀≤1, then the disease-free equilibrium is globally asymptotically stable, whereas if ℜ₀>1, then the endemic equilibrium is so. Based on this global stability result, we estimate ℜ₀ for HSV-2 by applying our model to the risk group structure and using US data from 2001 to 2014. Through sensitivity analysis, we find that ℜ₀ is approximately in the range of 2-3. Moreover, using the estimated parameters, we discuss the optimal vaccination strategy for the eradication of HSV-2.

Conclusions

Through discussion of the optimal vaccination strategy, we come to the following conclusions. (1) Improving vaccine efficacy is more effective than increasing the number of vaccines. (2) Although the transmission risk in female individuals is higher than that in male individuals, distributing the available vaccines almost equally between female and male individuals is more effective than concentrating them within the female population.

Clinical and public health implications of acute and early HIV detection and treatment: a scoping review

INTRODUCTION

The unchanged global HIV incidence may be related to ignoring acute HIV infection (AHI). This scoping review examines diagnostic, clinical, and public health implications of identifying and treating persons with AHI.

METHODS

We searched PubMed, in addition to hand-review of key journals identifying research pertaining to AHI detection and treatment. We focused on the relative contribution of AHI to transmission and the diagnostic, clinical, and public health implications. We prioritized research from low- and middle-income countries (LMICs) published in the last fifteen years.

RESULTS AND DISCUSSION

Extensive AHI research and limited routine AHI detection and treatment have begun in LMIC. Diagnostic challenges include ease-of-use, suitability for application and distribution in LMIC, and throughput for high-volume testing. Risk score algorithms have been used in LMIC to screen for AHI among individuals with behavioural and clinical characteristics more often associated with AHI. However, algorithms have not been implemented outside research settings. From a clinical perspective, there are substantial immunological and virological benefits to identifying and treating persons with AHI - evading the irreversible damage to host immune systems and seeding of viral reservoirs that occurs during untreated acute infection. The therapeutic benefits require rapid initiation of antiretrovirals, a logistical challenge in the absence of point-of-care testing. From a public health perspective, AHI diagnosis and treatment is critical to: decrease transmission via viral load reduction and behavioural interventions; improve pre-exposure prophylaxis outcomes by avoiding treatment initiation for HIV-seronegative persons with AHI; and, enhance partner services via notification for persons recently exposed or likely transmitting.

CONCLUSIONS

There are undeniable clinical and public health benefits to AHI detection and treatment, but also substantial diagnostic and logistical barriers to implementation and scale-up. Effective early ART initiation may be critical for HIV eradication efforts, but widespread use in LMIC requires simple and accurate diagnostic tools. Implementation research is critical to facilitate sustainable integration of AHI detection and treatment into existing health systems and will be essential for prospective evaluation of testing algorithms, point-of-care diagnostics, and efficacious and effective first-line regimens.

Impact of treatment on hepatitis C virus transmission and incidence in Egypt: A case for treatment as prevention

Egypt has launched a hepatitis C virus (HCV) treatment programme using direct-acting antivirals (DAAs). Our aim was to assess the impact of five plausible programme scale-up and sustainability scenarios for HCV treatment as prevention in Egypt. We developed and analysed a mathematical model to assess programme impact using epidemiologic, programming and health economics measures. The model was parametrized with current and representative natural history, HCV prevalence and programme data. HCV incidence in Egypt is declining, but will persist at a considerable level for decades unless controlled by interventions. Across the five programme scenarios, 1.75-5.60 million treatments were administered by 2030. Reduction in incidence (annual number of new infections) by 2030 ranged between 29% and 99%, programme-attributed reduction in incidence rate (new infections per susceptible person per year) ranged between 18% and 99%, number of infections averted ranged between 42 393 and 469 599, and chronic infection prevalence reached as low as 2.8%-0.1%. Reduction in incidence rate year by year hovered around 7%-15% in the first decade of the programme in most scenarios. Treatment coverage in 2030 ranged between 24.9% and 98.8%, and number of treatments required to avert one new infection ranged between 9.5 and 12.1. Stipulated targets for HCV by 2030 could not be achieved without scaling-up treatment to 365 000 per year and sustaining it for a decade. In conclusion, DAA scale-up will have an immense and immediate impact on HCV incidence in Egypt. Elimination by 2030 is feasible if sufficient resources are committed to programme scale-up and sustainability. HCV treatment as prevention is a potent and effective prevention approach.

Could Circumcision of HIV-Positive Males Benefit Voluntary Medical Male Circumcision Programs in Africa? Mathematical Modeling Analysis

Background

The epidemiological and programmatic implications of inclusivity of HIV-positive males in voluntary medical male circumcision (VMMC) programs are uncertain. We modeled these implications using Zambia as an illustrative example.

Methods and Findings

We used the Age-Structured Mathematical (ASM) model to evaluate, over an intermediate horizon (2010–2025), the effectiveness (number of VMMCs needed to avert one HIV infection) of VMMC scale-up scenarios with varying proportions of HIV-positive males. The model was calibrated by fitting to HIV prevalence time trend data from 1990 to 2014. We assumed that inclusivity of HIV positive males may benefit VMMC programs by increasing VMMC uptake among higher risk males, or by circumcision reducing HIV male-to-female transmission risk. All analyses were generated assuming no further antiretroviral therapy (ART) scale-up.

The number of VMMCs needed to avert one HIV infection was projected to increase from 12.2 VMMCs per HIV infection averted, in a program that circumcises only HIV-negative males, to 14.0, in a program that includes HIV-positive males. The proportion of HIV-positive males was based on their representation in the population (e.g. 12.6% of those circumcised in 2010 would be HIV-positive based on HIV prevalence among males of 12.6% in 2010). However, if a program that only reaches out to HIV-negative males is associated with 20% lower uptake among higher-risk males, the effectiveness would be 13.2 VMMCs per infection averted. If improved inclusivity of HIV-positive males is associated with 20% higher uptake among higher-risk males, the effectiveness would be 12.4. As the assumed VMMC efficacy against male-to-female HIV transmission was increased from 0% to 20% and 46%, the effectiveness of circumcising regardless of HIV status improved from 14.0 to 11.5 and 9.1, respectively. The reduction in the HIV incidence rate among females increased accordingly, from 24.7% to 34.8% and 50.4%, respectively.

