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Introduction: In sub-Saharan Africa, accurate estimates of the HIV epidemic in female sex workers are crucial for effective prevention and care strategies. These estimates are typically derived from mathematical models that assume certain demographic and behavioural characteristics like age and duration of sex work to remain constant over time. We reviewed this assumption for female sex workers in South Africa. Methods: We reviewed studies that reported estimates on either the age or the duration of sex work among female sex workers in South Africa. We used Bayesian hierarchical models to synthesize reported estimates and to study time trends. In a simulation exercise, we also investigated the potential impact of the "constant age and sex work duration"-assumption on estimates of HIV incidence. Results: We included 24 different studies, conducted between 1996 and 2019, contributing 42 estimates on female sex worker age and 27 estimates on sex work duration. There was evidence suggesting an increase in both the duration of sex work and the age of female sex workers over time. According to the fitted models, over each decade the expected duration of sex work increased by 55.6% (95%-credible interval [CrI]: 23.5%e93.9%) and the expected age of female sex workers increased by 14.3% (95%-CrI: 9.1%e19.1%). Over the 23year period, the predicted mean duration of sex work increased from 2.7 years in 1996 to 7.4 years in 2019, while the predicted mean age increased from 26.4 years to 32.3 years. Allowing for these time trends in the simulation exercise resulted in a notable decline in estimated HIV incidence rate among sex workers over time. This decline was significantly more pronounced than when assuming a constant age and duration of sex work. Conclusions: In South Africa, age and duration of sex work in female sex workers increased over time. While this trend might be influenced by factors like expanding community mobilization and improved rights advocacy, the ongoing criminalisation, stigmatisation of sex work and lack of alternative employment opportunities could also be contributing. It is important to account for these changes when estimating HIV indicators in female sex workers. [ABSTRACT FROM AUTHOR]

Introduction In high-burden settings, low-complexity screening tests for tuberculosis (TB) could expand the reach of community-based case-finding efforts. The potential costs and cost-effectiveness of approaches incorporating these tests are poorly understood. Methods We developed a microsimulation model assessing 3 approaches to community-based case-finding in hypothetical populations (India-, South Africa-, The Philippines-, Uganda-, and Vietnam-like settings) with TB prevalence 4 times that of national estimates: (1) screening with a point-of-care C-reactive protein (CRP) test, (2) screening with a more sensitive "Hypothetical Screening test" (95% sensitive for Xpert Ultra-positive TB, 70% specificity; equipment/labor costs similar to Xpert Ultra, but using a $2 cartridge) followed by sputum Xpert Ultra if positive, or (3) testing all individuals with sputum Xpert Ultra. Costs are expressed in 2023 US dollars and include treatment costs. Results Universal Xpert Ultra was estimated to cost a mean $4.0 million (95% uncertainty range: $3.5 to $4.6 million) and avert 3200 (2600 to 3900) TB-related disability-adjusted life years (DALYs) per 100 000 people screened ($670 [The Philippines] to $2000 [Vietnam] per DALY averted). CRP was projected to cost $550 (The Philippines) to $1500 (Vietnam) per DALY averted but with 44% fewer DALYs averted. The Hypothetical Screening test showed minimal benefit compared to universal Xpert Ultra, but if specificity were improved to 95% and per-test cost to $4.5 (all-inclusive), this strategy could cost $390 (The Philippines) to $940 (Vietnam) per DALY averted. Conclusions Screening tests can meaningfully improve the cost-effectiveness of community-based case-finding for TB but only if they are sensitive, specific, and inexpensive. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This research investigated an alternate method for establishing the complex coefficients used in an electric vehicle's mathematical energy consumption model. While other methods for creating electric vehicle energy models exist, it would be beneficial to have a rapid and inexpensive technique that remains accurate. Producing a mathematical energy model for such a vehicle has the challenge of determining its aerodynamic drag and rolling resistance coefficients. Currently and most often, expensive and tedious (time-consuming) methods are used to find these coefficients. Computational fluid dynamics (CFD), wind tunnel testing, and extensive mathematics make this objective challenging. For this work, a solar-powered electric vehicle provided the source data to derive its coefficients cost-effectively and efficiently. Data were collected during a road test of the solar electric vehicle from South Africa to Namibia stretching over 2000 km, in which all required energy variables were recorded. The collected data were used in an optimisation routine to establish the two coefficients by minimising the actual and modelled energy consumption error and controlling the driving speed. The outcome of the optimisation routine produced accurate coefficients with a final error value of less than 5% when applied to a validation data set not used during optimisation. With minor modifications, this method may be integrated into any electric vehicle computer system to autonomously identify its two hard-to-find coefficients while driving, which can be used to provide an accurate and realistic driving range estimation to the driver. [ABSTRACT FROM AUTHOR]

