Validation of the modes of transmission model as a tool to prioritize HIV prevention targets: a comparative modelling analysis

A sub-national HIV epidemic appraisal in Kenya: a new approach for identifying priority geographies, populations and programmes for optimizing coverage for HIV prevention

INTRODUCTION

The HIV Prevention 2025 Roadmap, developed by UNAIDS, recommends the adoption of a precision prevention approach focused on priority populations and geographies. With reduction in new HIV acquisitions in many countries, designing a differentiated HIV prevention response, using a Programme Science approach, based on the understanding of the epidemic and transmission dynamics at a sub-national level, is critical.

METHODS

To support strategic planning, an epidemic appraisal at the sub-national level across 47 counties, with the 2019 population ranging from 0.14 million in Lamu to 4.40 million in Nairobi City, was conducted in Kenya using several existing data sources. Using 2021 Spectrum/EPP/Naomi model estimates of national and sub-national HIV incidence and prevalence, counties with high HIV incidence and prevalence were identified for geographic prioritization. The size of local key population (KP) networks and HIV prevalence in key and general populations were used to define epidemic typology and prioritize populations for HIV prevention programmes. Analysis of routine programme monitoring data for 2021 was used to assess coverage gaps in HIV prevention programmes, including prevention of vertical transmission, anti-retroviral therapy, KP programmes, adolescent girls and young women programme, and voluntary male medical circumcision programme.

RESULTS

Ten counties with more than 1000 incident acquisitions in 2021 accounted for 57% of new acquisitions. Twenty-four counties were grouped into the concentrated epidemic type-due to their low prevalence in the general population, high prevalence in KPs and relatively higher density of female sex workers and men who have sex with men populations. Four counties reflected a generalized epidemic, where HIV prevalence was more than 10% and 30%, respectively, among the general and key populations. The remaining 19 counties were classified as having mixed epidemics. Gaps in programmes were identified and counties where these gaps need to be addressed were also prioritized.

CONCLUSIONS

The HIV burden in Kenya is unevenly distributed and hence the mix of prevention strategies may vary according to the epidemic typology of the county. Prioritization of programmes based not only on disease burden and epidemic typology, but also on the prevailing gaps in coverage for reducing inequities is a key aspect of this appraisal.

Comparison of Empirically Derived and Model-Based Estimates of Key Population HIV Incidence and the Distribution of New Infections by Population Group in Sub-Saharan Africa

BACKGROUND

The distribution of new HIV infections among key populations, including female sex workers (FSWs), gay men and other men who have sex with men (MSM), and people who inject drugs (PWID) are essential information to guide an HIV response, but data are limited in sub-Saharan Africa (SSA). We analyzed empirically derived and mathematical model-based estimates of HIV incidence among key populations and compared with the Joint United Nations Programme on HIV/AIDS (UNAIDS) estimates.

METHODS

We estimated HIV incidence among FSW and MSM in SSA by combining meta-analyses of empirical key population HIV incidence relative to the total population incidence with key population size estimates (KPSE) and HIV prevalence. Dynamic HIV transmission model estimates of HIV incidence and percentage of new infections among key populations were extracted from 94 country applications of 9 mathematical models. We compared these with UNAIDS-reported distribution of new infections, implied key population HIV incidence and incidence-to-prevalence ratios.

RESULTS

Across SSA, empirical FSW HIV incidence was 8.6-fold (95% confidence interval: 5.7 to 12.9) higher than total population female 15-39 year incidence, and MSM HIV incidence was 41.8-fold (95% confidence interval: 21.9 to 79.6) male 15-29 year incidence. Combined with KPSE, these implied 12% of new HIV infections in 2021 were among FSW and MSM (5% and 7% respectively). In sensitivity analysis varying KPSE proportions within 95% uncertainty range, the proportion of new infections among FSW and MSM was between 9% and 19%. Insufficient data were available to estimate PWID incidence rate ratios. Across 94 models, median proportion of new infections among FSW, MSM, and PWID was 6.4% (interquartile range 3.2%-11.7%), both much lower than the 25% reported by UNAIDS.

CONCLUSION

Empirically derived and model-based estimates of HIV incidence confirm dramatically higher HIV risk among key populations in SSA. Estimated proportions of new infections among key populations in 2021 were sensitive to population size assumptions and were substantially lower than estimates reported by UNAIDS.

Modelling Methods of Economic Evaluations of HIV Testing Strategies in Sub-Saharan Africa: A Systematic Review

BACKGROUND AND OBJECTIVE

Economic evaluations, a decision-support tool for policy makers, will be crucial in planning and tailoring HIV prevention and treatment strategies especially in the wake of stalled and decreasing funding for the global HIV response. As HIV testing and treatment coverage increase, case identification becomes increasingly difficult and costly. Determining which subset of the population these strategies should be targeted to becomes of vital importance as well. Generating quality economic evidence begins with the validity of the modelling approach and the model structure employed. This study synthesises and critiques the reporting around modelling methodology of economic models in the evaluation of HIV testing strategies in sub-Saharan Africa.

METHODS

The following databases were searched from January 2000 to September 2020: MEDLINE, Embase, Scopus, EconLit and Global Health. Any model-based economic evaluation of a unique HIV testing strategy conducted in sub-Saharan Africa presenting a cost-effectiveness measure published from 2013 onwards was eligible. Data were extracted around three components: general study characteristics; economic evaluation design; and quality of model reporting using a novel tool developed for the purposes of this study.

RESULTS

A total of 21 studies were included; 10 cost-effectiveness analyses, 11 cost-utility analyses. All but one study was conducted in Eastern and Southern Africa. Modelling approaches for HIV testing strategies can be broadly characterised as static aggregate models (3/21), static individual models (6/21), dynamic aggregate models (5/21) and dynamic individual models (7/21). Adequate reporting around data handling was the highest of the three categories assessed (74%), and model validation, the lowest (45%). Limitations to model structure, justification of chosen time horizon and cycle length, and description of external model validation process were all adequately reported in less than 40% of studies. The predominant limitation of this review relates to the potential implications of the narrow inclusion criteria.

CONCLUSIONS

This review is the first to synthesise economic evaluations of HIV testing strategies in sub-Saharan Africa. The majority of models exhibited dynamic, stochastic and individual properties. Model reporting against the 13 criteria in our novel tool was mixed. Future model-based economic evaluations of HIV testing strategies would benefit from transparency around the choice of modelling approach, model structure, data handling procedures and model validation techniques.

