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Disability-adjusted life years (DALYs) capture the mortality and morbidity arising from a disease: they incorporate the years of life lost (YLLs) and the years of life lived with disability (YLD) due to a disease. The relative importance of YLLs and YLDs differs across diseases. The magnitudes of YLLs and YLDs depend on parameters such as the age of onset of disease, duration of disease, the case fatality ratio and disability weight. In this paper, we examine the mathematical computation of the DALY and its underlying components, YLDs and YLLs. We aim to demonstrate under which circumstances (e.g. sets of input parameters) disease-specific YLDs and YLLs become sizeable relative to one another using the parameters of a set of diseases in low-income country settings. Researchers could then focus on understanding the key inputs that drive the relative extents of YLDs and YLLs (e.g. determine whether a detailed estimation of disability weights is essential), while maintaining DALYs as their key outcome metric consistent with disease burden assessments.

This chapter reviews the methods used to measure and evaluate health outcomes. There are a number of different measures that economists have developed over the years to quantify the effectiveness of vaccines and immunization programs. Two of the most commonly used in cost-effectiveness analysis are quality-adjusted life years and disability-adjusted life years, in addition to more intuitive measures such as mortality and incidence rates in an at-risk population. The chapter explores these effectiveness measurements and the types of psychometric approaches that have been developed to derive estimates of effectiveness of vaccines and immunization programs.

Objectives Clinical artificial intelligence (AI) is a novel technology, and few economic evaluations have focused on it to date. Before its wider implementation, it is important to highlight the aspects of AI that challenge traditional health technology assessment methods. Methods We used an existing broad value framework to assess potential ways AI can provide good value for money. We also developed a rubric of how economic evaluations of AI should vary depending on the case of its use. Results We found that the measurement of core elements of value—health outcomes and cost—are complicated by AI because its generalizability across different populations is often unclear and because its use may necessitate reconfigured clinical processes. Clinicians’ productivity may improve when AI is used. If poorly implemented though, AI may also cause clinicians’ workload to increase. Some AI has been found to exacerbate health disparities. Nevertheless, AI may promote equity by expanding access to medical care and, when properly trained, providing unbiased diagnoses and prognoses. The approach to assessment of AI should vary based on its use case: AI that creates new clinical possibilities can improve outcomes, but regulation and evidence collection may be difficult; AI that extends clinical expertise can reduce disparities and lower costs but may result in overuse; and AI that automates clinicians’ work can improve productivity but may reduce skills. Conclusions The potential uses of clinical AI create challenges for health technology assessment methods originally developed for pharmaceuticals and medical devices. Health economists should be prepared to examine data collection and methods used to train AI, as these may impact its future value.

Air pollution contributes to the global burden of disease, with ambient exposure to fine particulate matter of diameters smaller than 2.5 μm (PM

Background Similar to the study of the distribution of income within countries, population-level health disparities can be examined by analyzing the distribution of age at death. Methods We sourced period-specific death counts for 18 OECD countries over 1900–2020 from the Human Mortality Database. We studied the evolution of country-year-specific distributions of age at death, with an examination of the lower and upper tails of these distributions. For each country-year, we extracted the 1st, 5th, 10th, 90th, 95th and 99th percentiles of the age-at-death distribution. We then computed the corresponding shares of longevity—the sum of the ages weighted by the age-at-death distribution as a fraction of the sum of the ages weighted by the distribution—for each percentile. For example, for the 10th percentile, this would correspond to how much longevity accrues to the bottom 10% of the age-at-death distribution in a given country-year. Results We expose a characterization of the age-at-death distribution across populations with a focus on the lower and upper tails of the distribution. Our metrics, specifically the gap measures in age and share across the 10th and 90th percentiles of the distribution, enable a systematic comparison of national performances, which yields information supplementary to the cross-country differences commonly pointed by traditional indicators of life expectancy and coefficient of variation. Conclusions Examining the tails of age-at-death distributions can help characterize the comparative situations of the better- and worse-off individuals across nations, similarly to depictions of income distributions in economics.

SummaryBackgroundCountries have adopted different approaches, at different times, to reduce the transmission of coronavirus disease 2019 (COVID-19). Cross-country comparison could indicate the relative efficacy of these approaches. We assess various non-pharmaceutical interventions (NPIs) over time, comparing the effects of self-imposed (i.e. voluntary) behavior change and of changes enforced via official regulations, by statistically examining their impacts on subsequent death rates in 13 European countries.Methods and findingsWe examine two types of NPI: the introduction of government-enforced closure policies over time; and self-imposed alteration of individual behaviors in response to awareness of the epidemic, in the period prior to regulations. Our proxy for the latter is Google mobility data, which captures voluntary behavior change when disease salience is sufficiently high. The primary outcome variable is the rate of change in COVID-19 fatalities per day, 16-20 days after interventions take place. Linear multivariate regression analysis is used to evaluate impacts. Voluntarily reduced mobility, occurring prior to government policies, decreases the percent change in deaths per day by 9.2 percentage points (95% CI 4.5-14.0 pp). Government closure policies decrease the percent change in deaths per day by 14.0 percentage points (95% CI 10.8-17.2 pp). Disaggregating government policies, the most beneficial are intercity travel restrictions, cancelling public events, and closing non-essential workplaces. Other sub-components, such as closing schools and imposing stay-at-home rules, show smaller and statistically insignificant impacts.ConclusionsThis study shows that NPIs have substantially reduced fatalities arising from COVID-19. Importantly, the effect of voluntary behavior change is of the same order of magnitude as government-mandated regulations. These findings, including the substantial variation across dimensions of closure, have implications for the phased withdrawal of government policies as the epidemic recedes, and for the possible reimposition of regulations if a second wave occurs, especially given the substantial economic and human welfare consequences of maintaining lockdowns.

High out-of-pocket (OOP) medical expenses for cervical cancer (CC) can lead to catastrophic health expenditures (CHEs) and medical impoverishment in many low-resource settings. There are 32 million women at risk for CC in Ethiopia, where CC screening is extremely limited. An evaluation of the population health and financial risk protection benefits, and their distributional consequences across socioeconomic groups, from human papillomavirus (HPV) vaccination will be critical to support CC prevention efforts in this setting. We used a static cohort model that captures the main features of HPV vaccines and population demographics to project health and economic outcomes associated with routine HPV vaccination in Ethiopia. Health outcomes included the number of CC cases, and costs included vaccination and operational costs in 2015 US dollars over the years 2019–2118 and CC treatment costs over the lifetimes of cohorts eligible for vaccination in Ethiopia. We estimated the household OOP medical expenditures averted (assuming 68% of direct medical expenditures were financed OOP) and cases of CHE averted. A case of CHE was defined as 40% of household consumption expenditures, and the cases of CHE averted depended on wealth quintile, disease incidence, healthcare use and OOP payments. Our analysis shows that, assuming 100% vaccine efficacy against HPV-16/18 and 50% vaccination coverage, routine HPV vaccination could avert up to 970 000 cases of CC between 2019 and 2118, which translates to ∼932 000 lives saved. Additionally, routine HPV vaccination could avert 33 900 cases of CHE. Approximately one-third of health benefits would accrue to the poorest wealth quintile, whereas 50% of financial risk protection benefits would accrue to this quintile. HPV vaccination can reduce disparities in CC incidence, mortality and household health expenditures. This understanding and our findings can help policymakers in decisions regarding targeted CC control efforts and investment in a routine HPV vaccination programme following an initial catch-up programme.

