Compartmental Transmission Model Research Articles

Cost-effectiveness of screening and treating alcohol use and depression among people living with HIV in Zimbabwe: a mathematical modeling study

BackgroundAlcohol use disorder (AUD) and major depressive disorder (MDD) drive HIV transmission in many sub-Saharan African settings. The impact of screening and treating AUD and MDD on HIV outcomes is unknown. We aimed to identify the cost-effectiveness of AUD and MDD interventions in Zimbabwe, and their potential contribution to reaching Zimbabwe’s Ending the HIV Epidemic 2030 goal.MethodsUsing a validated HIV compartmental transmission model in Zimbabwe, we compared four policy scenarios: prevention as usual (baseline); implement AUD screening (using AUDIT) and treatment (motivational interviewing and cognitive-behavioral therapy); implement MDD screening (using PHQ-9) and treatment (cognitive-behavioral therapy); and implement screening and treatment for both. Outcomes were HIV incidence projections, infections averted through 2030, quality-adjusted life-years gained, cost per infection averted, and cost per QALY gained. Analyses considered “spillover,” when treatment for AUD also results in an improvement in MDD and the converse. Sensitivity analyses identified cost reductions necessary for AUD and MDD interventions to be as cost-effective as other HIV interventions, particularly the scale-up of long-acting PrEP.ResultsAUD and MDD combined will be responsible for 21.1% of new HIV infections in Zimbabwe by 2030. Without considering spillover, compared to the baseline, MDD intervention can reduce new infections by 5.4% at $2039/infection averted and $3186/QALY. AUD intervention can reduce new infections by 5.8%, but at $2,968/infection averted and $4753/QALY, compared to baseline. Both MDD and AUD interventions can reduce new infections by 11.1% at $2810/infection averted and $4229/QALY, compared to baseline. Considering spillover, compared to the baseline, MDD intervention can reduce new infections by 6.4% at $1714/infection averted and $2630/QALY. AUD intervention can reduce new infections by 7.4%, but at $2299/infection averted and $3560/QALY compared to baseline. Both MDD and AUD interventions can reduce new infections by 11.9% at $2247/infection averted and $3382/QALY compared to baseline. For MDD intervention to match the cost-effectiveness of scaling long-acting PrEP, the cost of MDD intervention would need to be reduced from $16.64 to $12.88 per person.ConclusionsImplementing AUD and MDD interventions can play an important role in HIV reduction in Zimbabwe, particularly if intervention cost can be decreased while preserving effectiveness.

Population and transmission dynamics model to determine WHO targets for eliminating Hepatitis C virus in Thailand.

Hepatitis C Virus is endemic to many areas of Thailand, whose population structure is tending towards older age groups as birth rate and mortality decrease. With around 790,000 cases in 2019, prevalence is still relatively high, but the World Health Organisation has called for elimination of HCV by 2030. An age structured compartmental transmission model was used to explore the effectiveness of screening strategies with respect to WHO elimination goals, as well as the effect of changing population structure on the success or failure of such strategies. Population structure did not appear to affect the timeline of elimination targets and screening individuals over the age of 30 at a high (50% per year) coverage could bring forward achievement of the incidence elimination target by four years compared to baseline (approximately 6% per year). Achievement of mortality elimination targets was not reached until after the end of the simulation (2040), and intensive screening strategies did not appear to lead to incidence elimination by 2030. The model suggested that with age-targeted screening programmes incidence elimination could be brought forward by several years. However, WHO elimination goals may not be met by 2030.

