A Comparison of Two Mathematical Modeling Frameworks for Evaluating Sexually Transmitted Infection Epidemiology

Dynamics of Neisseria gonorrhoeae transmission among female sex workers and clients: A mathematical modeling study

BACKGROUND

This study aimed to examine the transmission dynamics of Neisseria gonorrhoeae (NG) in heterosexual sex work networks (HSWNs) and the impact of variation in sexual behavior and interventions on NG epidemiology.

METHODS

The study employed an individual-based mathematical model to simulate NG transmission dynamics in sexual networks involving female sex workers (FSWs) and their clients, primarily focusing on the Middle East and North Africa region. A deterministic model was also used to describe NG transmission from clients to their spouses.

RESULTS

NG epidemiology in HSWNs displays two distinct patterns. In the common low-partner-number HSWNs, a significant proportion of NG incidence occurs among FSWs, with NG prevalence 13 times higher among FSWs than clients, and three times higher among clients than their spouses. Interventions substantially reduce incidence. Increasing condom use from 10 % to 50 % lowers NG prevalence among FSWs, clients, and their spouses from 12.2 % to 6.4 %, 1.2 % to 0.5 %, and 0.4 % to 0.2 %, respectively. Increasing symptomatic treatment coverage among FSWs from 0 % to 100 % decreases prevalence from 10.6 % to 4.5 %, 0.8 % to 0.4 %, and 0.3 % to 0.1 %, respectively. Increasing asymptomatic treatment coverage among FSWs from 0 % to 50 % decreases prevalence from 8.2 % to 0.4 %, 0.6 % to 0.1 %, and 0.2 % to 0.0 %, respectively, with very low prevalence when coverage exceeds 50 %. In high-partner-number HSWNs, prevalence among FSWs saturates at a high level, and the vast majority of incidence occurs among clients and their spouses, with a limited impact of incremental increases in interventions.

CONCLUSION

NG epidemiology in HSWNs is typically a "fragile epidemiology" that is responsive to a range of interventions even if the interventions are incremental, partially efficacious, and only applied to FSWs.

Potential impact of curative and preventive interventions toward hepatitis C elimination in people who inject drugs-A network modeling study

BACKGROUND

Injection-equipment-sharing networks play an important role in hepatitis C virus (HCV) transmission among people who inject drugs (PWID). Direct-acting antiviral (DAA) treatments for HCV infection and interventions to prevent HCV transmission are critical components of an overall hepatitis C elimination strategy, but how they contribute to the elimination outcomes in different PWID network settings are unclear.

METHODS

We developed an agent-based network model of HCV transmission through the sharing of injection equipment among PWID and parameterized and calibrated the model with rural PWID data in the United States. We modeled curative and preventive interventions at annual coverage levels of 12.5 %, 25 %, or 37.5 % (cumulative percentage of eligible individuals engaged), and two allocation approaches: random vs targeting PWID with more injection partners (hereafter 'degree-based'). We compared the impact of these intervention strategies on prevalence and incidence of HCV infections. We conducted sensitivity analysis on key parameters governing the effects of curative and preventive interventions and PWID network characteristics.

RESULTS

Combining curative and preventive interventions at 37.5 % annual coverage with degree-based allocation decreased prevalence and incidence of HCV infection by 67 % and 70 % over two years, respectively. Curative interventions decreased prevalence by six to 12 times more than preventive interventions, while curative and preventive interventions had comparable effectiveness on reducing incidence. Intervention impact increased with coverage almost linearly across all intervention strategies, and degree-based allocation was always more effective than random allocation, especially for preventive interventions. Results were sensitive to parameter values defining intervention effects and network mean degree.

CONCLUSION

DAA treatments are effective in reducing both prevalence and incidence of HCV infection in PWID, but preventive interventions play a significant role in reducing incidence when intervention coverage is low. Increasing coverage, including efforts in reaching individuals with the most injection partners, preventing reinfection, and improving compliance and retention in preventive services can substantially improve the outcomes. PWID network characteristics should be considered when designing hepatitis C elimination programs.

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

Introduction

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

Methods

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

Results

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

Conclusion

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

New HIV Infections Among Key Populations and Their Partners in 2010 and 2022, by World Region: A Multisources Estimation

BACKGROUND

Previously, The Joint United Nations Programme on HIV/AIDS estimated proportions of adult new HIV infections among key populations (KPs) in the last calendar year, globally and in 8 regions. We refined and updated these, for 2010 and 2022, using country-level trend models informed by national data.

