Protocol for the Adolescent Menstrual Experiences and Health Cohort (AMEHC) Study in Khulna, Bangladesh: A Prospective cohort to quantify the influence of menstrual health on adolescent girls' health and education outcomes.

BACKGROUND: Menstrual health is essential for gender equity and the well-being of women and girls. Qualitative research has described the burden of poor menstrual health on health and education; however, these impacts have not been quantified, curtailing investment. The Adolescent Menstrual Experiences and Health Cohort (AMEHC) Study aims to describe menstrual health and its trajectories across adolescence, and quantify the relationships between menstrual health and girls' health and education in Khulna, Bangladesh. METHODS AND ANALYSIS: AMEHC is a prospective longitudinal cohort of 2016 adolescent girls recruited at the commencement of class 6 (secondary school, mean age=12) across 101 schools selected through a proportional random sampling approach. Each year, the cohort will be asked to complete a survey capturing (1) girls' menstrual health and experiences, (2) support for menstrual health, and (3) health and education outcomes. Survey questions were refined through qualitative research, cognitive interviews and pilot survey in the year preceding the cohort. Girls' guardians will be surveyed at baseline and wave 2 to capture their perspectives and household demographics. Annual assessments will capture schools' water, sanitation and hygiene, and support for menstruation and collect data on participants' education, including school attendance and performance (in maths, literacy). Cohort enrolment and baseline survey commenced in February 2023. Follow-up waves are scheduled for 2024, 2025 and 2026, with plans for extension. A nested subcohort will follow 406 post-menarche girls at 2-month intervals throughout 2023 (May, August, October) to describe changes across menstrual periods. This protocol outlines a priori hypotheses regarding the impacts of menstrual health to be tested through the cohort. ETHICS AND DISSEMINATION: AMEHC has ethical approval from the Alfred Hospital Ethics Committee (369/22) and BRAC James P Grant School of Public Health Institutional Review Board (IRB-06 July 22-024). Study materials and outputs will be available open access through peer-reviewed publication and study web pages.

A Framework for Assessing the Impact of Outbreak Response Immunization Programs.

The impact of outbreak response immunization (ORI) can be estimated by comparing observed outcomes to modelled counterfactual scenarios without ORI, but the most appropriate metrics depend on stakeholder needs and data availability. This study developed a framework for using mathematical models to assess the impact of ORI for vaccine-preventable diseases. Framework development involved (1) the assessment of impact metrics based on stakeholder interviews and literature reviews determining data availability and capacity to capture as model outcomes; (2) mapping investment in ORI elements to model parameters to define scenarios; (3) developing a system for engaging stakeholders and formulating model questions, performing analyses, and interpreting results; and (4) example applications for different settings and pathogens. The metrics identified as most useful were health impacts, economic impacts, and the risk of severe outbreaks. Scenario categories included investment in the response scale, response speed, and vaccine targeting. The framework defines four phases: (1) problem framing and data sourcing (identification of stakeholder needs, metrics, and scenarios); (2) model choice; (3) model implementation; and (4) interpretation and communication. The use of the framework is demonstrated by application to two outbreaks, measles in Papua New Guinea and Ebola in the Democratic Republic of the Congo. The framework is a systematic way to engage with stakeholders and ensure that an analysis is fit for purpose, makes the best use of available data, and uses suitable modelling methodology.

Evaluation of the use of modelling in resource allocation decisions for HIV and TB.