Introduction Deterministic compartmental models of infectious diseases like measles typically reflect biological heterogeneities in the risk of infection and severity to characterize transmission dynamics. Given the known association of socioeconomic status and increased vulnerability to infection and mortality, it is also critical that such models further incorporate social heterogeneities. Methods Here, we aimed to explore the influence of integrating income-associated differences in parameters of traditional dynamic transmission models. We developed a measles SIR model, in which the Susceptible, Infected and Recovered classes were stratified by income quintile, with income-specific transmission rates, disease-induced mortality rates, and vaccination coverage levels. We further provided a stylized illustration with secondary data from Ethiopia, where we examined various scenarios demonstrating differences in transmission patterns by income and in distributional vaccination coverage, and quantified impacts on disparities in measles mortality. Results The income-stratified SIR model exhibited similar dynamics to that of the traditional SIR model, with amplified outbreak peaks and measles mortality among the poorest income group. All vaccination coverage strategies were found to substantially curb the overall number of measles deaths, yet most considerably for the poorest, with select strategies yielding clear reductions in measles mortality disparities. Discussion The incorporation of income-specific differences can reveal distinct outbreak patterns across income groups and important differences in the subsequent effects of preventative interventions like vaccination. Our case study highlights the need to extend traditional modeling frameworks (e.g. SIR models) to be stratified by socioeconomic factors like income and to consider ensuing income-associated differences in disease-related morbidity and mortality. In so doing, we build on existing tools and characterize ongoing challenges in achieving health equity.

Epidemiological and economic estimates suggest that the global burden of mental disorders is considerable, both in its impacts on human health and losses to societal welfare. The availability of additional data and the emergence of new approaches present an opportunity to examine these estimates, which form a critical part in making the investment case for global mental health.This study reviews, develops, and incorporates new estimates and methods in quantifying the global burden of mental illness. Using a composite estimation approach that accounts for premature mortality due to mental disorders and additional sources of morbidity and applying a value of a statistical life approach to economic valuation, we determine global and regional estimates of the economic cost that can be associated with mental disorders, building on data from the 2019 Global Burden of Disease study.We estimate that 418 million disability-adjusted life years (DALYs) could be attributable to mental disorders in 2019 (16% of global DALYs)-a more than three-fold increase compared to conventional estimates. The economic value associated with this burden is estimated at about USD 5 trillion. At a regional level, the losses could account for between 4% of gross domestic product in Eastern sub-Saharan Africa and 8% in High-income North America.The burden of mental illness in terms of both health and economic losses may be much higher than previously assessed.None.

All countries worldwide have signed up to the United Nations Sustainable Development Goals and have committed to the objective of achieving 'universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for all'. During the COVID-19 pandemic and beyond, advancement toward universal health coverage (UHC) will become more difficult for many countries, demonstrating that locally led priority setting is urgently needed to provide health services with appropriate financial protection to all. Because resources are limited and no national constituency can provide an unlimited number of services to their whole population in a sustainable manner, rationing and setting priorities for the selection of interventions to be included in a defined package of services is critical. In this Perspective, we discuss how packages of essential health services can be developed in resource-constrained settings, and detail how experts and the public can decide on principles and criteria, use a comprehensive array of analytical methods and choose which services to be provided free of charge. We illustrate these main steps while drawing on a recently conducted exercise of revising the national essential health services package in Ethiopia, which we compare with examples from other countries that have defined their essential benefits packages. This Perspective also provides recommendations for other low- and middle-income countries on their pathway to UHC.

Background Vaccine-preventable diseases (VPDs) remain major causes of morbidity and mortality in low- and middle-income countries (LMICs). Universal access to vaccination, besides improved health outcomes, would substantially reduce VPD-related out-of-pocket (OOP) expenditures and associated financial risks. This paper aims to estimate the extent of OOP expenditures and the magnitude of the associated catastrophic health expenditures (CHEs) for selected VPDs in Ethiopia. Methods and findings We conducted a cross-sectional costing analysis, from the household (patient) perspective, of care-seeking for VPDs in children aged under 5 years for pneumonia, diarrhea, measles, and pertussis, and in children aged under 15 years for meningitis. Data on OOP direct medical and nonmedical expenditures (2021 USD) and household consumption expenditures were collected from 995 households (1 child per household) in 54 health facilities nationwide between May 1 and July 31, 2021. We used descriptive statistics to measure the main outcomes: magnitude of OOP expenditures, along with the associated CHE within households. Drivers of CHE were assessed using a logistic regression model. The mean OOP expenditures per disease episode for outpatient care for diarrhea, pneumonia, pertussis, and measles were $5·6 (95% confidence interval (CI): $4·3, 6·8), $7·8 ($5·3, 10·3), $9·0 ($6·4, 11·6), and $7·4 ($3·0, 11·9), respectively. The mean OOP expenditures were higher for inpatient care, ranging from $40·6 (95% CI: $12·9, 68·3) for severe measles to $101·7 ($88·5, 114·8) for meningitis. Direct medical expenditures, particularly drug and supply expenses, were the major cost drivers. Among those who sought inpatient care (345 households), about 13·3% suffered CHE, at a 10% threshold of annual consumption expenditures. The type of facility visited, receiving inpatient care, and wealth were significant predictors of CHE (p-value < 0·001) while adjusting for area of residence (urban/rural), diagnosis, age of respondent, and household family size. Limitations include inadequate number of measles and pertussis cases. Conclusions The OOP expenditures induced by VPDs are substantial in Ethiopia and disproportionately impact those with low income and those requiring inpatient care. Expanding equitable access to vaccines cannot be overemphasized, for both health and economic reasons. Such realization requires the government’s commitment toward increasing and sustaining vaccine financing in Ethiopia.

Background Expansion of designated cycling networks increases cycling for transport that, in turn, increases physical activity, contributing to improvement in public health. This paper aims to determine whether cycle-network construction in a large city is cost-effective when compared to the status-quo. We developed a cycle-network investment model (CIM) for Oslo and explored its impact on overall health and wellbeing resulting from the increased physical activity. Methods First, we applied a regression technique on cycling data from 123 major European cities to model the effect of additional cycle-networks on the share of cyclists. Second, we used a Markov model to capture health benefits from increased cycling for people starting to ride cycle at the age of 30 over the next 25 years. All health gains were measured in quality-adjusted life years (QALYs). Costs were estimated in US dollars. Other data to populate the model were derived from a comprehensive literature search of epidemiological and economic evaluation studies. Uncertainty was assessed using deterministic and probabilistic sensitivity analyses. Results Our regression analysis reveals that a 100 km new cycle network construction in Oslo city would increase cycling share by 3%. Under the base-case assumptions, where the benefits of the cycle-network investment relating to increased physical activity are sustained over 25 years, the predicted average increases in costs and QALYs per person are $416 and 0.019, respectively. Thus, the incremental costs are $22,350 per QALY gained. This is considered highly cost-effective in a Norwegian setting. Conclusions The results support the use of CIM as part of a public health program to improve physical activity and consequently avert morbidity and mortality. CIM is affordable and has a long-term effect on physical activity that in turn has a positive impact on health improvement.