METHODS

Infections among 15-49 year olds were estimated for sex workers (SWs), male clients of female SW, men who have sex with men (MSM), people who inject drugs (PWID), transgender women (TGW), and non-KP sex partners of these groups. Transmission models used were Goals (71 countries), AIDS Epidemic Model (13 Asian countries), Optima (9 European and Central Asian countries), and Thembisa (South Africa). Statistical Estimation and Projection Package fits were used for 15 countries. For 40 countries, new infections in 1 or more KPs were approximated from first-time diagnoses by the mode of transmission. Infection proportions among nonclient partners came from Goals, Optima, AIDS Epidemic Model, and Thembisa. For remaining countries and groups not represented in models, median proportions by KP were extrapolated from countries modeled within the same region.

RESULTS

Across 172 countries, estimated proportions of new adult infections in 2010 and 2022 were both 7.7% for SW, 11% and 20% for MSM, 0.72% and 1.1% for TGW, 6.8% and 8.0% for PWID, 12% and 10% for clients, and 5.3% and 8.2% for nonclient partners. In sub-Saharan Africa, proportions of new HIV infections decreased among SW, clients, and non-KP partners but increased for PWID; elsewhere these groups' 2010-to-2022 differences were opposite. For MSM and TGW, the proportions increased across all regions.

CONCLUSIONS

KPs continue to have disproportionately high HIV incidence.

An agent-based model of binge drinking, inequitable gender norms and their contribution to HIV transmission, with application to South Africa

BACKGROUND

Binge drinking, inequitable gender norms and sexual risk behaviour are closely interlinked. This study aims to model the potential effect of alcohol counselling interventions (in men and women) and gender-transformative interventions (in men) as strategies to reduce HIV transmission.

METHODS

We developed an agent-based model of HIV and other sexually transmitted infections, allowing for effects of binge drinking on sexual risk behaviour, and effects of inequitable gender norms (in men) on sexual risk behaviour and binge drinking. The model was applied to South Africa and was calibrated using data from randomized controlled trials of alcohol counselling interventions (n = 9) and gender-transformative interventions (n = 4) in sub-Saharan Africa. The model was also calibrated to South African data on alcohol consumption and acceptance of inequitable gender norms. Binge drinking was defined as five or more drinks on a single day, in the last month.

RESULTS

Binge drinking is estimated to be highly prevalent in South Africa (54% in men and 35% in women, in 2021), and over the 2000-2021 period 54% (95% CI: 34-74%) of new HIV infections occurred in binge drinkers. Binge drinking accounted for 6.8% of new HIV infections (0.0-32.1%) over the same period, which was mediated mainly by an effect of binge drinking in women on engaging in casual sex. Inequitable gender norms accounted for 17.5% of incident HIV infections (0.0-68.3%), which was mediated mainly by an effect of inequitable gender norms on male partner concurrency. A multi-session alcohol counselling intervention that reaches all binge drinkers would reduce HIV incidence by 1.2% (0.0-2.5%) over a 5-year period, while a community-based gender-transformative intervention would reduce incidence by 3.2% (0.8-7.2%) or by 7.3% (0.6-21.2%) if there was no waning of intervention impact.

CONCLUSIONS

Although binge drinking and inequitable gender norms contribute substantially to HIV transmission in South Africa, recently-trialled alcohol counselling and gender-transformative interventions are likely to have only modest effects on HIV incidence. Further innovation in developing locally-relevant interventions to address binge drinking and inequitable gender norms is needed.

Impact and cost-effectiveness of the national scale-up of HIV pre-exposure prophylaxis among female sex workers in South Africa: a modelling analysis

INTRODUCTION

In 2016, South Africa (SA) initiated a national programme to scale-up pre-exposure prophylaxis (PrEP) among female sex workers (FSWs), with ∼20,000 PrEP initiations among FSWs (∼14% of FSW) by 2020. We evaluated the impact and cost-effectiveness of this programme, including future scale-up scenarios and the potential detrimental impact of the COVID-19 pandemic.

METHODS

A compartmental HIV transmission model for SA was adapted to include PrEP. Using estimates on self-reported PrEP adherence from a national study of FSW (67.7%) and the Treatment and Prevention for FSWs (TAPS) PrEP demonstration study in SA (80.8%), we down-adjusted TAPS estimates for the proportion of FSWs with detectable drug levels (adjusted range: 38.0-70.4%). The model stratified FSW by low (undetectable drug; 0% efficacy) and high adherence (detectable drug; 79.9%; 95% CI: 67.2-87.6% efficacy). FSWs can transition between adherence levels, with lower loss-to-follow-up among highly adherent FSWs (aHR: 0.58; 95% CI: 0.40-0.85; TAPS data). The model was calibrated to monthly data on the national scale-up of PrEP among FSWs over 2016-2020, including reductions in PrEP initiations during 2020. The model projected the impact of the current programme (2016-2020) and the future impact (2021-2040) at current coverage or if initiation and/or retention are doubled. Using published cost data, we assessed the cost-effectiveness (healthcare provider perspective; 3% discount rate; time horizon 2016-2040) of the current PrEP provision.