INTRODUCTION: Globally, resources for health spending, including HIV and tuberculosis (TB), are constrained, and a substantial gap exists between spending and estimated needs. Optima is an allocative efficiency modelling tool that has been used since 2010 in over 50 settings to generate evidence for country-level HIV and TB resource allocation decisions. This evaluation assessed the utilisation of modelling to inform financing priorities from the perspective of country stakeholders and their international partners. METHODS: In October to December 2021, the World Bank and Burnet Institute led 16 semi-structured small-group virtual interviews with 54 representatives from national governments and international health and funding organisations. Interviews probed participants' roles and satisfaction with Optima analyses and how model findings have had been used and impacted resource allocation. Interviewed stakeholders represented nine countries and 11 different disease programme-country contexts with prior Optima modelling analyses. Interview notes were thematically analysed to assess factors influencing the utilisation of modelling evidence in health policy and outcomes. RESULTS: Common influences on utilisation of Optima findings encompassed the perceived validity of findings, health system financing mechanisms, the extent of stakeholder participation in the modelling process-including engagement of funding organisations, sociopolitical context and timeliness of the analysis. Using workshops can facilitate effective stakeholder engagement and collaboration. Model findings were often used conceptually to localise global evidence and facilitate discussion. Secondary outputs included informing strategic and financial planning, funding advocacy, grant proposals and influencing investment shifts. CONCLUSION: Allocative efficiency modelling has supported evidence-informed decision-making in numerous contexts and enhanced the conceptual and practical understanding of allocative efficiency. Most immediately, greater involvement of country stakeholders in modelling studies and timing studies to key strategic and financial planning decisions may increase the impact on decision-making. Better consideration for integrated disease modelling, equity goals and financing constraints may improve relevance and utilisation of modelling findings.

Cost-effectiveness of a decentralized, community-based "one-stop-shop" hepatitis C testing and treatment program in Yangon, Myanmar.

Background and Aim: The availability of direct-acting antiviral (DAA) treatment and point-of-care diagnostic testing has made hepatitis C (HCV) elimination possible even in low- and middle-income countries (LMICs); however, testing and treatment costs remain a barrier. We estimated the cost and cost-effectiveness of a decentralized community-based HCV testing and treatment program (CT2) in Myanmar. Methods: Primary cost data included the costs of DAAs, investigations, medical supplies and other consumables, staff salaries, equipment, and overheads. A deterministic cohort-based Markov model was used to estimate the average cost of care, the overall quality-adjusted life years (QALYs) gained, and the incremental cost-effectiveness ratio (ICER) of providing testing and DAA treatment compared with a modeled counterfactual scenario of no testing and no treatment. Results: From 30 January to 30 September 2019, 633 patients were enrolled, of whom 535 were HCV RNA-positive, 489 were treatment eligible, and 488 were treated. Lifetime discounted costs and QALYs of the cohort in the counterfactual no testing and no treatment scenario were estimated to be USD61790 (57 898-66 898) and 6309 (5682-6363) respectively, compared with USD123 248 (122 432-124 101) and 6518 (5894-6671) with the CT2 model of care, giving an ICER of USD294 (192-340) per QALY gained. This "one-stop-shop" model of care has a 90% likelihood of being cost-effective if benchmarked against a willingness to pay of US$300, which is 20% of Myanmar's GDP per capita (2020). Conclusions: The CT2 model of HCV care is cost-effective in Myanmar and should be expanded to meet the National Hepatitis Control Program's 2030 target, alongside increasing the affordability and accessibility of services.

Connecting patients notified with hepatitis C to treatment (CONNECT Study): A randomized controlled trial of active case management by a health department to support primary care practitioners.

BACKGROUND: Despite subsidised access to direct-acting antivirals (DAAs), hepatitis C (HCV) treatment uptake in Australia is declining. Interventions are needed to link people living with HCV to care and treatment. We implemented and measured effectiveness of a state-wide, health department-led, enhanced case management through the primary care practitioner for all HCV notifications, aiming to encourage and support treatment commencement. METHODS: A randomised controlled trial compared enhanced case management, delivered by the health department to diagnosing clinicians, with standard of care using notifiable disease systems in Tasmania, Australia (2020-21). The intervention involved a nurse specialist contacting and providing support by telephone to primary care practitioners making an HCV notification. The primary outcome was the proportion of cases notified with chronic hepatitis C who commenced treatment within 12 weeks of notification. We allowed a 12-week extended follow-up period at the end of the study for participants with no outcomes. RESULTS: Eighty-five primary care practitioners randomised to the intervention and 86 to standard of care arms notified 111 and 115 HCV cases, respectively. The proportion of cases notified with chronic hepatitis (HCV RNA detected) commencing treatment within 12 weeks was similar between study arms (41% vs 33%; p=0·51) and after extended study follow-up (65% vs 48%; p=0·18). RNA test completion was higher in the intervention than in standard of care arm (89% vs. 78%; p=0·03), while completing pre-treatment workup for chronic patients (65% vs. 64%; p=0·93) was similar. CONCLUSION: This was the first prospective randomised study of the utility of immediate HCV notification follow-up of primary care practitioners to enhance treatment uptake using disease notification surveillance data. We demonstrated improvement in HCV RNA testing and trend toward better engagement in care, but no significant increase in treatment uptake.