What Is the Burden of Heterosexually Acquired HIV Due to HSV-2? Global and Regional Model-Based Estimates of the Proportion and Number of HIV Infections Attributable to HSV-2 Infection

BACKGROUND

Biological and epidemiological evidence suggest that herpes simplex virus type 2 (HSV-2) elevates HIV acquisition and transmission risks. We improved previous estimates of the contribution of HSV-2 to HIV infections by using a dynamic transmission model.

SETTING

World Health Organization regions.

METHODS

We developed a mathematical model of HSV-2/HIV transmission among 15- to 49-year-old heterosexual, non-drug-injecting populations, calibrated using region-specific demographic and HSV-2/HIV epidemiological data. We derived global and regional estimates of the contribution of HSV-2 to HIV infection over 10 years [the transmission population-attributable fraction (tPAF)] under 3 additive scenarios, assuming: (1) HSV-2 increases only HIV acquisition risk (conservative); (2) HSV-2 also increases HIV transmission risk (liberal); and (3) HIV or antiretroviral therapy (ART) also modifies HSV-2 transmission risk, and HSV-2 decreases ART effect on HIV transmission risk (fully liberal).

RESULTS

Under the conservative scenario, the predicted tPAF was 37.3% (95% uncertainty interval: 33.4%-43.2%), and an estimated 5.6 (4.5-7.0) million incident heterosexual HIV infections were due to HSV-2 globally over 2009-2018. The contribution of HSV-2 to HIV infections was largest for the African region [tPAF = 42.6% (38.0%-51.2%)] and lowest for the European region [tPAF = 11.2% (7.9%-13.8%)]. The tPAF was higher among female sex workers, their clients, and older populations, reflecting their higher HSV-2 prevalence. The tPAF was approximately 50% and 1.3- to 2.4-fold higher for the liberal or fully liberal scenario than the conservative scenario across regions.

CONCLUSION

HSV-2 may have contributed to at least 37% of incident HIV infections in the past decade worldwide, and even more in Africa, and may continue to do so despite increased ART access unless future improved HSV-2 control measures, such as vaccines, become available.

Estimating the epidemic consequences of HIV prevention gaps among key populations

INTRODUCTION

HIV epidemic appraisals are used to characterize heterogeneity and inequities in the context of the HIV pandemic and the response. However, classic measures used in appraisals have been shown to underestimate disproportionate risks of onward transmission, particularly among key populations. In response, a growing number of modelling studies have quantified the consequences of unmet prevention and treatment needs (prevention gaps) among key populations as a transmission population attributable fraction over time (tPAFt ). To aid its interpretation and use by programme implementers and policy makers, we outline and discuss a conceptual framework for understanding and estimating the tPAFt via transmission modelling as a measure of onward transmission risk from HIV prevention gaps; and discuss properties of the tPAFt .

DISCUSSION

The distribution of onward transmission risks may be defined by who is at disproportionate risk of onward transmission, and under which conditions. The latter reflects prevention gaps, including secondary prevention via treatment: the epidemic consequences of which may be quantified by the tPAFt . Steps to estimating the tPAFt include parameterizing the acquisition and onward transmission risks experienced by the subgroup of interest, defining the most relevant counterfactual scenario, and articulating the time-horizon of analyses and population among whom to estimate the relative difference in cumulative transmissions; such steps could reflect programme-relevant questions about onward transmission risks. Key properties of the tPAFt include larger onward transmission risks over longer time-horizons; seemingly mutually exclusive tPAFt measures summing to greater than 100%; an opportunity to quantify the magnitude of disproportionate onward transmission risks with a per-capita tPAFt ; and that estimates are conditional on what has been achieved so far in reducing prevention gaps and maintaining those conditions moving forward as the status quo.

CONCLUSIONS

The next generation of HIV epidemic appraisals has the potential to support a more specific HIV response by characterizing heterogeneity in disproportionate risks of onward transmission which are defined and conditioned on the past, current and future prevention gaps across subsets of the population.

Reductions in HIV incidence are likely to increase the importance of key population programmes for HIV control in sub-Saharan Africa

INTRODUCTION

An efficient HIV response requires that resources be focussed on effective interventions for those most at risk of acquiring and transmitting infection. As HIV epidemics evolve the distribution of HIV across key and other populations will change. Here, the epidemiological concepts underpinning these changes are described and the importance of appropriate allocation of effective interventions is discussed.

DISCUSSION

In many sub-Saharan African countries HIV epidemics have been categorized as "generalized," and HIV testing, treatment and prevention interventions have focussed on the "general" population. As HIV epidemics are better controlled the relative importance of "key" populations will increase, dominating the ongoing burden of disease and providing the potential for repeated outbreaks of HIV if interventions are relaxed. The basic reproductive number (R0 ) describes the potential for an infectious disease to spread at the boundary of invasion or elimination, whereas the effective reproduction number (Rt ) describes the current potential for spread. Heterogeneity in risk means that while Rt is temporarily below one and prevalence declining, the R0 can remain above one, preventing eventual elimination. Patterns of HIV acquisition are often used to guide interventions but inadequately capture the transmission dynamics of the virus and the most efficient approach to controlling HIV. Risks for HIV acquisition are not identical to risks for HIV transmission and will change depending on the epidemiological context. In addition to the challenges in measuring HIV transmission dynamics, there is a tension between using epidemiology to drive the HIV response and the social and political realities constraining how programmes and providers can practically and appropriately focus on key populations and maintain political support. In addition to being well focussed, interventions need to be effective and cost-effective, which requires a better understanding of packages of interventions rather than specific tools.

CONCLUSIONS

Continued control of HIV will increasingly rely on resources, programmes and interventions supporting key populations. Current epidemiological and programmatic approaches for key populations in sub-Saharan Africa are insufficient with a need for an improved understanding of local epidemiology and the effectiveness of interventions.

Phylogenetic Cluster Analysis Identifies Virological and Behavioral Drivers of Human Immunodeficiency Virus Transmission in Men Who Have Sex With Men

BACKGROUND

Identifying local outbreaks and their drivers is a key step toward curbing human immunodeficiency virus (HIV) transmission and potentially achieving HIV elimination. Such outbreaks can be identified as transmission clusters extracted from phylogenetic trees constructed of densely sampled viral sequences. In this study, we combined phylogenetic transmission clusters with extensive data on virological suppression and behavioral risk of cluster members to quantify the drivers of ongoing transmission over 10 years.

METHODS

Using the comprehensive Swiss HIV Cohort Study and its drug-resistance database, we reconstructed phylogenetic trees for each year between 2007 and 2017. We identified HIV transmission clusters dominated by men who have sex with men (MSM) and determined their annual growth. We used Poisson regression to assess if cluster growth was associated with a per-cluster infectivity and behavioral risk score.