RESULTS

Calibrated to national data, model projections suggest that 2.1% of HIV-negative FSWs were currently on PrEP in 2020, with PrEP preventing 0.45% (95% credibility interval, 0.35-0.57%) of HIV infections among FSWs over 2016-2020 or 605 (444-840) infections overall. Reductions in PrEP initiations in 2020 possibly reduced infections averted by 18.57% (13.99-23.29). PrEP is cost-saving, with $1.42 (1.03-1.99) of ART costs saved per dollar spent on PrEP. Going forward, existing coverage of PrEP will avert 5,635 (3,572-9,036) infections by 2040. However, if PrEP initiation and retention doubles, then PrEP coverage increases to 9.9% (8.7-11.6%) and impact increases 4.3 times with 24,114 (15,308-38,107) infections averted by 2040.

CONCLUSIONS

Our findings advocate for the expansion of PrEP to FSWs throughout SA to maximize its impact. This should include strategies to optimize retention and should target women in contact with FSW services.

Knowing the unknown: The underestimation of monkeypox cases. Insights and implications from an integrative review of the literature

Monkeypox is an emerging zoonotic disease caused by the monkeypox virus, which is an infectious agent belonging to the genus Orthopoxvirus. Currently, commencing from the end of April 2022, an outbreak of monkeypox is ongoing, with more than 43,000 cases reported as of 23 August 2022, involving 99 countries and territories across all the six World Health Organization (WHO) regions. On 23 July 2022, the Director-General of the WHO declared monkeypox a global public health emergency of international concern (PHEIC), since the outbreak represents an extraordinary, unusual, and unexpected event that poses a significant risk for international spread, requiring an immediate, coordinated international response. However, the real magnitude of the burden of disease could be masked by failures in ascertainment and under-detection. As such, underestimation affects the efficiency and reliability of surveillance and notification systems and compromises the possibility of making informed and evidence-based policy decisions in terms of the adoption and implementation of ad hoc adequate preventive measures. In this review, synthesizing 53 papers, we summarize the determinants of the underestimation of sexually transmitted diseases, in general, and, in particular, monkeypox, in terms of all their various components and dimensions (under-ascertainment, underreporting, under-detection, under-diagnosis, misdiagnosis/misclassification, and under-notification).

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.

Modelling the impact of prevention strategies on cervical cancer incidence in South Africa

In 2020, the World Health Organisation (WHO) published a strategy to eliminate cervical cancer as a public health concern. In South Africa, despite having a national screening policy in place since 2000, diagnosed cervical cancer incidence has shown no signs of decline. We extend a previously developed individual-based model for human immunodeficiency virus (HIV) and human papillomavirus (HPV) infection to include progression to cervical cancer. The model accounts for future reductions in HIV incidence and prevalence and includes a detailed cervical cancer screening algorithm, based on individual-level data from the public health sector. We estimate the impact of the current prevention programme and alternative screening scenarios on cervical cancer incidence. The South African screening programme prevented 8600 (95%CI 4700-12 300) cervical cancer cases between 2000 and 2019. At current levels of prevention (status quo vaccination, screening, and treatment), age-standardised cervical cancer incidence will reduce from 49.4 per 100 000 women (95%CI 36.6-67.2) in 2020, to 12.0 per 100 000 women (95%CI 8.0-17.2) in 2120. Reaching WHO's prevention targets by 2030 could help South Africa reach elimination (at the 10/100 000 threshold) by 2077 (94% probability of elimination by 2120). Using new screening technologies could reduce incidence to 4.7 per 100 000 women (95%CI 2.8-6.7) in 2120 (44% probability of elimination at the 4/100 000 threshold). HPV vaccination and decreasing HIV prevalence will substantially reduce cervical cancer incidence in the long term, but improvements to South Africa's current screening strategy will be required to prevent cases in the short term. Switching to new screening technologies will have the greatest impact.

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.

Strategic options for syphilis control in Papua New Guinea- impact and cost-effectiveness projections using the syphilis interventions towards elimination (SITE) model

Objectives

Papua New Guinea (PNG) has among the highest rates of sexually transmitted infections (STIs) globally and is committed to reducing their incidence. The Syphilis Interventions Towards Elimination (SITE) model was used to explore the expected impact and cost of alternative syphilis intervention scale-up scenarios.