Minimal guidance or maximal independence? How can teachers achieve that complex balance when teaching mathematics? In this pre-and post-test quasi-experimental research study, the authors explored the above broad questions in Grade 10 Financial Mathematics following guided discovery and mathematical modelling principles. Fifty-four (54) Grade 10 students at a Government High School in Johannesburg, South Africa, participated in the study. One group of students was taught following guided discovery and modelling principles and another group was taught the same contents but following explicit instruction. Students' mean scores were compared at the end of the interventions. Two teachers with similar experience and qualifications taught the two groups independently. The main findings revealed that although the overall performance in the posttest appeared similar in both groups, there was in fact a significant difference in understanding the concept of compound interest in the guided discovery and modelling group compared with the explicit instruction group. The research highlights the promise offered by the former teaching approaches over explicit instruction in supporting the understanding of difficult concepts to the students. Our findings led us to propose that foundation skills such as, plotting coordinate points, reading, and interpreting graphs, substituting into, and using formulas, and factorizing algebraic expressions should be thoroughly covered at the lower high school to prepare students to cope with more challenging related concepts at the higher level. [ABSTRACT FROM AUTHOR]

Human behaviour was tipped as the mainstay in the control of further SARS-CoV-2 (COVID-19) spread, especially after the lifting of restrictions by many countries. Countries in which restrictions were lifted soon after the first wave had subsequent waves of COVID-19 infections. In this study, we develop a deterministic model for COVID-19 that includes dynamic non-pharmaceutical interventions known as social dynamics with the goal of simulating the effects of dynamic social processes. The model steady states are determined and their stabilities analysed. The model has a disease-free equilibrium point that is locally asymptotically stable if R 0 < 1. The model exhibits a backward bifurcation, implying that reducing the reproduction number below one is not sufficient for the elimination of the disease. To ascertain the range of parameters that affect social dynamics, numerical simulations are conducted. The only wave in South Africa in which interventions were purely based on human behavior was the first wave. The model is thus fitted to COVID-19 data on the first wave in South Africa, and the findings given in this research have implications for the trajectory of the pandemic in the presence of evolving societal processes. The model presented has the potential to impact how social processes can be modelled in other infectious disease models. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

An upcoming trial may provide further evidence that adolescent/adult-targeted BCG revaccination prevents sustained Mycobacterium tuberculosis infection, but its public health value depends on its impact on overall tuberculosis morbidity and mortality, which will remain unknown. Using previously calibrated models for India and South Africa, we simulated BCG revaccination assuming 45% prevention-of-infection efficacy, and we evaluated scenarios varying additional prevention-of-disease efficacy between +50% (reducing risk) and -50% (increasing risk). Given the assumed prevention-of-infection efficacy and range in prevention-of-disease efficacy, BCG revaccination may have a positive health impact and be cost-effective. This may be useful when considering future evaluations and implementation of adolescent/adult BCG revaccination., Competing Interests: Potential conflicts of interest. R. A. C. was supported for other work by the Bill & Melinda Gates Foundation (BMGF; grant INV-001754) and the National Institutes of Health (NIH) (grant G-202303-69963). T. S. was supported for other work by the NIH (grant G-202303-69963). T. J. S. was supported by funding for the C-040-404 trial from Aeras, Sanofi Pasteur, and the BMGF, awarded to the University of Cape Town. R. G. W. was funded for other work by the Wellcome Trust (grant 218261/Z/19/Z), the NIH (grant 1R01AI147321-01), the European & Developing Countries Clinical Trials Partnership (grant RIA208D-2505B), the UK Medical Research Council (grant CCF 17-7779 via SET Bloomsbury), the Economic and Social Research Council (grant ES/P008011/1), the BMGF (grants OPP1084276, OPP1135288, and INV-001754), and World Health Organization. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Background: Recent years have seen important improvements in available preventive treatment regimens for tuberculosis (TB), and research is ongoing to develop these further. To assist with the formulation of target product profiles for future regimens, we examined which regimen properties would be most influential in the epidemiological impact of preventive treatment. Methods: Following expert consultation, we identified 5 regimen properties relevant to the incidence-reducing impact of a future preventive treatment regimen: regimen duration, efficacy, ease-of-adherence (treatment completion rates in programmatic conditions), forgiveness to non-completion and the barrier to developing rifampicin resistance during treatment. For each regimen property, we elicited expert input for minimally acceptable and optimal (ideal-but-feasible) performance scenarios for future regimens. Using mathematical modelling, we then examined how each regimen property would influence the TB incidence reduction arising from full uptake of future regimens according to current WHO guidelines, in four countries: South Africa, Kenya, India and Brazil. Results: Of all regimen properties, efficacy is the single most important predictor of epidemiological impact, while ease-of-adherence plays an important secondary role. These results are qualitatively consistent across country settings; sensitivity analyses show that these results are also qualitatively robust to a range of model assumptions, including the mechanism of action of future preventive regimens. Conclusions: As preventive treatment regimens against TB continue to improve, understanding the key drivers of epidemiological impact can assist in guiding further development. By meeting these key targets, future preventive treatment regimens could play a critical role in global efforts to end TB. [ABSTRACT FROM AUTHOR]