Mass incarceration as a driver of the tuberculosis epidemic in Latin America and projected effects of policy alternatives: a mathematical modelling study

Tuberculosis incidence is increasing in Latin America, where the incarcerated population has nearly quadrupled since 1990. We aimed to quantify the impact of historical and future incarceration policies on the tuberculosis epidemic, accounting for effects in and beyond prisons. In this modelling study, we calibrated dynamic compartmental transmission models to historical and contemporary data from Argentina, Brazil, Colombia, El Salvador, Mexico, and Peru, which comprise approximately 80% of the region's incarcerated population and tuberculosis burden. The model was fit independently for each country to incarceration and tuberculosis data from 1990 to 2023 (specific dates were country dependent). The model does not include HIV, drug resistance, gender or sex, or age structure. Using historical counterfactual scenarios, we estimated the transmission population attributable fraction (tPAF) for incarceration and the excess population-level burden attributable to increasing incarceration prevalence since 1990. We additionally projected the effect of alternative incarceration policies on future population tuberculosis incidence. Population tuberculosis incidence in 2019 was 29·4% (95% uncertainty interval [UI] 23·9-36·8) higher than expected without the rise in incarceration since 1990, corresponding to 34 393 (28 295-42 579) excess incident cases across countries. The incarceration tPAF in 2019 was 27·2% (20·9-35·8), exceeding estimates for other risk factors like HIV, alcohol use disorder, and undernutrition. Compared with a scenario where incarceration rates remain stable at current levels, a gradual 50% reduction in prison admissions and duration of incarceration by 2034 would reduce population tuberculosis incidence by over 10% in all countries except Mexico. The historical rise in incarceration in Latin America has resulted in a large excess tuberculosis burden that has been under-recognised to date. International health agencies, ministries of justice, and national tuberculosis programmes should collaborate to address this health crisis with comprehensive strategies, including decarceration. National Institutes of Health.

Mass incarceration as a driver of the tuberculosis epidemic in Latin America and projected impacts of policy alternatives: A mathematical modeling study.

Tuberculosis incidence is increasing in Latin America, where the incarcerated population has nearly quadrupled since 1990. The full impact of incarceration on the tuberculosis epidemic, accounting for effects beyond prisons, has never been quantified. We calibrated dynamic compartmental transmission models to historical and contemporary data from Argentina, Brazil, Colombia, El Salvador, Mexico, and Peru, which comprise approximately 80% of the region's incarcerated population and tuberculosis burden. Using historical counterfactual scenarios, we estimated the transmission population attributable fraction (tPAF) for incarceration and the excess population-level burden attributable to increasing incarceration prevalence since 1990. We additionally projected the impact of alternative incarceration policies on future population tuberculosis incidence. Population tuberculosis incidence in 2019 was 29.4% (95% UI, 23.9-36.8) higher than expected without the rise in incarceration since 1990, corresponding to 34,393 (95% UI, 28,295-42,579) excess incident cases across countries. The incarceration tPAF in 2019 was 27.2% (95% UI, 20.9-35.8), exceeding estimates for other risk factors like HIV, alcohol use disorder, and undernutrition. Compared to a scenario where incarceration rates remain stable at current levels, a gradual 50% reduction in prison admissions and duration of incarceration by 2034 would reduce population tuberculosis incidence by over 10% in all countries except Mexico. The historical rise in incarceration in Latin America has resulted in a large excess tuberculosis burden that has been under-recognized to-date. International health agencies, ministries of justice, and national tuberculosis programs should collaborate to address this health crisis with comprehensive strategies, including decarceration. National Institutes of Health.

Bayesian workflow for time-varying transmission in stratified compartmental infectious disease transmission models.

Compartmental models that describe infectious disease transmission across subpopulations are central for assessing the impact of non-pharmaceutical interventions, behavioral changes and seasonal effects on the spread of respiratory infections. We present a Bayesian workflow for such models, including four features: (1) an adjustment for incomplete case ascertainment, (2) an adequate sampling distribution of laboratory-confirmed cases, (3) a flexible, time-varying transmission rate, and (4) a stratification by age group. Within the workflow, we benchmarked the performance of various implementations of two of these features (2 and 3). For the second feature, we used SARS-CoV-2 data from the canton of Geneva (Switzerland) and found that a quasi-Poisson distribution is the most suitable sampling distribution for describing the overdispersion in the observed laboratory-confirmed cases. For the third feature, we implemented three methods: Brownian motion, B-splines, and approximate Gaussian processes (aGP). We compared their performance in terms of the number of effective samples per second, and the error and sharpness in estimating the time-varying transmission rate over a selection of ordinary differential equation solvers and tuning parameters, using simulated seroprevalence and laboratory-confirmed case data. Even though all methods could recover the time-varying dynamics in the transmission rate accurately, we found that B-splines perform up to four and ten times faster than Brownian motion and aGPs, respectively. We validated the B-spline model with simulated age-stratified data. We applied this model to 2020 laboratory-confirmed SARS-CoV-2 cases and two seroprevalence studies from the canton of Geneva. This resulted in detailed estimates of the transmission rate over time and the case ascertainment. Our results illustrate the potential of the presented workflow including stratified transmission to estimate age-specific epidemiological parameters. The workflow is freely available in the R package HETTMO, and can be easily adapted and applied to other infectious diseases.