Methods

SITE is a dynamical model of syphilis transmission among adults 15-49 years. Individuals are divided into nine groups based on sexual behaviour and into six stages of infection. The model was calibrated to PNG using data from routine surveillance, bio-behavioural surveys, research studies and program records. Inputs included syphilis prevalence, risk behaviours, intervention coverage and service delivery unit costs. Scenarios compared different interventions (clinical treatment, contact tracing, syphilis screening, and condom promotion) for incidence and cost per infection averted over 2021-2030.

Results

Increasing treatment coverage of symptomatic primary/secondary-stage syphilis cases from 25-35% in 2020 to 60% from 2023 onwards reduced estimated incidence over 2021-2030 by 55%, compared to a scenario assuming constant coverage at 2019-2020 levels. The introduction of contact tracing in 2020, assuming 0.4 contacts per symptomatic person treated, reduced incidence over 2021-2030 by 10%. Increasing screening coverage by 20-30 percentage points from the 2019-2020 level reduced incidence over 2021-2030 by 3-16% depending on the target population. Scaling-up clinical, symptom-driven treatment and contact tracing had the lowest cost per infection averted, followed by condom promotion and periodic screening of female sex workers and men who have sex with men.

Conclusions

PNG could considerably reduce its syphilis burden by scaling-up clinical treatment and contact tracing alongside targeted behavioural risk reduction interventions. SITE is a useful tool countries can apply to inform national STI programming and resource allocation.

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.

•

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

•

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

•

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

•

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

•

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

Global epidemiology of Neisseria gonorrhoeae in infertile populations: systematic review, meta-analysis and metaregression

Objective

To provide an in-depth systematic assessment of the global epidemiology of gonorrhoea infection in infertile populations.

Methods

A systematic literature review was conducted up to 29 April 2019 on international databases and WHO regional databases, and reported following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. All prevalence measures of gonorrhoea infection among infertile populations, based on primary data, qualified for inclusion. Infertile populations were broadly defined to encompass women/men undergoing infertility evaluation or treatment (infertility clinic attendees and partners). Pooled mean prevalence by relevant strata was estimated using random-effects meta-analysis. Associations with prevalence and sources of heterogeneity were explored using metaregression. Risk of bias was assessed using four quality domains.

Findings

A total of 147 gonorrhoea prevalence studies were identified from 56 countries. The pooled mean prevalence of current gonorrhoea infection was estimated globally at 2.2% (95% CI 1.3% to 3.2%), with the highest prevalence in Africa at 5.0% (95% CI 1.9% to 9.3%). The mean prevalence was higher for populations with tubal factor infertility (3.6%, 95% CI 0.9%–7.7%) and mixed cause and unexplained infertility (3.6%, 95% CI 0.0% to 11.6%) compared with other diagnoses, such as ovarian and non-tubal infertility (0.1%, 95% CI 0.0% to 0.8%), and for secondary (2.5%, 95% CI 0.2% to 6.5%) compared with primary (0.5%, 95% CI 0.0% to 1.7%) infertility. Metaregression identified evidence of variations in prevalence by region and by infertility diagnosis, higher prevalence in women than men and a small-study effect. There was a trend of declining prevalence by about 3% per year over the last four decades (OR=0.97, 95% CI 0.95 to 0.99).

Conclusions

Gonorrhoea prevalence in infertile populations is several folds higher than that in the general population, with even higher prevalence in women with tubal factor infertility and in individuals with secondary infertility. These findings support the potential role of gonorrhoea in infertility and suggest that some infertility is possibly preventable by controlling gonorrhoea transmission.

PROSPERO registration number

CRD42018102934.

Calibration of individual-based models to epidemiological data: A systematic review