RESULTS

Both infectivity and behavioral risk scores were significantly higher in growing MSM transmission clusters compared to nongrowing clusters (P ≤ .01). The fraction of transmission clusters without infectious members acquiring new infections increased significantly over the study period. The infectivity score was significantly associated with per-capita incidence of MSM transmission clusters in 8 years, while the behavioral risk score was significantly associated with per-capita incidence of MSM transmission clusters in 3 years.

CONCLUSIONS

We present a phylogenetic method to identify hotspots of ongoing transmission among MSM. Our results demonstrate the effectiveness of treatment as prevention at the population level. However, the significantly increasing number of new infections among transmission clusters without infectious members highlights a relative shift from diagnosed to undiagnosed individuals as drivers of HIV transmission in Swiss MSM.

Is modelling complexity always needed? Insights from modelling PrEP introduction in South Africa

BACKGROUND

Mathematical models can be powerful policymaking tools. Simple, static models are user-friendly for policymakers. More complex, dynamic models account for time-dependent changes but are complicated to understand and produce. Under which conditions are static models adequate? We compare static and dynamic model predictions of whether behavioural disinhibition could undermine the impact of HIV pre-exposure prophylaxis (PrEP) provision to female sex workers in South Africa.

METHODS

A static model of HIV risk was developed and adapted into a dynamic model. Both models were used to estimate the possible reduction in condom use, following PrEP introduction, without increasing HIV risk. The results were compared over a 20-year time horizon, in two contexts: at epidemic equilibrium and during an increasing epidemic.

RESULTS

Over time horizons of up to 5 years, the models are consistent. Over longer timeframes, the static model overstates the tolerated reduction in condom use where initial condom use is reasonably high ($\ge$50%) and/or PrEP effectiveness is low ($\le$45%), especially during an increasing epidemic.

CONCLUSIONS

Static models can provide useful deductions to guide policymaking around the introduction of a new HIV intervention over short-medium time horizons of up to 5 years. Over longer timeframes, static models may not sufficiently emphasise situations of programmatic importance, especially where underlying epidemics are still increasing.

Community and Campus COVID-19 Risk Uncertainty Under University Reopening Scenarios: Model-Based Analysis

BACKGROUND

Significant uncertainty has existed about the safety of reopening college and university campuses before the COVID-19 pandemic is better controlled. Moreover, little is known about the effects that on-campus students may have on local higher-risk communities.

OBJECTIVE

We aimed to estimate the range of potential community and campus COVID-19 exposures, infections, and mortality under various university reopening plans and uncertainties.

METHODS

We developed campus-only, community-only, and campus × community epidemic differential equations and agent-based models, with inputs estimated via published and grey literature, expert opinion, and parameter search algorithms. Campus opening plans (spanning fully open, hybrid, and fully virtual approaches) were identified from websites and publications. Additional student and community exposures, infections, and mortality over 16-week semesters were estimated under each scenario, with 10% trimmed medians, standard deviations, and probability intervals computed to omit extreme outliers. Sensitivity analyses were conducted to inform potential effective interventions.

RESULTS

Predicted 16-week campus and additional community exposures, infections, and mortality for the base case with no precautions (or negligible compliance) varied significantly from their medians (4- to 10-fold). Over 5% of on-campus students were infected after a mean of 76 (SD 17) days, with the greatest increase (first inflection point) occurring on average on day 84 (SD 10.2 days) of the semester and with total additional community exposures, infections, and mortality ranging from 1-187, 13-820, and 1-21 per 10,000 residents, respectively. Reopening precautions reduced infections by 24%-26% and mortality by 36%-50% in both populations. Beyond campus and community reproductive numbers, sensitivity analysis indicated no dominant factors that interventions could primarily target to reduce the magnitude and variability in outcomes, suggesting the importance of comprehensive public health measures and surveillance.

CONCLUSIONS

Community and campus COVID-19 exposures, infections, and mortality resulting from reopening campuses are highly unpredictable regardless of precautions. Public health implications include the need for effective surveillance and flexible campus operations.

Potential Community and Campus Covid-19 Outcomes Under University and College Reopening Scenarios

BACKGROUND

Significant uncertainty exists in many countries about the safety of, and best strategies for, reopening college and university campuses until the Covid-19 pandemic is better controlled. Little also is known about the effects on-campus students may have on local higher-risk communities. We aimed to estimate potential community and campus Covid-19 exposures, infections, and mortality due to various university reopening and precaution plans under current ranges of assumptions and uncertainties.

METHODS

We developed and calibrated campus-only, community-only, and campus-x-community epidemic differential equation and agent-based models. Input parameters for campus and surrounding communities were estimated via published and grey literature, scenario development, expert opinion, accuracy optimization algorithms, and Monte Carlo simulation; models were cross-validated against each other using February-June 2020 data from heterogeneous U.S. counties and states. Campus opening plans (spanning various fully open, hybrid, and fully virtual approaches) were identified from websites and publications. All scenarios were simulated assuming 16-week semesters and estimated ranges for Covid-19 prevalence among community residents and arriving students, precaution compliance, contact frequency, virus attack rates, and tracing and isolation effectiveness. Additional student and community exposures, infections, and mortality were estimated under each scenario, with 10% trimmed medians, standard deviations, and probability intervals computed to omit extreme outlier scenarios. Factorial analyses were conducted to identify intervention inputs with largest and smallest effects.

RESULTS

As a base case with no precautions (or no compliance), predicted 16-week student infections and mortality under normal operations ranged significantly from 471 to 9,495 (median: 2,286, SD: 2,627) and 0 to 123 (median: 9, SD: 14) per 10,000 students, respectively. The maximum active exposures across a semester was 15.76% of all students warranting tracing. Total additional community exposures, infections, and mortality ranged from 1 to 187, 13 to 820, and 1 to 21 per 10,000 residents, respectively. 1% and 5% of on-campus students were infected after a mean (SD) of 11 (3) and 76 (17) days, respectively; >10% students infected by the end of a semester in 34.8% of scenarios, with the greatest increase (first inflection point) occurring on aver-age on day 84 (SD: 10.2 days). Common reopening precautions reduced infections by 24% to 26% and mortality by 36% to 50% in both populations. Uncertainties in many factors, however, produced tremendous variability in all results, ranging from medians by -67% to +342%.

CONCLUSIONS

Consequences on community and student Covid-19 exposures, infections, and mortality of reopening physical campuses are very highly unpredictable, depending on a combination of random chance, controllable (e.g. physical layouts), and uncontrollable (e.g. human behavior) factors. Implications include needs for criteria to adapt campus operations mid-semester, methods to detect when necessary, and contingency plans for doing so.