Vaccination May Be Economically and Epidemiologically Advantageous Over Frequent Screening for Gonorrhea Prevention.

Gonorrhea's rapid development of antimicrobial resistance underscores the importance of new prevention modalities. Recent evidence suggests that a serogroup B meningococcal vaccine may be partially effective against gonococcal infection. However, the viability of vaccination and the role it should play in gonorrhea prevention are an open question. We modeled the transmission of gonorrhea over a 10-year period in a heterosexual population to find optimal patterns of year-over-year investment of a fixed budget in vaccination and screening programs. Each year, resources could be allocated to vaccinating people or enrolling them in a quarterly screening program. Stratifying by mode (vaccination vs. screening), sex (male vs. female), and enrollment venue (background screening vs. symptomatic visit), we consider 8 different ways of controlling gonorrhea. We then found the year-over-year pattern of investment among those 8 controls that most reduced the incidence of gonorrhea under different assumptions. A compartmental transmission model was parameterized from existing literature in the US context. Vaccinating men with recent symptomatic infection, which selected for higher sexual activity, was optimal for population-level gonorrhea control. Given a prevention budget of $3 per capita, 9.5% of infections could be averted ($299 per infection averted), decreasing gonorrhea sequelae and associated antimicrobial use by similar percentages. These results were consistent across sensitivity analyses that increased the budget, prioritized incidence or prevalence reductions in women, or lowered screening costs. Under a scenario where only screening was implemented, just 5.5% of infections were averted. A currently available vaccine, although only modestly effective, may be superior to frequent testing for population-level gonorrhea control.

A competitive infectious transmission model

Compartmental disease transmission models are widely used to model state transmission in infectious diseases, using differential equations to model the change in the number of units in different states over time, and recently has produced significant practical implications in many downstream fields. However, inspired by the transmission of rumors in social media, we note that the previous compartmental transfer models neglect the "competitiveness" during the transfer process, that is, the "infection" of people with positive and negative opinions to "susceptibles" or even people with opposing views. To tackle the above issues, in this paper, we propose a novel competitive infectious transmission model in which the "infection" will lead to more people supporting the opinion of the infector, effectively establishing the change of the number of units in the positive, negative, and neutral parties over time. In addition, we performed extensive theoretical analysis to investigate the property of the disease-free equilibrium and to calculate the basic reproduction numbers for three different scenarios. For each system, we derive explicit solutions for the basic reproduction numbers and discuss their important implications for guidance in practice.

Transmission dynamics and effect of control measures on the 2022 outbreak of mpox among gay, bisexual, and other men who have sex with men in England: a mathematical modelling study