BackgroundThe COVID-19 pandemic has caused widespread health and socioeconomic disruptions around the world. Understanding the impact that this crisis has had on health workers and the delivery of routine health care services within countries provides evidence on pandemic preparedness and response. Here, we conduct an investigation into these factors for the Ethiopian context.Methods and findingsWe conducted an online cross-sectional survey with Ethiopian health care professionals between August 27 and October 10, 2020 via existing research networks. The variables of interest were confidence in COVID-19 related knowledge, training and experience, the adoption of precautionary health practices, risk perceptions, and respondent concerns. The majority of surveyed health care professionals in Ethiopia reported seeing fewer patients than usual during the COVID-19 crisis, gaps in pandemic training, inadequate access to personal protective equipment (PPE) and barriers to accessing COVID-19 testing. Most health care professionals were also deeply concerned and worried about their own COVID-19 risks and the likelihood that they would transmit the disease to others.ConclusionsOur study findings point to a possible reduction in routine health care services during the COVID-19 pandemic and gaps in pandemic preparedness in Ethiopia. The ministry of health and other stakeholders should work towards improving access to PPE and testing, and identify approaches to ensure that essential healthcare provision (such as immunizations) is not disrupted during crises akin to the COVID-19 outbreak.

IntroductionSouth 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.MethodsWe 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.ResultsWe 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.ConclusionsA 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.

Background Road traffic injuries are among the most important causes of morbidity and mortality and cause substantial economic loss to households in Ethiopia. This study estimates the financial risks of seeking trauma care due to road traffic injuries in Addis Ababa, Ethiopia. Methods This is a cross-sectional survey on out-of-pocket (OOP) expenditures related to trauma care in three public and one private hospital in Addis Ababa from December 2018 to February 2019. Direct medical and non-medical costs (2018 USD) were collected from 452 trauma cases. Catastrophic health expenditures were defined as OOP health expenditures of 10% or more of total household expenditures. Additionally, we investigated the impoverishment effect of OOP expenditures using the international poverty line of $1.90 per day per person (adjusted for purchasing power parity). Results Trauma care seeking after road traffic injuries generate catastrophic health expenditures for 67% of households and push 24% of households below the international poverty line. On average, the medical OOP expenditures per patient seeking care were $256 for outpatient visits and $690 for inpatient visits per road traffic injury. Patients paid more for trauma care in private hospitals, and OOP expenditures were six times higher in private than in public hospitals. Transport to facilities and caregiver costs were the two major cost drivers, amounting to $96 and $68 per patient, respectively. Conclusion Seeking trauma care after a road traffic injury poses a substantial financial threat to Ethiopian households due to lack of strong financial risk protection mechanisms. Ethiopia's government should enact multisectoral interventions for increasing the prevention of road traffic injuries and implement universal public finance of trauma care.

Background Vietnam9s 2007 comprehensive motorcycle helmet policy increased helmet use from about 30% of riders to about 93%. We aimed to simulate the effect that this legislation might have on: (a) road traffic deaths and non-fatal injuries, (b) individuals’ direct acute care injury treatment costs, (c) individuals’ income losses from missed work and (d) individuals’ protection against medical impoverishment. Methods and findings We used published secondary data from the literature to perform a retrospective extended cost-effectiveness analysis simulation study of the policy. Our model indicates that in the year following its introduction a helmet policy employing standard helmets likely prevented approximately 2200 deaths and 29 000 head injuries, saved individuals US$18 million in acute care costs and averted US$31 million in income losses. From a societal perspective, such a comprehensive helmet policy would have saved $11 000 per averted death or $830 per averted non-fatal injury. In terms of financial risk protection, traffic injury is so expensive to treat that any injury averted would necessarily entail a case of catastrophic health expenditure averted. Conclusions The high costs associated with traffic injury suggest that helmet legislation can decrease the burden of out-of-pocket payments and reduced injuries decrease the need for access to and coverage for treatment, allowing the government and individuals to spend resources elsewhere. These findings suggest that comprehensive motorcycle helmet policies should be adopted by low-income and middle-income countries where motorcycles are pervasive yet helmet use is less common.

BackgroundEarly childhood development (ECD) sets the foundation for healthy and successful lives with important ramifications for education, labour market outcomes and other domains of well-being. Even though a large number of interventions that promote ECD have been implemented and evaluated globally, there is currently no standardised framework that allows a comparison of the relative cost-effectiveness of these interventions.MethodsWe first reviewed the existing literature to document the main approaches that have been used to assess the relative effectiveness of interventions that promote ECD, including early parenting and at-home psychosocial stimulation interventions. We then present an economic evaluation framework that builds on these reviewed approaches and focuses on the immediate impact of interventions on motor, cognitive, language and socioemotional skills. Last, we apply our framework to compute the relative cost-effectiveness of interventions for which recent effectiveness and costing data were published. For this last part, we relied on a recently published review to obtain effect sizes documented in a consistent manner across interventions.FindingsOur framework enables direct value-for-money comparison of interventions across settings. Cost-effectiveness estimates, expressed in $ per units of improvement in ECD outcomes, vary greatly across interventions. Given that estimated costs vary by orders of magnitude across interventions while impacts are relatively similar, cost-effectiveness rankings are dominated by implementation costs and the interventions with higher value for money are generally those with a lower implementation cost (eg, psychosocial interventions involving limited staff).ConclusionsWith increasing attention and investment into ECD programmes, consistent assessments of the relative cost-effectiveness of available interventions are urgently needed. This paper presents a unified analytical framework to address this need and highlights the rather remarkable range in both costs and cost-effectiveness across currently available intervention strategies.

Background The COVID-19 pandemic has caused profound health, economic, and social disruptions globally. We assessed the full costs of hospitalization for COVID-19 disease at Ekka Kotebe COVID-19 treatment center in Addis Ababa, the largest hospital dedicated to COVID-19 patient care in Ethiopia. Methods and findings We retrospectively collected and analysed clinical and cost data on patients admitted to Ekka Kotebe with laboratory-confirmed COVID-19 infections. Cost data included personnel time and salaries, drugs, medical supplies and equipment, facility utilities, and capital costs. Facility medical records were reviewed to assess the average duration of stay by disease severity (either moderate, severe, or critical). The data collected covered the time-period March-November 2020. We then estimated the cost per treated COVID-19 episode, stratified by disease severity, from the perspective of the provider. Over the study period there were 2,543 COVID-19 cases treated at Ekka Kotebe, of which, 235 were critical, 515 were severe, and 1,841 were moderate. The mean patient duration of stay varied from 9.2 days (95% CI: 7.6–10.9; for moderate cases) to 19.2 days (17.9–20.6; for critical cases). The mean cost per treated episode was USD 1,473 (95% CI: 1,197–1,750), but cost varied by disease severity: the mean cost for moderate, severe, and critical cases were USD 1,266 (998–1,534), USD 1,545 (1,413–1,677), and USD 2,637 (1,788–3,486), respectively. Conclusions Clinical management and treatment of COVID-19 patients poses an enormous economic burden to the Ethiopian health system. Such estimates of COVID-19 treatment costs inform financial implications for resource-constrained health systems and reinforce the urgency of implementing effective infection prevention and control policies, including the rapid rollout of COVID-19 vaccines, in low-income countries like Ethiopia.