Evolving HIV epidemics: the urgent need to refocus on populations with risk

Purpose of review

To explore the comparative importance of HIV infections among key populations and their intimate partners as HIV epidemics evolve, and to review implications for guiding responses.

Recent findings

Even as concentrated epidemics evolve, new infections among current and former key population members and their intimate partners dominate new infections. Prevalent infections in the general population grow primarily because of key population turnover and infections among their intimate partners. In generalized epidemic settings, data and analysis on key populations are often inadequate to assess the impact of key population-focused responses, so they remain limited in coverage and under resourced. Models must incorporate downstream infections in comparing impacts of alternative responses.

Summary

Recognize that every epidemic is unique, moving beyond the overly simplistic concentrated/generalized epidemic paradigm that can misdirect resources. Guide HIV responses by gathering and using locally relevant data, understanding risk heterogeneity, and applying modeling at both national and sub-national levels to optimize resource allocations among different populations for greatest impact. Translate this improved understanding into clear, unequivocal advice for policymakers on where to focus for impact, breaking them free of the generalized/concentrated paradigm limiting their thinking and affecting their decisions.

Sex Worker Community-led Interventions Interrupt Sexually Transmitted Infection/Human Immunodeficiency Virus Transmission and Improve Human Immunodeficiency Virus Cascade Outcomes: A Program Review from South India

A review of a community-led sex worker program in 2 districts of South India that has achieved near elimination of curable sexually transmitted infections and optimal human immunodeficiency virus cascade outcomes.

Supplemental digital content is available in the text.

Ashodaya Samithi, an organization run by and for female, male, and transgender sex workers in Mysore, India, has worked since 2004 to prevent sexually transmitted infection (STI)/human immunodeficiency virus (HIV) transmission and improve HIV cascade outcomes. We reviewed published and programmatic data, including measures of coverage, uptake, utilization and retention, and relate STI/HIV outcomes to evolving phases of community mobilization. Early interventions designed “for” sex workers mapped areas of sex work and reached half the sex workers in Mysore with condoms and STI services. By late 2005, when Ashodaya Samithi registered as a community-based organization, interventions were implemented “with” sex workers as active partners. Microplanning was introduced to enable peer educators to better organize and monitor their outreach work to reach full coverage. By 2008, programs were run “by” sex workers, with active community decision making. Program data show complete coverage of community outreach and greater than 90% clinic attendance for quarterly checkups by 2010. Reported condom use with last occasional client increased from 65% to 90%. Surveys documented halving of HIV and syphilis prevalence between 2004 and 2009, while gonorrhoea declined by 80%. Between 2005 and 2013, clinic checkups tripled, whereas the number of STIs requiring treatment declined by 99%. New HIV infections also declined, and Ashodaya achieved strong cascade outcomes for HIV testing, antiretroviral treatment linkage, and retention. Program performance dropped markedly during several periods of interrupted funding, then rebounded when restored. Ashodaya appear to have achieved rapid STI/HIV control with community-led approaches including microplanning. Available data support near elimination of curable STIs and optimal cascade outcomes.

Special Measures for Quality and Challenged Providers: Study Protocol for Evaluating the Impact of Improvement Interventions in NHS Trusts

Background: Healthcare organisations in England rated as inadequate in terms of leadership and one other domain enter the Special Measures for Quality (SMQ) regime to receive increased support and oversight. There is also a ‘watch list’ of challenged National Health Service (NHS) providers at risk of going into SMQ that receive support. There is limited knowledge about whether the interventions used to deliver this support drive improvements in quality, their costs, and whether they strike the right balance between support and scrutiny. The study will seek to determine how provider organisations respond to these interventions, and whether and how these interventions impact organisations’ capacity to achieve and sustain quality improvements over time.

Methods: This is a multi-site, mixed methods study. We will carry out interviews at national level to understand the programme theory underpinning the interventions. We will conduct 8 NHS case studies to explore the impact and implementation of the interventions that form part of the SMQ and challenged providers programme. We will use a conceptual framework based on models of organisational readiness for change and draw on board maturity research for implementing quality improvement. We will also review the use of quantitative metrics and data for tracking the progress of improvements in quality of care and sustainability upon leaving SMQ, as well as the costs and benefits of the interventions through a cost-consequence analysis (CCA).

Discussion: High-quality interventions that successfully support struggling healthcare organisations are essential and an issue that is an international concern. Our study will allow a greater understanding of the programme theory, impact, and staff views and experiences of the SMQ and challenged providers regime. Formative feedback will be reported to key stakeholders.

HIV Modes of Transmission in Sudan in 2014

Background: In Sudan, where studies on HIV dynamics are few, model projections provide an additional source of information for policy-makers to identify data collection priorities and develop prevention programs. In this study, we aimed to estimate the distribution of new HIV infections by mode of exposure and to identify populations who are disproportionately contributing to the total number of new infections in Sudan.

Methods: We applied the modes of transmission (MoT) mathematical model in Sudan to estimate the distribution of new HIV infections among the 15-49 age group for 2014, based on the main routes of exposure to HIV. Data for the MoT model were collected through a systematic review of peer-reviewed articles, grey literature, interviews with key participants and focus groups. We used the MoT uncertainty module to represent uncertainty in model projections and created one general model for the whole nation and 5 sub-models for each region (Northern, Central, Eastern, Kurdufan, and Khartoum regions). We also examined how different service coverages could change HIV incidence rates and distributions in Sudan.

Results: The model estimated that about 6000 new HIV infections occurred in Sudan in 2014 (95% CI: 4651-7432). Men who had sex with men (MSM) (30.52%), female sex workers (FSW) (16.37%), and FSW’s clients accounted (19.43%) for most of the new HIV cases. FSW accounted for the highest incidence rate in the Central, Kurdufan, and Khartoum regions; and FSW’s clients had the highest incidence rate in the Eastern and Northern regions. The annual incidence rate of HIV in the total adult population was estimated at 330 per 1 000 000 populations. The incidence rate was at its highest in the Eastern region (980 annual infections per 1 000 000 populations).

Conclusion: Although the national HIV incidence rate estimate was relatively low compared to that observed in some sub-Saharan African countries with generalized epidemics, a more severe epidemic existed within certain regions and key populations. HIV burden was mostly concentrated among MSM, FSW, and FSW’s clients both nationally and regionally. Thus, the authorities should pay more attention to key populations and Eastern and Northern regions when developing prevention programs. The findings of this study can improve HIV prevention programs in Sudan.