Conclusion

Improving inclusivity of males in VMMC programs regardless of HIV status increases VMMC effectiveness, if there is moderate increase in VMMC uptake among higher-risk males and/or if there is moderate efficacy for VMMC against male-to-female transmission. In these circumstances, VMMC programs can reduce the HIV incidence rate in males by nearly as much as expected by some ART programs, and additionally, females can benefit from the intervention nearly as much as males.

HCV prevalence can predict HIV epidemic potential among people who inject drugs: mathematical modeling analysis

BACKGROUND

Hepatitis C virus (HCV) and HIV are both transmitted through percutaneous exposures among people who inject drugs (PWID). Ecological analyses on global epidemiological data have identified a positive association between HCV and HIV prevalence among PWID. Our objective was to demonstrate how HCV prevalence can be used to predict HIV epidemic potential among PWID.

METHODS

Two population-level models were constructed to simulate the evolution of HCV and HIV epidemics among PWID. The models described HCV and HIV parenteral transmission, and were solved both deterministically and stochastically.

RESULTS

The modeling results provided a good fit to the epidemiological data describing the ecological HCV and HIV association among PWID. HCV was estimated to be eight times more transmissible per shared injection than HIV. A threshold HCV prevalence of 29.0% (95% uncertainty interval (UI): 20.7-39.8) and 46.5% (95% UI: 37.6-56.6) were identified for a sustainable HIV epidemic (HIV prevalence >1%) and concentrated HIV epidemic (HIV prevalence >5%), respectively. The association between HCV and HIV was further described with six dynamical regimes depicting the overlapping epidemiology of the two infections, and was quantified using defined and estimated measures of association. Modeling predictions across a wide range of HCV prevalence indicated overall acceptable precision in predicting HIV prevalence at endemic equilibrium. Modeling predictions were found to be robust with respect to stochasticity and behavioral and biological parameter uncertainty. In an illustrative application of the methodology, the modeling predictions of endemic HIV prevalence in Iran agreed with the scale and time course of the HIV epidemic in this country.

CONCLUSIONS

Our results show that HCV prevalence can be used as a proxy biomarker of HIV epidemic potential among PWID, and that the scale and evolution of HIV epidemic expansion can be predicted with sufficient precision to inform HIV policy, programming, and resource allocation.

Acute HIV infection transmission among people who inject drugs in a mature epidemic setting

OBJECTIVE

Estimates for the contribution of transmission arising from acute HIV infections (AHIs) to overall HIV incidence vary significantly. Furthermore, little is known about AHI-attributable transmission among people who inject drugs (PWID), including the extent to which interventions targeting chronic infections (e.g. HAART as prevention) are limited by AHI transmission. Thus, we estimated the proportion of transmission events attributable to AHI within the mature HIV epidemic among PWID in New York City (NYC).

DESIGN

Modeling study.

METHODS

We constructed an interactive sexual and injecting transmission network using an agent-based model simulating the HIV epidemic in NYC between 1996 and 2012. Using stochastic microsimulations, we cataloged transmission from PWID based on the disease stage of index agents to determine the proportion of infections transmitted during AHI (in primary analyses, assumed to last 3 months).

RESULTS

Our calibrated model approximated the epidemiological features of the mature HIV epidemic in NYC between 1996 and 2012. Annual HIV incidence among PWID dropped from approximately 1.8% in 1996 to 0.7% in 2012. Over the 16-year period, AHI accounted for 4.9% (10th/90th percentile: 0.1-12.3%) of incident HIV cases among PWID. The annualized contribution of AHI increased over this period from 3.6% in 1996 to 5.9% in 2012.

CONCLUSION

Our results suggest that, in mature epidemics such as NYC, between 3% and 6% of transmission events are attributable to AHI among PWID. Current HIV treatment as prevention strategies are unlikely to be substantially affected by AHI-attributable transmission among PWID populations in mature epidemic settings.

Tenofovir-based oral preexposure prophylaxis prevents HIV infection among women

PURPOSE OF REVIEW

Despite tremendous promise as a female-controlled HIV prevention strategy, implementation of preexposure prophylaxis (PrEP) among women has been limited, in part because of disparate efficacy results from randomized trials in this population. This review synthesizes existing evidence regarding PrEP efficacy for preventing HIV infection in women and considerations for delivering PrEP to women.

RECENT FINDINGS

In three efficacy trials, conducted among men and women, tenofovir-based oral PrEP reduced HIV acquisition in subgroups of women by 49-79% in intent-to-treat analyses, and by >85% when accounting for PrEP adherence. Two trials did not demonstrate an HIV prevention benefit from PrEP in women, but substantial evidence indicates those results were compromised by very low adherence to the study medication. Qualitative research has identified risk perception, stigma, and aspects of clinical trial participation as influencing adherence to study medication. Pharmacokinetic studies provide supporting evidence that PrEP offers HIV protection in women who are adherent to the medication.

SUMMARY

Tenofovir-based daily oral PrEP prevents HIV acquisition in women. Offering PrEP as an HIV prevention option for women at high risk of HIV acquisition is a public health imperative and opportunities to evaluate implementation strategies for PrEP for women are needed.

Investigating Voluntary Medical Male Circumcision Program Efficiency Gains through Subpopulation Prioritization: Insights from Application to Zambia

Background

Countries in sub-Saharan Africa are scaling-up voluntary male medical circumcision (VMMC) as an HIV intervention. Emerging challenges in these programs call for increased focus on program efficiency (optimizing program impact while minimizing cost). A novel analytic approach was developed to determine how subpopulation prioritization can increase program efficiency using an illustrative application for Zambia.