In Ethiopia, little is known about the extent of out-of-pocket health expenditures and the associated financial hardships at national and regional levels. We estimated the incidence of both catastrophic and impoverishing health expenditures using data from the 2015/16 Ethiopian household consumption and expenditure and welfare monitoring surveys. We computed incidence of catastrophic health expenditures (CHE) at 10% and 25% thresholds of total household consumption and 40% threshold of household capacity to pay, and impoverishing health expenditures (IHE) using Ethiopia's national poverty line (ETB 7184 per adult per year). Around 2.1% (SE: 0.2, P

Objectives In many countries, measles disproportionately affects poorer households. To achieve equitable delivery, national immunization programs can use 2 main delivery platforms: routine immunization and supplementary immunization activities (SIAs). The objective of this article is to use data concerning measles vaccination coverage delivered via routine and SIA strategies to make inferences about the associated equity impact. Methods We relied on Demographic and Health Survey and Multiple Indicator Cluster Surveys multi-country survey data to conduct a comparative analysis of routine and SIA measles vaccination status of children by wealth quintile. We estimated the value of the angle, θ, for the ratio of the difference between coverage levels of adjacent wealth quintiles by using the arc-tangent formula. For each country/year observation, we averaged the θ estimates into one summary measurement, defined as the “equity impact number.” Results Across 20 countries, the equity impact number summarized across wealth quintiles was greater (and hence less equitable) for routine delivery than for SIAs in the survey rounds (years) during, before, and after an SIA about 65% of the time. The equity impact numbers for routine measles vaccination averaged across wealth quintiles were usually greater than for SIA measles vaccination across country-year observations. Conclusions This analysis examined how different measles vaccine delivery platforms can affect equity. It can serve to elucidate the impact of immunization and public health programs in terms of comparing horizontal to vertical delivery efforts and in reducing health inequalities in global and country-level decision-making.

Background Malaria is a public health burden and a major cause for morbidity and mortality in Ethiopia. Malaria also places a substantial financial burden on families and Ethiopia’s national economy. Economic evaluations, with evidence on equity and financial risk protection (FRP), are therefore essential to support decision-making for policymakers to identify best buys amongst possible malaria interventions. The aim of this study is to estimate the expected health and FRP benefits of universal public financing of key malaria interventions in Ethiopia. Methods Using extended cost-effectiveness analysis (ECEA), the potential health and FRP benefits were estimated, and their distributions across socio-economic groups, of publicly financing a 10% coverage increase in artemisinin-based combination therapy (ACT), long-lasting insecticide-treated bed nets (LLIN), indoor residual spraying (IRS), and malaria vaccine (hypothetical). Results ACT, LLIN, IRS, and vaccine would avert 358, 188, 107 and 38 deaths, respectively, each year at a net government cost of $5.7, 16.5, 32.6, and 5.1 million, respectively. The annual cost of implementing IRS would be two times higher than that of the LLIN interventions, and would be the main driver of the total costs. The averted deaths would be mainly concentrated in the poorest two income quintiles. The four interventions would eliminate about $4,627,800 of private health expenditures, and the poorest income quintiles would see the greatest FRP benefits. ACT and LLINs would have the largest impact on malaria-related deaths averted and FRP benefits. Conclusions ACT, LLIN, IRS, and vaccine interventions would bring large health and financial benefits to the poorest households in Ethiopia.

Ethiopia's HIV prevalence has decreased by 75% in the past 20 years with the implementation of antiretroviral therapy, but HIV transmission continues in high-risk clusters. Identifying the spatial and temporal trends, and epidemiologic correlates, of these clusters can lead to targeted interventions.We used biomarker and survey data from the 2005, 2011 and 2016 Ethiopia Demographic and Health Surveys (DHS). The spatial-temporal distribution of HIV was estimated using the Kulldorff spatial scan statistic, a likelihood-based method for determining clustering. Significant clusters (P 0.05) were identified and compared based on HIV risk factors to non-cluster areas.In 2005, 2011 and 2016, respectively, 219, 568 and 408 individuals tested positive for HIV. Four HIV clusters were identified, representing 17% of the total population and 43% of all HIV cases. The clusters were centred around Addis Ababa (1), Afar (2), Dire Dawa (3) and Gambella (4). Cluster 1 had higher rates of unsafe injections (4.9% vs. 2.2%, P 0.001) and transactional sex (6.0% vs. 1.6%, P 0.001) than non-cluster regions, but more male circumcision (98.5% vs. 91.3%, P 0.001). Cluster 2 had higher levels of transactional sex (4.9% vs. 1.6%, P 0.01), but lower levels of unsafe injections (0.8% vs. 2.2%, P 0.01). Cluster 3 had fewer individuals with 1 sexual partner (0% vs. 1.7%, P 0.001) and more male circumcision (100% vs. 91.3%, P 0.001). Cluster 4 had less male circumcision (59.1% vs. 91.3%, P 0.01).In Ethiopia, geographic HIV clusters are driven by different risk factors. Decreasing the HIV burden requires targeted interventions.La prévalence du VIH en Ethiopie a diminué de 75% au cours des 20 dernières années avec l’implémentation du traitement antirétroviral, mais la transmission du VIH se poursuit dans les grappes à haut risque. L'identification des tendances spatiales et temporelles et des corrélations épidémiologiques de ces grappes peut mener à des interventions ciblées. MÉTHODES: Nous avons utilisé des biomarqueurs et des données d'enquête provenant des Surveillances Démographiques et de Santé (SDS) en Ethiopie de 2005, 2011 et 2016. La distribution spatiotemporelle du VIH a été estimée à l'aide de la statistique de balayage spatial de Kulldorff, une méthode basée sur la probabilité de déterminer des regroupements. Des grappes significatives (P 0.05) ont été identifiées et comparées sur base des facteurs de risque du VIH dans les zones sans regroupements. RÉSULTATS: En 2005, 2011 et 2016, respectivement, 219, 568 et 408 personnes ont été testées positives pour le VIH. Quatre grappes de VIH ont été identifiées, représentant 17% de la population totale et 43% de tous les cas de VIH. Les grappes étaient centrées sur Addis-Abeba (1), Afar (2), Dire Dawa (3) et Gambella(4). La grappe 1 avait des taux plus élevés d'injections à risque (4,9% contre 2,2%, P 0.001) et de rapports sexuels transactionnels (6,0% contre 1,6%, P 0.001) que les régions sans regroupement, mais plus de circoncisions masculines (98,5% contre 91,3%, p0,001). La grappe 2 avait des taux plus élevés de rapports sexuels transactionnels (4,9% contre 1,6%, P 0.01), mais des taux inférieurs d'injections à risque (0,8% contre 2,2%, P 0.01). La grappe 3 avait moins d'individus avec1 partenaire sexuel (0% contre 1,7%, P 0.001) et plus de circoncisions masculines (100% contre 91,3%, P 0.001). La grappe 4 avait moins de circoncisions masculines (59,1% contre 91,3%, P 0.01).En Ethiopie, les grappes géographiques du VIH sont guidées par différents facteurs de risque. La réduction de la charge du VIH nécessite des interventions ciblées.