Individual-based models (IBMs) informing public health policy should be calibrated to data and provide estimates of uncertainty. Two main components of model-calibration methods are the parameter-search strategy and the goodness-of-fit (GOF) measure; many options exist for each of these. This review provides an overview of calibration methods used in IBMs modelling infectious disease spread. We identified articles on PubMed employing simulation-based methods to calibrate IBMs informing public health policy in HIV, tuberculosis, and malaria epidemiology published between 1 January 2013 and 31 December 2018. Articles were included if models stored individual-specific information, and calibration involved comparing model output to population-level targets. We extracted information on parameter-search strategies, GOF measures, and model validation. The PubMed search identified 653 candidate articles, of which 84 met the review criteria. Of the included articles, 40 (48%) combined a quantitative GOF measure with an algorithmic parameter-search strategy–either an optimisation algorithm (14/40) or a sampling algorithm (26/40). These 40 articles varied widely in their choices of parameter-search strategies and GOF measures. For the remaining 44 (52%) articles, the parameter-search strategy could either not be identified (32/44) or was described as an informal, non-reproducible method (12/44). Of these 44 articles, the majority (25/44) were unclear about the GOF measure used; of the rest, only five quantitatively evaluated GOF. Only a minority of the included articles, 14 (17%) provided a rationale for their choice of model-calibration method. Model validation was reported in 31 (37%) articles. Reporting on calibration methods is far from optimal in epidemiological modelling studies of HIV, malaria and TB transmission dynamics. The adoption of better documented, algorithmic calibration methods could improve both reproducibility and the quality of inference in model-based epidemiology. There is a need for research comparing the performance of calibration methods to inform decisions about the parameter-search strategies and GOF measures.

Calibration—that is, “fitting” the model to data—is a crucial part of using mathematical models to better forecast and control the population-level spread of infectious diseases. Evidence that the mathematical model is well-calibrated improves confidence that the model provides a realistic picture of the consequences of health policy decisions. To make informed decisions, Policymakers need information about uncertainty: i.e., what is the range of likely outcomes (rather than just a single prediction). Thus, modellers should also strive to provide accurate measurements of uncertainty, both for their model parameters and for their predictions. This systematic review provides an overview of the methods used to calibrate individual-based models (IBMs) of the spread of HIV, malaria, and tuberculosis. We found that less than half of the reviewed articles used reproducible, non-subjective calibration methods. For the remaining articles, the method could either not be identified or was described as an informal, non-reproducible method. Only one-third of the articles obtained estimates of parameter uncertainty. We conclude that the adoption of better-documented, algorithmic calibration methods could improve both reproducibility and the quality of inference in model-based epidemiology.

The impact of self-selection based on HIV risk on the cost-effectiveness of preexposure prophylaxis in South Africa

OBJECTIVES

We explored the impact and cost-effectiveness of preexposure prophylaxis (PrEP) provision to different populations in South Africa, with and without effective self-selection by individuals at highest risk of contracting HIV (through concurrent partnerships and/or commercial sex).

DESIGN AND METHODS

We used a previously developed HIV transmission model to analyse the epidemiological impact of PrEP provision to adolescents, young adults, pregnant women, female sex workers (FSWs) and (MSM), and data from South African PrEP programmes to estimate the cost and cost-effectiveness of PrEP (cost in 2019 USD per HIV infection averted over 20 years, 2019, 38). PrEP uptake followed data from early implementation sites, scaled-up linearly over 3 years, with target coverage set to 18% for adolescents, young adults and pregnant women, 30% for FSW and 54% for MSM.

RESULTS

The annual cost of PrEP provision ranges between $75 and $134 per person. PrEP provision adolescents and young adults, regardless of risk behaviour, will each avert 3.2--4.8% of HIV infections over 20 years; provision to high-risk individuals only has similar impact at lower total cost. The incremental cost per HIV infection averted is lower in high-risk vs. all-risk sub-populations within female adolescents ($507 vs. $4537), male adolescents ($2108 vs. $5637), young women ($1592 vs. $10 323) and young men ($2605 vs. $7715), becoming cost saving within 20 years for high-risk adolescents, young women, MSM and FSWs.

CONCLUSION

PrEP is an expensive prevention intervention but uptake by those at the highest risk of HIV infection will make it more cost-effective, and cost-saving after 14-18 years.

Modelling the impact of screening for chlamydia and gonorrhoea in youth and other high-prevalence groups in a resource-limited setting

OBJECTIVES

Modelling the potential impact of screening for chlamydia and gonorrhoea in youth and other populations in a resource-limited setting.

METHODS

We extended an agent-based model of heterosexual chlamydia and gonorrhoea transmission in South Africa to investigate the impact of screening strategies in key populations including youth, patients in HIV care, pregnant women and female sex workers (FSWs). Additionally, we compared the modelled impact of a standardised screening programme to results obtained from other published mathematical models of chlamydia screening.

RESULTS

All strategies resulted in reductions in general and targeted population chlamydia and gonorrhoea transmission. Opportunistic screening of patients in youth and HIV care was shown to be the most effective, and FSW screening was shown to be the most efficient strategy. Differences between models could be attributed to differences in the modelled heterogeneity in sexual behaviour as well as differences in assumptions about immunity following chlamydia recovery.