A global investment case for hepatitis B elimination: a modelling study.

Hepatitis B is estimated to cause 500 000-900 000 deaths globally each year. WHO has targets for elimination by 2030; however, progress has stalled due to multiple barriers, notably a paucity of global funding and insufficient evidence on the economic burden of disease. Using a dynamic mathematical model of hepatitis B transmission, disease progression, and mortality in the six WHO regions, we estimate the costs and benefits of reaching 90% vaccination, 90% diagnosis, and 80% treatment coverage by either 2030 (as targeted), 2040, or 2050. Without increased intervention coverage, hepatitis B mortality was estimated to cost US$784·35 billion (95% Crl 731·63-798·33 billion) globally in lost productivity over 2022-50. Achieving targets by 2030 averted 25·64 million infections (95% Crl 17·39-34·55 million) and 8·63 million hepatitis B-attributable deaths (95% Crl 7·12-9·74 million) over 2022-50. This achievement incurred an incremental cost of $2934·55 (95% Crl 2778·55-3173·52) per disability-adjusted life year averted by 2050 under a health systems perspective, and was cost-saving with a net economic benefit of $99·03 billion (95% Crl 78·66-108·96 billion) by 2050 from a societal perspective. Delayed achievement of intervention coverage targets had reduced health and economic benefits. These findings highlight that hepatitis B is an underappreciated cause of economic burden and show investment toward elimination will probably yield substantial returns.

Keeping kids in school: modelling school-based testing and quarantine strategies during the COVID-19 pandemic in Australia.

Background: In 2021, the Australian Government Department of Health commissioned a consortium of modelling groups to generate evidence assisting the transition from a goal of no community COVID-19 transmission to 'living with COVID-19', with adverse health and social consequences limited by vaccination and other measures. Due to the extended school closures over 2020-21, maximizing face-to-face teaching was a major objective during this transition. The consortium was tasked with informing school surveillance and contact management strategies to minimize infections and support this goal. Methods: Outcomes considered were infections and days of face-to-face teaching lost in the 45 days following an outbreak within an otherwise COVID-naïve school setting. A stochastic agent-based model of COVID-19 transmission was used to evaluate a 'test-to-stay' strategy using daily rapid antigen tests (RATs) for close contacts of a case for 7 days compared with home quarantine; and an asymptomatic surveillance strategy involving twice-weekly screening of all students and/or teachers using RATs. Findings: Test-to-stay had similar effectiveness for reducing school infections as extended home quarantine, without the associated days of face-to-face teaching lost. Asymptomatic screening was beneficial in reducing both infections and days of face-to-face teaching lost and was most beneficial when community prevalence was high. Interpretation: Use of RATs in school settings for surveillance and contact management can help to maximize face-to-face teaching and minimize outbreaks. This evidence supported the implementation of surveillance testing in schools in several Australian jurisdictions from January 2022.

COVID-19 epidemic modelling for policy decision support in Victoria, Australia 2020-2021.

BACKGROUND: Policy responses to COVID-19 in Victoria, Australia over 2020-2021 have been supported by evidence generated through mathematical modelling. This study describes the design, key findings, and process for policy translation of a series of modelling studies conducted for the Victorian Department of Health COVID-19 response team during this period. METHODS: An agent-based model, Covasim, was used to simulate the impact of policy interventions on COVID-19 outbreaks and epidemic waves. The model was continually adapted to enable scenario analysis of settings or policies being considered at the time (e.g. elimination of community transmission versus disease control). Model scenarios were co-designed with government, to fill evidence gaps prior to key decisions. RESULTS: Understanding outbreak risk following incursions was critical to eliminating community COVID-19 transmission. Analyses showed risk depended on whether the first detected case was the index case, a primary contact of the index case, or a 'mystery case'. There were benefits of early lockdown on first case detection and gradual easing of restrictions to minimise resurgence risk from undetected cases. As vaccination coverage increased and the focus shifted to controlling rather than eliminating community transmission, understanding health system demand was critical. Analyses showed that vaccines alone could not protect health systems and need to be complemented with other public health measures. CONCLUSIONS: Model evidence offered the greatest value when decisions needed to be made pre-emptively, or for questions that could not be answered with empiric data and data analysis alone. Co-designing scenarios with policy-makers ensured relevance and increased policy translation.