On March 2–3, 2011—ahead of the first UN High-Level Meeting on NCDs—a conference hosted in Boston (MA, USA) focused on the NCDs of the world's poorest billion, whose poverty was embodied in young average age, low energy intake, and subsistence through physical labour.30 Participants at the Boston event argued that global thinking about NCDs had been too focused on a theory of epidemiological transition, which projected epidemics of chronic disease associated with development.31 This theory created a blind spot regarding the existence and pattern of non-infectious conditions before declines in infectious mortality (pre-transitional NCDIs). The poorest populations were still experiencing NCDIs as part of a nexus of hunger, toxic environments, infectious diseases, and lack of health care. The NCDIs that emerged under these circumstances were both more severe and more varied than could be captured by frameworks developed for other populations. In April, 2011, the WHO African Regional Office held a consultation of health ministers in Congo (Brazzaville).32 The Brazzaville Declaration on NCDs called for an expanded NCDI agenda addressing haemoglobinopathies (sickle cell disease), mental disorders, and violence and injury.32 Other prominent African health experts called for a 5 × 5 strategy inclusive of neuropsychiatric disorders and infectious risks.33, 34 In July, 2013, at a meeting in Rwanda, a group of NCD unit leaders from ten African ministries of health called for a complementary strategy for NCDIs.35 This NCDI equity agenda focused on policies and integrated health-sector interventions to eliminate deaths among the poorest children and young adults (aged

Objectives: Financial risk protection (FRP), or the prevention of medical impoverishment, is a major objective of health systems, particularly in low- and middle-income countries where the extent of out-of-pocket (OOP) health expenditures can be substantial. We sought to develop a method that allows decision makers to explicitly integrate FRP outcomes into their priority-setting activities. Methods: We used literature review to identify 31 interventions in low- and middle-income countries, each of which provided measures of health outcomes, costs, OOP health expenditures averted, and FRP (proxied by OOP health expenditures averted as a percentage of income), all disaggregated by income quintile. We developed weights drawn from the Z-score of each quintile-intervention pair based on the distribution of FRP of all quintile-intervention pairs. We next ranked the interventions by unweighted and weighted health outcomes for each income quintile. We also evaluated how pro-poor they were by, first, ordering the interventions by cost-effectiveness for each quintile and, next, calculating the proportion of interventions each income quintile would be targeted for a given random budget. A ranking was said to be pro-poor if each quintile received the same or higher proportion of interventions than richer quintiles. Results: Using FRP weights produced a more pro-poor priority setting than unweighted outcomes. Most of the reordering produced by the inclusion of FRP weights occurred in interventions of moderate cost-effectiveness, suggesting that these weights would be most useful as a way of distinguishing moderately cost-effective interventions with relatively high potential FRP. Conclusions: This preliminary method of integrating FRP into priority-setting would likely be most suitable to deciding between health interventions with intermediate cost-effectiveness.

ObjectiveHealth system strengthening (HSS) activities should accompany disease-targeting interventions in low/middle-income countries (LMICs). Economic evaluations provide information on how these types of investment might best be balanced but can be challenging. We conducted a systematic review to evaluate how researchers address these economic evaluation challenges.MethodsWe identified studies about economic evaluation of HSS activities in LMICs using a two-stage approach. First, we conducted a broad search to identify areas where economic evaluations of HSS activities were being conducted. Next, we selected specific interventions for more targeted literature review. We extracted study characteristics using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. Finally, we summarised authors’ modelling decisions using a framework that examines how models are developed to emphasise generalisability, precision, or realism.FindingsOur searches produced 1978 studies, out of which we included 36. Most studies used data from prospective trials and calculated cost-effectiveness directly from these trial inputs, rather than using simulation methods. As a group, these studies primarily emphasised precision and realism over generalisability, meaning that their results were best suited to specific settings.ConclusionsThe number of included studies was small. Our findings suggest that most economic evaluations of HSS do not leverage methods like sensitivity analyses or inputs from literature review that would produce more generalisable (but potentially less precise) results. More research into how decision-makers would use economic evaluations to define the expansion path to strengthening health systems would allow for conceptualising impactful work on the economic value of HSS.

Universal health coverage (UHC) aims to provide access to health services for all without financial hardship. Moving toward UHC while ensuring financial risk protection (FRP) from out-of-pocket (OOP) health expenditures is a critical objective of the Sustainable Development Goal for Health. In tracking country progress toward UHC, analysts and policymakers usually report on two summary indicators of lack of FRP: the prevalence of catastrophic health expenditures (CHE) and the prevalence of impoverishing health expenditures. In this paper, we build on the CHE indicator: we examine the distribution (density) of health OOP budget share as a way to capture both the magnitude and dispersion in the ratio of households’ OOP health expenditures relative to consumption or income at the population level. We illustrate our approach with country-specific examples using data from the World Health Organization’s World Health Surveys.

Health management information systems (HMIS) are a crucial source of timely health statistics and have the potential to improve reporting in low-income countries. However, concerns about data quality have hampered their widespread adoption in research and policy decisions. This article presents results from a data verification study undertaken to gain insights into the quality of HMIS data in Ethiopia. We also provide recommendations for working with HMIS data for research and policy translation. We linked the HMIS to the 2016 Emergency Obstetric and Newborn Care Assessment, a national census of all health facilities that provided maternal and newborn health services in Ethiopia. We compared the number of visits for deliveries and caesarean sections (C-sections) reported in the HMIS in 2015 (January–December) to those found in source documents (paper-based labour and delivery and operating theatre registers) in 2425 facilities across Ethiopia. We found that two-thirds of facilities had ‘good’ HMIS reporting for deliveries (defined as reporting within 10% of source documents) and half had ‘very good’ reporting (within 5% of source documents). Results were similar for reporting on C-section deliveries. We found that good reporting was more common in urban areas (OR: 1.30, 95% CI 1.06 to 1.59), public facilities (OR: 2.95, 95% CI 1.38 to 6.29) and in hospitals compared with health centres (OR: 1.71, 95% CI 1.13 to 2.61). Facilities in the Somali and Afar regions had the lowest odds of good reporting compared with Addis Ababa and were more likely to over-report deliveries in the HMIS. Further work remains to address remaining discrepancies in the Ethiopian HMIS. Nonetheless, our findings corroborate previous data verification exercises in Ethiopia and support greater use and uptake of HMIS data for research and policy decisions (particularly, greater use of HMIS data elements (eg, absolute number of services provided each month) rather than coverage indicators). Increased use of these data, combined with feedback mechanisms, is necessary to maintain data quality.

Immunization is one of the most effective public health interventions, saving millions of lives every year. Ethiopia has seen gradual improvements in immunization coverage and access to child health care services; however, inequalities in child mortality across wealth quintiles and regions remain persistent. We model the relative distributional incidence and mortality of four vaccine-preventable diseases (VPDs) (rotavirus diarrhea, human papillomavirus, measles, and pneumonia) by wealth quintile and geographic region in Ethiopia. Our approach significantly extends an earlier methodology, which utilizes the population attributable fraction and differences in the prevalence of risk and prognostic factors by population subgroup to estimate the relative distribution of VPD incidence and mortality. We use a linear system of equations to estimate the joint distribution of risk and prognostic factors in population subgroups, treating each possible combination of risk or prognostic factors as computationally distinct, thereby allowing us to account for individuals with multiple risk factors. Across all modeling scenarios, our analysis found that the poor and those living in rural and primarily pastoralist or agrarian regions have a greater risk than the rich and those living in urban regions of becoming infected with or dying from a VPD. While in absolute terms all population subgroups benefit from health interventions (e.g., vaccination and treatment), current unequal levels and pro-rich gradients of vaccination and treatment-seeking patterns should be redressed so to significantly improve health equity across wealth quintiles and geographic regions in Ethiopia.