In this paper, we provide a brief survey of mathematical modelling of malaria and how it is used to understand the transmission and progression of the disease and design strategies for its control to support public health interventions and decisionmaking. We discuss some of the past and present contributions of mathematical modelling of malaria, including the recent development of modelling the transmission-blocking drugs. We also comment on the complexity of the malaria dynamics and, in particular, on its multiscale character with its challenges and opportunities. We illustrate the discussion by presenting a curve fitting using a 95% confidence interval for the South African data for malaria from the years 2001-2018 and provide projections for the number of malaria cases and deaths up to the year 2025. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Evidence suggests HSV-2 infection increases HIV acquisition risk and HIV/HSV-2 coinfection increases transmission risk of both infections. We analysed the potential impact of HSV-2 vaccination in South Africa, a high HIV/HSV-2 prevalence setting., Methods: We adapted a dynamic HIV transmission model for South Africa to incorporate HSV-2, including synergistic effects with HIV, to evaluate the impact of: (i) cohort vaccination of 9-year-olds with a prophylactic vaccine that reduces HSV-2 susceptibility; (ii) vaccination of symptomatically HSV-2-infected individuals with a therapeutic vaccine that reduces HSV shedding., Findings: An 80% efficacious prophylactic vaccine offering lifetime protection with 80% uptake could reduce HSV-2 and HIV incidence by 84.1% (95% Credibility Interval: 81.2-86.0) and 65.4% (56.5-71.6) after 40 years, respectively. This reduces to 57.4% (53.6-60.7) and 42.1% (34.1-48.1) if efficacy is 50%, 56.1% (53.4-58.3) and 41.5% (34.2-46.9) if uptake is 40%, and 29.4% (26.0-31.9) and 24.4% (19.0-28.7) if protection lasts 10 years. An 80% efficacious therapeutic vaccine offering lifetime protection with 40% coverage among symptomatic individuals could reduce HSV-2 and HIV incidence by 29.6% (21.8-40.9) and 26.4% (18.5-23.2) after 40 years, respectively. This reduces to 18.8% (13.7-26.4) and 16.9% (11.7-25.3) if efficacy is 50%, 9.7% (7.0-14.0) and 8.6% (5.8-13.4) if coverage is 20%, and 5.4% (3.8-8.0) and 5.5% (3.7-8.6) if protection lasts 2 years., Interpretation: Prophylactic and therapeutic vaccines offer promising approaches for reducing HSV-2 burden and could have important impact on HIV in South Africa and other high prevalence settings., Funding: WHO, NIAID., Competing Interests: Declaration of interests K.J.L. has received funding from GSK to model the impact and cost-effectiveness of an adolescent gonorrhoea vaccine. KMET reports that since the completion of this work she has changed position and has received payment to her current employer (Aquarius Population Health) for expert consultation in related projects including participation in an expert advisory board for GSK on gonorrhoea., (Copyright © 2023 World Health Organization. Published by Elsevier B.V. All rights reserved.)