Pathway to global elimination of hepatitis B: HBV cure is just the first step.

Hepatitis B (HBV) is a major cause of global morbidity and mortality, and the leading cause of liver cancer worldwide. Significant advances have recently been made toward the development of a finite HBV treatment that achieves permanent loss of HBsAg and HBV DNA (so-called "HBV cure"), which could provide the means to eliminate HBV as a public health threat. However, the HBV cure is just one step toward achieving WHO HBV elimination targets by 2030, and much work must be done now to prepare for the successful implementation of the HBV cure. In this review, we describe the required steps to rapidly scale-up future HBV cure equitably. We present key actions required for successful HBV cure implementation, integrated within the World Health Organization (WHO) Global Health Sector Strategy (GHSS) 2022-2030 framework. Finally, we highlight what can be done now to progress toward the 2030 HBV elimination targets using available tools to ensure that we are preparing, but not waiting, for the cure.

Health and economic benefits of achieving contraceptive and maternal health targets in Small Island Developing States in the Pacific and Caribbean.

INTRODUCTION: Reducing unmet need for modern contraception and expanding access to quality maternal health (MH) services are priorities for improving women's health and economic empowerment. To support investment decisions, we estimated the additional cost and expected health and economic benefits of achieving the United Nations targets of zero unmet need for modern contraceptive choices and 95% coverage of MH services by 2030 in select Small Island Developing States. METHODS: Five Pacific (Kiribati, Samoa, Solomon Islands, Tonga and Vanuatu) and four Caribbean (Barbados, Guyana, Jamaica and Saint Lucia) countries were considered based on population survey data availability. For each country, the Lives Saved Tool was used to model costs, health outcomes and economic benefits for two scenarios: business-as-usual (BAU) (coverage maintained) and coverage-targets-achieved, which scaled linearly from 2022 (following COVID-19 disruptions) coverage of evidence-based family planning and MH interventions to reach United Nations targets, including modern contraceptive methods and access to complete antenatal, delivery and emergency care. Unintended pregnancies, maternal deaths, stillbirths and newborn deaths averted by the coverage-targets-achieved scenario were converted to workforce, education and social economic benefits; and benefit-cost ratios were calculated. RESULTS: The coverage-targets-achieved scenario required an additional US$12.6M (US$10.8M-US$15.9M) over 2020-2030 for the five Pacific countries (15% more than US$82.4M to maintain BAU). This additional investment was estimated to avert 126 000 (40%) unintended pregnancies, 2200 (28%) stillbirths and 121 (29%) maternal deaths and lead to a 15-fold economic benefit of US$190.6M (US$67.0M-US$304.5M) by 2050. For the four Caribbean countries, an additional US$17.8M (US$15.3M-US$22.4M) was needed to reach the targets (4% more than US$405.4M to maintain BAU). This was estimated to avert 127 000 (23%) unintended pregnancies, 3600 (23%) stillbirths and 221 (25%) maternal deaths and lead to a 24-fold economic benefit of US$426.2M (US$138.6M-US$745.7M) by 2050. CONCLUSION: Achieving full coverage of contraceptive and MH services in the Pacific and Caribbean is likely to have a high return on investment.

Implementing the WHO Labour Care Guide to reduce the use of Caesarean section in four hospitals in India: protocol and statistical analysis plan for a pragmatic, stepped-wedge, cluster-randomized pilot trial.