HIV treatment response among female sex workers participating in a treatment as prevention demonstration project in Cotonou, Benin

OBJECTIVES

Female sex workers (FSWs) play a key role in HIV transmission in West Africa, while they have limited access to antiretroviral therapy (ART). In line with UNAIDS recommendations extending ART to all HIV-infected individuals, we conducted this demonstration project on immediate treatment as prevention (TasP) among FSWs in Cotonou, Benin. We report data on treatment response and its relation to adherence, as well as on ART-resistant genotypes.

METHODS

Complete follow-up varied between 12 and 24 months. At each three-monthly visit, a questionnaire was administered, clinical examinations were carried out and blood samples collected. Adherence to treatment was estimated by self-report. Viral RNA was genotyped at baseline and final visits for drug resistance. Generalized estimating equations for repeated measures with a log-binomial link were used to analyze time trends and the association between adherence and virological response to treatment.

RESULTS

One-hundred-seven HIV-positive and ART-naive FSWs were enrolled; 59.8% remained in the cohort till study completion and 62.6% had a final visit. Viral load<1000 (below quantification limit [<50]) was attained in 73.1% (64.6%) of participants at month-6, 84.8% (71.2%) at month-12, and 80.9% (65.1%) at the final visit. The proportion of women with suppressed (below quantification limit) viral load increased with increasing self-reported adherence (p = 0.06 (0.003), tests for trend). The proportion of participants with CD4≤500 also decreased drastically throughout follow-up (p < .0001). Twelve participants exhibited ART-resistant genotypes at baseline, but only two at their final visit.

CONCLUSION

Our findings indicate that TasP is widely accepted among FSWs in Cotonou and could be implemented with relative success. However, due to mobility in this population, follow-up was sub-optimal, suggesting that large geographical coverage of FSW-friendly clinics is needed for sustained treatment implementation. We also fell short of the UNAIDS objective of 90% viral suppression among treated patients, underlining the need for better adherence support programs.

Cost-Effectiveness of Accelerated HIV Response Scenarios in Côte d'Ivoire

BACKGROUND

Despite Côte d'Ivoire epidemic being labeled as "generalized," key populations (KPs) are important to overall transmission. Using a dynamic model of HIV transmission, we previously estimated the impact of several treatment-as-prevention strategies that reached-or missed-the UNAIDS 90-90-90 targets in different populations groups, including KP and clients of female sex workers (CFSWs). To inform program planning and resources allocation, we assessed the cost-effectiveness of these scenarios.

METHODS

Costing was performed from the provider's perspective. Unit costs were obtained from the Ivorian Programme national de lutte contre le Sida (USD 2015) and discounted at 3%. Net incremental cost-effectiveness ratios (ICER) per adult HIV infection prevented and per disability-adjusted life-years (DALY) averted were estimated over 2015-2030.

RESULTS

The 3 most cost-effective and affordable scenarios were the ones that projected current programmatic trends [ICER = $210; 90% uncertainty interval (90% UI): $150-$300], attaining the 90-90-90 objectives among KP and CFSW (ICER = $220; 90% UI: $80-$510), and among KP only (ICER = $290; 90% UI: $90-$660). The least cost-effective scenario was the one that reached the UNAIDS 90-90-90 target accompanied by a 25% point drop in condom use in KP (ICER = $710; 90% UI: $450-$1270). In comparison, the UNAIDS scenario had a net ICER of $570 (90% UI: $390-$900) per DALY averted.

CONCLUSIONS

According to commonly used thresholds, accelerating the HIV response can be considered very cost-effective for all scenarios. However, when balancing epidemiological impact, cost-effectiveness, and affordability, scenarios that sustain both high condom use and rates of viral suppression among KP and CFSW seem most promising in Côte d'Ivoire.

Genetic Cluster Analysis for HIV Prevention

PURPOSE OF REVIEW

This review summarizes the use of genetic similarity clusters to understand HIV transmission and inform prevention efforts.

RECENT FINDINGS

Recent emphases include the development of real-time cluster identification in order to interrupt transmission chains, the use of clusters to estimate rates of transmission along the HIV care cascade, and the extension of cluster analyses to understand transmission in the generalized epidemics of sub-Saharan Africa. Importantly, this recent empirical work has been accompanied by theoretical work that elucidates the processes that underlie HIV genetic similarity clusters; multiple studies suggest that clusters are not necessarily enriched with individuals with high transmission rates, but rather can reflect variation in sampling times within a population, with individuals sampled early in infection more likely to cluster. Analyses of genetic similarity clusters have great promise to inform HIV epidemiology and prevention. Future emphases should include the collection of additional sequence data from underrepresented populations, such as those in sub-Saharan Africa, and further development and evaluation of clustering methods.

HIV-related data among key populations to inform evidence-based responses: protocol of a systematic review

BACKGROUND

Key populations who bear a disproportionate burden of HIV, including female sex workers, men who have sex with men, people who use drugs, transgender people, and incarcerated populations, have been understudied, especially in the context of broadly generalized HIV epidemics. Program and investment planning documents often do not take into account the data that do exist. Prior systematic reviews have been comprehensive, but lack sustainability and relevance over time. This review aims to synthesize all available data for key populations and present the data through an accessible, updatable user-friendly graphic interface. The outputs of this systematic review will serve as a resource for decision-makers, providing government stakeholders and donors with the tools to make evidence-based decisions for national planning.

METHODS

We will conduct a systematic review of data published or made available between January 1, 2006, and January 1, 2019, that captures the burden of HIV, both prevalence and incidence estimates, HIV prevention and treatment cascades, key population size estimates, experienced violence, consistent condom use, and engagement with healthcare systems for female sex workers, men who have sex with men, people who use drugs, transgender people, and incarcerated populations. A team of reviewers will use Covidence to conduct two independent reviews of both title/abstract and full text for each article. REDCap will be used for data abstraction and storage.

DISCUSSION

Findings from this systematic review and the development of the enhanced graphical interface to display data, along with ongoing efforts to build capacity among key stakeholders to better use and interpret available data, will help ensure that available epidemiologic data related to key populations can be appropriately used to guide large-scale HIV funding and programmatic responses.

SYSTEMATIC REVIEW REGISTRATION

PROPSERO CRD42016047259 .

The importance of local epidemic conditions in monitoring progress towards HIV epidemic control in Kenya: a modelling study

INTRODUCTION

Setting and monitoring progress towards targets for HIV control is critical in ensuring responsive programmes. Here, we explore how to apply targets for reduction in HIV incidence to local settings and which indicators give the strongest signal of a change in incidence in the population and are therefore most important to monitor.