The 2022 global outbreak of mpox (formerly known as monkeypox) spread primarily among gay, bisexual, and other men who have sex with men (GBMSM), with the initial cluster being identified in England in May, 2022. Understanding its epidemiological characteristics and the reasons for its downturn in July, 2022, will help to control future outbreaks. We collated data for all diagnosed mpox cases (3621) from England from May 1, 2022, to Nov 16, 2022. Data from 75 individuals with mpox allowed estimation of the incubation period, while data from 121 case-contact pairs were used to estimate the serial interval. Six methods, including a structured dynamic compartmental transmission model, were used to estimate the basic reproduction number (R0). The structured model assumed all male individuals with mpox were GBMSM, who were then stratified into subgroups for those at low risk and high risk for mpox. This best fitting model was used to estimate the reduction in transmissibility, and the effective infectious period (before isolating), that resulted in the outbreak downturn, and the effect of vaccination initiated from June 27, 2022. Bayesian methods were used for parameter estimation and model calibration. Most cases occurred in men (3544 of 3621, 97·9%). The median incubation period for mpox was 6·90 days (95% credible interval [CrI] 4·08-20·21), and the serial interval was 8·82 days (5·22-25·81). R0 estimates ranged from 1·41 to 2·17. The structured transmission model estimated that 83·8% of infections (95% CrI 83·5-85·3) resulted from sexual partnerships with GBMSM individuals at high risk of mpox. The outbreak downturn probably resulted from a 44·5% reduction in the sexual partner rate among all GBMSM (24·9-55·8) and 20·0% reduction in the effective infectious period (4·1-33·9), preventing 165 896 infections (115 584-217 730). Vaccination marginally increased the number of infections prevented (166 081, 115 745-217 947), but minimised a resurgence in cases from January, 2023, and could have averted four times more infections if initiated earlier. Our findings were sensitive to assumptions regarding the vaccine's effectiveness and the GBMSM subgroup at high risk of mpox. The mpox outbreak in England probably resulted from high sexual partner rates among some GBMSM, with reductions in partner rates reversing the outbreak, and with vaccination minimising future outbreaks. National Institute for Health Research (UK).

New tuberculosis vaccines in India: modelling the potential health and economic impacts of adolescent/adult vaccination with M72/AS01E and BCG-revaccination

BackgroundIndia had an estimated 2.9 million tuberculosis cases and 506 thousand deaths in 2021. Novel vaccines effective in adolescents and adults could reduce this burden. M72/AS01E and BCG-revaccination have recently completed phase IIb trials and estimates of their population-level impact are needed. We estimated the potential health and economic impact of M72/AS01E and BCG-revaccination in India and investigated the impact of variation in vaccine characteristics and delivery strategies.MethodsWe developed an age-stratified compartmental tuberculosis transmission model for India calibrated to country-specific epidemiology. We projected baseline epidemiology to 2050 assuming no-new-vaccine introduction, and M72/AS01E and BCG-revaccination scenarios over 2025–2050 exploring uncertainty in product characteristics (vaccine efficacy, mechanism of effect, infection status required for vaccine efficacy, duration of protection) and implementation (achieved vaccine coverage and ages targeted). We estimated reductions in tuberculosis cases and deaths by each scenario compared to the no-new-vaccine baseline, as well as costs and cost-effectiveness from health-system and societal perspectives.ResultsM72/AS01E scenarios were predicted to avert 40% more tuberculosis cases and deaths by 2050 compared to BCG-revaccination scenarios. Cost-effectiveness ratios for M72/AS01E vaccines were around seven times higher than BCG-revaccination, but nearly all scenarios were cost-effective. The estimated average incremental cost was US$190 million for M72/AS01E and US$23 million for BCG-revaccination per year. Sources of uncertainty included whether M72/AS01E was efficacious in uninfected individuals at vaccination, and if BCG-revaccination could prevent disease.ConclusionsM72/AS01E and BCG-revaccination could be impactful and cost-effective in India. However, there is great uncertainty in impact, especially given the unknowns surrounding the mechanism of effect and infection status required for vaccine efficacy. Greater investment in vaccine development and delivery is needed to resolve these unknowns in vaccine product characteristics.

Estimating the effectiveness of control actions on African swine fever transmission in commercial swine populations in the United States.