Methods and Findings

A population-level mathematical model was constructed describing the heterosexual HIV epidemic and impact of VMMC programs (age-structured mathematical (ASM) model). The model stratified the population according to sex, circumcision status, age group, sexual-risk behavior, HIV status, and stage of infection. A three-level conceptual framework was also developed to determine maximum epidemic impact and program efficiency through subpopulation prioritization, based on age, geography, and risk profile. In the baseline scenario, achieving 80% VMMC coverage by 2017 among males 15–49 year old, 12 VMMCs were needed per HIV infection averted (effectiveness). The cost per infection averted (cost-effectiveness) was USD $1,089 and 306,000 infections were averted. Through age-group prioritization, effectiveness ranged from 11 (20–24 age-group) to 36 (45–49 age-group); cost-effectiveness ranged from $888 (20–24 age-group) to $3,300 (45–49 age-group). Circumcising 10–14, 15–19, or 20–24 year old achieved the largest incidence rate reduction; prioritizing 15–24, 15–29, or 15–34 year old achieved the greatest program efficiency. Through geographic prioritization, effectiveness ranged from 9–12. Prioritizing Lusaka achieved the highest effectiveness. Through risk-group prioritization, prioritizing the highest risk group achieved the highest effectiveness, with only one VMMC needed per infection averted; the lowest risk group required 80 times more VMMCs.

Conclusion

Epidemic impact and efficiency of VMMC programs can be improved by prioritizing young males (sexually active or just before sexual debut), geographic areas with higher HIV prevalence than the national, and high sexual-risk groups.

Trends in HIV Prevalence in Pregnant Women in Rural South Africa

BACKGROUND

Despite substantial progress in the delivery of HIV prevention programs, some communities continue to experience high rates of HIV infection. We report on temporal trends in HIV prevalence in pregnant women in a community in rural KwaZulu-Natal in South Africa.

METHODS

Annual, anonymous cross-sectional HIV sero-prevalence surveys were conducted between 2001 and 2013 among first visit prenatal clinic attendees. The time periods 2001 to 2003 were defined as pre-antiretroviral therapy (ART), 2004 to 2008 as early ART, and 2009 to 2013 as contemporary ART roll-out, to correspond with the substantial scale-up of ART program.

RESULTS

Overall, HIV prevalence rose from 35.3% [95% confidence interval (CI): 32.3 to 38.3] pre-ART (2001-2003) to 39.0% (95% CI: 36.8 to 41.1) in the early ART (2004-2008) to 39.3% (95% CI: 37.2 to 41.4) in the contemporary ART (2009-2013) roll-out periods. In teenage women (<20 years), HIV prevalence declined from 22.5% (95% CI: 17.5 to 27.5) to 20.7% (95% CI: 17.5 to 23.8) and to 17.2% (95% CI: 14.3 to 20.2) over the similar ART roll-out periods (P = 0.046). Prevalence increased significantly in women 30 years and older (P < 0.001) over the same time period largely because of survival after ART scale up. Teenage girls with male partners of age 20-24 and ≥ 25 years had a 1.7-fold (95% CI: 1.3-2.4; P = 0.001) and 3-fold (95% CI: 2.1 to 4.3; P < 0.001) higher HIV prevalence respectively.

CONCLUSIONS

Notwithstanding the encouraging decline in teenagers, the ongoing high HIV prevalence in pregnant women in this rural community, despite prevention and treatment programs, is deeply concerning. Targeted interventions for teenagers, especially for those in age-disparate relationships, are needed to impact this HIV epidemic trajectory.

Programmatic Implications of Acute and Early HIV Infection

Human immunodeficiency virus (HIV) infection includes acute, early, chronic, and late stages. Acute HIV infection lasts approximately 3 weeks and early HIV infection, which includes acute HIV infection, lasts approximately 7 weeks. Many testing and blood screening algorithms detect HIV antibodies about 3 weeks after HIV infection. Incidence estimates are based on results of modeling, cohort studies, surveillance, and/or assays. Viral load is the key modifiable risk factor for HIV transmission and peaks during acute and early HIV infection. Empirical evidence characterizing the impact of acute and early HIV infection on the spread of the HIV epidemic are limited. Time trends of HIV prevalence collected from concentrated and generalized epidemics suggest that acute and early HIV infection may have a limited role in population HIV transmission. Collectively, these data suggest that acute and early HIV infection is relatively short and does not currently require fundamentally different programmatic approaches to manage the HIV/AIDS epidemic in most settings. Research and surveillance will inform which epidemic contexts and phases may require tailored strategies for these stages of HIV infection.

Dynamic Variation in Sexual Contact Rates in a Cohort of HIV-Negative Gay Men

Human immunodeficiency virus (HIV) transmission models that include variability in sexual behavior over time have shown increased incidence, prevalence, and acute-state transmission rates for a given population risk profile. This raises the question of whether dynamic variation in individual sexual behavior is a real phenomenon that can be observed and measured. To study this dynamic variation, we developed a model incorporating heterogeneity in both between-person and within-person sexual contact patterns. Using novel methodology that we call iterated filtering for longitudinal data, we fitted this model by maximum likelihood to longitudinal survey data from the Centers for Disease Control and Prevention's Collaborative HIV Seroincidence Study (1992-1995). We found evidence for individual heterogeneity in sexual behavior over time. We simulated an epidemic process and found that inclusion of empirically measured levels of dynamic variation in individual-level sexual behavior brought the theoretical predictions of HIV incidence into closer alignment with reality given the measured per-act probabilities of transmission. The methods developed here provide a framework for quantifying variation in sexual behaviors that helps in understanding the HIV epidemic among gay men.

Reassessment of HIV-1 acute phase infectivity: accounting for heterogeneity and study design with simulated cohorts

BACKGROUND

The infectivity of the HIV-1 acute phase has been directly measured only once, from a retrospectively identified cohort of serodiscordant heterosexual couples in Rakai, Uganda. Analyses of this cohort underlie the widespread view that the acute phase is highly infectious, even more so than would be predicted from its elevated viral load, and that transmission occurring shortly after infection may therefore compromise interventions that rely on diagnosis and treatment, such as antiretroviral treatment as prevention (TasP). Here, we re-estimate the duration and relative infectivity of the acute phase, while accounting for several possible sources of bias in published estimates, including the retrospective cohort exclusion criteria and unmeasured heterogeneity in risk.