METHODS

We use location-specific HIV transmission models, tailored to the epidemics in the counties and major cities in Kenya, to project a wide range of plausible future epidemic trajectories through varying behaviours, treatment coverage and prevention interventions. We look at the change in incidence across modelled scenarios in each location between 2015 and 2030 to inform local target setting. We also simulate the measurement of a library of potential indicators and assess which are most strongly associated with a change in incidence.

RESULTS

Considerable variation was observed in the trajectory of the local epidemics under the plausible scenarios defined (only 10 of 48 locations saw a median reduction in incidence of greater than or equal to an 80% target by 2030). Indicators that provide strong signals in certain epidemic types may not perform consistently well in settings with different epidemiological features. Predicting changes in incidence is more challenging in advanced generalized epidemics compared to concentrated epidemics where changes in high-risk sub-populations track more closely to the population as a whole. Many indicators demonstrate only limited association with incidence (such as "condom use" or "pre-exposure prophylaxis coverage"). This is because many other factors (low effectiveness, impact of other interventions, countervailing changes in risk behaviours, etc.) can confound the relationship between interventions and their ultimate long-term impact, especially for an intervention with low expected coverage. The population prevalence of viral suppression shows the most consistent associations with long-term changes in incidence even in the largest generalized epidemics.

CONCLUSIONS

Target setting should be appropriate for the local epidemic and what can feasibly be achieved. There is no one universally reliable indicator to predict future HIV incidence across settings. Thus, the signature of epidemic control must contain indications of success across a wide range of interventions and outcomes.

Defining the population attributable fraction for infectious diseases

Background

The population attributable fraction (PAF) is used to quantify the contribution of a risk group to disease burden. For infectious diseases, high-risk individuals may increase disease risk for the wider population in addition to themselves; therefore methods are required to estimate the PAF for infectious diseases.

Methods

A mathematical model of disease transmission in a population with a high-risk group was used to compare existing approaches for calculating the PAF. We quantify when existing methods are consistent and when estimates diverge. We introduce a new method, based on the basic reproduction number, for calculating the PAF, which bridges the gap between existing methods and addresses shortcomings. We illustrate the methods with two examples of the contribution of badgers to bovine tuberculosis in cattle and the role of commercial sex in an HIV epidemic.

Results

We demonstrate that current methods result in irreconcilable PAF estimates, depending on how chains of transmission are categorized. Using two novel simple formulae for emerging and endemic diseases, we demonstrate that the largest differences occur when transmission in the general population is not self-sustaining. Crucially, some existing methods are not able to discriminate between multiple risk groups. We show that compared with traditional estimates, assortative mixing leads to a decreased PAF, whereas disassortative mixing increases PAF.

Conclusions

Recent methods for calculating the population attributable fraction (PAF) are not consistent with traditional approaches. Policy makers and users of PAF statistics should be aware of these differences. Our approach offers a straightforward and parsimonious method for calculating the PAF for infectious diseases.

The contributions and future direction of Program Science in HIV/STI prevention

Background

Program Science is an iterative, multi-phase research and program framework where programs drive the scientific inquiry, and both program and science are aligned towards a collective goal of improving population health.

Discussion

To achieve this, Program Science involves the systematic application of theoretical and empirical knowledge to optimize the scale, quality and impact of public health programs. Program Science tools and approaches developed for strategic planning, program implementation, and program management and evaluation have been incorporated into HIV and sexually transmitted infection prevention programs in Kenya, Nigeria, India, and the United States.

Conclusion

In this paper, we highlight key scientific contributions that emerged from the growing application of Program Science in the field of HIV and STI prevention, and conclude by proposing future directions for Program Science.

Effects of exposure to an intensive HIV-prevention programme on behavioural changes among female sex workers in Nairobi, Kenya

While Kenya has had a long-standing national HIV-prevention programme, evidence on the level of exposure to its interventions and related effects on behavioural changes among female sex workers (FSWs) is limited. Using cross-sectional behavioural data collected in 2013 from 1 357 FSWs aged 18 years and above in Nairobi, Kenya, this study explores the relationship between FSW programme exposure levels and behavioural outcomes including condom use, sexually transmitted infection (STI)-treatment, and empowerment measures like disclosure of self-identity and violence reporting. We categorised programme exposure levels as none, moderate and intensive. Multivariate logistic regression was used for analysis. Overall, 35% of the FSWs were not exposed to any HIV prevention programme, whereas about 24% had moderate and 41% had intensive exposure. FSWs having intensive programme exposure had a higher likelihood of using condoms consistently with occasional clients (AOR: 1.57; 95% CI: 1.08-2.31) and seeking treatment for STIs (AOR: 3.37; 95% CI: 1.63-7.02) compared to FSWs with no or moderate exposure. Intensive programme exposure was also associated with higher self-disclosure of sex-work identity (AOR: 1.63; 95% CI: 1.19-2.24), reporting of violence to police (AOR: 2.45; 95% CI: 1.03-5.84), and negotiation of condom use at last sex when the client was under the influence of alcohol (AOR: 1.63; 95% CI: 0.94-2.82). Although HIV prevention programmes in Kenya have been underway for over a decade, programme efforts were largely focused on saturating the coverage (intervention breadth). Strategies should now focus on ensuring improved quality of contacts through intensified programme exposure (intervention depth) to enhance gains in behavioural change among FSWs and preventing the burden of HIV infection among them.

Mapping of new HIV infections in Morocco and impact of select interventions

OBJECTIVES

The aim of this study was to assess HIV modes of exposure in Morocco at the national level and also for Souss-Massa-Drâa, the region most affected by HIV. Another aim was to assess the impact of different scenarios of select intervention packages.

METHODS

The Modes of Transmission Model was adapted and used, and was parameterized using quality bio-behavioral surveillance data among key populations, routine data sources, and literature reviews.

RESULTS

Nationally in 2013, the largest number of new infections occurred among clients of female sex workers (FSWs) (25%; 95% confidence interval (CI) 14-37%), followed by men who have sex with men (MSM) (22%; 95% CI 12-35%), HIV serodiscordant couples (22%; 95% CI 12-34%), FSWs (11%; 95% CI 6-18%), and people who inject drugs (5%; 95% CI 2-9%). A similar pattern of results was observed in Souss-Massa-Drâa, but the HIV incidence rate was four-fold that at the national level. Different scenarios of feasible intervention packages reduced HIV incidence by 8-44%.

CONCLUSIONS

Commercial heterosexual sex networks continue as the leading driver of the epidemic, with half of HIV incidence. A quarter of new infections occurred among MSM, a third of which in Souss-Massa-Drâa. Feasible expanded coverage of interventions could lead to large reductions in incidence.