Given the proximity of African swine fever (ASF) to the U.S., there is an urgent need to better understand the possible dissemination pathways of the virus within the U.S. swine industry and to evaluate mitigation strategies. Here, we extended PigSpread, a farm-level spatially-explicit stochastic compartmental transmission model incorporating six transmission routes including between-farm swine movements, vehicle movements, and local spread, to model the dissemination of ASF. We then examined the effectiveness of control actions similar to the ASF national response plan. The average number of secondary infections during the first 60 days of the outbreak was 49 finisher farms, 17 nursery farms, 5 sow farms, and less than one farm in other production types. The between-farm movements of swine were the predominant route of ASF transmission with an average contribution of 71.1%, while local spread and movement of vehicles were less critical with average contributions of 14.6% and 14.4%. We demonstrated that the combination of quarantine, depopulation, movement restrictions, contact tracing, and enhanced surveillance, was the most effective mitigation strategy, resulting in an average reduction of 79.0% of secondary cases by day 140 of the outbreak. Implementing these control actions led to a median of 495,619 depopulated animals, 357,789 diagnostic tests, and 54,522 movement permits. Our results suggest that the successful elimination of an ASF outbreak is likely to require the deployment of all control actions listed in the ASF national response plan for more than 140 days, as well as estimating the resources needed for depopulation, testing, and movement permits under these controls.

Design of effective outpatient sentinel surveillance for COVID-19 decision-making: a modeling study

BackgroundDecision-makers impose COVID-19 mitigations based on public health indicators such as reported cases, which are sensitive to fluctuations in supply and demand for diagnostic testing, and hospital admissions, which lag infections by up to two weeks. Imposing mitigations too early has unnecessary economic costs while imposing too late leads to uncontrolled epidemics with unnecessary cases and deaths. Sentinel surveillance of recently-symptomatic individuals in outpatient testing sites may overcome biases and lags in conventional indicators, but the minimal outpatient sentinel surveillance system needed for reliable trend estimation remains unknown.MethodsWe used a stochastic, compartmental transmission model to evaluate the performance of various surveillance indicators at reliably triggering an alarm in response to, but not before, a step increase in transmission of SARS-CoV-2. The surveillance indicators included hospital admissions, hospital occupancy, and sentinel cases with varying levels of sampling effort capturing 5, 10, 20, 50, or 100% of incident mild cases. We tested 3 levels of transmission increase, 3 population sizes, and conditions of either simultaneous transmission increase or lagged increase in the older population. We compared the indicators’ performance at triggering alarm soon after, but not prior, to the transmission increase.ResultsCompared to surveillance based on hospital admissions, outpatient sentinel surveillance that captured at least 20% of incident mild cases could trigger an alarm 2 to 5 days earlier for a mild increase in transmission and 6 days earlier for a moderate or strong increase. Sentinel surveillance triggered fewer false alarms and averted more deaths per day spent in mitigation. When transmission increase in older populations lagged the increase in younger populations by 14 days, sentinel surveillance extended its lead time over hospital admissions by an additional 2 days.ConclusionsSentinel surveillance of mild symptomatic cases can provide more timely and reliable information on changes in transmission to inform decision-makers in an epidemic like COVID-19.

Long-term projections of the impacts of warming temperatures on Zika and dengue risk in four Brazilian cities using a temperature-dependent basic reproduction number.

For vector-borne diseases the basic reproduction number [Formula: see text], a measure of a disease's epidemic potential, is highly temperature-dependent. Recent work characterizing these temperature dependencies has highlighted how climate change may impact geographic disease spread. We extend this prior work by examining how newly emerging diseases, like Zika, will be impacted by specific future climate change scenarios in four diverse regions of Brazil, a country that has been profoundly impacted by Zika. We estimated a [Formula: see text], derived from a compartmental transmission model, characterizing Zika (and, for comparison, dengue) transmission potential as a function of temperature-dependent biological parameters specific to Aedes aegypti. We obtained historical temperature data for the five-year period 2015-2019 and projections for 2045-2049 by fitting cubic spline interpolations to data from simulated atmospheric data provided by the CMIP-6 project (specifically, generated by the GFDL-ESM4 model), which provides projections under four Shared Socioeconomic Pathways (SSP). These four SSP scenarios correspond to varying levels of climate change severity. We applied this approach to four Brazilian cities (Manaus, Recife, Rio de Janeiro, and São Paulo) that represent diverse climatic regions. Our model predicts that the [Formula: see text] for Zika peaks at 2.7 around 30°C, while for dengue it peaks at 6.8 around 31°C. We find that the epidemic potential of Zika will increase beyond current levels in Brazil in all of the climate scenarios. For Manaus, we predict that the annual [Formula: see text] range will increase from 2.1-2.5, to 2.3-2.7, for Recife we project an increase from 0.4-1.9 to 0.6-2.3, for Rio de Janeiro from 0-1.9 to 0-2.3, and for São Paulo from 0-0.3 to 0-0.7. As Zika immunity wanes and temperatures increase, there will be increasing epidemic potential and longer transmission seasons, especially in regions where transmission is currently marginal. Surveillance systems should be implemented and sustained for early detection.

