HIV treatment as prevention: systematic comparison of mathematical models of the potential impact of antiretroviral therapy on HIV incidence in South Africa

Improving the contribution of mathematical modelling evidence to guidelines and policy: Experiences from tuberculosis

We read with great interest the recent paper by Lo et al., who argue that there is an urgent need to ensure the quality of modelling evidence used to support international and national guideline development. Here we outline efforts by the Tuberculosis Modelling and Analysis Consortium, together with the World Health Organization Global Task Force on Tuberculosis Impact Measurement, to develop material to improve the quality and transparency of country-level tuberculosis modelling to inform decision-making.

Challenges and Opportunities in Big Data Science to Address Health Inequities and Focus the HIV Response

PURPOSE OF REVIEW

Big Data Science can be used to pragmatically guide the allocation of resources within the context of national HIV programs and inform priorities for intervention. In this review, we discuss the importance of grounding Big Data Science in the principles of equity and social justice to optimize the efficiency and effectiveness of the global HIV response.

RECENT FINDINGS

Social, ethical, and legal considerations of Big Data Science have been identified in the context of HIV research. However, efforts to mitigate these challenges have been limited. Consequences include disciplinary silos within the field of HIV, a lack of meaningful engagement and ownership with and by communities, and potential misinterpretation or misappropriation of analyses that could further exacerbate health inequities. Big Data Science can support the HIV response by helping to identify gaps in previously undiscovered or understudied pathways to HIV acquisition and onward transmission, including the consequences for health outcomes and associated comorbidities. However, in the absence of a guiding framework for equity, alongside meaningful collaboration with communities through balanced partnerships, a reliance on big data could continue to reinforce inequities within and across marginalized populations.

Forecasting the effect of HIV-targeted interventions on the age distribution of people with HIV in Kenya

OBJECTIVES

To provide accurate forecasts of the age distribution of people with HIV (PWH) in Kenya from 2025 to 2040.

DESIGN

Development of a compartmental model of HIV in Kenya, calibrated to historical estimates of HIV epidemiology.

METHODS

We forecasted changes in population size and age distribution of new HIV infections and PWH under the status quo and under scale-up of HIV services.

RESULTS

Without scale-up, new HIV infections were forecasted to fall from 34 000 (28 000-41 000) in 2,025 to 29 000 (15 000-57 000) in 2,040; the percentage of new infections occurring among persons over 30 increased from 33% (20-50%) to 40% (24-62%). The median age of PWH increased from 39 years (38-40) in 2025 to 43 years (39-46) in 2040, and the percentage of PWH over age 50 increased from 26% (23-29%) to 34% (26-43%). Under the full intervention scenario, new infections were forecasted to fall to 6,000 (3,000-12 000) in 2,040. The percentage of new infections occurring in people over age 30 increased to 52% (34-71%) in 2,040, and there was an additional shift in the age structure of PWH [forecasted median age of 46 (43-48) and 40% (33-47%) over age 50].

CONCLUSION

PWH in Kenya are forecasted to age over the next 15 years; improvements to the HIV care continuum are expected to contribute to the growing proportion of older PWH.

Moving beyond hotspots of HIV prevalence to geospatial hotspots of UNAIDS 95-95-95 targets in sub-Saharan Africa

The HIV epidemic in sub-Saharan Africa displays a varied geographical distribution, with particular regions termed as HIV hotspots due to a higher prevalence of infection. Addressing these hotspots is essential for controlling the epidemic. However, these regions, influenced by historical factors, challenge standard interventions. Legacy effects-the lasting impact of past events-play a substantial role in the persistence of these hotspots. To address this challenge of the standard interventions, we propose a shift towards the UNAIDS 95-95-95 targets. Spatial analysis of HIV viral load and antiretroviral therapy coverage can provide a more comprehensive perspective on the epidemic's dynamics. Studies in Zambia and Zimbabwe, using this approach, have revealed disparities in HIV care metrics across regions. By focusing on the UNAIDS 95-95-95 targets, more effective control strategies can be designed, with consideration of both historical and current factors. This approach would offer a solution-oriented strategy, emphasising tailored interventions based on specific regional needs.

Scenario design for infectious disease projections: Integrating concepts from decision analysis and experimental design

Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision makers and scientists. In the past decade, and especially during the COVID-19 pandemic, the field of epidemiology has seen substantial growth in the use of scenario projections. Multiple scenarios are often projected at the same time, allowing important comparisons that can guide the choice of intervention, the prioritization of research topics, or public communication. The design of the scenarios is central to their ability to inform important questions. In this paper, we draw on the fields of decision analysis and statistical design of experiments to propose a framework for scenario design in epidemiology, with relevance also to other fields. We identify six different fundamental purposes for scenario designs (decision making, sensitivity analysis, situational awareness, horizon scanning, forecasting, and value of information) and discuss how those purposes guide the structure of scenarios. We discuss other aspects of the content and process of scenario design, broadly for all settings and specifically for multi-model ensemble projections. As an illustrative case study, we examine the first 17 rounds of scenarios from the U.S. COVID-19 Scenario Modeling Hub, then reflect on future advancements that could improve the design of scenarios in epidemiological settings.

A novel simulation-based analysis of a stochastic HIV model with the time delay using high order spectral collocation technique

The economic impact of Human Immunodeficiency Virus (HIV) goes beyond individual levels and it has a significant influence on communities and nations worldwide. Studying the transmission patterns in HIV dynamics is crucial for understanding the tracking behavior and informing policymakers about the possible control of this viral infection. Various approaches have been adopted to explore how the virus interacts with the immune system. Models involving differential equations with delays have become prevalent across various scientific and technical domains over the past few decades. In this study, we present a novel mathematical model comprising a system of delay differential equations to describe the dynamics of intramural HIV infection. The model characterizes three distinct cell sub-populations and the HIV virus. By incorporating time delay between the viral entry into target cells and the subsequent production of new virions, our model provides a comprehensive understanding of the infection process. Our study focuses on investigating the stability of two crucial equilibrium states the infection-free and endemic equilibriums. To analyze the infection-free equilibrium, we utilize the LaSalle invariance principle. Further, we prove that if reproduction is less than unity, the disease free equilibrium is locally and globally asymptotically stable. To ensure numerical accuracy and preservation of essential properties from the continuous mathematical model, we use a spectral scheme having a higher-order accuracy. This scheme effectively captures the underlying dynamics and enables efficient numerical simulations.

Future HIV epidemic trajectories in South Africa and projected long-term consequences of reductions in general population HIV testing: a mathematical modelling study

BACKGROUND

After successful intensive interventions to rapidly increase HIV awareness, coverage of antiretroviral therapy (ART), and viral suppression, HIV programmes in eastern and southern Africa are considering scaling back of some interventions, such as widespread general population HIV testing. We aimed to model whether scaling back of general population HIV testing in South Africa could result in a resurgence of the HIV epidemic or substantial slowing of declines in HIV incidence, resulting in increased long-term ART.

METHODS

In this modelling study, we used the Thembisa 4.5 model (a deterministic compartmental model of HIV transmission in South Africa) to project the South African HIV epidemic to 2100 assuming the continuation of 2022 epidemiological conditions and HIV programme implementation. We assessed how implementing reductions in general population HIV testing services in 2025 (while maintaining antenatal, symptom-based, and risk-based testing modalities and other HIV prevention services at 2022 levels) would affect HIV incidence and prevalence among people aged 15-49 years, the year in which incidence would reach one per 1000 people aged 15-49 years (the threshold for virtual elimination of HIV), and associated costs, as well as numbers of additional new HIV infections and AIDS-related deaths. We also modelled the effects of delaying reductions in general population testing services by 5-year increments. Additionally, we modelled the potential effects of reductions in general population testing services in combination with increases or decreases in ART interruption rates (ie, the annual rate at which people who are on ART discontinue ART) and condom usage in 2025-35.

FINDINGS

If general population HIV testing services and the HIV risk environment of 2022 were maintained, we projected that HIV incidence would steadily decline from 4·95 (95% CI 4·40-5·34) per 1000 population in 2025 to 0·14 (0·05-0·31) per 1000 in 2100, and that the so-called virtual elimination threshold of less than one new infection per 1000 population per year would be reached in 2055 (95% CI 2051-2060). Scaling back of general population HIV testing services by 25%, 50%, or 75% in 2025 delayed time to reaching the virtual elimination threshold by 5, 13, or 35 years, respectively, whereas complete cessation of general population testing would result in the threshold not being attained by 2100. Although the incidence of HIV continued to fall when general HIV testing services were reduced, our modelling suggested that, with reductions of between 25% and 100%, between 396 000 (95% CI 299 000-474 000) and 2·50 million (1·97 million-2·98 million) additional HIV infections and between 115 000 (94 000-135 000) and 795 000 (670 000-926 000) additional AIDS-related deaths would occur between 2025 and 2075, depending on the extent of reduction in testing. Delaying reductions in general population HIV testing services for 5-25 years mitigated some of these effects. HIV testing accounted for only 5% of total programmatic costs at baseline; reducing testing moderately reduced short-term total annual costs, but increased annual costs after 25 years. Increases in ART interruption and reductions in condom usage were projected to slow the decline in incidence and increase the coverage of general HIV testing services required to control transmission but did not cause rapid resurgence in HIV infections.