Model-based economic evaluations of new interventions have shown that user behaviour (uptake) is a critical driver of overall impact achieved. However, early economic evaluations, prior to introduction, often rely on assumed levels of uptake based on expert opinion or uptake of similar interventions. In addition to the likely uncertainty surrounding these uptake assumptions, they also do not allow for uptake to be a function of product, intervention, or user characteristics. This letter proposes using uptake projections from discrete choice experiments (DCE) to better parameterize uptake and substitution in cost-effectiveness models. A simple impact model is developed and illustrated using an example from the HIV prevention field in South Africa. Comparison between the conventional approach and the DCE-based approach shows that, in our example, DCE-based impact predictions varied by up to 50% from conventional estimates and provided far more nuanced projections. In the absence of observed uptake data and to model the effect of variations in intervention characteristics, DCE-based uptake predictions are likely to greatly improve models parameterizing uptake solely based on expert opinion. This is particularly important for global and national level decision making around introducing new and probably more expensive interventions, particularly where resources are most constrained. [ABSTRACT FROM AUTHOR]

Data on social contact patterns are widely used to parameterize age-mixing matrices in mathematical models of infectious diseases. Most studies focus on close contacts only (i.e., persons spoken with face-to-face). This focus may be appropriate for studies of droplet and short-range aerosol transmission but neglects casual or shared air contacts, who may be at risk from airborne transmission. Using data from 2 provinces in South Africa, we estimated age mixing patterns relevant for droplet transmission, nonsaturating airborne transmission, and Mycobacterium tuberculosis transmission, an airborne infection where saturation of household contacts occurs. Estimated contact patterns by age did not vary greatly between the infection types, indicating that widespread use of close contact data may not be resulting in major inaccuracies. However, contact in persons >50 years of age was lower when we considered casual contacts, and therefore the contribution of older age groups to airborne transmission may be overestimated.

The COVID-19 pandemic caused multiple waves of mortality in South Africa, where three genetic variants of SARS-COV-2 and their ancestral strain dominated consecutively. State-of-the-art mathematical modeling approach was used to estimate the time-varying transmissibility of SARS-COV-2 and the relative transmissibility of Beta, Delta, and Omicron variants. The transmissibility of the three variants were about 73%, 87%, and 276% higher than their preceding variants. To the best of our knowledge, our model is the first simple model that can simulate multiple mortality waves and three variants' replacements in South Africa. The transmissibility of the Omicron variant is substantially higher than that of previous variants.

Background: There is a high risk of Mycobacterium tuberculosis ( Mtb ) transmission in healthcare facilities in high burden settings. WHO guidelines on tuberculosis (TB) infection prevention and control (IPC) recommend a range of measures to reduce transmission in healthcare settings. These were evaluated primarily based on evidence for their effects on transmission to healthcare workers in hospitals. To estimate the overall impact of IPC interventions, it is necessary to also consider their impact on community-wide TB incidence and mortality., Methods: We developed an individual-based model of Mtb transmission in households, primary healthcare (PHC) clinics, and all other congregate settings. The model was parameterised using data from a high HIV prevalence community in South Africa, including data on social contact by setting, by sex, age, and HIV/antiretroviral therapy status; and data on TB prevalence in clinic attendees and the general population. We estimated the proportion of disease in adults that resulted from transmission in PHC clinics, and the impact of a range of IPC interventions in clinics on community-wide TB., Results: We estimate that 7.6% (plausible range 3.9%-13.9%) of non-multidrug resistant and multidrug resistant TB in adults resulted directly from transmission in PHC clinics in the community in 2019. The proportion is higher in HIV-positive people, at 9.3% (4.8%-16.8%), compared with 5.3% (2.7%-10.1%) in HIV-negative people. We estimate that IPC interventions could reduce incident TB cases in the community in 2021-2030 by 3.4%-8.0%, and deaths by 3.0%-7.2%., Conclusions: A non-trivial proportion of TB results from transmission in clinics in the study community, particularly in HIV-positive people. Implementing IPC interventions could lead to moderate reductions in disease burden. We recommend that IPC measures in clinics should be implemented for their benefits to staff and patients, but also for their likely effects on TB incidence and mortality in the surrounding community., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Abstract: The ineffectiveness of policy advice in most African countries could be attributed, amongst others, to the problem of scientists not being able to present or communicate a holistic solutions to policy challenges. As a result, the potential and actual consequences of policies are seldom indicated. It may be demanding to use a more comprehensive and quantitative research method in policy analysis because of limited resources to integrate technical, biophysical with the socio-economic and political variables when analysing policy effects. To exemplify this phenomenon, a forward-looking and prescriptive economic analysis that is being widely used for ex-ante policy analyses was used to make a contribution to the discussion on land redistribution, which is presently not only one of the most definitive political and development issues, but perhaps the most intractable in South Africa. The study develops and uses a mathematical model for regionalised farm-level resource use and output supply response to show that the current policy requires more economic imperatives, as it tends towards smallholder agriculture that has elements of low capital threshold trap. After 30% of the farmland will have been transferred from the large farm type to settle more units of small farm type by 2015, the decrease in the number of large farm units from about 8531 units in the base year to about 7112 farm units will lead to a decline in crop and animal product supplies. Such declines (about 15.3%) will overwhelm the increase of more than 1600% in supplies as a result of increased small farm units. Given the challenges of a free market and the fact that the current farm settlement arrangement lacks appreciable efficiency, the study prescribes land redistribution strategies that consider efficiency along with equity. Taking size as an indication of efficiency, an increase in technical progress at 1, 5 and 10% is expected to shift the supply curves to the right for less risky crop and animal enterprises meaning having more farmland, which may imply reduced lack of capital constraints would not necessarily imply a general increase in all the production activities because of relative risks in revenues. The study however, suggests that agricultural land can act as a safety net for the poor, where the efficiency argument does not hold. [Copyright &y& Elsevier]