The National COVID-19 Epi Model (NCEM): Estimating cases, admissions and deaths for the first wave of COVID-19 in South Africa.

In March 2020 the South African COVID-19 Modelling Consortium was formed to support government planning for COVID-19 cases and related healthcare. Models were developed jointly by local disease modelling groups to estimate cases, resource needs and deaths due to COVID-19. The National COVID-19 Epi Model (NCEM) while initially developed as a deterministic compartmental model of SARS-Cov-2 transmission in the nine provinces of South Africa, was adapted several times over the course of the first wave of infection in response to emerging local data and changing needs of government. By the end of the first wave, the NCEM had developed into a stochastic, spatially-explicit compartmental transmission model to estimate the total and reported incidence of COVID-19 across the 52 districts of South Africa. The model adopted a generalised Susceptible-Exposed-Infectious-Removed structure that accounted for the clinical profile of SARS-COV-2 (asymptomatic, mild, severe and critical cases) and avenues of treatment access (outpatient, and hospitalisation in non-ICU and ICU wards). Between end-March and early September 2020, the model was updated 11 times with four key releases to generate new sets of projections and scenario analyses to be shared with planners in the national and provincial Departments of Health, the National Treasury and other partners. Updates to model structure included finer spatial granularity, limited access to treatment, and the inclusion of behavioural heterogeneity in relation to the adoption of Public Health and Social Measures. These updates were made in response to local data and knowledge and the changing needs of the planners. The NCEM attempted to incorporate a high level of local data to contextualise the model appropriately to address South Africa's population and health system characteristics that played a vital role in producing and updating estimates of resource needs, demonstrating the importance of harnessing and developing local modelling capacity.

Modeling Respiratory Syncytial Virus Adult Vaccination in the United States with a Dynamic Transmission Model.

Respiratory syncytial virus (RSV) is shown to cause substantial morbidity, hospitalization, and mortality in infants and older adults. Population-level modelling of RSV would allow for estimation of the full burden of disease and the potential epidemiological impact of novel prophylactics. We model the epidemiology of RSV in the US across all ages using a deterministic compartmental transmission model. Population-level symptomatic RSV acute respiratory tract infection (ARI) cases were projected across different natural history scenarios, both with and without vaccination of older adults aged ≥ 60. Impact of vaccine efficacy against ARIs and infectiousness and vaccine coverage on ARI incidence were assessed. Impact on medical attendance, hospitalization, complications, death and other outcomes were also derived. In the absence of a vaccine, we project 17.5-22.6 million symptomatic RSV ARI cases per year in ≥18-year-olds in the US, with 3.6-4.8 million/year occurring in ≥60-year-olds. Modelling indicates that up to 2.0 million symptomatic RSV ARI cases per year could be prevented in ≥60-year-olds with a hypothetical vaccine (70% vaccine efficacy against symptomatic ARI, and 60% vaccine coverage), and up to 0.69 million cases per year can be prevented in the non-vaccinated population, assuming 50% vaccine impact on infectiousness. The model provides estimated burden of RSV in the US across all age groups, with substantial burden projected specifically in older adults. Vaccination of ≥ 60 years-old population could significantly reduce the burden of disease in this population, with additional indirect effect in the < 60 years-old population due to reduced transmissibility.