INTERPRETATION

Our modelling suggests that scaling back of general population HIV testing would not result in a resurgence of HIV infections, but would delay attainment of incidence-reduction targets and result in long-term increases in HIV infections, AIDS-related deaths, and costs (via increased need for ART provision). HIV programmes need to balance short-term potential resource savings with long-term epidemic control objectives.

FUNDING

Bill & Melinda Gates Foundation.

A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study

BACKGROUND

Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV services, in this study we compare projections from five mathematical models of the HIV epidemic in South Africa: EMOD-HIV, Goals, HIV-Synthesis, Optima, and Thembisa.

METHODS

The five modelling groups produced estimates of the total population, HIV incidence, HIV prevalence, proportion of people living with HIV who are diagnosed, ART coverage, proportion of those on ART who are virally suppressed, AIDS-related deaths, total deaths, and the proportion of adult males who are circumcised. Estimates were made under a "status quo" scenario for the period 1990 to 2040. For each output variable we assessed the consistency of model estimates by calculating the coefficient of variation and examining the trend over time.

RESULTS

For most outputs there was significant inter-model variability between 1990 and 2005, when limited data was available for calibration, good consistency from 2005 to 2025, and increasing variability towards the end of the projection period. Estimates of HIV incidence, deaths in people living with HIV, and total deaths displayed the largest long-term variability, with standard deviations between 35 and 65% of the cross-model means. Despite this variability, all models predicted a gradual decline in HIV incidence in the long-term. Projections related to the UNAIDS 95-95-95 targets were more consistent, with the coefficients of variation below 0.1 for all groups except children.

CONCLUSIONS

While models produced consistent estimates for several outputs, there are areas of variability that should be investigated. This is important if projections are to be used in subsequent cost-effectiveness studies.

Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design

Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision makers and scientists. In the past decade, and especially during the COVID-19 pandemic, the field of epidemiology has seen substantial growth in the use of scenario projections. Multiple scenarios are often projected at the same time, allowing important comparisons that can guide the choice of intervention, the prioritization of research topics, or public communication. The design of the scenarios is central to their ability to inform important questions. In this paper, we draw on the fields of decision analysis and statistical design of experiments to propose a framework for scenario design in epidemiology, with relevance also to other fields. We identify six different fundamental purposes for scenario designs (decision making, sensitivity analysis, value of information, situational awareness, horizon scanning, and forecasting) and discuss how those purposes guide the structure of scenarios. We discuss other aspects of the content and process of scenario design, broadly for all settings and specifically for multi-model ensemble projections. As an illustrative case study, we examine the first 17 rounds of scenarios from the U.S. COVID-19 Scenario Modeling Hub, then reflect on future advancements that could improve the design of scenarios in epidemiological settings.

Effects of depression on medication adherence in HIV/AIDS patients: Korea HIV/AIDS cohort study

BACKGROUND

The number of people with HIV/AIDS has consistently increased in Korea since the first case of HIV/AIDS infection was reported in 1985. The depressive symptoms of patients with HIV/AIDS may lead to medication non-adherence. This study sought to investigate the cross-sectional and longitudinal association between depression and antiretroviral treatment adherence in the Korean HIV/AIDS population.

METHODS

We included participants of the Korea HIV/AIDS cohort study between 2009 and 2017. All information was collected at the enrollment and every annual visit, including sociodemographic characteristics, health-related behaviors, HIV/AIDS infection-related factors, depression score, and frequency of skipped medication. We performed a cross-sectional analysis of 601 participants registered between 2009 and 2017. Longitudinal data were evaluated by panel regression analysis in 515 patients who registered from 2009 to 2013.

RESULTS

In cross-sectional analysis, the HIV/AIDS patients with depressive symptoms were more likely to be non-adherent (adjusted OR = 0.52, 95 % CI 0.34, 0.79, p = 0.002). Medication adherence was significantly associated with a health-related lifestyle; the adjusted odds ratio of the non-smoking and non-drinking group was 1.75 (95 % CI 1.05, 2.90, p = 0.031). The longitudinal panel regression model revealed a significant negative impact of depression on medication adherence (adjusted OR = 0.50, 95 % CI 0.30, 0.84, p = 0.009). Non-smoking and non-drinking participants were 2.31 times more likely to adhere to antiretroviral treatment (95 % CI 1.29, 4.15, p = 0.005).

CONCLUSIONS

Our finding of depression and lifestyle modifications being significant contributors underscore the importance of proactive interventions to optimize the treatment outcomes of PLWH.

Estimating contact network properties by integrating multiple data sources associated with infectious diseases

To effectively mitigate the spread of communicable diseases, it is necessary to understand the interactions that enable disease transmission among individuals in a population; we refer to the set of these interactions as a contact network. The structure of the contact network can have profound effects on both the spread of infectious diseases and the effectiveness of control programs. Therefore, understanding the contact network permits more efficient use of resources. Measuring the structure of the network, however, is a challenging problem. We present a Bayesian approach to integrate multiple data sources associated with the transmission of infectious diseases to more precisely and accurately estimate important properties of the contact network. An important aspect of the approach is the use of the congruence class models for networks. We conduct simulation studies modeling pathogens resembling SARS-CoV-2 and HIV to assess the method; subsequently, we apply our approach to HIV data from the University of California San Diego Primary Infection Resource Consortium. Based on simulation studies, we demonstrate that the integration of epidemiological and viral genetic data with risk behavior survey data can lead to large decreases in mean squared error (MSE) in contact network estimates compared to estimates based strictly on risk behavior information. This decrease in MSE is present even in settings where the risk behavior surveys contain measurement error. Through these simulations, we also highlight certain settings where the approach does not improve MSE.

Temporal trend analysis of the HIV/AIDS burden before and after the implementation of antiretroviral therapy at the population level from 1990 to 2020 in Ghana

BACKGROUND

Antiretroviral therapy (ART) has helped reduce the burden of human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) in the majority of countries. Its contribution to the HIV/AIDS burden in Ghana is still understudied. This study examined HIV/AIDS trends in Ghana before (1990-2004) and after (2004-2020) the implementation and expansion of ART.

METHODS

We obtained HIV/AIDS epidemiology and treatment data for the years 1990-2020 from the United Nations Programme on HIV/AIDS. We investigated the impact of the ART rollout on HIV/AIDS in Ghana using Joinpoint regression models.

RESULTS

The HIV incidence, prevalence, and AIDS-related deaths decreased significantly after 2004, as ART coverage increased from 1% to 2004 to 60% in 2020. The HIV incidence decreased by approximately 3% (AAPC = -2.6%; 95% CI: -3.2, -1.9) per year from 1990 to 2004 and approximately 5% (AAPC = -4.5%; 95% CI: -4.9, -4.2) per year from 2004 to 2020. Between 1990 and 2004, the HIV prevalence increased by approximately 5% (AAPC = 4.7%; 95% CI: 3.6, 5.8) per year but decreased by 2% (AAPC = -1.9%; 95% CI: -2.1, -1.6) per year between 2004 and 2020. Between 1990 and 2004, the annual increase in AIDS-related mortality was 14% (AAPC = 13.8%; 95% CI: 12.6, 15.0), but between 2004 and 2020, it decreased at nearly a 4% (AAPC= -3.6%; 95% CI: -4.7, -2.5) annual rate.

CONCLUSIONS

We found trends indicating progress in Ghana's fight against HIV/AIDS. However, the most significant declines occurred after the introduction of ART, suggesting that the scale-up of ART may have contributed to the decline in HIV/AIDS in Ghana. We advocate for the rapid expansion of ART in Ghana.