CONCLUSIONS

Taking modelling assumptions into account, opportunistic chlamydia and gonorrhoea screening of youth and those in HIV care represents a viable intervention for reducing sexually transmitted infections in the South African population.

Achieving 90-90-90 Human Immunodeficiency Virus (HIV) Targets Will Not Be Enough to Achieve the HIV Incidence Reduction Target in Australia

Background

We estimated the human immunodeficiency virus (HIV) incidence reduction in Australia that would correspond to achieving the United Nations Program on HIV and AIDS (UNAIDS) 90-90-90 targets by 2020 and extended targets of 95-95-95 by 2030. This was done in combination with various scale-ups of HIV testing, primary prevention, and preexposure prophylaxis (PrEP) among high-risk men who have sex with men (MSM). These projections were evaluated against the target of achieving a 90% reduction in HIV incidence by 2030 compared with 2010 levels.

Methods

A mathematical model.

Results

Achieving 90-90-90 by 2020 was estimated to reduce incidence by 10% from 2010 levels. Achieving 95-95-95 by 2030 was estimated to reduce incidence by 17% from 2010 levels, with the first "95" being achievable by testing low- and high-risk MSM 2 and 4 times per year, respectively. This was improved to a 34% reduction by including a 5-year scale-up of PrEP to 30% coverage among high-risk MSM and to 45% by also increasing MSM condom use from 42% to 60%. However, even with 95-95-95, 2 and 4 tests per year for low- and high-risk MSM, 100% high-risk MSM PrEP coverage, and 100% MSM condom use, only an 80% reduction in incidence was possible by 2030.

Conclusions

Many countries, particularly those with low HIV prevalence, will struggle to achieve a 90% reduction in HIV incidence by 2030, even if UNAIDS targets are met. Most will require substantially higher levels of prevention coverage and higher testing frequencies to reach this target.

Optimal HIV testing strategies for South Africa: a model-based evaluation of population-level impact and cost-effectiveness

Although many African countries have achieved high levels of HIV diagnosis, funding constraints have necessitated greater focus on more efficient testing approaches. We compared the impact and cost-effectiveness of several potential new testing strategies in South Africa, and assessed the prospects of achieving the UNAIDS target of 95% of HIV-positive adults diagnosed by 2030. We developed a mathematical model to evaluate the potential impact of home-based testing, mobile testing, assisted partner notification, testing in schools and workplaces, and testing of female sex workers (FSWs), men who have sex with men (MSM), family planning clinic attenders and partners of pregnant women. In the absence of new testing strategies, the diagnosed fraction is expected to increase from 90.6% in 2020 to 93.8% by 2030. Home-based testing combined with self-testing would have the greatest impact, increasing the fraction diagnosed to 96.5% by 2030, and would be highly cost-effective compared to currently funded HIV interventions, with a cost per life year saved (LYS) of $394. Testing in FSWs and assisted partner notification would be cost-saving; the cost per LYS would also be low in the case of testing MSM ($20/LYS) and self-testing by partners of pregnant women ($130/LYS).

Modeling Public Health Campaigns for Sexually Transmitted Infections via Optimal and Feedback Control

Control of sexually transmitted infections (STIs) poses important challenges to public health authorities. Obstacles for STIs' control include low priority in public health programs and disease transmission mechanisms. This work uses a compartmental pair model to explore different public health strategies on the evolution of STIs. Optimal control and feedback control are used to model realistic strategies for reducing the prevalence of these infections. Feedback control is proposed to model the reaction of public health authorities relative to an alert level. Optimal control is used to model the optimization of available resources for implementing strategies. Numerical simulations are performed using trichomoniasis, gonorrhea, chlamydia and human papillomavirus (HPV) as study cases. HPV is non-curable, and it is analyzed only under transmission control such as condom promotion campaigns. Trichomoniasis, gonorrhea and chlamydia are curable STIs that are modeled here additionally under treatment control. Increased cost-effectiveness ratio is employed as a criterion to measure control strategies performance. The features and drawbacks of control strategies under the pair formation process are discussed.