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

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. 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. 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. 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.

The epidemiological impact and cost-effectiveness of key population-led PrEP delivery to prevent HIV among men who have sex with men in Thailand: A modelling study.

Although key populations (KPs), such as men-who-have-sex-with-men (MSM) are disproportionately affected by HIV, many prevention and treatment services are not easily accessible for KP members. To address the needs of KPs, Thailand established pre-exposure prophylaxis (PrEP) service delivery together with and led by KP members. This study determines the epidemiological impact and cost-effectiveness of key population-led (KP-led) PrEP. We calibrated a compartmental deterministic HIV transmission model to the HIV epidemic among Thai MSM. Besides KP-led PrEP, we included other Thai service delivery models of PrEP (fee-based PrEP, the government PrEP program).Data on consistent PrEP use (5 years daily use, 95% effectiveness for preventing HIV) came from Thai PrEP delivery models. For the period 2015-2032, we ranged the number of PrEP starters (40,000-120,000), effectiveness of PrEP (45%-95%), and proportion of consistent users (10%-50%). The analysis started in 2015 when PrEP was introduced. A cost-effectiveness ratio of <160,000 Baht per quality-adjusted life year (QALY) over 40 years was cost-effective. Without PrEP, 53,800 (interquartile range 48,700-59,700) new HIV infections are expected in 2015-2032. KP-led PrEP was found to have the strongest epidemiological impact of all delivery models averting 58% of infections compared to without PrEP. The epidemiological impact depends on the number of PrEP starters and proportion of consistent use. Although all PrEP service delivery models are cost-effective, KP-led PrEP is most cost-effective with incremental cost-effectiveness ratios of 28,000-37,300 Thai Baht per QALY. Our model projects KP-led PrEP having the greatest epidemiological impact and being the most cost-effective service delivery model of PrEP in Thailand. This study was supported by the US Agency for International Development and U.S. President's Emergency Plan for AIDS Relief through the Linkages Across the Continuum of HIV Services for Key Populations cooperative agreement (AID-OAA-A-14- 0045) managed by FHI 360.

Maximizing the impact of limited vaccine supply under different early epidemic conditions: a 2-city modelling analysis of monkeypox virus transmission among men who have sex with men.

The current global monkeypox virus (MPXV) outbreak has disproportionately affected gay, bisexual and other men who have sex with men (GBMSM). Given that many jurisdictions have been faced with limited supplies of MPXV vaccine, we aimed to explore optimal vaccine allocation between 2 linked GBMSM transmission networks over a short-term time horizon, across several epidemic conditions. We constructed a deterministic compartmental MPXV transmission model. We parameterized the model to reflect 2 representative, partially connected GBMSM sexual networks ( cities), using 2022 data from Ontario. We simulated a roll-out of 5000 vaccine doses over 30 days that started 45 days after epidemic seeding with 10 imported cases. Within this model, we varied the relative city (network) sizes, epidemic potentials (R 0), between-city mixing and distribution of seed cases between cities. For each combination of varied factors, we identified the allocation of doses between cities that maximized infections averted by day 90. Under our modelling assumptions, we found that a limited MPXV vaccine supply could generally avert more early infections when prioritized to networks that were larger, had more initial infections or had greater R 0. Greater between-city mixing decreased the influence of initial seed cases and increased the influence of city R 0 on optimal allocation. Under mixed conditions (e.g., fewer seed cases but greater R 0), optimal allocation required doses shared between cities. In the context of the current global MPXV outbreak, we showed that prioritization of a limited supply of vaccines based on network-level factors can help maximize infections averted during an emerging epidemic. Such prioritization should be grounded in an understanding of context-specific risk drivers and should acknowledge potential connectedness of multiple transmission networks.