Biomedical bargains: Negotiating "safe sex" on antiretroviral treatment in rural South Africa

Wide-scale availability of antiretroviral treatment (ART) has transformed the global landscape for HIV prevention, shifting emphasis away from a strictly behavioral focus on changing sexual practices towards a biomedical approach. Successful ART management is measured by an undetectable viral load, which helps maintain overall health and prevent onward viral transmission. The latter utility of ART, however, must be understood in the context of its implementation. In South Africa, ART has become easily accessible - yet ART knowledge spreads unevenly, while counseling advice and normative expectations and experiences of gender and aging interact to inform sexual practices. As ART enters the sexual lives of middle-aged and older people living with HIV (MOPLH), a population growing rapidly, how has it informed sexual decisions and negotiations? Drawing on in-depth interviews with MOPLH on ART, corroborated with focus group discussions and national ART-related policies and guidelines, we find that for MOPLH, sexual decisions increasingly feature compliance with biomedical directives and concern for ART efficacy. Seeking consensus regarding the biological risks of sex on ART becomes an important feature of sexual negotiations, and anticipated disagreements can pre-empt sexual relationships altogether. We introduce the concept of biomedical bargains to explain what happens when disagreements arise, and the terms of sex are negotiated using competing interpretations of biomedical information. For both men and women, ostensibly gender-neutral biomedical discourses provide new discursive resources and strategies for sexual decisions and negotiations, yet biomedical bargains are still embedded in gender dynamics-women invoke the dangers of jeopardizing treatment efficacy and longevity to insist on condoms or justify abstinence, while men utilize biomedical arguments in an effort to render condomless sex safe. While the full therapeutic benefits of ART are critical for the efficacy and equity of HIV programs, they will nonetheless always affect, and be affected by, social life.

HIV care continuum among cisgender and transgender women sex workers in Greater Kuala Lumpur, Malaysia

An estimated 37,000 cisgender and transgender women work as sex workers in Malaysia, a population that has been disproportionately affected by the HIV epidemic. Although Malaysia provides no-cost antiretroviral therapy (ART) to people with HIV, little is known about sex workers' engagement in the HIV care continuum. We analyzed data from 57 HIV-infected cisgender women (n = 33) and transgender women (n = 24) sex workers from a respondent-driven sampling study on HIV prevalence among sex workers in Kuala Lumpur, Malaysia. We examined the proportion of women who were newly diagnosed with HIV, had a baseline CD-4 count test, were initiated and retained on antiretroviral treatment (ART). Overall, only 26.3% had ever been HIV tested and almost 60% were newly diagnosed. Only a small proportion of cisgender (15.2%) and transgender (12.5%) women were currently taking ART. Interventions to enhance sex workers' engagement in the HIV care continuum are urgently needed. Deployment of evidence-based strategies to improve linkage and retention in HIV care should be adapted to address the unique needs of this important key population.

The Application of Systems Thinking to the Prevention and Control of Sexually Transmissible Infections among Adolescents and Adults: A Scoping Review

Systems thinking is a mechanism for making sense of complex systems that challenge linear explanations of cause-and-effect. While the prevention and control of sexually transmissible infections (STIs) has been identified as an area that may benefit from systems-level analyses, no review on the subject currently exists. The aim of this study is to conduct a scoping review to identify literature in which systems thinking has been applied to the prevention and control of STIs among adolescent and adult populations. Joanna Briggs Institute guidelines for the conduct of scoping reviews were followed. Five databases were searched for English-language studies published after 2011. A total of n = 6102 studies were screened against inclusion criteria and n = 70 were included in the review. The majority of studies (n = 34) were conducted in African nations. Few studies focused on priority sub-populations, and 93% were focused on HIV (n = 65). The most commonly applied systems thinking method was system dynamics modelling (n = 28). The review highlights areas for future research, including the need for more STI systems thinking studies focused on: (1) migrant and Indigenous populations; (2) conditions such as syphilis; and (3) innovations such as pre-exposure prophylaxis and at-home testing for HIV. The need for conceptual clarity around 'systems thinking' is also highlighted.

Accounting for historical injustices in mathematical models of infectious disease transmission: An analytic overview

Differences in infectious disease risk, acquisition, and severity arise from intersectional systems of oppression and resulting historical injustices that shape individual behavior and circumstance. We define historical injustices as distinct events and policies that arise out of intersectional systems of oppression. We view historical injustices as a medium through which structural forces affect health both directly and indirectly, and are thus important to study in the context of infectious disease disparities. In this critical analysis we aim to highlight the importance of incorporating historical injustices into mathematical models of infectious disease transmission and provide context on the methodologies to do so. We offer two illustrations of elements of model building (i.e., parameterization, validation and calibration) that can allow for a better understanding of health disparities in infectious disease outcomes. Mathematical models that do not recognize the historical forces that underlie infectious disease dynamics inevitably lead to the individualization of our focus and the recommendation of untenable individual-behavioral prescriptions to address the burden of infectious disease.

Comparison of model predictions of typhoid conjugate vaccine public health impact and cost-effectiveness

Models are useful to inform policy decisions on typhoid conjugate vaccine (TCV) deployment in endemic settings. However, methodological choices can influence model-predicted outcomes. To provide robust estimates for the potential public health impact of TCVs that account for structural model differences, we compared four dynamic and one static mathematical model of typhoid transmission and vaccine impact. All models were fitted to a common dataset of age-specific typhoid fever cases in Kolkata, India. We evaluated three TCV strategies: no vaccination, routine vaccination at 9 months of age, and routine vaccination at 9 months with a one-time catch-up campaign (ages 9 months to 15 years). The primary outcome was the predicted percent reduction in symptomatic typhoid cases over 10 years after vaccine introduction. For three models with economic analyses (Models A-C), we also compared the incremental cost-effectiveness ratios (ICERs), calculated as the incremental cost (US$) per disability-adjusted life-year (DALY) averted. Routine vaccination was predicted to reduce symptomatic cases by 10-46 % over a 10-year time horizon under an optimistic scenario (95 % initial vaccine efficacy and 19-year mean duration of protection), and by 2-16 % under a pessimistic scenario (82 % initial efficacy and 6-year mean protection). Adding a catch-up campaign predicted a reduction in incidence of 36-90 % and 6-35 % in the optimistic and pessimistic scenarios, respectively. Vaccine impact was predicted to decrease as the relative contribution of chronic carriers to transmission increased. Models A-C all predicted routine vaccination with or without a catch-up campaign to be cost-effective compared to no vaccination, with ICERs varying from $95-789 per DALY averted; two models predicted the ICER of routine vaccination alone to be greater than with the addition of catch-up campaign. Despite differences in model-predicted vaccine impact and cost-effectiveness, routine vaccination plus a catch-up campaign is likely to be impactful and cost-effective in high incidence settings such as Kolkata.

Molecular Epidemiology and Trends in HIV-1 Transmitted Drug Resistance in Mozambique 1999–2018

HIV drug resistance (HIVDR) can become a public health concern, especially in low- and middle-income countries where genotypic testing for people initiating antiretroviral therapy (ART) is not available. For first-line regimens to remain effective, levels of transmitted drug resistance (TDR) need to be monitored over time. To determine the temporal trends of TDR in Mozambique, a search for studies in PubMed and sequences in GenBank was performed. Only studies covering the pol region that described HIVDR and genetic diversity from treatment naïve patients were included. A dataset from seven published studies and one novel unpublished study conducted between 1999 and 2018 were included. The Calibrated Population Resistance tool (CPR) and REGA HIV-1 Subtyping Tool version 3 for sequences pooled by sampling year were used to determine resistance mutations and subtypes, respectively. The prevalence of HIVDR amongst treatment-naïve individuals increased over time, reaching 14.4% in 2018. The increase was most prominent for non-nucleoside reverse transcriptase inhibitors (NNRTIs), reaching 12.7% in 2018. Subtype C was predominant in all regions, but a higher genetic variability (19% non-subtype C) was observed in the north region of Mozambique. These findings confirm a higher diversity of HIV in the north of the country and an increased prevalence of NNRTI resistance among treatment naïve individuals over time.

Cost-effectiveness of implementing HIV and HIV/syphilis dual testing among key populations in Viet Nam: a modelling analysis

OBJECTIVES

Key populations, including sex workers, men who have sex with men, and people who inject drugs, have a high risk of HIV and sexually transmitted infections. We assessed the health and economic impacts of different HIV and syphilis testing strategies among three key populations in Viet Nam using a dual HIV/syphilis rapid diagnostic test (RDT).

SETTING

We used the spectrum AIDS impact model to simulate the HIV epidemic in Viet Nam and evaluated five testing scenarios among key populations. We used a 15-year time horizon and a provider perspective for costs.

PARTICIPANTS

We simulate the entire population of Viet Nam in the model.

INTERVENTIONS

We modelled five testing scenarios among key populations: (1) annual testing with an HIV RDT, (2) annual testing with a dual RDT, (3) biannual testing using dual RDT and HIV RDT, (4) biannual testing using HIV RDT and (5) biannual testing using dual RDT.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome is incremental cost-effectiveness ratios. Secondary outcomes include HIV and syphilis cases.