BACKGROUND: The World Health Organization (WHO) Labour Care Guide (LCG) is a paper-based labour monitoring tool designed to facilitate the implementation of WHO's latest guidelines for effective, respectful care during labour and childbirth. Implementing the LCG into routine intrapartum care requires a strategy that improves healthcare provider practices during labour and childbirth. Such a strategy might optimize the use of Caesarean section (CS), along with potential benefits on the use of other obstetric interventions, maternal and perinatal health outcomes, and women's experience of care. However, the effects of a strategy to implement the LCG have not been evaluated in a randomised trial. This study aims to: (1) develop and optimise a strategy for implementing the LCG (formative phase); and (2) To evaluate the implementation of the LCG strategy compared with usual care (trial phase). METHODS: In the formative phase, we will co-design the LCG strategy with key stakeholders informed by facility assessments and provider surveys, which will be field tested in one hospital. The LCG strategy includes a LCG training program, ongoing supportive supervision from senior clinical staff, and audit and feedback using the Robson Classification. We will then conduct a stepped-wedge, cluster-randomized pilot trial in four public hospitals in India, to evaluate the effect of the LCG strategy intervention compared to usual care (simplified WHO partograph). The primary outcome is the CS rate in nulliparous women with singleton, term, cephalic pregnancies in spontaneous labour (Robson Group 1). Secondary outcomes include clinical and process of care outcomes, as well as women's experience of care outcomes. We will also conduct a process evaluation during the trial, using standardized facility assessments, in-depth interviews and surveys with providers, audits of completed LCGs, labour ward observations and document reviews. An economic evaluation will consider implementation costs and cost-effectiveness. DISCUSSION: Findings of this trial will guide clinicians, administrators and policymakers on how to effectively implement the LCG, and what (if any) effects the LCG strategy has on process of care, health and experience outcomes. The trial findings will inform the rollout of LCG internationally. TRIAL REGISTRATION: CTRI/2021/01/030695 (Protocol version 1.4, 25 April 2022).

The new WHO Labour Care Guide (LCG) is an innovative partograph that emphasises women-centred, evidence-based care during labour and childbirth. Together with clinicians working at four hospitals in India, we will develop and test a strategy to implement the LCG into routine care in labour wards of these hospitals. We will use a randomised trial design where this LCG strategy is introduced sequentially in each of the four hospitals, in a random order. We will collect data on all women giving birth and their newborns during this period and analyse whether the LCG strategy has any effects on the use of Caesarean section, women's and newborn's health outcomes, and women's experiences during labour and childbirth. While the trial is being conducted, we will also collect qualitative and quantitative data from doctors, nurses and midwives working in these hospitals, to understand their perspectives and experiences of using the LCG in their day-to-day work. In addition, we will collect economic data to understand how much the LCG strategy costs, and how much money it might save if it is effective. Through this study, our international collaboration will generate critical evidence and innovative tools to support implementation of the LCG in other countries.

The cost-effectiveness of universal hepatitis B screening for reaching WHO diagnosis targets in Australia by 2030.

OBJECTIVES: To assess the impact on diagnosis targets, cost, and cost-effectiveness of universal hepatitis B screening in Australia. DESIGN: Markov model simulation of disease and care cascade progression for people with chronic hepatitis B in Australia. SETTING: Three scenarios were compared: 1. no change to current hepatitis B virus (HBV) testing practice; 2. universal screening strategy, with the aim of achieving the WHO diagnosis target by 2030 (90% of people with chronic hepatitis B diagnosed), based on opportunistic (general practitioner-initiated) screening for HBsAg; 3. universal screening strategy, and also ensuring that 50% of people with chronic hepatitis B are receiving appropriate clinical management by 2030. MAIN OUTCOME MEASURES: Projected care cascade for people with chronic hepatitis B, cumulative number of HBV-related deaths, intervention costs, and health utility (quality-adjusted life-years [QALYs] gained during 2020-2030). An incremental cost-effectiveness ratio (ICER) threshold (v scenario 1) of $50 000 per QALY gained was applied. RESULTS: Compared with scenario 1, 80 HBV-related deaths (interquartile range [IQR], 41-127 deaths) were averted during 2020-2030 in scenario 2, 315 HBV-related deaths (IQR, 211-454 deaths) in scenario 3. Scenario 2 cost $84 million (IQR, $41-106 million) more than scenario 1 during 2020-2030 (+8%), yielding an ICER of $104 921 (IQR, $49 587-107 952) per QALY gained. Scenario 3 cost $263 million (IQR, $214-316 million) more than scenario 1 during 2020-2030 (+24%), yielding an ICER of $47 341 (IQR, $32 643-58 200) per QALY gained. Scenario 3 remained cost-effective if the test positivity rate was higher than 0.35% or the additional costs per person tested did not exceed $4.02. CONCLUSIONS: Universal screening for hepatitis B will be cost-effective only if the cost of testing is kept low and people receive appropriate clinical management.