METHODS AND FINDINGS

We estimated acute phase infectivity using two approaches. First, we combined viral load trajectories and viral load-infectivity relationships to estimate infectivity trajectories over the course of infection, under the assumption that elevated acute phase infectivity is caused by elevated viral load alone. Second, we estimated the relative hazard of transmission during the acute phase versus the chronic phase (RHacute) and the acute phase duration (dacute) by fitting a couples transmission model to the Rakai retrospective cohort using approximate Bayesian computation. Our model fit the data well and accounted for characteristics overlooked by previous analyses, including individual heterogeneity in infectiousness and susceptibility and the retrospective cohort's exclusion of couples that were recorded as serodiscordant only once before being censored by loss to follow-up, couple dissolution, or study termination. Finally, we replicated two highly cited analyses of the Rakai data on simulated data to identify biases underlying the discrepancies between previous estimates and our own. From the Rakai data, we estimated RHacute = 5.3 (95% credibility interval [95% CrI]: 0.79-57) and dacute = 1.7 mo (95% CrI: 0.55-6.8). The wide credibility intervals reflect an inability to distinguish a long, mildly infectious acute phase from a short, highly infectious acute phase, given the 10-mo Rakai observation intervals. The total additional risk, measured as excess hazard-months attributable to the acute phase (EHMacute) can be estimated more precisely: EHMacute = (RHacute - 1) × dacute, and should be interpreted with respect to the 120 hazard-months generated by a constant untreated chronic phase infectivity over 10 y of infection. From the Rakai data, we estimated that EHMacute = 8.4 (95% CrI: -0.27 to 64). This estimate is considerably lower than previously published estimates, and consistent with our independent estimate from viral load trajectories, 5.6 (95% confidence interval: 3.3-9.1). We found that previous overestimates likely stemmed from failure to account for risk heterogeneity and bias resulting from the retrospective cohort study design. Our results reflect the interaction between the retrospective cohort exclusion criteria and high (47%) rates of censorship amongst incident serodiscordant couples in the Rakai study due to loss to follow-up, couple dissolution, or study termination. We estimated excess physiological infectivity during the acute phase from couples data, but not the proportion of transmission attributable to the acute phase, which would require data on the broader population's sexual network structure.

CONCLUSIONS

Previous EHMacute estimates relying on the Rakai retrospective cohort data range from 31 to 141. Our results indicate that these are substantial overestimates of HIV-1 acute phase infectivity, biased by unmodeled heterogeneity in transmission rates between couples and by inconsistent censoring. Elevated acute phase infectivity is therefore less likely to undermine TasP interventions than previously thought. Heterogeneity in infectiousness and susceptibility may still play an important role in intervention success and deserves attention in future analyses.

HIV transmissions by stage and sex role in long-term concurrent sexual partnerships

Most mathematical models used to examine the role of different stages of human immunodeficiency virus (HIV) infection unrealistically assume that HIV is transmitted through one-off contacts or that transmission rates are the same between males and females. We sought to examine whether inferences from previous models are robust to the relaxation of those unrealistic assumptions. We developed a model of HIV transmissions through sexual partnerships assuming that (1) sexual partnerships have variable duration, (2) sexual partnerships are concurrent, and (3) the male-to-female transmission rate is higher than the female-to-male transmission rate, with a focus on the third assumption. Assuming a higher rate for male-to-female than female-to-male transmissions decreases the overall transmission of HIV but increases the equilibrium fraction of transmissions during primary HIV infection (PHI) in long-term partnerships, compared to the case where transmission rates are assumed to be symmetric between males an females. Previous modeling studies that assume symmetric transmission rates between males and females may have overestimated the overall spread of HIV, but underestimated the relative contribution of PHI. To make robust inferences on the role of different stages of HIV infection in the sexual spread of HIV, models should take into account that transmission rates may be asymmetric by sex.

Why the proportion of transmission during early-stage HIV infection does not predict the long-term impact of treatment on HIV incidence

Antiretroviral therapy (ART) reduces the infectiousness of HIV-infected persons, but only after testing, linkage to care, and successful viral suppression. Thus, a large proportion of HIV transmission during a period of high infectiousness in the first few months after infection ("early transmission") is perceived as a threat to the impact of HIV "treatment-as-prevention" strategies. We created a mathematical model of a heterosexual HIV epidemic to investigate how the proportion of early transmission affects the impact of ART on reducing HIV incidence. The model includes stages of HIV infection, flexible sexual mixing, and changes in risk behavior over the epidemic. The model was calibrated to HIV prevalence data from South Africa using a Bayesian framework. Immediately after ART was introduced, more early transmission was associated with a smaller reduction in HIV incidence rate--consistent with the concern that a large amount of early transmission reduces the impact of treatment on incidence. However, the proportion of early transmission was not strongly related to the long-term reduction in incidence. This was because more early transmission resulted in a shorter generation time, in which case lower values for the basic reproductive number (R0) are consistent with observed epidemic growth, and R0 was negatively correlated with long-term intervention impact. The fraction of early transmission depends on biological factors, behavioral patterns, and epidemic stage and alone does not predict long-term intervention impacts. However, early transmission may be an important determinant in the outcome of short-term trials and evaluation of programs.

Quantifying transmission by stage of infection in the field: the example of SIV-1 and STLV-1 infecting mandrills

The early stage of viral infection is often followed by an important increase of viral load and is generally considered to be the most at risk for pathogen transmission. Most methods quantifying the relative importance of the different stages of infection were developed for studies aimed at measuring HIV transmission in Humans. However, they cannot be transposed to animal populations in which less information is available. Here we propose a general method to quantify the importance of the early and late stages of the infection on micro-organism transmission from field studies. The method is based on a state space dynamical model parameterized using Bayesian inference. It is illustrated by a 28 years dataset in mandrills infected by Simian Immunodeficiency Virus type-1 (SIV-1) and the Simian T-Cell Lymphotropic Virus type-1 (STLV-1). For both viruses we show that transmission is predominant during the early stage of the infection (transmission ratio for SIV-1: 1.16 [0.0009; 18.15] and 9.92 [0.03; 83.8] for STLV-1). However, in terms of basic reproductive number (R0 ), which quantifies the weight of both stages in the spread of the virus, the results suggest that the epidemics of SIV-1 and STLV-1 are mainly driven by late transmissions in this population.