Ethiopia is one of the sub-Saharan African countries contributing to the highest number of maternal and neonatal deaths. Coverage of maternal and neonatal health (MNH) interventions has remained very low in Ethiopia. We examined the cost-effectiveness of selected MNH interventions in an Ethiopian setting. We analysed 13 case management and preventive MNH interventions. For all interventions, we used an ingredients-based approach for cost estimation. We employed a static life table model to estimate the health impact of a 20% increase in intervention coverage relative to the baseline. We used disability-adjusted life years (DALYs) as the health outcome measure while costs were expressed in 2018 US$. Analyses were based on local epidemiological, demographic and cost data when available. Our finding shows that 12 out of the 13 interventions included in our analysis were highly cost-effective. Interventions targeting newborns such as neonatal resuscitation (institutional), kangaroo mother care and management of newborn sepsis with injectable antibiotics were the most cost-effective interventions with incremental cost-effectiveness ratios of US$7, US$8 and US$17 per DALY averted, respectively. Obstetric interventions (induction of labour, active management of third stage of labour, management of pre-eclampsia/eclampsia and maternal sepsis, syphilis treatment and tetanus toxoid during pregnancy) and safe abortion cost between US$100 and US$300 per DALY averted. Calcium supplementation for pre-eclampsia and eclampsia prevention was the least cost-effective, with a cost per DALY of about US$3100. Many of the MNH interventions analysed were highly cost-effective, and this evidence can inform the ongoing essential health services package revision in Ethiopia. Our analysis also shows that calcium supplementation does not appear to be cost-effective in our setting.

Summary Background In the 21st century, increases in immunisation coverage and decreases in under-5 mortality have substantially reduced the global burden of measles mortality. However, the assessment of measles mortality burden is highly dependent on estimates of case-fatality ratios for measles, which can vary according to geography, health systems infrastructure, prevalence of underlying risk factors, and measles endemicity. With imprecise case-fatality ratios, there is continued uncertainty about the burden of measles mortality and the effect of measles vaccination. In this study, we aimed to update the estimations of case-fatality ratios for measles, to develop a prediction model to estimate case-fatality ratios across heterogeneous groupings, and to project future case-fatality ratios for measles up to 2030. Methods We did a review of the literature to identify studies examining measles cases and deaths in low-income and middle-income countries in all age groups from 1980 to 2016. We extracted data on case-fatality ratios for measles overall and by age, where possible. We developed and examined several types of generalised linear models and determined the best-fit model according to the Akaike information criterion. We then selected a best-fit model to estimate measles case-fatality ratios from 1990 to 2015 and projected future case-fatality ratios for measles up to 2030. Findings We selected 124 peer-reviewed journal articles published between Jan 1, 1980, and Dec 31, 2016, for inclusion in the final review—85 community-based studies and 39 hospital-based studies. We selected a log-linear prediction model, resulting in a mean case-fatality ratio of 2·2% (95% CI 0·7–4·5) in 1990–2015. In community-based settings, the mean case-fatality ratio was 1·5% (0·5–3·1) compared with 2·9% (0·9–6·0) in hospital-based settings. The mean projected case-fatality ratio in 2016–2030 was 1·3% (0·4–3·7). Interpretation Case-fatality ratios for measles have seen substantial declines since the 1990s. Our study provides an updated estimation of case-fatality ratios that could help to refine assessment of the effect on mortality of measles control and elimination programmes. Funding Bill & Melinda Gates Foundation.

Background Financial risk protection (FRP) is a key objective of national health systems and a core pillar of universal health coverage (UHC). Yet, little is known about the disease-specific distribution of catastrophic health expenditure (CHE) at the national level. Methods Using the World Health Surveys (WHS) from 39 countries, we quantified CHE, or household health spending that surpasses 40% of capacity-to-pay by key disease areas. We restricted our analysis to households in which the respondent used health care in the last 30 days and categorized CHE into disease areas included as WHS response options: maternal and child health (MCH); high fever, severe diarrhea, or cough; heart disease; asthma; injury; surgery; and other. We compared disease-specific CHE estimates by income, pooled funding as a share of total health expenditure, share of the population affected by the different diseases, and poverty status. Results Across countries, an average of 45.1% of CHE cases could not be tied to a specific cause; 37.6% (95% UI 35.4–39.9%) of CHE cases were associated with high fever, severe cough, or diarrhea; 3.9% (3.0–4.9%) with MCH; and 4.1% (3.3–4.9%) with heart disease. Injuries constituted 5.2% (4.2–6.4%) of CHE cases. The distribution of CHE varied substantially by national income. A 10% increase in heart disease prevalence was associated with a 1.9% (1.3–2.4%) increase in heart disease CHE, an association stronger than any other disease area. Conclusions Our approach is comparable, comprehensive, and empirically based and highlights how financial risk protection may not be aligned with disease burden. Disease-specific CHE estimates can illuminate how health systems can target reform to best protect households from financial risk. Electronic supplementary material The online version of this article (10.1186/s12916-019-1266-0) contains supplementary material, which is available to authorized users.

Public spending can improve population well-being, for example, by averting or reducing poverty. We aim to conceptualize monetary benchmarks for health sector investments oriented towards poverty alleviation in low- and lower middle-income countries. These benchmarks are meant to indicate the approximate range of health sector costs incurred to avert a single case of poverty across countries. Such conceptualizations could help identify the health interventions that are worthwhile investing in from financial risk protection and social welfare standpoints. We sourced secondary data from the World Bank for low-income and lower-middle-income countries over 2002–2019, including: per capita government expenditures on health, the proportion of a country’s population living under the international poverty line ($1.90 per day, 2011 Purchasing Power Parity), and the features of national social protection programs whose primary intent is poverty reduction. We then examined the associations between poverty headcount and per capita government health spending to gauge the potential relationship between this spending and poverty reduction. Subsequently, we derived a range of plausible poverty reduction benchmarks (PRBs). We also computed the per capita costs of national poverty reduction programs so as to contrast these with the estimated range of PRBs. Priority setting in low- and lower-middle-income countries could be informed by health-sector PRBs, in addition to burden of disease and cost-effectiveness considerations. The computed PRBs, expressed in dollars per poverty case averted, can possibly be viewed in a manner akin to economic evaluation thresholds which are usually expressed in dollars per disability-adjusted life year averted.

Ethiopia raised taxes on tobacco products in early 2020, increasing the overall price of the typical pack of cigarettes by about 67%. We quantify the potential impacts of Ethiopia's tobacco tax hike on various outcomes-life years, tax revenues, cigarette expenditures and catastrophic health expenditures (CHE). Using parameters like price elasticity of demand for cigarettes and smoking prevalence in Ethiopia from the existing literature and secondary data sources, we model the potential implications of the reform at the population level and for different wealth quintiles. We focus only on men since a small proportion of Ethiopian women smoke. Results indicate that Ethiopia's tax hike could induce a significant proportion of current smokers to quit smoking and thereby save almost eight million years of life in the current population. The reform is also likely to increase tax revenues by USD26 million in the first year after its introduction. The richest quintile will bear the greatest share of this higher tax burden and the poorest will bear the least. Additionally, deaths due to the main diseases associated with smoking will fall. This is expected to avert up to 173,000 CHE cases due to the out-of-pocket costs that would have been incurred in obtaining medical treatment. This analysis highlights that cigarette tax hikes in countries that have low smoking prevalence can reduce smoking even further, and thereby protect against the future health and financial costs of smoking. Importantly, the effects of these policies can be progressive across the income spectrum.