A dynamic power-law sexual network model of gonorrhoea outbreaks

Human networks of sexual contacts are dynamic by nature, with partnerships forming and breaking continuously over time. Sexual behaviours are also highly heterogeneous, so that the number of partners reported by individuals over a given period of time is typically distributed as a power-law. Both the dynamism and heterogeneity of sexual partnerships are likely to have an effect in the patterns of spread of sexually transmitted diseases. To represent these two fundamental properties of sexual networks, we developed a stochastic process of dynamic partnership formation and dissolution, which results in power-law numbers of partners over time. Model parameters can be set to produce realistic conditions in terms of the exponent of the power-law distribution, of the number of individuals without relationships and of the average duration of relationships. Using an outbreak of antibiotic resistant gonorrhoea amongst men have sex with men as a case study, we show that our realistic dynamic network exhibits different properties compared to the frequently used static networks or homogeneous mixing models. We also consider an approximation to our dynamic network model in terms of a much simpler branching process. We estimate the parameters of the generation time distribution and offspring distribution which can be used for example in the context of outbreak reconstruction based on genomic data. Finally, we investigate the impact of a range of interventions against gonorrhoea, including increased condom use, more frequent screening and immunisation, concluding that the latter shows great promise to reduce the burden of gonorrhoea, even if the vaccine was only partially effective or applied to only a random subset of the population.

Adult gonorrhea, chlamydia and syphilis prevalence, incidence, treatment and syndromic case reporting in South Africa: Estimates using the Spectrum-STI model, 1990-2017

OBJECTIVES

To estimate trends in prevalence and incidence of syphilis, gonorrhea and chlamydia in adult men and women in South Africa.

METHODS

The Spectrum-STI tool estimated trends in prevalence and incidence of active syphilis, gonorrhea and chlamydia, fitting South African prevalence data. Results were used, alongside programmatic surveillance data, to estimate trends in incident gonorrhea cases resistant to first-line treatment, and the reporting gap of symptomatic male gonorrhea and chlamydia cases treated but not reported as cases of urethritis syndrome.

RESULTS

In 2017 adult (15-49 years) the estimated female and male prevalences for syphilis were 0.50% (95% CI: 0.32-0.80%) and 0.97% (0.19-2.28%), for gonorrhea 6.6% (3.8-10.8%) and 3.5% (1.7-6.1%), and for chlamydia 14.7% (9.9-21%) and 6.0% (3.8-10.4%), respectively. Between 1990 and 2017 the estimated prevalence of syphilis declined steadily in women and men, probably in part reflecting improved treatment coverage. For gonorrhea and chlamydia, estimated prevalence and incidence showed no consistent time trend in either women or men. Despite growing annual numbers of gonorrhea cases - reflecting population growth - the estimated number of first line treatment-resistant gonorrhea cases did not increase between 2008 and 2017, owing to changes in first-line antimicrobial treatment regimens for gonorrhea in 2008 and 2014/5. Case reporting completeness among treated male urethritis syndrome episodes was estimated at 10-28% in 2017.

CONCLUSION

South Africa continues to suffer a high STI burden. Improvements in access and quality of maternal, STI and HIV health care services likely contributed to the decline in syphilis prevalence. The lack of any decline in gonorrhea and chlamydia prevalence highlights the need to enhance STI services beyond clinic-based syndromic case management, to reinvigorate primary STI and HIV prevention and, especially for women, to screen for asymptomatic infections.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Are associations between HIV and human papillomavirus transmission due to behavioural confounding or biological effects?

OBJECTIVES

Cohort studies have shown significant increased risk of HIV acquisition following human papillomavirus (HPV) detection and increased risk of new HPV detection in individuals with HIV infection, after adjusting for behavioural risk factors. This study uses an individual-based model to assess whether confounding sexual behaviour factors and network level effects can explain these associations between HIV and HPV infection status, without biological interactions.

METHODS

The model simulates infection with 13 oncogenic HPV types and HIV. It allows for different relationship types, with heterogeneity in probabilities of concurrency and rates of partner change. No effect of prevalent HPV infection on HIV acquisition is assumed and vice versa. The model is calibrated to South African HIV and type-specific HPV prevalence data using a Bayesian approach. The model is used to simulate cohorts with quarterly HIV and HPV testing from 2000 to 2002. These simulated data are analysed using proportional hazard models.

RESULTS

The mean of the unadjusted HRs of HIV acquisition following detection of an oncogenic HPV type calculated for each simulated cohort is 2.6 (95% CI 2.2 to 3.1). The mean of the unadjusted HRs for the effect of HIV on newly detected HPV is 2.5 (95% CI 2.2 to 2.8). Simulated associations between HIV and HPV infection status are similar to corresponding empirical estimates. In sensitivity analyses in which HIV and HPV were assumed to increase each other's transmission risk, simulated associations were stronger but not inconsistent with empirical estimates.

CONCLUSIONS

Although we cannot rule out the possibility that associations between HIV and HPV transmission may be due in part to biological interactions, these results suggest that observed associations could be explained entirely by residual confounding by behavioural factors and network-level effects that observational studies cannot account for.