RESULTS

Annual testing using a dual HIV/syphilis RDT was cost-effective (US$10 per disability-adjusted life year (DALY)) and averted 3206 HIV cases and treated 27 727 syphilis cases compared with baseline over 15 years. Biannual testing using one dual test and one HIV RDT (US$1166 per DALY), or two dual tests (US$5672 per DALY) both averted an additional 875 HIV cases, although only the former scenario was cost-effective. Annual or biannual HIV testing using HIV RDTs and separate syphilis tests were more costly and less effective than using one or two dual RDTs.

CONCLUSIONS

Annual HIV and syphilis testing using dual RDT among key populations is cost-effective in Vietnam and similar settings to reach global reduction goals for HIV and syphilis.

Risk heterogeneity in compartmental HIV transmission models of ART as prevention in Sub-Saharan Africa: A scoping review

BACKGROUND

Transmission models provide complementary evidence to clinical trials about the potential population-level incidence reduction attributable to ART (ART prevention impact). Different modelling assumptions about risk heterogeneity may influence projected ART prevention impacts. We sought to review representations of risk heterogeneity in compartmental HIV transmission models applied to project ART prevention impacts in Sub-Saharan Africa.

METHODS

We systematically reviewed studies published before January 2020 that used non-linear compartmental models of sexual HIV transmission to simulate ART prevention impacts in Sub-Saharan Africa. We summarized data on model structure/assumptions (factors) related to risk and intervention heterogeneity, and explored multivariate ecological associations of ART prevention impacts with modelled factors.

RESULTS

Of 1384 search hits, 94 studies were included. 64 studies considered sexual activity stratification and 39 modelled at least one key population. 21 studies modelled faster/slower ART cascade transitions (HIV diagnosis, ART initiation, or cessation) by risk group, including 8 with faster and 4 with slower cascade transitions among key populations versus the wider population. In ecological analysis of 125 scenarios from 40 studies (subset without combination intervention), scenarios with risk heterogeneity that included turnover of higher risk groups were associated with smaller ART prevention benefits. Modelled differences in ART cascade across risk groups also influenced the projected ART benefits, including: ART prioritized to key populations was associated with larger ART prevention benefits. Of note, zero of these 125 scenarios considered lower ART coverage among key populations.

CONCLUSION

Among compartmental transmission models applied to project ART prevention impacts in Sub-Saharan Africa, representations of risk heterogeneity and projected impacts varied considerably. Inclusion/exclusion of risk heterogeneity with turnover, and intervention heterogeneity across risk groups could influence the projected impacts of ART scale-up. These findings highlight a need to capture risk heterogeneity with turnover and cascade heterogeneity when projecting ART prevention impacts.

Timely linkage to care among men who have sex with men newly diagnosed with HIV: A structural equation model integrated HIV-related stigma framework

HIV prevalence among men who have sex with men in China has increased dramatically, and timely linkage to care after being diagnosed with HIV is important to treatment success. This cross-sectional study aims to utilize structural equation modeling to test a hypothesized model of timely linkage to care adapted from the HIV-related stigma framework. Data were collected from 257 men who have sex with men living with HIV. The proportion of participants with timely linkage to care within one month was 63.42%. The model result showed a good fit. Higher HIV-related stigma was significantly associated with a lower level of social support, mental health, maladaptive coping (three mechanism variables), and attitude toward linkage to care. Higher CD4⁺ T-cell count, disclosure of HIV positivity to sexual partners, and greater convenience of accessing care were related to timely linkage to care (p< 0.05). These model results suggest that enhancing attention to family reactions and social support are needed for further research and interventions to accelerate newly diagnosed people's access to HIV care in China.

Challenges for modelling interventions for future pandemics

Mathematical modelling and statistical inference provide a framework to evaluate different non-pharmaceutical and pharmaceutical interventions for the control of epidemics that has been widely used during the COVID-19 pandemic. In this paper, lessons learned from this and previous epidemics are used to highlight the challenges for future pandemic control. We consider the availability and use of data, as well as the need for correct parameterisation and calibration for different model frameworks. We discuss challenges that arise in describing and distinguishing between different interventions, within different modelling structures, and allowing both within and between host dynamics. We also highlight challenges in modelling the health economic and political aspects of interventions. Given the diversity of these challenges, a broad variety of interdisciplinary expertise is needed to address them, combining mathematical knowledge with biological and social insights, and including health economics and communication skills. Addressing these challenges for the future requires strong cross-disciplinary collaboration together with close communication between scientists and policy makers.

Real-Time Infectious Disease Modeling to Inform Emergency Public Health Decision Making

Infectious disease transmission is a nonlinear process with complex, sometimes unintuitive dynamics. Modeling can transform information about a disease process and its parameters into quantitative projections that help decision makers compare public health response options. However, modelers face methodologic challenges, data challenges, and communication challenges, which are exacerbated under the time constraints of a public health emergency. We review methods, applications, challenges and opportunities for real-time infectious disease modeling during public health emergencies, with examples drawn from the two deadliest pandemics in recent history: HIV/AIDS and coronavirus disease 2019 (COVID-19).

Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The information-motivation-behavioral skills (IMB) model of antiretroviral therapy (ART) adherence among people living with HIV in Shanghai

The Information-Motivation-Behavioral skills (IMB) model of antiretroviral therapy (ART) adherence was applied in people living with HIV/AIDS in Shanghai, China to understand how adherence-related information, motivation and behavioral skills would affect ART adherence. The LifeWindows Information-Motivation-Behavioral Skills ART Adherence Questionnaire (LW-IMB-AAQ) was translated into Chinese and used. The IMB model was then implemented by testing standardized path estimates with standard model fitness indices in the participants. 426 participants from 11 community centres in Putuo district of Shanghai were recruited, of which 95.3% reported a high level of adherence (>95% adherence). The fitness indices of the final adjusted model were χ2 = 6.110, df = 7, p = 0.527(>0.05), CFI = 1.000(>0.9) and RMSEA = 0.000 (<0.08). In the model, information, which was separated into two sections (the perceived effect of ART on health and knowledge about ART medication), had an indirect effect on the ART adherence through behavioral skills, while motivation did not have such an effect. Neither information nor motivation had a direct effect on ART adherence. In addition, motivation was related to the two sections of information. The feasibility of the IMB model of ART adherence is verified by its application to predictive of adherence-related behaviors among HIV+ patients in this study.

HIV Pretreatment Drug Resistance Trends in Mexico City, 2017-2020

In response to increasing pretreatment drug resistance (PDR), Mexico changed its national antiretroviral treatment (ART) policy, recommending and procuring second-generation integrase strand-transfer inhibitor (INSTI)-based regimens as preferred first-line options since 2019. We present a four-year observational study describing PDR trends across 2017-2020 at the largest HIV diagnosis and primary care center in Mexico City. A total of 6688 baseline protease-reverse transcriptase and 6709 integrase sequences were included. PDR to any drug class was 14.4% (95% CI, 13.6-15.3%). A significant increasing trend for efavirenz/nevirapine PDR was observed (10.3 to 13.6%, p = 0.02). No increase in PDR to second-generation INSTI was observed, remaining under 0.3% across the study period. PDR was strongly associated with prior exposure to ART (aOR: 2.9, 95% CI: 1.9-4.6, p < 0.0001). MSM had higher odds of PDR to efavirenz/nevirapine (aOR: 2.0, 95% CI: 1.0-3.7, p = 0.04), reflecting ongoing transmission of mutations such as K103NS and E138A. ART restarters showed higher representation of cisgender women and injectable drug users, higher age, and lower education level. PDR to dolutegravir/bictegravir remained low in Mexico City, although further surveillance is warranted given the short time of ART optimization. Our study identifies demographic characteristics of groups with higher risk of PDR and lost to follow-up, which may be useful to design differentiated interventions locally.

Modelling the impact of HIV and HCV prevention and treatment interventions for people who inject drugs in Dar es Salaam, Tanzania

Introduction

People who inject drugs (PWID) in Dar es Salaam, Tanzania, have a high prevalence of HIV and hepatitis C virus (HCV). While needle and syringe programmes (NSP), opioid agonist therapy (OAT) and anti‐retroviral therapy (ART) are available in Tanzania, their coverage is sub‐optimal. We assess the impact of existing and scaled up harm reduction (HR) interventions on HIV and HCV transmission among PWID in Dar es Salaam.