The contribution of unsafe blood transfusion to human immunodeficiency virus incidence in sub-Saharan Africa: reexamination of the 5% to 10% convention

BACKGROUND

Historical estimates have attributed 5% to 10% of new human immunodeficiency virus (HIV) infections in sub-Saharan Africa (SSA) to unsafe blood transfusions. Although frequently cited, the validity of this statistic is uncertain or outdated. Recent estimates suggest blood transfusion's contribution to new HIV infections in the region may be much lower.

STUDY DESIGN AND METHODS

We searched the peer-reviewed and gray literature for quantitative estimates of the specific contribution of unsafe blood transfusion to the proportion of new HIV infections occurring in SSA. The sources and methods used to generate attribution estimates were evaluated against published country-specific HIV prevalence data.

RESULTS

Despite multiple secondary citations, a primary published source attributing 5% to 10% of new HIV infections to blood transfusions in SSA could not be established for the current era. The United Nations Programme on HIV and AIDS (UNAIDS) modes of transmission (MOT) reports representing 15 countries suggest that between 0 and 1.1% of new HIV infections per year (median, 0.2% or approx. two out of 1000 new infections each year) may be attributable to blood transfusions.

CONCLUSION

Recent modeled estimates suggest that blood transfusions account for a very low proportion of new HIV infections in SSA, likely an order of magnitude lower than 5% to 10%. Direct quantification of risk is challenging given the paucity of data on the variables that impact transfusion-associated HIV. Specifically, data on HIV incidence in blood donors, blood bank laboratory test performance, and posttransfusion surveillance are lacking. Findings suggest an urgent need for improved surveillance and modeling of transfusion-associated HIV transmission in the region.

The Incidence Patterns Model to Estimate the Distribution of New HIV Infections in Sub-Saharan Africa: Development and Validation of a Mathematical Model

BACKGROUND

Programmatic planning in HIV requires estimates of the distribution of new HIV infections according to identifiable characteristics of individuals. In sub-Saharan Africa, robust routine data sources and historical epidemiological observations are available to inform and validate such estimates.

METHODS AND FINDINGS

We developed a predictive model, the Incidence Patterns Model (IPM), representing populations according to factors that have been demonstrated to be strongly associated with HIV acquisition risk: gender, marital/sexual activity status, geographic location, "key populations" based on risk behaviours (sex work, injecting drug use, and male-to-male sex), HIV and ART status within married or cohabiting unions, and circumcision status. The IPM estimates the distribution of new infections acquired by group based on these factors within a Bayesian framework accounting for regional prior information on demographic and epidemiological characteristics from trials or observational studies. We validated and trained the model against direct observations of HIV incidence by group in seven rounds of cohort data from four studies ("sites") conducted in Manicaland, Zimbabwe; Rakai, Uganda; Karonga, Malawi; and Kisesa, Tanzania. The IPM performed well, with the projections' credible intervals for the proportion of new infections per group overlapping the data's confidence intervals for all groups in all rounds of data. In terms of geographical distribution, the projections' credible intervals overlapped the confidence intervals for four out of seven rounds, which were used as proxies for administrative divisions in a country. We assessed model performance after internal training (within one site) and external training (between sites) by comparing mean posterior log-likelihoods and used the best model to estimate the distribution of HIV incidence in six countries (Gabon, Kenya, Malawi, Rwanda, Swaziland, and Zambia) in the region. We subsequently inferred the potential contribution of each group to transmission using a simple model that builds on the results from the IPM and makes further assumptions about sexual mixing patterns and transmission rates. In all countries except Swaziland, individuals in unions were the single group contributing to the largest proportion of new infections acquired (39%-77%), followed by never married women and men. Female sex workers accounted for a large proportion of new infections (5%-16%) compared to their population size. Individuals in unions were also the single largest contributor to the proportion of infections transmitted (35%-62%), followed by key populations and previously married men and women. Swaziland exhibited different incidence patterns, with never married men and women accounting for over 65% of new infections acquired and also contributing to a large proportion of infections transmitted (up to 56%). Between- and within-country variations indicated different incidence patterns in specific settings.

CONCLUSIONS

It is possible to reliably predict the distribution of new HIV infections acquired using data routinely available in many countries in the sub-Saharan African region with a single relatively simple mathematical model. This tool would complement more specific analyses to guide resource allocation, data collection, and programme planning.

Data and methods to characterize the role of sex work and to inform sex work programs in generalized HIV epidemics: evidence to challenge assumptions

In the context of generalized human immunodeficiency virus (HIV) epidemics, there has been limited recent investment in HIV surveillance and prevention programming for key populations including female sex workers. Often implicit in the decision to limit investment in these epidemic settings are assumptions including that commercial sex is not significant to the sustained transmission of HIV, and HIV interventions designed to reach "all segments of society" will reach female sex workers and clients. Emerging empiric and model-based evidence is challenging these assumptions. This article highlights the frameworks and estimates used to characterize the role of sex work in HIV epidemics as well as the relevant empiric data landscape on sex work in generalized HIV epidemics and their strengths and limitations. Traditional approaches to estimate the contribution of sex work to HIV epidemics do not capture the potential for upstream and downstream sexual and vertical HIV transmission. Emerging approaches such as the transmission population attributable fraction from dynamic mathematical models can address this gap. To move forward, the HIV scientific community must begin by replacing assumptions about the epidemiology of generalized HIV epidemics with data and more appropriate methods of estimating the contribution of unprotected sex in the context of sex work.

Feasible, Efficient and Necessary, without Exception - Working with Sex Workers Interrupts HIV/STI Transmission and Brings Treatment to Many in Need

BACKGROUND AND OVERVIEW

High rates of partner change in sex work-whether in professional, 'transactional' or other context-disproportionately drive transmission of HIV and other sexually transmitted infections. Several countries in Asia have demonstrated that reducing transmission in sex work can reverse established epidemics among sex workers, their clients and the general population. Experience and emerging research from Africa reaffirms unprotected sex work to be a key driver of sexual transmission in different contexts and regardless of stage or classification of HIV epidemic. This validation of the epidemiology behind sexual transmission carries an urgent imperative to realign prevention resources and scale up effective targeted interventions in sex work settings, and, given declining HIV resources, to do so efficiently. Eighteen articles in this issue highlight the importance and feasibility of such interventions under four themes: 1) epidemiology, data needs and modelling of sex work in generalised epidemics; 2) implementation science addressing practical aspects of intervention scale-up; 3) community mobilisation and 4) the treatment cascade for sex workers living with HIV.