Objectives Improving health and financial risk protection (FRP, the prevention of medical impoverishment) and their distributions is a major objective of national health systems. Explicitly describing FRP and disaggregated (eg, across socioeconomic groups) impact of health interventions in economic evaluations can provide decision makers with a broader set of health and financial outcomes to compare and prioritize interventions against each other. Methods We propose methods to synthesize such a broader set of outcomes by estimating and comparing the distributions in both health and FRP benefits procured by health interventions. We build on benefit-cost analysis frameworks and utility-based models, and we illustrate our methods with the case study of universal public finance (financing by government regardless of whom an intervention is targeting) of disease treatment in a low- and middle-income country setting. Results Two key findings seem to emerge: FRP is critical when diseases are less lethal (eg, case fatality rates

In Ethiopia, despite the introduction of new vaccines and a steady increase in access to immunization services over the last decade, considerable coverage gaps have persisted leading to a heavier vaccine-preventable disease (VPD) burden among poorer households. In this paper, we present a brief overview including available evidence and published studies on vaccine economics in Ethiopia, covering the topics of cost-effectiveness analysis, cost of illness associated with VPDs, equitable access to vaccines, and immunization financing. We can then point that large disparities in vaccine access exist by geographic location, socioeconomic and maternal educational status. Ethiopian households, especially the poorest, can incur impoverishing out-of-pocket expenditures for VPDs. Financing for immunization services has shown modest improvements in Ethiopia over recent years prior to the COVID-19 pandemic. A number of economic evaluation studies have pointed to the potentially pro-poor benefits of immunization programs in Ethiopia, yielding health and financial risk protection gains among the poorest households.

The growing burden of non-communicable diseases (NCDs) in low- and middle-income countries may have implications for health system performance in the area of financial risk protection, as measured by catastrophic health expenditure (CHE). We compare NCD CHE to the CHE cases caused by communicable diseases (CDs) across health systems to examine whether: (1) disease burden and CHE are linked, (2) NCD CHE disproportionately affects wealthier households and (3) whether the drivers of NCD CHE differ from the drivers of CD CHE. We used the Study on Global Aging and Adult Health survey, which captured nationally representative samples of 44 089 adults in China, Ghana, India, Mexico, Russia and South Africa. Using two-part regression and random forests, we estimated out-of-pocket spending and CHE by disease area. We compare the NCD share of CHE to the NCD share of disability-adjusted life years (DALYs) or years of life lost to disability and death. We tested for differences between NCDs and CDs in the out-of-pocket costs per visit and the number of visits occurring before spending crosses the CHE threshold. NCD CHE increased with the NCD share of DALYs except in South Africa, where NCDs caused more than 50% of CHE cases but only 30% of DALYs. A larger share of households incurred CHE due to NCDs in the lowest than the highest wealth quintile. NCD CHE cases were more likely to be caused by five or more health care visits relative to communicable disease CHE cases in Ghana (P = 0.003), India (P = 0.004) and China (P = 0.093). Health system attributes play a key mediating factor in how disease burden translates into CHE by disease. Health systems must target the specific characteristics of CHE by disease area to bolster financial risk protection as the epidemiological transition proceeds.

BackgroundWe develop a framework for quantifying monetary values associated with changes in disease-specific mortality risk in low- and middle-income countries to help quantify trade-offs involved in investing in mortality reduction due to one disease versus another.MethodsWe monetized the changes in mortality risk for communicable and non-communicable diseases (CD and NCD, respectively) between 2017 and 2030 for low-income, lower-middle-income, and upper-middle-income countries (LICs, LMICs, and UMICs, respectively). We modeled three mortality trajectories (“base-case”, “high-performance”, and “low-performance”) using Global Burden of Disease study forecasts and estimated disease-specific mortality risk changes relative to the base-case. We assigned monetary values to changes in mortality risk using value of a statistical life (VSL) methods and conducted multiple sensitivity analyses.ResultsIn terms of NCDs, the absolute monetary value associated with changing mortality risk was highest for cardiovascular diseases in older age groups. For example, being on the low-performance trajectory relative to the base-case in 2030 was valued at $9100 (95% uncertainty range $6800; $11,400), $28,300 ($24,200; $32,400), and $30,300 ($27,200; $33,300) for females aged 70–74 years in LICs, LMICs, and UMICs, respectively. Changing the mortality rate from the base-case to the high-performance trajectory was associated with high monetary value for CDs as well, especially among younger age groups. Estimates were sensitive to assumptions made in calculating VSL.ConclusionsOur framework provides a priority setting paradigm to best allocate investments toward the health sector and enables intersectoral comparisons of returns on investments from health interventions.

In Cambodia, diabetes caused nearly 3% of the country’s mortality in 2016 and became the fourth highest cause of disability in 2017. Providing sufficient financial risk protection from health care expenditures may be part of the solution towards effectively tackling the diabetes burden and motivating individuals to appropriately seek care to effectively manage their condition. In this study, we aim to estimate the distributional health and financial impacts of strategies providing financial coverage for diabetes services through the Health Equity Funds (HEF) in Cambodia. The trajectory of diabetes was represented using a Markov model to estimate the societal costs, health impacts, and individual out-of-pocket expenditures associated with six strategies of HEF coverage over a time horizon of 45 years. Input parameters for the model were compiled from published literature and publicly available household survey data. Strategies covered different combinations of types of diabetes care costs (i.e., diagnostic services, medications, and management of diabetes-related complications). Health impacts were computed as the number of disability-adjusted life-years (DALYs) averted and financial risk protection was analyzed in terms of cases of catastrophic health expenditure (CHE) averted. Model simulations demonstrated that coverage for medications would be cost-effective, accruing health benefits ($27 per DALY averted) and increases in financial risk protection ($2 per case of CHE averted) for the poorest in Cambodia. Women experienced particular gains in health and financial risk protection. Increasing the number of individuals eligible for financial coverage also improved the value of such investments. For HEF coverage, the government would pay between an estimated $28 and $58 per diabetic patient depending on the extent of coverage and services covered. Efforts to increase the availability of services and capacity of primary care facilities to support diabetes care could have far-reaching impacts on the burden of diabetes and contribute to long-term health system strengthening.

Policymakers face difficult choices over which health interventions to publicly finance. We developed an approach to health benefits package design that accommodates explicit tradeoffs between improvements in health and provision of financial risk protection (FRP). We designed a mathematical optimization model to balance gains in health and FRP across candidate interventions when publicly financed. The optimal subset of interventions selected for inclusion was determined with bi-criterion integer programming conditional on a budget constraint. The optimal set of interventions to publicly finance in a health benefits package varied according to whether the objective for optimization was population health benefits or FRP. When both objectives were considered jointly, the resulting optimal essential benefits package depended on the weights placed on the two objectives. In the Sustainable Development Goals era, smart spending toward universal health coverage is essential. Mathematical optimization provides a quantitative framework for policymakers to design health policies and select interventions that jointly prioritize multiple objectives with explicit financial constraints. publishedVersion

Introduction: Globally, there are 370 million children receiving school meals every day. Coverage is least in low-income countries, where the need is greatest and where program costs are viewed as high in comparison with the benefits to public health alone. Here we explore the policy implications of including the returns of school feeding to other sectors in an economic analysis.Methods: We develop an economic evaluation methodology to estimate the costs and benefits of school feeding programs across four sectors: health and nutrition; education; social protection; and the local agricultural economy. We then apply this multi-sectoral benefit-cost analytical framework to school feeding programs in 14 countries (Botswana, Brazil, Cape Verde, Chile, Côte d'Ivoire, Ecuador, Ghana, India, Kenya, Mali, Mexico, Namibia, Nigeria, and South Africa) for which input data are readily available.Results: Across the 14 countries, we estimate that 190 million schoolchildren benefit from school feeding programs, with total program budgets reaching USD11 billion per year. Estimated annual human capital returns are USD180 billion: USD24 billion from health and nutrition gains, and USD156 billion from education. In addition, school feeding programs offer annual social protection benefits of USD7 billion and gains to local agricultural economies worth USD23 billion.Conclusions: This multi-sectoral analysis suggests that the overall benefits of school feeding are several times greater than the returns to public health alone, and that the overall benefit-cost ratio of school feeding programs could vary between 7 and 35, with particular sensitivity to the value of local wages. The scale of the findings suggests that school feeding programs are potentially much more cost-beneficial when viewed from the perspective of their multi-sectoral returns, and that it would be worthwhile following up with more detailed analyses at the national level to enhance the precision of these estimates.