Structural identifiability of compartmental models for infectious disease transmission is influenced by data type

If model identifiability is not confirmed, inferences from infectious disease transmission models may not be reliable, so they might result in misleading recommendations. Structural identifiability analysis characterises whether it is possible to obtain unique solutions for all unknown model parameters, given the model structure. In this work, we studied the structural identifiability of some typical deterministic compartmental models for infectious disease transmission, focusing on the influence of the data type considered as model output on the identifiability of unknown model parameters, including initial conditions. We defined 26 model versions, each having a unique combination of underlying compartmental structure and data type(s) considered as model output(s). Four compartmental model structures and three common data types in disease surveillance (incidence, prevalence and detected vector counts) were studied. The structural identifiability of some parameters varied depending on the type of model output. In general, models with multiple data types as outputs had more structurally identifiable parameters, than did models with a single data type as output. This study highlights the importance of a careful consideration of data types as an integral part of the inference process with compartmental infectious disease transmission models.

The Cost-Effectiveness of Vaccination of Older Adults with an MF59-Adjuvanted Quadrivalent Influenza Vaccine Compared to Other Available Quadrivalent Vaccines in Germany.

Enhanced quadrivalent influenza vaccines that include an adjuvant (aQIV) or a high dose of antigen (QIV-HD), which stimulate a stronger immune response in older adults than the standard vaccine (QIVe), are now approved. The objective of this research is to compare available vaccines and determine the cost-effectiveness of immunizing persons aged 65 years and above with aQIV compared to QIVe and QIV-HD in Germany. A compartmental transmission model calibrated to outpatient visits for influenza in Germany was used to predict the number of medically attended infections using the three vaccines. The rates of hospitalizations, deaths, and other economic consequences were estimated with a decision tree using German data where available. Based on meta-analysis, the rVE of −2.5% to 8.9% for aQIV versus QIV-HD, the vaccines are similar clinically, but aQIV is cost saving compared to QIV-HD (unit cost of EUR 40.55). All results were most sensitive to changes in vaccine effectiveness. aQIV may be cost-effective compared to QIVe depending on the willingness to pay for additional benefits in Germany. As aQIV and QIV-HD are similar in terms of effectiveness, aQIV is cost saving compared to QIV-HD at current unit prices.

Population benefits of addressing programmatic and social determinants of gender disparities in tuberculosis in Viet Nam: A modelling study.

High prevalence of infectious tuberculosis among men suggests potential population-wide benefits from addressing programmatic and social determinants of gender disparities. Utilising a sex-stratified compartmental transmission model calibrated to tuberculosis burden estimates for Viet Nam, we modelled interventions to increase active case finding, to reduce tobacco smoking, and to reduce alcohol consumption by 2025 in line with national and global targets. For each intervention, we examined scenarios differentially targeting men and women and evaluated impact on tuberculosis morbidity and mortality in men, women, and children in 2035. Active case finding interventions targeting men projected greater reductions in tuberculosis incidence in men, women, and children (16.2%, uncertainty interval, UI, 11.4-23.0%, 11.8%, UI 8.0-18.6%, and 21.5%, UI 16.9-28.5%, respectively) than those targeting women (5.2%, UI 3.8-7.1%, 5.4%, UI 3.9-7.3%, and 8.6%, UI 6.9-10.7%, respectively). Projected reductions in tuberculosis incidence for interventions to reduce male tobacco smoking and alcohol consumption were greatest for men (17.4%, UI 11.8-24.7%, and 11.0%, UI 5.4-19.4%, respectively), but still substantial for women (6.9%, UI 3.8-12.5%, and 4.4%, UI 1.9-10.6%, respectively) and children (12.7%, UI 8.4-19.0%, and 8.0%, UI 3.9-15.0%, respectively). Comparable interventions targeting women projected limited impact, with declines of 0.3% (UI 0.2%-0.3%) and 0.1% (UI 0.0%-0.1%), respectively. Addressing programmatic and social determinants of men's tuberculosis burden has population-wide benefits. Future interventions to increase active case finding, to reduce tobacco smoking, and to reduce harmful alcohol consumption, whilst not ignoring women, should focus on men to most effectively reduce tuberculosis morbidity and mortality in men, women, and children.