Methods

An HIV and HCV transmission model among PWID in Tanzania was calibrated to data over 2006–2018 on HIV (∼30% and ∼67% prevalence in males and females in 2011) and HCV prevalence (∼16% in 2017), numbers on HR interventions (5254 ever on OAT in 2018, 766–1479 accessing NSP in 2017) and ART coverage (63.1% in 2015). We evaluated the impact of existing interventions in 2019 and impact by 2030 of scaling‐up the coverage of OAT (to 50% of PWID), NSP (75%, both combined termed “full HR”) and ART (81% with 90% virally suppressed) from 2019, reducing sexual HIV transmission by 50%, and/or HCV‐treating 10% of PWID infected with HCV annually.

Results

The model projects HIV and HCV prevalence of 19.0% (95% credibility interval: 16.4–21.2%) and 41.0% (24.4–49.0%) in 2019, respectively. For HIV, 24.6% (13.6–32.6%) and 70.3% (59.3–77.1%) of incident infections among male and female PWID are sexually transmitted, respectively. Due to their low coverage (22.8% for OAT, 16.3% for NSP in 2019), OAT and NSP averted 20.4% (12.9–24.7%) of HIV infections and 21.7% (17.0–25.2%) of HCV infections in 2019. Existing ART (68.5% coverage by 2019) averted 48.1% (29.7–64.3%) of HIV infections in 2019. Scaling up to full HR will reduce HIV and HCV incidence by 62.6% (52.5–74.0%) and 81.4% (56.7–81.4%), respectively, over 2019–2030; scaled up ART alongside full HR will decrease HIV incidence by 66.8% (55.6–77.5%), increasing to 81.5% (73.7–87.5%) when sexual risk is also reduced. HCV‐treatment alongside full HR will decrease HCV incidence by 92.4% (80.7–95.8%) by 2030.

Conclusions

Combination interventions, including sexual risk reduction and HCV treatment, are needed to eliminate HCV and HIV among PWID in Tanzania.

HIV Viral Suppression and Pre-exposure Prophylaxis in HIV and Syphilis Contact Tracing Networks: An Analysis of Disease Surveillance and Prescription Claims Data

BACKGROUND

HIV and syphilis contact tracing networks offer efficient platforms for HIV treatment and prevention interventions, but intervention coverage within these networks has not been characterized.

SETTING

HIV and syphilis sexual contact tracing networks among men who have sex with men (MSM) in North Carolina (NC).

METHODS

Using surveillance data, we identified 2 types of "network events" that occurred between January 2013 and June 2017 among MSM in NC: being diagnosed with early syphilis or being named as a recent sexual contact of a person diagnosed with HIV or early syphilis. We estimated prevalent and incident HIV viral suppression among persons diagnosed with HIV before the network event, and we assessed the effect of contact tracing services on a 6-month cumulative incidence of viral suppression among previously HIV-diagnosed, virally unsuppressed persons. Using linked prescription claims data, we also evaluated prevalent and incident pre-exposure prophylaxis (PrEP) use in an insured subset of HIV-negative network members.

RESULTS

Viral suppression prevalence among previously HIV-diagnosed persons was 52.6%. The 6-month cumulative incidence of viral suppression was 35.4% overall and 13.1 (95% confidence interval: 8.8 to 17.4) percentage points higher among persons reached than among those not reached by contact tracing services. Few HIV-negative persons had prevalent (5.4%) or incident (4.1%) PrEP use in the 6 months before or after network events, respectively.

CONCLUSIONS

Suboptimal viral suppression and PrEP use among MSM in NC in HIV/syphilis contact tracing networks indicate a need for intensified intervention efforts. In particular, expanded services for previously HIV-diagnosed persons could improve viral suppression and reduce HIV transmission within these networks.

Pre-exposure prophylaxis use among HIV serodiscordant couples: a qualitative study in Mozambique

Background

Pre-exposure prophylaxis (PrEP) has the potential to reduce HIV transmission and stem the HIV epidemic. Unfortunately, PrEP uptake in rural sub-Saharan Africa has been slow and medication adherence has been suboptimal.

Objective

To explore the perspectives, attitudes, and experiences of HIV serodiscordant partners taking PrEP and develop a messaging campaign to improve PrEP uptake in rural Mozambique to reduce HIV transmission among serodiscordant partners.

Methods

In this qualitative study, we interviewed 20 people in serodiscordant relationships using PrEP at a rural health center in Zambézia province, Mozambique and employed inductive and deductive coding to elicit their perspectives, attitudes, and experiences related to learning their partner’s HIV status, barriers to PrEP uptake, obstacles to PrEP adherence, and decisions to disclose their PrEP use with family and friends using thematic analysis.

Results

Our analysis generated nine themes across various levels of the socioecological model. Participants reported a strong desire to stay in the discordant relationship and highlighted the importance of working together to ensure PrEP and antiretroviral therapy adherence, with the majority skeptical that adherence could be achieved without both partners’ support (individual and interpersonal). Although most participants were reticent about sharing their serodiscordant status with family and friends (individual and interpersonal), those who did found their family and friends supportive (interpersonal). Participants suggested increasing community health agent availability to help people navigate HIV prevention and treatment (organizational). We then created three oral stories, using themes from the interviews, with examples from various levels of the socioecological model that will be used to generate support for PrEP use among community members.

Conclusions

Our findings informed oral template stories that will be used to emphasize how couples can work together to improve PrEP uptake and reduce incident HIV infections in serodiscordant couples elsewhere in rural Mozambique.

An approach for improving the quality of country-level TB modelling

Mathematical modelling is increasingly used to inform budgeting and strategic decision-making by national TB programmes. Despite the importance of these decisions, there is currently no mechanism to review and confirm the appropriateness of modelling analyses. We have developed a benchmarking, reporting, and review (BRR) approach and accompanying tools to allow constructive review of country-level TB modelling applications. This approach has been piloted in five modelling applications and the results of this study have been used to revise and finalise the approach. The BRR approach consists of 1) quantitative benchmarks against which model assumptions and results can be compared, 2) standardised reporting templates and review criteria, and 3) a multi-stage review process providing feedback to modellers during the application, as well as a summary evaluation after completion. During the pilot, use of the tools prompted important changes in the approaches taken to modelling. The pilot also identified issues beyond the scope of a review mechanism, such as a lack of empirical evidence and capacity constraints. This approach provides independent evaluation of the appropriateness of modelling decisions during the course of an application, allowing meaningful changes to be made before results are used to inform decision-making. The use of these tools can improve the quality and transparency of country-level TB modelling applications.

Comparison of two simulators for individual based models in HIV epidemiology in a population with HSV 2 in Yaoundé (Cameroon)

Model comparisons have been widely used to guide intervention strategies to control infectious diseases. Agreement between different models is crucial for providing robust evidence for policy-makers because differences in model properties can influence their predictions. In this study, we compared models implemented by two individual-based model simulators for HIV epidemiology in a heterosexual population with Herpes simplex virus type-2 (HSV-2). For each model simulator, we constructed four models, starting from a simplified basic model and stepwise including more model complexity. For the resulting eight models, the predictions of the impact of behavioural interventions on the HIV epidemic in Yaoundé-Cameroon were compared. The results show that differences in model assumptions and model complexity can influence the size of the predicted impact of the intervention, as well as the predicted qualitative behaviour of the HIV epidemic after the intervention. These differences in predictions of an intervention were also observed for two models that agreed in their predictions of the HIV epidemic in the absence of that intervention. Without additional data, it is impossible to determine which of these two models is the most reliable. These findings highlight the importance of making more data available for the calibration and validation of epidemiological models.

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.

Projecting the number of new HIV infections to formulate the "Getting to Zero" strategy in Illinois, USA

OBJECTIVES

Getting to Zero (GTZ) initiatives focus on expanding use of antiretroviral treatment (ART) and pre-exposure prophylaxis (PrEP) to eliminate new HIV infections. Computational models help inform policies for implementation of ART and PrEP continuums. Such models, however, vary in their design, and may yield inconsistent predictions. Using multiple approaches can help assess the consistency in results obtained from varied modeling frameworks, and can inform optimal implementation strategies.

METHODS

A study using three different modeling approaches is conducted. Two approaches use statistical time series analysis techniques that incorporate temporal HIV incidence data. A third approach uses stochastic stimulation, conducted using an agent-based network model (ABNM). All three approaches are used to project HIV incidence among a key population, young Black MSM (YBMSM), over the course of the GTZ implementation period (2016-2030).

RESULTS

All three approaches suggest that simultaneously increasing PrEP and ART uptake is likely to be more effective than increasing only one, but increasing ART and PrEP by 20% points may not eliminate new HIV infections among YBMSM. The results further suggest that a 20% increase in ART is likely to be more effective than a 20% increase in PrEP. All three methods consistently project that increasing ART and PrEP by 30% simultaneously can help reach GTZ goals.