All countries worldwide have signed up to the United Nations Sustainable Development Goals and have committed to the objective of achieving 'universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for all'. During the COVID-19 pandemic and beyond, advancement toward universal health coverage (UHC) will become more difficult for many countries, demonstrating that locally led priority setting is urgently needed to provide health services with appropriate financial protection to all. Because resources are limited and no national constituency can provide an unlimited number of services to their whole population in a sustainable manner, rationing and setting priorities for the selection of interventions to be included in a defined package of services is critical. In this Perspective, we discuss how packages of essential health services can be developed in resource-constrained settings, and detail how experts and the public can decide on principles and criteria, use a comprehensive array of analytical methods and choose which services to be provided free of charge. We illustrate these main steps while drawing on a recently conducted exercise of revising the national essential health services package in Ethiopia, which we compare with examples from other countries that have defined their essential benefits packages. This Perspective also provides recommendations for other low- and middle-income countries on their pathway to UHC.

IntroductionThe identification of spatial–temporal clusters of forced migrant mortality is urgently needed to inform preventative policies and humanitarian response. As a first step towards understanding the geography of forced migrant mortality, this study investigates spatial–temporal patterns in death at a global scale.MethodsWe used information on the location and dates of forced migrant deaths reported in the International Organization for Migration’s Missing Migrant Project from 2014 to 2018. Kulldorff’s spatial–temporal and seasonal scans were used to detect spatial–temporal and temporal heterogeneity in mortality.ResultsA total of 16 314 deaths were reported during the study period. A preponderance of deaths occurred at sea each year (range 26%–54% across 5 years). Twelve spatial–temporal clusters of forced migrant mortality were detected by maximum likelihood testing. Annually, the period of August–October was associated with a 40-percentage-point increase in the risk of mortality, relative to other time periods.ConclusionsDeath during forced migration occurs close to national borders and during periods of intense conflict. This evidence may inform the design of policies and targeting of interventions to prevent forced migration-related deaths.

In health outcomes terms, the poorest countries stand to lose the most from these disruptions. In this paper, we make the case for a rational approach to public sector health spending and decision making during and in the early recovery phase of the COVID-19 pandemic. Based on ethics and equity principles, it is crucial to ensure that patients not infected by COVID-19 continue to get access to healthcare and that the services they need continue to be resourced. We present a list of 120 essential non-COVID-19 health interventions that were adapted from the model health benefit packages developed by the Disease Control Priorities project.

Background The burden of non-communicable diseases (NCDs) is rapidly increasing in low- and middle-income countries, but remains largely unknown among people living with HIV (PLWH) in most sub-Saharan African countries. Methods We estimated the proportion of PLWH in Uganda with raised blood pressure and high total cholesterol, and used a modified cardiovascular disease (CVD) risk prediction model (Globorisk) to assess the 10-year risk of atherosclerotic cardiovascular disease using individual-level data on cardiometabolic risk factors, population-level data on HIV prevalence and ART coverage, and the impact of HIV on blood pressure and cholesterol. Results Among PLWH aged 30 to 69 years, the prevalence of raised blood pressure was 30% (95% uncertainty range, UR=27-33%) in women and 26% in men (95% UR=23-29%). The predicted mean 10-year CVD risk was 5% for HIV-infected women, and 6% for HIV-infected men. Five percent (n=41,000) of PLWH may experience a CVD event from 2016 to 2025 with an estimated 38% of these events being fatal. Full ART coverage would have little effect on the predicted number of CVD cases. Conclusions Despite having a high prevalence of raised blood pressure, the burden of atherosclerotic CVD among PLWH in Uganda remains low. ART programs should prioritize routine screening and treatment of raised blood pressure. An approach of using HIV treatment delivery platforms to deliver care for NCDs may miss the larger burden of disease among HIV-uninfected individuals that are not routinely seen at health facilities.

ObjectivesThe rate of change in key health indicators (eg, intervention coverage) is an understudied area of health system performance. Rates of change in health services indicators can augment traditional measures that solely involve the absolute level of performance in those indicators. Growth curves are a class of mathematical models that can parameterise dynamic phenomena and estimate rates of change summarising these phenomena; however, they are not commonly used in global health. We sought to characterise the changes over time in antiretroviral therapy (ART) coverage in sub-Saharan Africa using growth curve models.DesignThis was a retrospective observational study. We used publicly available data on ART coverage levels from 2000 to 2017 in 42 sub-Saharan African countries. We developed two ordinary differential equations models, the Gompertz and logistic growth models, that allowed for the estimation of summary parameters related to scale-up and rates of change in ART coverage. We fitted non-linear regressions for the two models, assessed goodness of fit using the Bayesian information criterion (BIC), and ranked countries based on their estimated performance drawn from the fitted model parameters.ResultsWe extracted country performance in rates of scale-up of ART coverage, which ranged from ≤2.5 percentage points per year (South Sudan, Sudan, and Madagascar) to ≥8.0 percentage points per year (Benin, Zimbabwe and Namibia), using the Gompertz model. Based on BIC, the Gompertz model provided a better fit than the logistic growth model for most countries studied.ConclusionsGrowth curve models can provide benchmarks to assess country performance in ART coverage evolution. They could be a useful approach that yields summary metrics for synthesising country performance in scaling up key health services.

Background: Despite rapid economic development, child stunting remains a persistent problem in China. Stunting prevalence varies greatly across geographical regions and wealth groups. To address child undernutrition, the Ying Yang Bao (YYB) nutritional package has been piloted in China since 2001. Objective: We aimed to evaluate the distributional impact of a hypothetical rollout of the YYB nutritional package on child stunting across provinces and wealth groups in China, with a specific focus on equity. Methods: We used data from China Family Panel Studies and built on extended cost-effectiveness analysis methods. We estimated the distributional impact of a 12-month YYB program targeting children aged 6&ndash, 36 months across 25 provinces and two wealth groups along three dimensions: the cost of the YYB program, the number of child stunting cases averted by YYB, and the cost per stunting case averted. Children in each province were divided into poverty and non-poverty groups based on the international poverty line of $5.50 per day. We also conducted a range of sensitivity analyses. Results: We showed that 75% coverage of YYB could avert 1.9 million stunting cases among children aged 6&ndash, 36 months, including 1.3 million stunting cases among children living under the poverty line, at a total cost of &yen, 5.4&ndash, 6.2 billion ($1.5&ndash, 1.8 billion) depending on the type of YYB delivery. The cost per stunting case averted would greatly vary across Chinese provinces and wealth groups, ranging from &yen, 800 (around $220, Chongqing province) to &yen, 23,300 (around $6600, Jilin province). In most provinces, the cost per stunting case averted would be lower for children living under the poverty line. Conclusions: YYB could be a pro-poor nutritional intervention package that brings substantial health benefits to poor and marginalized Chinese children, but with large variations in value for money across provinces and wealth groups. This analysis points to the need for prioritization across provinces and a targeted approach for YYB rollout in China.