The detection and management of early HIV infection: a clinical and public health emergency

This review considers the detection and management of early HIV infection (EHI), defined here as the first 6 months of infection. This phase is clinically important because a reservoir of infected cells formed in the individual renders HIV incurable, and the magnitude of viremia at the end of this period predicts the natural history of disease. Epidemiologically, it is critical because the very high viral load that typically accompanies early infection also makes infected individuals maximally contagious to their sexual partners. Future efforts to prevent HIV transmission with expanded testing and treatment may be compromised by elevated transmission risk earlier in the course of HIV infection, although the extent of this impact is yet unknown. Treatment as prevention efforts will nevertheless need to develop strategies to address testing, linkage to care, and treatment of EHI. Cost-effective and efficient identification of more persons with early HIV will depend on advancements in diagnostic technology and strengthened symptom-based screening strategies. Treatment for persons with EHI must balance individual health benefits and reduction of the risk of onward viral transmission. An increasing body of evidence supports the use of immediate antiretroviral therapy to treat EHI to maintain CD4 count and functionality, limit the size of the HIV reservoir, and reduce the risk of onward viral transmission. Although we can anticipate considerable challenges in identifying and linking to care persons in the earliest phases of HIV infection, there are many reasons to pursue this strategy.

Mapping HIV clustering: a strategy for identifying populations at high risk of HIV infection in sub-Saharan Africa

Background

The geographical structure of an epidemic is ultimately a consequence of the drivers of the epidemic and the population susceptible to the infection. The ‘know your epidemic’ concept recognizes this geographical feature as a key element for identifying populations at higher risk of HIV infection where prevention interventions should be targeted. In an effort to clarify specific drivers of HIV transmission and identify priority populations for HIV prevention interventions, we conducted a comprehensive mapping of the spatial distribution of HIV infection across sub-Saharan Africa (SSA).

Methods

The main source of data for our study was the Demographic and Health Survey conducted in 20 countries from SSA. We identified and compared spatial clusters with high and low numbers of HIV infections in each country using Kulldorff spatial scan test. The test locates areas with higher and lower numbers of HIV infections than expected under spatial randomness. For each identified cluster, a likelihood ratio test was computed. A P-value was determined through Monte Carlo simulations to evaluate the statistical significance of each cluster.

Results

Our results suggest stark geographic variations in HIV transmission patterns within and across countries of SSA. About 14% of the population in SSA is located in areas of intense HIV epidemics. Meanwhile, another 16% of the population is located in areas of low HIV prevalence, where some behavioral or biological protective factors appear to have slowed HIV transmission.

Conclusions

Our study provides direct evidence for strong geographic clustering of HIV infection across SSA. This striking pattern of heterogeneity at the micro-geographical scale might reflect the fact that most HIV epidemics in the general population in SSA are not far from their epidemic threshold. Our findings identify priority geographic areas for HIV programming, and support the need for spatially targeted interventions in order to maximize the impact on the epidemic in SSA.

Cost-effectiveness of pre-exposure prophylaxis (PrEP) in preventing HIV-1 infections in rural Zambia: a modeling study

BACKGROUND

Pre-exposure prophylaxis (PrEP) with tenofovir and emtricitabine effectively prevents new HIV infections. The optimal scenario for implementing PrEP where most infections are averted at the lowest cost is unknown. We determined the impact of different PrEP strategies on averting new infections, prevalence, drug resistance and cost-effectiveness in Macha, a rural setting in Zambia.

METHODS

A deterministic mathematical model of HIV transmission was constructed using data from the Macha epidemic (antenatal prevalence 7.7%). Antiretroviral therapy is started at CD4<350 cells/mm(3). We compared the number of infections averted, cost-effectiveness, and potential emergence of drug resistance of two ends of the prioritization spectrum: prioritizing PrEP to half of the most sexually active individuals (5-15% of the total population), versus randomly putting 40-60% of the total population on PrEP.

RESULTS

Prioritizing PrEP to individuals with the highest sexual activity resulted in more infections averted than a non-prioritized strategy over ten years (31% and 23% reduction in new infections respectively), and also a lower HIV prevalence after ten years (5.7%, 6.4% respectively). The strategy was very cost-effective at $323 per quality adjusted life year gained and appeared to be both less costly and more effective than the non-prioritized strategy. The prevalence of drug resistance due to PrEP was as high as 11.6% when all assumed breakthrough infections resulted in resistance, and as low as 1.3% when 10% of breakthrough infections resulted in resistance in both our prioritized and non-prioritized scenarios.

CONCLUSIONS

Even in settings with low test rates and treatment retention, the use of PrEP can still be a useful strategy in averting infections. Our model has shown that PrEP is a cost-effective strategy for reducing HIV incidence, even when adherence is suboptimal and prioritization is imperfect.

A model of HIV drug resistance driven by heterogeneities in host immunity and adherence patterns

Background

Population transmission models of antiretroviral therapy (ART) and pre-exposure prophylaxis (PrEP) use simplistic assumptions – typically constant, homogeneous rates – to represent the short-term risk and long-term effects of drug resistance. In contrast, within-host models of drug resistance allow for more detailed dynamics of host immunity, latent reservoirs of virus, and drug PK/PD. Bridging these two levels of modeling detail requires an understanding of the “levers” – model parameters or combinations thereof – that change only one independent observable at a time. Using the example of accidental tenofovir-based pre-exposure prophyaxis (PrEP) use during HIV infection, we will explore methods of implementing host heterogeneities and their long-term effects on drug resistance.