CONCLUSIONS

Increasing PrEP and ART uptake by about 30% might be necessary to accomplish GTZ goals. Such scale-up may require addressing psychosocial and structural barriers to engagement in HIV and PrEP care continuums. ABNMs and other flexible modeling approaches can be extended to examine specific interventions that address these barriers and may provide important data to guide the successful intervention implementation.

Partnership dynamics in mathematical models and implications for representation of sexually transmitted infections: a review

Mathematical models of sexually transmitted disease (STI) are increasingly relied on to inform policy, practice, and resource allocation. Because STI transmission requires sexual contact between two or more people, a model's ability to represent the dynamics of sexual partnerships can influence the validity of findings. This ability is to a large extent constrained by the model type, as different modeling frameworks vary in their capability to capture patterns of sexual contact at individual, partnership, and network levels. In this paper, we classify models into three groups: compartmental, individual-based, and statistical network models. For each framework, we describe the basic model structure and discuss key aspects of sexual partnership dynamics: how and with whom partnerships are formed, partnership duration and dissolution, and temporal overlap in partnerships (concurrency). We illustrate the potential implications of accurately accounting for partnership dynamics, but these effects depend on characteristics of both the population and pathogen; the combined impact of these partnership and epidemiologic dynamics can be difficult to predict. While each of the reviewed model frameworks may be appropriate to inform certain research or policy questions, modelers and consumers of models should carefully consider the implications of sexual partnership dynamics for the questions under study.

Model-Based Predictions of HIV Incidence Among African Women Using HIV Risk Behaviors and Community-Level Data on Male HIV Prevalence and Viral Suppression

BACKGROUND

Pre-exposure prophylaxis (PrEP) with tenofovir disoproxil fumarate and emtricitabine has proven highly effective in preventing HIV acquisition and is therefore offered to all participants in the control group as part of the standard of care package in many new HIV prevention studies. We propose a methodology for predicting HIV incidence in a hypothetical "placebo arm" for open-label studies or clinical trials with active control among African women. We apply the method to an open-label PrEP study, HIV Prevention Trials Network 082, which tested strategies to improve PrEP adherence in young African women all of whom were offered PrEP.

METHODS

Our model predicted HIV infection risk for female study cohorts in sub-Saharan Africa using baseline behavioral risk factors and contemporary HIV prevalence and viral suppression in the local male population. The model was calibrated to HIV incidence in the Vaginal and Oral Interventions to Control the Epidemic study.

RESULTS

Our model reproduced the annual HIV incidence of 3.2%-4.8% observed over 1 year of follow-up in the placebo groups of 4 completed clinical studies. We predicted an annual HIV incidence of 3.7% (95% confidence interval: 3.2 to 4.2) among HIV Prevention Trials Network 082 participants in the absence of PrEP and other risk reduction interventions.

CONCLUSIONS

We demonstrated the potential of the proposed methodology to provide HIV incidence predictions based on assessment of individual risk behaviors and community and time-specific HIV exposure risk using HIV treatment and viral suppression data. These estimates may serve as comparators in HIV prevention trials without a placebo group.

Implementation of Universal HIV Testing and Treatment to Reduce HIV Incidence in Botswana: the Ya Tsie Study

PURPOSE OF REVIEW

Antiretroviral treatment (ART) can dramatically reduce the risk of HIV transmission, but the feasibility of scaling up HIV testing, linkage and treatment to very high population levels, and its impact on population HIV incidence, were unknown. We review key findings from a community-randomized trial in which we evaluated the impact of "universal test and treat" (UTT) on population HIV incidence in Botswana, a resource-constrained country with both high HIV prevalence and high ART coverage before study inception.

RECENT FINDINGS

We conducted a community-randomized trial (the "Ya Tsie" trial or Botswana Combination Prevention Project (BCPP)) in 30 villages in Botswana from 2013 to 2018, with the goal of determining whether a combination of prevention interventions-with a focus on universal HIV testing and treatment-would reduce population-level HIV incidence. The intervention included universal HIV testing (home-based and mobile), active linkage to HIV care and treatment with patient tracing for persons not linking, universal ART coverage, rapid ART start (at the first clinic visit), and enhanced male circumcision services. Botswana had very high HIV diagnosis, treatment, and viral suppression levels (approaching the UNAIDS "90-90-90" targets) prior to intervention roll-out. By study end, we were able to exceed the overall 95-95-95 coverage target of 86%: an estimated 88% of all persons living with HIV were on ART and had viral suppression in the Ya Tsie intervention arm. In addition, annual HIV incidence was 30% lower in the intervention arm as compared with the control arm over a 29-month follow-up period. With universal HIV testing and relatively simple linkage activities, it was possible to achieve one of the highest reported population levels of HIV diagnosis, linkage to care, and viral suppression globally and to reduce population HIV incidence by about one-third over a short period of time (< 3 years). We were able to significantly increase population viral suppression and to decrease HIV incidence even in a resource-constrained setting with pre-existing very high testing and treatment coverage. Universal community-based HIV testing and tracing of individuals through the HIV care cascade were key intervention components.

Cost-Effectiveness of HIV Pre-exposure Prophylaxis Among Heterosexual Men in South Africa: A Cost-Utility Modeling Analysis

INTRODUCTION

Heterosexual men are not considered a key population in the HIV response and are mostly absent from pre-exposure prophylaxis (PrEP) studies to date. Yet, South African men face considerable HIV risk. We estimate the incremental cost-effectiveness of providing oral PrEP, injectable PrEP, or a combination of both to heterosexual South African men to assess whether providing PrEP would efficiently use resources.

METHODS

Epidemiological and costing models estimated the one-year costs and outcomes associated with PrEP use in 3 scenarios. PrEP uptake was estimated for younger (aged 18-24) and older (aged 25-49) men using a discrete choice experiment. Scenarios were compared with a baseline scenario of male condom use, while a health system perspective was used to estimate discounted lifetime costs averted per HIV infection. PrEP benefit was estimated in disability-adjusted life years (DALYs) averted. Uncertainty around the estimated incremental cost-effectiveness ratios (ICERs) was assessed using deterministic and probabilistic sensitivity analyses.

RESULTS

No PrEP intervention scenarios were cost-effective for both age groups at a willingness-to-pay threshold of $1175/DALY averted. The lowest ICER ($2873/DALY averted) was for the provision of oral PrEP to older men, although probability of cost-effectiveness was just 0.26%. Results found that ICERs were sensitive to HIV incidence and antiretroviral coverage.

CONCLUSIONS

This study estimates that providing PrEP to heterosexual South African men is not cost-effective at current cost-effectiveness thresholds. Given the ICERs' sensitivity to several variables, alongside the heterogeneity of HIV infection among South African men, PrEP may be cost-effective for older men with high incidence and other subgroups based on locality and race. We recommend further investigation to better identify and target these groups.

Estimating the contribution of key populations towards HIV transmission in South Africa

INTRODUCTION

In generalized epidemic settings, there is insufficient understanding of how the unmet HIV prevention and treatment needs of key populations (KPs), such as female sex workers (FSWs) and men who have sex with men (MSM), contribute to HIV transmission. In such settings, it is typically assumed that HIV transmission is driven by the general population. We estimated the contribution of commercial sex, sex between men, and other heterosexual partnerships to HIV transmission in South Africa (SA).

METHODS

We developed the "Key-Pop Model"; a dynamic transmission model of HIV among FSWs, their clients, MSM, and the broader population in SA. The model was parameterized and calibrated using demographic, behavioural and epidemiological data from national household surveys and KP surveys. We estimated the contribution of commercial sex, sex between men and sex among heterosexual partnerships of different sub-groups to HIV transmission over 2010 to 2019. We also estimated the efficiency (HIV infections averted per person-year of intervention) and prevented fraction (% IA) over 10-years from scaling-up ART (to 81% coverage) in different sub-populations from 2020.

RESULTS

Sex between FSWs and their paying clients, and between clients with their non-paying partners contributed 6.9% (95% credibility interval 4.5% to 9.3%) and 41.9% (35.1% to 53.2%) of new HIV infections in SA over 2010 to 2019 respectively. Sex between low-risk groups contributed 59.7% (47.6% to 68.5%), sex between men contributed 5.3% (2.3% to 14.1%) and sex between MSM and their female partners contributed 3.7% (1.6% to 9.8%). Going forward, the largest population-level impact on HIV transmission can be achieved from scaling up ART to clients of FSWs (% IA = 18.2% (14.0% to 24.4%) or low-risk individuals (% IA = 20.6% (14.7 to 27.5) over 2020 to 2030), with ART scale-up among KPs being most efficient.