How various design decisions on matching individuals in relationships affect the outcomes of microsimulations of sexually transmitted infection epidemics

Microsimulations are increasingly used to estimate the prevalence of sexually transmitted infections (STIs). These models consist of agents which represent a sexually active population. Matching agents into sexual relationships is computationally intensive and presents modellers with difficult design decisions: how to select which partnerships between agents break up, which agents enter a partnership market, and how to pair agents in the partnership market. The aim of this study was to analyse the effect of these design decisions on STI prevalence. We compared two strategies for selecting which agents enter a daily partnership market and which agent partnerships break up: random selection in which agents are treated homogenously versus selection based on data from a large German longitudinal data set that accounts for sex, sexual orientation and age heterogeneity. We also coupled each of these strategies with one of several recently described algorithms for pairing agents and compared their speed and outcomes. Additional design choices were also considered, such as the number of agents used in the model, increasing the heterogeneity of agents' sexual behaviour, and the proportion of relationships which are casual sex encounters. Approaches which account for agent heterogeneity estimated lower prevalence than less sophisticated approaches which treat agents homogeneously. Also, in simulations with non-random pairing of agents, as the risk of infection increased, incidence declined as the number of agents increased. Our algorithms facilitate the execution of thousands of simulations with large numbers of agents quickly. Fast pair-matching algorithms provide a practical way for microsimulation modellers to account for varying sexual behaviour within the population they are studying. For STIs with high infection rates modellers may need to experiment with different population sizes.

Age bias in survey sampling and implications for estimating HIV prevalence in men who have sex with men: insights from mathematical modelling

Respondent-driven sampling (RDS) is widely used to estimate HIV prevalence in men who have sex with men (MSM). Mathematical models that are calibrated to these data may be compromised if they fail to account for selection biases in RDS surveys. To quantify the potential extent of this bias, an agent-based model of HIV in South Africa was calibrated to HIV prevalence and sexual behaviour data from South African studies of MSM, first reweighting the modelled MSM population to match the younger age profile of the RDS surveys (age-adjusted analysis) and then without reweighting (unadjusted analysis). The model estimated a median HIV prevalence in South African MSM in 2015 of 34.6% (inter-quartile range (IQR): 31.4-37.2%) in the age-adjusted analysis, compared with 26.1% (IQR: 24.1-28.4%) in the unadjusted analysis. The median lifetime risk of acquiring HIV in exclusively homosexual men was 88% (IQR: 82-92%) in the age-adjusted analysis, compared with 76% (IQR: 64-85%) in the unadjusted analysis. These results suggest that RDS studies may under-estimate the exceptionally high HIV prevalence rates in South African MSM because of over-sampling of younger MSM. Mathematical models that are calibrated to these data need to control for likely over-sampling of younger MSM.

Bypassing the 'rapid-clearance-in-males-buffer': A fourth mechanism to explain how concurrency enhances STI spread

A number of sexually transmitted infections (STIs) persist for a considerably shorter period in the male urethra than the vagina. If the gap between sequential partnerships is longer than the duration of STI colonization in males, then this would protect future female partners from this STI in a setting of serial monogamy. If, however, males have more than one partner at a time (concurrency), then this would enable the STI to bypass this gap/buffer. We therefore propose bypassing the rapid-clearance-in-males-buffer as a fourth mechanism, whereby concurrency could enhance the spread of STIs.

The relationship between intimate partner violence and HIV: A model-based evaluation

Background

Many studies have shown that women who have experienced intimate partner violence (IPV) are at a greater risk of HIV, but the factors accounting for this association are unclear, and trials of interventions to reduce IPV have not consistently reduced HIV incidence.

Methods

This study uses an agent-based model, calibrated to South African data sources, to evaluate hypotheses about likely causal pathways linking IPV, HIV, and other confounding factors. Assumptions about associations between IPV and HIV risk behaviours were based on reviews of international literature.

Findings

There is an association between past IPV experience and HIV incidence even when no causal effects are assumed (IRR 1.28, 95% CI 1.23–1.34), because women with a propensity for multiple partners are more likely to have ever been in a relationship with a violent partner. If, in addition, men with a propensity for concurrent relationships are more likely to perpetrate IPV, the IRR increases to 1.42 (95% CI 1.36–1.48), consistent with empirical IRR estimates. Alternative scenarios in which experience of IPV is assumed to cause changes in women's sexual behaviour have little effect on the IRR. An intervention that reduces IPV by 50% could be expected to reduce HIV incidence by at most 1.3%.

Interpretation

Much of the observed association between IPV and HIV is likely to be due to confounding behavioural factors. Although interventions to reduce IPV are important, these interventions alone are unlikely to have a substantial impact on HIV incidence.

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.