Results

We combined and extended existing models of virus dynamics by incorporating pharmacokinetics, pharmacodynamics, and adherence behavior. We identified two “levers” associated with the host immune pressure against the virus, which can be used to independently modify the setpoint viral load and the shape of the acute phase viral load peak. We propose parameter relationships that can explain differences in acute and setpoint viral load among hosts, and demonstrate their influence on the rates of emergence and reversion of drug resistance. The importance of these dynamics is illustrated by modeling long-lived latent reservoirs of virus, through which past intervals of drug resistance can lead to failure of suppressive drug regimens. Finally, we analyze assumptions about temporal patterns of drug adherence and their impact on resistance dynamics, finding that with the same overall level of adherence, the dwell times in drug-adherent versus not-adherent states can alter the levels of drug-resistant virus incorporated into latent reservoirs.

Conclusions

We have shown how a diverse range of observable viral load trajectories can be produced from a basic model of virus dynamics using immunity-related “levers”. Immune pressure, in turn, influences the dynamics of drug resistance, with increased immune activity delaying drug resistance and driving more rapid return to dominance of drug-susceptible virus after drug cessation. Both immune pressure and patterns of drug adherence influence the long-term risk of drug resistance. In the case of accidental PrEP use during infection, rapid transitions between adherence states and/or weak immunity fortifies the “memory” of previous PrEP exposure, increasing the risk of future drug resistance. This model framework provides a means for analyzing individual-level risks of drug resistance and implementing heterogeneities among hosts, thereby achieving a crucial prerequisite for improving population-level models of drug resistance.

Developing concurrency messages for the black community in Seattle, Washington

In the United States, Blacks are disproportionately impacted by HIV/AIDS. Sexual networks and concurrent relationships have emerged as important contributors to the heterosexual transmission of HIV. To date, Africa is the only continent where an understanding of the impact of sexual concurrency has been conveyed in HIV prevention messaging. This project was developed by researchers and members of the Seattle, Washington, African American and African-Born communities, using the principles of community-based participatory research (CBPR). Interest in developing concurrency messaging came from the community and resulted in the successful submission of a community-academic partnership proposal to develop and disseminate HIV prevention messaging around concurrency. The authors describe (a) the development of concurrency messaging through the integration of collected formative data and findings from the scientific literature; (b) the process of disseminating the message in the local Black community; and (c) important factors to consider in the development of similar campaigns.

Is concurrency driving HIV transmission in sub-Saharan African sexual networks? The significance of sexual partnership typology

Recently, there has been debate about the role of concurrent partnerships in driving the transmission of HIV, particularly in Southern Africa, where HIV prevalence is up to 25 % in many heterosexual populations and where evidence from sexual behavior surveys also suggests high levels of male concurrency. While mathematical modeling studies have shown that concurrency has the potential to enhance the speed at which HIV spreads in a population, empirical studies up to now have failed to provide conclusive evidence supportive of these effects. Here we discuss some reasons for the apparent discrepancy between theoretical and empirical studies. We propose that studying the impact of concurrency on HIV transmission should be differentiated by taking more insight from social and behavioral studies on sexual partnerships into account. We also suggest that a more rigorous definition is needed for when a factor is considered a driving force for HIV epidemic spread. We illustrate this with a modeling example.

Size matters: concurrency and the epidemic potential of HIV in small networks

Background

Generalized heterosexual epidemics are responsible for the largest share of the global burden of HIV. These occur in populations that do not have high rates of partner acquisition, and research suggests that a pattern of fewer, but concurrent, partnerships may be the mechanism that provides the connectivity necessary for sustained transmission. We examine how network size affects the impact of concurrency on network connectivity.

Methodology/Principal Findings

We use a stochastic network model to generate a sample of networks, varying the size of the network and the level of concurrency, and compare the largest components for each scenario to the asymptotic expected values. While the threshold for the growth of a giant component does not change, the transition is more gradual in the smaller networks. As a result, low levels of concurrency generate more connectivity in small networks.

Conclusions/Significance

Generalized HIV epidemics are by definition those that spread to a larger fraction of the population, but the mechanism may rely in part on the dynamics of transmission in a set of linked small networks. Examples include rural populations in sub-Saharan Africa and segregated minority populations in the US, where the effective size of the sexual network may well be in the hundreds, rather than thousands. Connectivity emerges at lower levels of concurrency in smaller networks, but these networks can still be disconnected with small changes in behavior. Concurrency remains a strategic target for HIV combination prevention programs in this context.

Effectiveness of a no-sex or safe-sex month in reducing HIV transmission

OBJECTIVE

To build a deterministic compartmental model for exploring the effects on the transmission of human immunodeficiency virus (HIV) of a population abstaining from sex or practising only "safe" sex for one month each year.

METHODS

A model of HIV transmission was built to simulate the effects of the intervention (i.e. an annual no-sex or safe-sex month in which no transmission occurred) in three countries, under several optimistic assumptions. The reduction in the modelled annual incidence of transmission that was attributable to this "test" intervention was compared with that seen with an alternative intervention. In the latter, monthly incidences of transmission were each reduced by one twelfth, so that, essentially, the month-long interruption was spread evenly across a full year.

FINDINGS

Over the first modelled year, the test intervention averted only 2.5% (Kenya), 3.3% (South Africa) and 1.6% (Swaziland) more HIV infections than the alternative interruption. According to the model, if the test intervention were repeated each January, it would avert only 2% (Kenya), 2% (South Africa) and 1% (Swaziland) more HIV infections over 5 years than the alternative intervention.

CONCLUSION

Although it did not appear markedly more effective than the alternative intervention, the test intervention may still be more feasible and therefore worthwhile. Before the test intervention can be recommended, the cost-effectiveness and feasibility of such an annual month-long break in HIV transmission need to be assessed and compared with those of other interventions that may reduce new HIV infections, such as circumcision and concurrency-reduction campaigns.