Introduction: South Africa experiences significant levels of alcohol-related harm. Recent research suggests minimum unit pricing (MUP) for alcohol would be an effective policy, but high levels of income inequality raise concerns about equity impacts. This paper quantifies the equity impact of MUP on household health and finances in rich and poor drinkers in South Africa., Methods: We draw from extended cost-effectiveness analysis (ECEA) methods and an epidemiological policy appraisal model of MUP for South Africa to simulate the equity impact of a ZAR 10 MUP over a 20-year time horizon. We estimate the impact across wealth quintiles on: (i) alcohol consumption and expenditures; (ii) mortality; (iii) government healthcare cost savings; (iv) reductions in cases of catastrophic health expenditures (CHE) and household savings linked to reduced health-related workplace absence., Results: We estimate MUP would reduce consumption more among the poorest than the richest drinkers. Expenditure would increase by ZAR 353 000 million (1 US$=13.2 ZAR), the poorest contributing 13% and the richest 28% of the increase, although this remains regressive compared with mean income. Of the 22 600 deaths averted, 56% accrue to the bottom two quintiles; government healthcare cost savings would be substantial (ZAR 3.9 billion). Cases of CHE averted would be 564 700, 46% among the poorest two quintiles. Indirect cost savings amount to ZAR 51.1 billion., Conclusions: A MUP policy in South Africa has the potential to reduce harm and health inequality. Fiscal policies for population health require structured policy appraisal, accounting for the totality of effects using mathematical models in association with ECEA methodology., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Background: Elevated rates of tuberculosis in healthcare workers demonstrate the high rate of Mycobacterium tuberculosis (Mtb ) transmission in health facilities in high-burden settings. In the context of a project taking a whole systems approach to tuberculosis infection prevention and control (IPC), we aimed to evaluate the potential impact of conventional and novel IPC measures on Mtb transmission to patients and other clinic attendees., Methods: An individual-based model of patient movements through clinics, ventilation in waiting areas, and Mtb transmission was developed, and parameterised using empirical data from eight clinics in two provinces in South Africa. Seven interventions-codeveloped with health professionals and policy-makers-were simulated: (1) queue management systems with outdoor waiting areas, (2) ultraviolet germicidal irradiation (UVGI) systems, (3) appointment systems, (4) opening windows and doors, (5) surgical mask wearing by clinic attendees, (6) simple clinic retrofits and (7) increased coverage of long antiretroviral therapy prescriptions and community medicine collection points through the Central Chronic Medicine Dispensing and Distribution (CCMDD) service., Results: In the model, (1) outdoor waiting areas reduced the transmission to clinic attendees by 83% (IQR 76%-88%), (2) UVGI by 77% (IQR 64%-85%), (3) appointment systems by 62% (IQR 45%-75%), (4) opening windows and doors by 55% (IQR 25%-72%), (5) masks by 47% (IQR 42%-50%), (6) clinic retrofits by 45% (IQR 16%-64%) and (7) increasing the coverage of CCMDD by 22% (IQR 12%-32%)., Conclusions: The majority of the interventions achieved median reductions in the rate of transmission to clinic attendees of at least 45%, meaning that a range of highly effective intervention options are available, that can be tailored to the local context. Measures that are not traditionally considered to be IPC interventions, such as appointment systems, may be as effective as more traditional IPC measures, such as mask wearing., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Introduction: Age-mixing patterns can have substantial effects on infectious disease dynamics and intervention effects. Data on close contacts (people spoken to and/or touched) are often used to estimate age-mixing. These are not the only relevant contacts for airborne infections such as tuberculosis, where transmission can occur between anybody 'sharing air' indoors. Directly collecting data on age-mixing patterns between casual contacts (shared indoor space, but not 'close') is difficult however. We demonstrate a method for indirectly estimating age-mixing patterns between casual indoor contacts from social contact data., Methods: We estimated age-mixing patterns between close, casual, and all contacts using data from a social contact survey in South Africa. The age distribution of casual contacts in different types of location was estimated from the reported time spent in the location type by respondents in each age group., Results: Patterns of age-mixing calculated from contact numbers were similar between close and all contacts, however patterns of age-mixing calculated from contact time were more age-assortative in all contacts than in close contacts. There was also more variation by age group in total numbers of casual and all contacts, than in total numbers of close contacts. Estimates were robust to sensitivity analyses., Conclusions: Patterns of age-mixing can be estimated for all contacts using data that can be easily collected as part of social contact surveys or time-use surveys, and may differ from patterns between close contacts., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