CONCLUSION

Decades of empirical evidence, extended by analyses in this collection, argue that protecting sex work is, without exception, feasible and necessary for controlling HIV/STI epidemics. In addition, the disproportionate burden of HIV borne by sex workers calls for facilitated access to ART, care and support. The imperative for Africa is rapid scale-up of targeted prevention and treatment, facilitated by policies and action to improve conditions where sex work takes place. The opportunity is a wealth of accumulated experience working with sex workers in diverse settings, which can be tapped to make up for lost time. Elsewhere, even in countries with strong interventions and services for sex workers, an emerging challenge is to find ways to sustain them in the face of declining global resources.

Optima: A Model for HIV Epidemic Analysis, Program Prioritization, and Resource Optimization

Optima is a software package for modeling HIV epidemics and interventions that we developed to address practical policy and program problems encountered by funders, governments, health planners, and program implementers. Optima's key feature is its ability to perform resource optimization to meet strategic HIV objectives, including HIV-related financial commitment projections and health economic assessments. Specifically, Optima allows users to choose a set of objectives (such as minimizing new infections, minimizing HIV-related deaths, and/or minimizing long-term financial commitments) and then determine the optimal resource allocation (and thus program coverage levels) for meeting those objectives. These optimizations are based on the following: calibrations to epidemiological data; assumptions about the costs of program implementation and the corresponding coverage levels; and the effects of these programs on clinical, behavioral, and other epidemiological outcomes. Optima is flexible for which population groups (specified by behavioral, epidemiological, and/or geographical factors) and which HIV programs are modeled, the amount of input data used, and the types of outputs generated. Here, we introduce this model and compare it with existing HIV models that have been used previously to inform decisions about HIV program funding and coverage targets. Optima has already been used in more than 20 countries, and there is increasing demand from stakeholders to have a tool that can perform evidence-based HIV epidemic analyses, revise and prioritize national strategies based on available resources, set program coverage targets, amend subnational program implementation plans, and inform the investment strategies of governments and their funding partners.

What really is a concentrated HIV epidemic and what does it mean for West and Central Africa? Insights from mathematical modeling

BACKGROUND

HIV epidemics have traditionally been classified as "concentrated" among key populations if overall HIV prevalence was below 1% and as "generalized" otherwise. We aimed to objectively determine the utility of this classification by determining how high overall HIV prevalence can reach in epidemics driven by unprotected sex work (SW) and how estimates of the contribution of SW to HIV transmission changes over time in these epidemics.

METHODS

We developed a deterministic model of HIV transmission specific to West and Central Africa to simulate 1000 synthetic HIV epidemics, where SW is the sole behavioral driver that sustains HIV in the population (ie, truly concentrated epidemics), and it is based on a systematic extraction of model parameters specific to West and Central Africa. We determined the range of plausible HIV prevalence in the total population over time and calculated the population attributable fraction (PAF) of SW over different time periods.

RESULTS

In 1988 and 2008, HIV prevalence across the 1000 synthetic concentrated HIV epidemics ranged (5th-95th percentile) between 0.1%-4.2% and 0.1%-2.8%, respectively. The maximum HIV prevalence peaked at 12%. The PAF of SW measured from 2008 over 1 year was <5%-18% compared with 16%-59% over 20 years in these SW-driven epidemics.

CONCLUSIONS

Even high HIV-prevalence epidemics can be driven by unprotected SW and therefore concentrated. Overall, HIV prevalence and the short-term PAF are poor makers of underlying transmission dynamics and underestimate the role of SW in HIV epidemics and thus should not be used alone to inform HIV programs.

Scaling-up HIV responses with key populations in West Africa

BACKGROUND

Despite decades of HIV responses in pockets of West and Central Africa (WCA), the HIV response with key populations remains an understudied area. Recently, there has been a proliferation of studies highlighting epidemiologic and behavioral data that challenge attitudes of complacency among donors and country governments uncomfortable in addressing key populations.

METHODS

The articles in this series highlight new studies that provide a better understanding of the epidemiologic and structural burden facing key populations in the WCA region and how to improve responses through more effective targeting.

RESULTS

Key populations face pervasive structural barriers including institutional and sexual violence and an intersection of stigma, criminalization, and marginalization as sexual minorities. Despite decades of smaller interventions that have shown the importance of integrated services for key populations, there remains incongruent provision of outreach or testing or family planning pointing to sustained risk. There remains an incongruent resource provision for key populations where they shoulder the burden of HIV and their access to services alone could turn around HIV epidemics within the region.

CONCLUSIONS

These proximal and distal determinants must be addressed in regional efforts, led by the community, and resourced for scale, targeting those most at risk for the acquisition and transmission of HIV. This special issue builds the knowledge base for the region focusing on interventions that remove barriers to service access including treatment uptake for those living with HIV. Better analysis and use of data for strategic planning are shown to lead to more effective targeting of prevention, care, and HIV treatment programs with key populations. These articles further demonstrate the immediate need for comprehensive action to address HIV among key populations throughout the WCA region.

The HIV Modes of Transmission model: a systematic review of its findings and adherence to guidelines

INTRODUCTION

The HIV Modes of Transmission (MOT) model estimates the annual fraction of new HIV infections (FNI) acquired by different risk groups. It was designed to guide country-specific HIV prevention policies. To determine if the MOT produced context-specific recommendations, we analyzed MOT results by region and epidemic type, and explored the factors (e.g. data used to estimate parameter inputs, adherence to guidelines) influencing the differences.

METHODS

We systematically searched MEDLINE, EMBASE and UNAIDS reports, and contacted UNAIDS country directors for published MOT results from MOT inception (2003) to 25 September 2012.

RESULTS

We retrieved four journal articles and 20 UNAIDS reports covering 29 countries. In 13 countries, the largest FNI (range 26 to 63%) was acquired by the low-risk group and increased with low-risk population size. The FNI among female sex workers (FSWs) remained low (median 1.3%, range 0.04 to 14.4%), with little variability by region and epidemic type despite variability in sexual behaviour. In India and Thailand, where FSWs play an important role in transmission, the FNI among FSWs was 2 and 4%, respectively. In contrast, the FNI among men who have sex with men (MSM) varied across regions (range 0.1 to 89%) and increased with MSM population size. The FNI among people who inject drugs (PWID, range 0 to 82%) was largest in early-phase epidemics with low overall HIV prevalence. Most MOT studies were conducted and reported as per guidelines but data quality remains an issue.

CONCLUSIONS

Although countries are generally performing the MOT as per guidelines, there is little variation in the FNI (except among MSM and PWID) by region and epidemic type. Homogeneity in MOT FNI for FSWs, clients and low-risk groups may limit the utility of MOT for guiding country-specific interventions in heterosexual HIV epidemics.