Comparability of results from pair and classical model formulations for different sexually transmitted infections

The "classical model" for sexually transmitted infections treats partnerships as instantaneous events summarized by partner change rates, while individual-based and pair models explicitly account for time within partnerships and gaps between partnerships. We compared predictions from the classical and pair models over a range of partnership and gap combinations. While the former predicted similar or marginally higher prevalence at the shortest partnership lengths, the latter predicted self-sustaining transmission for gonorrhoea (GC) and Chlamydia (CT) over much broader partnership and gap combinations. Predictions on the critical level of condom use (C(c)) required to prevent transmission also differed substantially when using the same parameters. When calibrated to give the same disease prevalence as the pair model by adjusting the infectious duration for GC and CT, and by adjusting transmission probabilities for HIV, the classical model then predicted much higher C(c) values for GC and CT, while C(c) predictions for HIV were fairly close. In conclusion, the two approaches give different predictions over potentially important combinations of partnership and gap lengths. Assuming that it is more correct to explicitly model partnerships and gaps, then pair or individual-based models may be needed for GC and CT since model calibration does not resolve the differences.

Should we treat acute HIV infection?

Critical advances in the early diagnosis of HIV now allow for treatment opportunities during acute infection. It remains unclear whether treatment of acute HIV infection with antiretroviral therapy improves long-term clinical outcomes for the individual and current guidelines are not definitive in recommending therapy at this stage of infection. However, treatment of acute HIV infection may have short-term benefit on viral set point when compared to delayed therapy as well as reducing the risk of transmission to others. Herein we review the immunological and clinical literature to discuss whether we should treat acute HIV infection, both from the perspective of the individual HIV-infected patient and from the public health perspective. As transmission of drug-resistant HIV variants are of concern, we also review recent clinical trial data to provide recommendations for which specific antiretroviral treatment regimens should be considered for the treatment of acute HIV infection.

Modeling the impact of supra-structural network nodes: The case of anonymous syringe sharing and HIV among people who inject drugs

Networks are well understood as crucial to the diffusion of HIV among injection drug users (IDUs), but quasi-anonymous risk nodes - such as shooting galleries - resist measurement and incorporation into empirical analyses of disease diffusion. Drawing on network data from 767 IDUs in Bushwick, Brooklyn, we illustrate the use of calibrated agent-based models (CABMs) to account for network structure, injection practices, and quasi-anonymous transmission in shooting galleries. Results confirm the importance of network structure and actor heterogeneity to the magnitude and speed of HIV transmission. Models further demonstrate that quasi-anonymous injections in shooting galleries increase the speed of HIV diffusion across the whole network and have the greatest impact on HIV seroconversion levels for IDUs at the network periphery. Shooting galleries are shown to be transmission hubs that operate independently of traceable structural ties, linking otherwise unconnected network components. CABMs potentially increase understandings of HIV diffusion dynamics by infusing computer simulations with empirical data.

Unraveling the divergent results of pre-exposure prophylaxis trials for HIV prevention

Although the balance of recent evidence supports the efficacy of antiretroviral (ARV)-based pre-exposure prophylaxis (PrEP) against HIV-1 infection, recent negative trial results are perplexing. Of seven trials with available HIV endpoints, three different products have been tested: tenofovir 1% vaginal gel, oral tenofovir disoproxil fumarate (TDF) tablets, and TDF/emtricitabine tablets. Six of these trials were conducted exclusively in sub-Saharan Africa; all found the products to be well tolerated, and four demonstrated effectiveness. Furthermore, the HIV Prevention Trial Network (HPTN) 052 trial recently confirmed that antiretroviral treatment leads to 96% reduction in transmission to HIV-negative partners in HIV-serodiscordant couples. These results, along with human and animal data, provide substantial evidence for the efficacy of antiretroviral-based HIV prevention. Yet assessment of oral TDF/emtricitabine in the FEM-PrEP study and of oral and vaginal tenofovir in the Microbicide Trial Network (MTN)-003 trial (VOICE) was stopped for futility. How do we make sense of these discrepant results? We believe that adherence is a key factor, although it cannot be the only factor. Expanding upon a recent editorial in the Lancet, we discuss the impact of suboptimal product adherence on PrEP efficacy in the context of variable drug concentration at the exposure site, integrity of the vaginal epithelium, and the role of acute infection.

The contribution of maternal HIV seroconversion during late pregnancy and breastfeeding to mother-to-child transmission of HIV

BACKGROUND

The prevention of mother-to-child transmission (PMTCT) of HIV has been focused mainly on women who are HIV positive at their first antenatal visit, but there is uncertainty regarding the contribution to overall transmission from mothers who seroconvert after their first antenatal visit and before weaning.

METHOD

A mathematical model was developed to simulate changes in mother-to-child transmission of HIV over time, in South Africa. The model allows for changes in infant feeding practices as infants age, temporal changes in the provision of antiretroviral prophylaxis and counseling on infant feeding, as well as temporal changes in maternal HIV prevalence and incidence.

RESULTS

The proportion of mother-to-child transmission (MTCT) from mothers who seroconverted after their first antenatal visit was 26% [95% confidence interval (CI): 22% to 30%] in 2008, or 15,000 of 57,000 infections. It is estimated that by 2014, total MTCT will reduce to 39,000 per annum, and transmission from mothers seroconverting after their first antenatal visit will reduce to 13,000 per annum, accounting for 34% (95% CI: 29% to 39%) of MTCT. If maternal HIV incidence during late pregnancy and breastfeeding were reduced by 50% after 2010, and HIV screening were repeated in late pregnancy and at 6-week immunization visits after 2010, the average annual number of MTCT cases over the 2010-2015 period would reduce by 28% (95% CI: 25% to 31%), from 39,000 to 28,000 per annum.

CONCLUSION

Maternal seroconversion during late pregnancy and breastfeeding contributes significantly to the pediatric HIV burden and needs greater attention in the planning of prevention of MTCT programs.

Recent HIV-1 infection contributes to the viral diffusion over the French territory with a recent increasing frequency

Objective

To analyse the contribution of primary human immunodeficiency virus type 1 (HIV-1) infection (PHI) to the French viral epidemic.

Methods

HIV-1 pol sequences included 987 PHI from the French ANRS PRIMO cohort between 1999 and 2010 and were analysed using a population-based phylogenetic approach. Clinical features, risk factors, sexual behaviour and drug resistance for clustered and nonclustered transmission events were ascertained.