CONCLUSIONS

Clients of FSWs play a fundamental role in HIV transmission in SA. Addressing the HIV prevention and treatment needs of KPs in generalized HIV epidemics is central to a comprehensive HIV response.

Development and dissemination of infectious disease dynamic transmission models during the COVID-19 pandemic: what can we learn from other pathogens and how can we move forward?

The current COVID-19 pandemic has resulted in the unprecedented development and integration of infectious disease dynamic transmission models into policy making and public health practice. Models offer a systematic way to investigate transmission dynamics and produce short-term and long-term predictions that explicitly integrate assumptions about biological, behavioural, and epidemiological processes that affect disease transmission, burden, and surveillance. Models have been valuable tools during the COVID-19 pandemic and other infectious disease outbreaks, able to generate possible trajectories of disease burden, evaluate the effectiveness of intervention strategies, and estimate key transmission variables. Particularly given the rapid pace of model development, evaluation, and integration with decision making in emergency situations, it is necessary to understand the benefits and pitfalls of transmission models. We review and highlight key aspects of the history of infectious disease dynamic models, the role of rigorous testing and evaluation, the integration with data, and the successful application of models to guide public health. Rather than being an expansive history of infectious disease models, this Review focuses on how the integration of modelling can continue to be advanced through policy and practice in appropriate and conscientious ways to support the current pandemic response.

Control Intervention Strategies for Within-Host, Between-Host and their Efficacy in the Treatment, Spread of COVID-19 : A Multi Scale Modeling Approach

The COVID-19 pandemic has resulted in more than 65.5 million infections and 15,14,695 deaths in 212 countries over the last few months. Different drug intervention acting at multiple stages of pathogenesis of COVID-19 can substantially reduce the infection induced, thereby decreasing the mortality. Also population level control strategies can reduce the spread of the COVID-19 substantially. Motivated by these observations, in this work we propose and study a multi scale model linking both within-host and between-host dynamics of COVID-19. Initially the natural history dealing with the disease dynamics is studied. Later comparative effectiveness is performed to understand the efficacy of both the within-host and population level interventions. Findings of this study suggest that a combined strategy involving treatment with drugs such as Arbidol, remdesivir, Lopinavir/Ritonavir that inhibits viral replication and immunotherapies like monoclonal antibodies, along with environmental hygiene and generalized social distancing proved to be the best and optimal in reducing the basic reproduction number and environmental spread of the virus at the population level.

Barriers and Facilitators of Same-Day Antiretroviral Therapy Initiation Among People Newly Diagnosed with HIV in Ethiopia: Qualitative Study Using the Transtheoretical Model of Behavioral Change

Purpose

HIV test and treat approach is currently a strategy used as a part of the prevention and control program in Ethiopia. The strategy adopts initiating antiretroviral therapy (ART) on the same-day as HIV diagnosis or in the next visit. However, there is little evidence on barriers and facilitators of same-day (ART) initiation in Ethiopia. Therefore, this study aimed to investigate barriers and facilitators of same-day (ART) initiation in the northwest Ethiopia.

Patients and Methods

A qualitative study was conducted in East Gojjam Zone in northwest Ethiopia. Purposively selected HIV patients, healthcare workers, and treatment assistants participated in the qualitative study. Data were collected through in-depth interviews and focus group discussions (FGDs). Coding was done via ATLAS.ti software thematically. The interviews and FGDs were conducted in Amharic (local language) and then transcribed verbatim and translated into English. Coding was done via ATLAS.ti software. The thematic analysis approach was employed using the constructs of the transtheoretical behavioral model (TTM) to show stages of change that newly HIV diagnosed experienced in the course of preparation for treatment initiation.

Results

A total of 19 patients, 12 treatment supporters, and 9 healthcare workers participated in the qualitative study. Shocking due to the test result, having no symptoms, mistrust of the test result, and seeking spiritual healing from holy water were the major barriers to start ART in the same-day of diagnosis or within the next visit.

Conclusion

During HIV diagnosis, more barriers were observed in the early stages, while treatment facilitators emerged in the later stages of TTM. The TTM model can be applied to characterize where participants were in the stages of change.

High variability in the measurement of HIV primary prevention activities and outcomes

INTRODUCTION

While there is a global consensus on monitoring Human Immunodeficiency Virus (HIV) treatment progress, there has been less attention to the degree of consistency of the measurement of HIV prevention programmes-and the global prevention response is not on-track to achieve 2020 goals. In this paper, we assess the degree of variability in primary prevention indicators selected by national strategic plans (NSPs) and global stakeholder monitoring and evaluation (M&E) strategies.

METHODS

We obtained the most recent NSPs from low and middle income Joint United Nations Programme on HIV/AIDS (UNAIDS) Fast-Track countries, and M&E documents from The Global Fund to Fight AIDS, Tuberculosis and Malaria (The Global Fund), President's Emergency Plan for AIDS Relief (PEPFAR), UNAIDS, the Global HIV Prevention Coalition and the World Health Organization (WHO). We extracted HIV primary prevention indicators from each document, standardized and aggregated them by age/ sex, categorized indicators by topic, and evaluated the frequency of matched indicators between countries and stakeholders. Data were collected between February and April of 2019.

RESULTS

Twenty-one NSPs and five global stakeholder documents were assessed; 736 primary prevention indicators were identified; 284 remained following standardization and aggregation. NSPs contained from 3 to 48 primary prevention indicators, with an average of 23; categories included: HIV education and outreach (17.6%), testing (17.3%) and condom use (16.2%). Of unique national indicators, only 34% was shared between two or more countries. Sixty-nine per cent was applied in a single country only. 56% of NSP indicators did not appear in any global stakeholder document. Conversely, 42% of global indicators did not appear in any surveyed NSPs. Within global indicators, 63% was only measured by one global body, and no single indicator was measured by all five.

CONCLUSIONS

These analyses reveal a lack of consensus both between and within countries' and global stakeholders' measurement of HIV prevention. Though some variability is expected, these findings point to a need to refocus attention on achieving greater consensus on a global measurement framework for HIV prevention.

Lower rates of ART initiation and decreased retention among ART-naïve patients who consume alcohol enrolling in HIV care and treatment programs in Kenya and Uganda

Objectives

Almost 13 million people are estimated to be on antiretroviral therapy in Eastern and Southern Africa, and their disease course and program effectiveness could be significantly affected by the concurrent use of alcohol. Screening for alcohol use may be important to assess the prevalence of alcohol consumption and its impact on patient and programmatic outcomes.

Methods

As part of this observational study, data on patient characteristics and alcohol consumption were collected on a cohort of 765 adult patients enrolling in HIV care in East Africa. Alcohol consumption was assessed with the AUDIT questionnaire at enrollment. Subjects were classified as consuming any alcohol (AUDIT score >0), hazardous drinkers (AUDIT score ≥8) and hyper drinkers (AUDIT score ≥16). The effects of alcohol consumption on retention in care, death and delays in antiretroviral therapy (ART) initiation were assessed through competing risk (Fine & Gray) models.

Results

Of all study participants, 41.6% consumed alcohol, 26.7% were classified as hazardous drinkers, and 16.0% as hyper drinkers. Depending on alcohol consumption classification, men were 3–4 times more likely to consume alcohol compared to women. Hazardous drinkers (median age 32.8 years) and hyper drinkers (32.7 years) were slightly older compared to non-hazardous drinkers (30.7 years) and non-hyper drinkers (30.8 years), (p-values = 0.014 and 0.053 respectively). Median CD4 at enrollment was 330 cells/μl and 16% were classified World Health Organization (WHO) stage 3 or 4. There was no association between alcohol consumption and CD4 count or WHO stage at enrollment. Alcohol consumption was associated with significantly lower probability of ART initiation (adjusted sub-distribution hazard ratio aSHR = 0.77 between alcohol consumers versus non-consumers; p-value = 0.008), and higher patient non-retention in care (aSHR = 1.77, p-value = 0.023).

Discussion

Alcohol consumption is associated with significant delays in ART initiation and reduced retention in care for patients enrolling in HIV care and treatment programs in East Africa. Consequently, interventions that target alcohol consumption may have a significant impact on the HIV care cascade.

Evidence of sociodemographic heterogeneity across the HIV treatment cascade and progress towards 90-90-90 in sub-Saharan Africa - a systematic review and meta-analysis

Introduction

Heterogeneity of sociodemographics and risk behaviours across the HIV treatment cascade could influence the public health impact of universal ART in sub‐Saharan Africa if those not virologically suppressed are more likely to be part of a risk group contributing to onward infections. Sociodemographic and risk heterogeneity across the treatment cascade has not yet been comprehensively described or quantified and we seek to systematically review and synthesize research on this topic among adults in Africa.