Frequent and unpredictable changes in COVID-19 policies and restrictions reduce the accuracy of model forecasts.

Between June and August 2020, an agent-based model was used to project rates of COVID-19 infection incidence and cases diagnosed as positive from 15 September to 31 October 2020 for 72 geographic settings. Five scenarios were modelled: a baseline scenario where no future changes were made to existing restrictions, and four scenarios representing small or moderate changes in restrictions at two intervals. Post hoc, upper and lower bounds for number of diagnosed Covid-19 cases were compared with actual data collected during the prediction window. A regression analysis with 17 covariates was performed to determine correlates of accurate projections. It was found that the actual data fell within the lower and upper bounds in 27 settings and out of bounds in 45 settings. The only statistically significant predictor of actual data within the predicted bounds was correct assumptions about future policy changes (OR 15.04; 95% CI 2.20-208.70; p = 0.016). Frequent changes in restrictions implemented by governments, which the modelling team was not always able to predict, in part explains why the majority of model projections were inaccurate compared with actual outcomes and supports revision of projections when policies are changed as well as the importance of modelling teams collaborating with policy experts.

Estimating the proportion of Victorians infected with COVID-19 during the Omicron BA.1 epidemic wave of January 2022 in Australia.

OBJECTIVE: To estimate the proportion of Victorians infected with COVID-19 in January 2022. METHODS: Between 11-19 February 2022 we conducted a nested cross-sectional survey on experiences of COVID-19 testing, symptoms, test outcome and barriers to testing during January 2022 in Victoria, Australia. Respondents were participants of the Optimise Study, a prospective cohort of adults considered at increased risk of COVID-19 or the unintended consequences of COVID-19-related interventions. RESULTS: Of the 577 participants, 78 (14%) reported testing positive to COVID-19, 240 (42%) did not test in January 2022 and 91 of those who did not test (38%) reported COVID-19-like symptoms. Using two different definitions of symptoms, we calculated symptomatic (27% and 39%) and asymptomatic (4% and 11%) test positivity. We extrapolated these positivity rates to participants who did not test and estimated 19-22% of respondents may have had COVID-19 infection in January 2022. CONCLUSION: The proportion of Victorians infected with COVID-19 in January 2022 was likely considerably higher than officially reported numbers. IMPLICATIONS FOR PUBLIC HEALTH: Our estimate is approximately double the COVID-19 case numbers obtained from official case reporting. This highlights a major limitation of diagnosis data that must be considered when preparing for future waves of infection.

Cost optimisation analysis of the expanded programme for immunisation: balancing equity and coverage in Pakistan.

INTRODUCTION: With limited resources, attaining maximal average health service coverage can be at odds with maximising equity which attempts to promote greater reach among underserved populations. In this study, we examined the trade-offs in immunisation coverage levels and equity for children under 5 years of age in Pakistan across various subpopulations who can be targeted with different combinations of immunisation service modalities. METHODS: We conducted a detailed costing exercise across 16 geographically and demographically diverse districts in Pakistan. These data were the basis for (a) technical efficiency benchmarking via Data Envelopment Analysis to identify potential efficiency gains by location, delivery model and cost ingredient; (b) allocative efficiency optimisation modelling to understand how resource allocations could be optimised and to devise recommended budget allocations and operational metrics. Finally, the hypothetical overall efficiency gains attainable were estimated if available resources were allocated with the optimal emphases, and if service delivery models operated at productivity levels at the benchmarked frontier of efficiency. RESULTS: Benchmarking suggests that ~44% of delivery models are running efficiently and 37% are highly inefficient. While coverage and equity are usually at odds, surprisingly, the optimisation modelling revealed that substantial improvements in equity between subpopulations does not necessarily cost very much in overall immunisation coverage: theoretically, equity can be achieved while still attaining close to maximal immunisation coverage. Overall, analyses suggest greater emphases should be placed on outreach delivery models which particularly target rural areas and slum populations. CONCLUSION: The unit cost differentials within districts are not sufficiently large for there to be a large reduction in potential Fully Immunised Children coverage if one focuses on maximising equity. However, reallocations of programme budgets can have a significant impact on equity outcomes, particularly at current low spending amounts. Therefore, it is recommended to address equity as the key objective in national immunisation programming.