Results

Viruses from 125 (12.7%) of PHI cosegregated into 56 transmission chains, with increasing frequency during the last years (10.2% before 2006 versus 15.2% of clusters in 2006–2010, p = 0.02). The mean number of patients per cluster was 2.44. Compared to unique PHI, clusters involved more often men, infected through homosexual intercourse, of young age, with a high number of casual sexual partnerships and frequent previous HIV serological tests. Resistant strains were found in 16.0% and 11.1% of clusters and unique PHI, respectively (p = 0.11). Overall, 34% (n = 19) clusters included patients followed in French regions far apart, involving 13 clusters with at least one Parisian patient.

Conclusions

PHIs are a significant source of onward transmission, especially in the MSM population. Recently infected people contribute to the spread of the viral epidemic throughout the French territory. Survey of transmitted drug resistance and behavioural characteristics of patients involved into clustered PHI may help to guide prevention and treatment interventions.

Concurrent partnerships, acute infection and HIV epidemic dynamics among young adults in Zimbabwe

This paper explores the roles of acute infection and concurrent partnerships in HIV transmission dynamics among young adults in Zimbabwe using realistic representations of the partnership network and all published estimates of stage-specific infectivity. We use dynamic exponential random graph models to estimate partnership network parameters from an empirical study of sexual behavior and drive a stochastic simulation of HIV transmission through this dynamic network. Our simulated networks match observed frequencies and durations of short- and long-term partnerships, with concurrency patterns specific to gender and partnership type. Our findings suggest that, at current behavior levels, the epidemic cannot be sustained in this population without both concurrency and acute infection; removing either brings transmission below the threshold for persistence. With both present, we estimate 20-25% of transmissions stem from acute-stage infections, 30-50% from chronic-stage, and 30-45% from AIDS-stage. The impact of acute infection is strongly moderated by concurrency. Reducing this impact by reducing concurrency could potentially end the current HIV epidemic in Zimbabwe.

HIV transmissions by stage in dynamic sexual partnerships

Most models assessing relative transmissions during different progressive stages of human immunodeficiency virus (HIV) infection assume that infections are transmitted through instantaneous sexual contacts. In reality, however, HIV will often be transmitted through repeated sex acts during partnerships that form and dissolve at varying rates. We sought to understand how dynamic sexual partnerships would influence transmissions during different progression stages of HIV infection: primary HIV infection (PHI) and chronic stage. Using a system of ordinary differential equations with a pair approximation technique, we constructed a model of HIV transmission in a homogeneous population in which sexual partnerships form and dissolve. We derived analytical expressions for useful epidemiological quantities such as basic reproduction number and also did simulation runs of the model. Partnership dynamics strongly influence transmissions during progressive stages of HIV infection. The fraction of transmissions during PHI has a U-shaped relationship with respect to the rate of partnership change, where the minimum and maximum occur given partnerships of about 100 days and fixed partnerships, respectively. Models that assume instantaneous contacts may overestimate transmissions during PHI for real, dynamic sexual partnerships with varying (non-zero) durations.

Episodic HIV Risk Behavior Can Greatly Amplify HIV Prevalence and the Fraction of Transmissions from Acute HIV Infection

A deterministic compartmental model was explored that relaxed the unrealistic assumption in most HIV transmission models that behaviors of individuals are constant over time. A simple model was formulated to better explain the effects observed. Individuals had a high and a low contact rate and went back and forth between them. This episodic risk behavior interacted with the short period of high transmissibility during acute HIV infection to cause dramatic increases in prevalence as the differences between high and low contact rates increased and as the duration of high risk better matched the duration of acute HIV infection. These same changes caused a considerable increase in the fraction of all transmissions that occurred during acute infection. These strong changes occurred despite a constant total number of contacts and a constant total transmission potential from acute infection. Two phenomena played a strong role in generating these effects. First, people were infected more often during their high contact rate phase and they remained with high contact rates during the highly contagious acute infection stage. Second, when individuals with previously low contact rates moved into an episodic high-risk period, they were more likely to be susceptible and thus provided more high contact rate susceptible individuals who could get infected. These phenomena make test and treat control strategies less effective and could cause some behavioral interventions to increase transmission. Signature effects on genetic patterns between HIV strains could make it possible to determine whether these episodic risk effects are acting in a population.

HIV treatment as prevention: principles of good HIV epidemiology modelling for public health decision-making in all modes of prevention and evaluation

Public health responses to HIV epidemics have long relied on epidemiological modelling analyses to help prospectively project and retrospectively estimate the impact, cost-effectiveness, affordability, and investment returns of interventions, and to help plan the design of evaluations. But translating model output into policy decisions and implementation on the ground is challenged by the differences in background and expectations of modellers and decision-makers. As part of the PLoS Medicine Collection "Investigating the Impact of Treatment on New HIV Infections"--which focuses on the contribution of modelling to current issues in HIV prevention--we present here principles of "best practice" for the construction, reporting, and interpretation of HIV epidemiological models for public health decision-making on all aspects of HIV. Aimed at both those who conduct modelling research and those who use modelling results, we hope that the principles described here will become a shared resource that facilitates constructive discussions about the policy implications that emerge from HIV epidemiology modelling results, and that promotes joint understanding between modellers and decision-makers about when modelling is useful as a tool in quantifying HIV epidemiological outcomes and improving prevention programming.

The HIV Modelling Consortium Treatment as Prevention Editorial Writing Group. HIV treatment as prevention: models, data, and questions--towards evidence-based decision-making

Antiretroviral therapy (ART) for those infected with HIV can prevent onward transmission of infection, but biological efficacy alone is not enough to guide policy decisions about the role of ART in reducing HIV incidence. Epidemiology, economics, demography, statistics, biology, and mathematical modelling will be central in framing key decisions in the optimal use of ART. PLoS Medicine, with the HIV Modelling Consortium, has commissioned a set of articles that examine different aspects of HIV treatment as prevention with a forward-looking research agenda. Interlocking themes across these articles are discussed in this introduction. We hope that this article, and others in the collection, will provide a foundation upon which greater collaborations between disciplines will be formed, and will afford deeper insights into the key factors involved, to help strengthen the support for evidence-based decision-making in HIV prevention.