Methods

We conducted a systematic review of peer‐reviewed literature in Embase and MEDLINE databases as well as grey literature sources published in English between 2014 and 2018. We included studies that included people living with HIV (PLHIV) aged ≥15 years, and reported a 90‐90‐90 outcome: awareness of HIV‐positive status, ART use among those diagnosed or viral suppression among those on ART. We summarized measures of association between sociodemographics, within each outcome, and as a composite measure of population‐wide viral suppression.

Results and discussion

From 3533 screened titles, we extracted data from 92 studies (50 peer‐reviewed, 42 grey sources). Of included studies, 32 reported on awareness, 53 on ART use, 32 on viral suppression and 23 on population‐wide viral suppression. The majority of studies were conducted in South Africa, Uganda, and Malawi and reported data for age and gender. When stratified, PLHIV ages 15 to 24 years had lower median achievement of the treatment cascade (60‐49‐81), as compared to PLHIV ≥25 years (70‐63‐91). Men also had lower median achievement of the treatment cascade (66‐72‐85), compared to women (79‐76‐89). For population‐wide viral suppression, women aged ≥45 years had achieved the 73% target, while the lowest medians were among 15‐ to 24‐year‐old men (37%) and women (49%).

Conclusions

Considerable heterogeneity exists by age and gender for achieving the HIV 90‐90‐90 treatment goals. These results may inform delivery of HIV testing and treatment in sub‐Saharan Africa, as targeting youth and men could be a strategic way to maximize the population‐level impact of ART.

GRADE Guidelines 30: the GRADE approach to assessing the certainty of modeled evidence-An overview in the context of health decision-making

OBJECTIVES

The objective of the study is to present the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) conceptual approach to the assessment of certainty of evidence from modeling studies (i.e., certainty associated with model outputs).

STUDY DESIGN AND SETTING

Expert consultations and an international multidisciplinary workshop informed development of a conceptual approach to assessing the certainty of evidence from models within the context of systematic reviews, health technology assessments, and health care decisions. The discussions also clarified selected concepts and terminology used in the GRADE approach and by the modeling community. Feedback from experts in a broad range of modeling and health care disciplines addressed the content validity of the approach.

RESULTS

Workshop participants agreed that the domains determining the certainty of evidence previously identified in the GRADE approach (risk of bias, indirectness, inconsistency, imprecision, reporting bias, magnitude of an effect, dose-response relation, and the direction of residual confounding) also apply when assessing the certainty of evidence from models. The assessment depends on the nature of model inputs and the model itself and on whether one is evaluating evidence from a single model or multiple models. We propose a framework for selecting the best available evidence from models: 1) developing de novo, a model specific to the situation of interest, 2) identifying an existing model, the outputs of which provide the highest certainty evidence for the situation of interest, either "off-the-shelf" or after adaptation, and 3) using outputs from multiple models. We also present a summary of preferred terminology to facilitate communication among modeling and health care disciplines.

CONCLUSION

This conceptual GRADE approach provides a framework for using evidence from models in health decision-making and the assessment of certainty of evidence from a model or models. The GRADE Working Group and the modeling community are currently developing the detailed methods and related guidance for assessing specific domains determining the certainty of evidence from models across health care-related disciplines (e.g., therapeutic decision-making, toxicology, environmental health, and health economics).

Addressing Uptake of HIV Testing and Linkage to Care Among Men in Côte d'Ivoire: An Evaluation of the Brothers for Life Program Implementation

BACKGROUND

Historically, men in sub-Saharan Africa have worse outcomes along the HIV care continuum than women. Brothers for Life (BFL) is a community-based behavior change intervention for men, adapted for Côte d'Ivoire, involving group discussions that address salient gender norms and promote HIV prevention, testing, and linkage to care with support from peer navigators. The goal of this study was to describe the BFL program as implemented in Côte d'Ivoire, evaluate program implementation, and report uptake of HIV testing and treatment among BFL participants.

SETTING

Three urban and periurban sites in Côte d'Ivoire.

METHODS

The implementation evaluation assessed the fidelity and acceptability of the BFL program and the reach of program completion, testing and peer navigation using qualitative and quantitative approaches.

RESULTS

BFL facilitation fidelity and content fidelity were high. Semistructured interviews with BFL participants indicated that men appreciated the format and content and that the BFL program helped some participants overcome their fears and adopt more positive attitudes and behaviors around testing and treatment. Assessments of reach showed that, of the 7187 BFL participants, 81% tested for HIV as part of BFL and 2.3% (135) tested HIV-positive. Of those, 76% (102) accepted peer navigator support, and 97% (131) initiated treatment. After 6 months, 100% of the 131 men who initiated treatment remained in care.

CONCLUSION

The implementation of BFL in Côte d'Ivoire successfully achieved the goals of engaging participants in discussions around HIV prevention, encouraging HIV testing, and achieving linkage to care, treatment initiation, and retention.

Modelling hepatitis B virus infection and impact of timely birth dose vaccine: A comparison of two simulation models

Hepatitis B is a global epidemic that requires carefully orchestrated vaccination initiatives in geographical regions of medium to high endemicity to reach the World Health Organization’s elimination targets by 2030. This study compares two widely-used deterministic hepatitis B models—the Imperial HBV model and the CDA Foundation’s PRoGReSs—based on their predicted outcomes in four countries. The impact of scaling up of the timely birth dose of the hepatitis B vaccine is also investigated. The two models predicted largely similar outcomes for the impact of vaccination programmes on the projected numbers of new cases and deaths under high levels of the infant hepatitis B vaccine series. However, scenarios for the scaling up of the infant hepatitis B vaccine series had a larger impact in the PRoGReSs model than in the Imperial model due to the infant vaccine series directly leading to the reduction of perinatal transmission in the PRoGReSs model, but not in the Imperial model. Meanwhile, scaling up of the timely birth dose vaccine had a greater impact on the outcomes of the Imperial hepatitis B model than in the PRoGReSs model due to the greater protection that the birth dose vaccine confers to infants in the Imperial model compared to the PRoGReSs model. These differences underlie the differences in projections made by the models under some circumstances. Both sets of assumptions are consistent with available data and reveal a structural uncertainty that was not apparent in either model in isolation. Those relying on projections from models should consider outputs from both models and this analysis provides further evidence of the benefits of systematic model comparison for enhancing modelling analyses.

Contribution of high risk groups' unmet needs may be underestimated in epidemic models without risk turnover: A mechanistic modelling analysis

Background

Epidemic models of sexually transmitted infections (STIs) are often used to characterize the contribution of risk groups to overall transmission by projecting the transmission population attributable fraction (tPAF) of unmet prevention and treatment needs within risk groups. However, evidence suggests that STI risk is dynamic over an individual’s sexual life course, which manifests as turnover between risk groups. We sought to examine the mechanisms by which turnover influences modelled projections of the tPAF of high risk groups.

Methods

We developed a unifying, data-guided framework to simulate risk group turnover in deterministic, compartmental transmission models. We applied the framework to an illustrative model of an STI and examined the mechanisms by which risk group turnover influenced equilibrium prevalence across risk groups. We then fit a model with and without turnover to the same risk-stratified STI prevalence targets and compared the inferred level of risk heterogeneity and tPAF of the highest risk group projected by the two models.

Results

The influence of turnover on group-specific prevalence was mediated by three main phenomena: movement of previously high risk individuals with the infection into lower risk groups; changes to herd effect in the highest risk group; and changes in the number of partnerships where transmission can occur. Faster turnover led to a smaller ratio of STI prevalence between the highest and lowest risk groups. Compared to the fitted model without turnover, the fitted model with turnover inferred greater risk heterogeneity and consistently projected a larger tPAF of the highest risk group over time.

Implications

If turnover is not captured in epidemic models, the projected contribution of high risk groups, and thus, the potential impact of prioritizing interventions to address their needs, could be underestimated. To aid the next generation of tPAF models, data collection efforts to parameterize risk group turnover should be prioritized.

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A new framework for parameterizing turnover in risk groups is developed.

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Mechanisms by which turnover influences sexually transmitted infection (STI), prevalence in risk groups are examined.

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Turnover reduces the ratio of equilibrium STI prevalence in high vs low risk groups.

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Inferred risk heterogeneity is higher when fitting transmission models with turnover.

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Ignoring turnover in risk could underestimate the transmission population attributable fraction (tPAF), of high risk groups to the overall epidemic.