A framework for considering the utility of models when facing tough decisions in public health: a guideline for policy-makers.

The COVID-19 pandemic has brought the combined disciplines of public health, infectious disease and policy modelling squarely into the spotlight. Never before have decisions regarding public health measures and their impacts been such a topic of international deliberation, from the level of individuals and communities through to global leaders. Nor have models-developed at rapid pace and often in the absence of complete information-ever been so central to the decision-making process. However, after nearly 3 years of experience with modelling, policy-makers need to be more confident about which models will be most helpful to support them when taking public health decisions, and modellers need to better understand the factors that will lead to successful model adoption and utilization. We present a three-stage framework for achieving these ends.

Modeling the cost and impact of injectable opioid agonist therapy on overdose and overdose deaths.

AIMS: Unsupervised injectable opioid agonist therapy (iOAT) may decrease the unmet treatment needs for people who inject opioids. We aimed to model whether unsupervised iOAT may be effective in reducing fatal and non-fatal overdose, and estimate the cost per life saved. METHODS: The study used a decision tree model based on Australian and international parameters for overdose risk in people who inject opioids who are: not on OAT; new/stable to methadone/buprenorphine treatment; on iOAT; or on unsupervised iOAT. We modeled scenarios of (1) current OAT only (status quo), or current OAT plus either (2) 5% supervised iOAT, (3) 5% supervised or 5.69% unsupervised iOAT (based on willingness to enroll), OR (4) 1.2% supervised and 10% unsupervised iOAT (the same cost as scenario 2). The study measured overdoses (fatal and nonfatal) and treatment costs per 10,000 people who inject opioids per annum, and cost-per deaths averted on implementation of iOAT. RESULTS: With current OAT, the study found an estimated 1655.5 (1552.7-1705.3) overdoses, 19.3 (17.9-20.3) overdose deaths and AUD 23,335,081 in treatment costs per 10,000 people per annum. Implementation of 5% enrollment in supervised iOAT costs an additional AUD 14,807,855 and showed a reduction of 122.9 (95% UI 114.2-130.5) overdoses and 2.0 (1.8-2.0) overdose deaths per 10,000 people per annum ($7,774,172 [7,283,182-8,146,989] per death averted). For the same treatment costs, additional coverage of 10% unsupervised iOAT and 1.2% supervised iOAT could be achieved, which the study estimated to prevent 269.0 (95% UI 250.0-278.7) overdoses and 4.0 (3.7-4.2) overdose deaths per 10,000 people per annum ($3,723,340 (3,385,878-3,894,379) per death averted), alongside further benefits of treatment unaccounted for in this study. CONCLUSION: An implementation scenario with greater unsupervised iOAT compared to supervised iOAT allows for an increased reduction in overdose and overdose deaths per annum at the same cost, with the additional benefit of increased treatment coverage among people who inject opioids.

Reducing malaria transmission in forest-going mobile and migrant populations in Lao PDR and Cambodia: protocol for stepped-wedge cluster-randomised controlled trial.