UNAIDS established fast-track targets of 73% and 86% viral suppression among human immunodeficiency virus (HIV)-positive individuals by 2020 and 2030, respectively. The epidemiologic impact of achieving these goals is unknown. The HIV-Calibrated Dynamic Model, a calibrated agent-based model of HIV transmission, is used to examine scenarios of incremental improvements to the testing and antiretroviral therapy (ART) continuum in South Africa in 2015. The speed of intervention availability is explored, comparing policies for their predicted effects on incidence, prevalence and achievement of fast-track targets in 2020 and 2030. Moderate (30%) improvements in the continuum will not achieve 2020 or 2030 targets and have modest impacts on incidence and prevalence. Improving the continuum by 80% and increasing availability reduces incidence from 2.54 to 0.80 per 100 person-years (-1.73, interquartile range (IQR): -1.42, -2.13) and prevalence from 26.0 to 24.6% (-1.4 percentage points, IQR: -0.88, -1.92) from 2015 to 2030 and achieves fast track targets in 2020 and 2030. Achieving 90-90-90 in South Africa is possible with large improvements to the testing and treatment continuum. The epidemiologic impact of these improvements depends on the balance between survival and transmission benefits of ART with the potential for incidence to remain high.

Background: Evidence on the relative costs and effects of interventions that do not consider 'real-world' constraints on implementation may be misleading. However, in many low- and middle-income countries, time and data scarcity mean that incorporating health system constraints in priority setting can be challenging. Methods: We developed a 'proof of concept' method to empirically estimate health system constraints for inclusion in model-based economic evaluations, using intensified case-finding strategies (ICF) for tuberculosis (TB) in South Africa as an example. As part of a strategic planning process, we quantified the resources (fiscal and human) needed to scale up different ICF strategies (cough triage and WHO symptom screening). We identified and characterised three constraints through discussions with local stakeholders: (1) financial constraint: potential maximum increase in public TB financing available for new TB interventions; (2) human resource constraint: maximum current and future capacity among public sector nurses that could be dedicated to TB services; and (3) diagnostic supplies constraint: maximum ratio of Xpert MTB/RIF tests to TB notifications. We assessed the impact of these constraints on the costs of different ICF strategies. Results: It would not be possible to reach the target coverage of ICF (as defined by policy makers) without addressing financial, human resource and diagnostic supplies constraints. The costs of addressing human resource constraints is substantial, increasing total TB programme costs during the period 2016–2035 by between 7% and 37% compared to assuming the expansion of ICF is unconstrained, depending on the ICF strategy chosen. Conclusions: Failure to include the costs of relaxing constraints may provide misleading estimates of costs, and therefore cost-effectiveness. In turn, these could impact the local relevance and credibility of analyses, thereby increasing the risk of sub-optimal investments. [ABSTRACT FROM AUTHOR]

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.