BACKGROUND: Countries of the Greater Mekong Sub-region aim to achieve malaria elimination by 2030. In the region, malaria is concentrated in high-risk areas and populations such as forest-going mobile and migrant populations (MMPs). However, routine protective measures such as long-lasting insecticidal nets do not prevent all infectious bites in these high-risk populations. Evidence for the effectiveness of a personal protection package tailored to forest-going MMPs which is acceptable, feasible, and cost-effective for reducing malaria transmission is required to inform the malaria elimination toolkit in the region. METHODS: A personal protection package consisting of long-lasting insecticidal hammock net, insect repellent and health communication pamphlet was developed in consultation with relevant implementing partners from Cambodia and Lao PDR. An open stepped-wedge cluster-randomised controlled trial will be conducted over a period of 12 months in a minimum of 488 villages (~ 428 in Lao PDR and ~ 60 in Cambodia) to evaluate the effectiveness of the personal protection package. Villages will be randomised into 11 blocks, with blocks transitioned in random order from control to intervention states at monthly intervals, following a 1-month baseline period. The primary outcome of the trial is the prevalence of Plasmodium spp. infection diagnosed by rapid diagnostic test. Difference in prevalence of malaria infection will be estimated across intervention and control periods using generalized linear mixed modelling. Nested within the stepped-wedge cluster-randomised controlled trial is a mixed-methods study to explore the acceptability of the personal protection package, feasibility of implementing a personal protection package as a vector control intervention, and knowledge, attitude and practice of MMPs regarding malaria prevention; and cost-analysis to determine the cost-effectiveness of implementing a personal protection package. DISCUSSION: This study, using a rigorous design and mixed-methods methodology, will evaluate whether a personal protection package can reduce residual malaria transmission among forest-going MMPs in Cambodia and Lao PDR. It will also measure implementation research outcomes such as effectiveness of the intervention package, cost-effectiveness, acceptability, and feasibility, in order to inform potential national and regional policy. Trial registration This trial was prospectively registered on ClinicalTrials.gov (NCT05117567) on 11th November 2021.

Controlled temperature chain for vaccination in low- and middle-income countries: a realist evidence synthesis.

Objective: To evaluate the evidence describing how the controlled temperature chain approach for vaccination could lead to improved equitable immunization coverage in low- and middle-income countries. Methods: We created a theory of change construct from the Controlled temperature chain: strategic roadmap for priority vaccines 2017-2020, containing four domains: (i) uptake and demand for the approach; (ii) compliance and safe use of the approach; (iii) programmatic efficiency gains from the approach; and (iv) improved equitable immunization coverage. To verify and improve the theory of change, we applied a realist review method to analyse published descriptions of controlled temperature chain or closely related experiences. Findings: We evaluated 34 articles, describing 22 unique controlled temperature chain or closely related experiences across four World Health Organization regions. We identified a strong demand for this approach among service delivery providers; however, generating an equal level of demand among policy-makers requires greater evidence on economic benefits and on vaccination coverage gains, and use case definitions. Consistent evidence supported safety of the approach when integrated into special vaccination programmes. Feasible training and supervision supported providers in complying with protocols. Time-savings were the main evidence for efficiency gains, while cost-saving data were minimal. Improved equitable coverage was reported where vaccine storage beyond the cold chain enabled access to hard-to-reach populations. No evidence indicated an inferior vaccine effectiveness nor increased adverse event rates for vaccines delivered under the approach. Conclusion: Synthesized evidence broadly supported the initial theory of change. Addressing evidence gaps on economic benefits and coverage gains may increase future uptake.

A log-odds system for waning and boosting of COVID-19 vaccine effectiveness.

Immunity to SARS-CoV-2 following vaccination wanes over time in a non-linear fashion, making modelling of likely population impacts of COVID-19 policy options challenging. We observed that it was possible to mathematize non-linear waning of vaccine effectiveness (VE) on the percentage scale as linear waning on the log-odds scale, and developed a random effects logistic regression equation based on UK Health Security Agency data to model VE against Omicron following two and three doses of a COVID-19 vaccine. VE on the odds scale reduced by 47% per month for symptomatic infection after two vaccine doses, lessening to 35% per month for hospitalisation. Waning on the odds scale after triple dose vaccines was 35% per month for symptomatic disease and 19% for hospitalisation. This log-odds system for estimating waning and boosting of COVID-19 VE provides a simple solution that may be used to parametrize SARS-CoV-2 immunity over time parsimoniously in epidemiological models.