Background Sustainable Development Goal (SDG) 3.3, targets to eliminate HIV from being a public health threat by 2030. For better tracking of this target interim Fast Track milestones for 2020 and composite complementary measures have been indicated. This study measured the Fast Track progress in the epidemiology of HIV/AIDS in Ethiopia across ages compared to neighboring countries. Methods The National Data Management Center for health's research team at the Ethiopian Public Health Institute has analyzed the Global Burden of Disease (GBD) 2017 secondary data for the year 2010 to 2017 for Ethiopia and its neighbors. GBD 2017 data sources were census, demographic and a health survey, prevention of mother-to-child HIV transmission, antiretroviral treatment programs, sentinel surveillance, and UNAIDS reports. Age-standardized and age-speci c HIV/AIDS incidence, prevalence, mortality, Disability-Adjusted Life Years (DALYs), incidence:mortality ratio and incidence:prevalence ratio were calculated with corresponding 95% con dence intervals. Results Ethiopia and neighboring countries recorded slow progress in reducing new HIV infection since 2010. Only Uganda would achieve the 75% target by 2020. Ethiopia, Tanzania, and Uganda already achieved the 75% mortality reduction target set for 2020. The incidence: prevalence ratio for Ethiopia, Rwanda, and Uganda were < 0.03, indicating the countries were on track to end HIV by 2030. Ethiopia had an incidence: mortality ratio <1 due to high mortality; while Kenya, Rwanda, Tanzania and Uganda had a ratio of >1 due to high incidence. The HIV incidence rate in Ethiopia was dropped by 76% among under 5 children in 2017 compared to 2010 and the country would likely to attain the 2020 national target, but far behind achieving the target among the 15-49 age group. Conclusions Ethiopia and neighboring countries have made remarkable progress towards achieving the 75% HIV/AIDS mortality reduction target by 2020, although they progressed poorly in reducing HIV incidence. By recording an incidence:prevalence ratio benchmark of less than 0.03, Ethiopia, Rwanda, and Uganda are well heading towards epidemic control. Nonetheless, the high HIV/AIDS mortality rate in Ethiopia for its incidence requires innovative strategies to reach out undiagnosed cases and to build institutional capacity for generating strong evidence to ensure sustainable epidemic control.

Summary Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast,...

Summary Background Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. Methods We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories—government, out-of-pocket, and prepaid private health spending—and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Findings Between 1995 and 2016, health spending grew at a rate of 4·00% (95% uncertainty interval 3·89–4·12) annually, although it grew slower in per capita terms (2·72% [2·61–2·84]) and increased by less than $1 per capita over this period in 22 of 195 countries. The highest annual growth rates in per capita health spending were observed in upper-middle-income countries (5·55% [5·18–5·95]), mainly due to growth in government health spending, and in lower-middle-income countries (3·71% [3·10–4·34]), mainly from DAH. Health spending globally reached $8·0 trillion (7·8–8·1) in 2016 (comprising 8·6% [8·4–8·7] of the global economy and $10·3 trillion [10·1–10·6] in purchasing-power parity-adjusted dollars), with a per capita spending of US$5252 (5184–5319) in high-income countries, $491 (461–524) in upper-middle-income countries, $81 (74–89) in lower-middle-income countries, and $40 (38–43) in low-income countries. In 2016, 0·4% (0·3–0·4) of heal...

Researchers and policymakers have long been interested in developing simple decision rules to aid in determining whether an intervention is, or is not, cost-effective. In global health, interventions that impose costs per disability-adjusted life year averted less than three and one times gross domestic product per capita are often considered cost-effective and very cost-effective, respectively. This article explores the conceptual foundation and derivation of these thresholds. Its goal is to promote understanding of how these thresholds were derived and their implications, as well as to suggest options for improvement. These thresholds are intended to reflect the monetary value of the benefits to affected individuals, based on their preferences for spending on health vs spending on other goods and services. However, the current values were not rigorously derived, which means that their application may lead to inappropriate conclusions regarding which interventions should be adopted as well as misallocation of resources across health and other investments. Improving the basis for these cost-effectiveness thresholds is of particular importance in low- and middle-income countries, given the limited resources available and the significant needs of their populations.

SummaryBackgroundAchieving universal health coverage (UHC) requires health financing systems that provide prepaid pooled resources for key health services without placing undue financial stress on households. Understanding current and future trajectories of health financing is vital for progress towards UHC. We used historical health financing data for 188 countries from 1995 to 2015 to estimate future scenarios of health spending and pooled health spending through to 2040.MethodsWe extracted historical data on gross domestic product (GDP) and health spending for 188 countries from 1995 to 2015, and projected annual GDP, development assistance for health, and government, out-of-pocket, and prepaid private health spending from 2015 through to 2040 as a reference scenario. These estimates were generated using an ensemble of models that varied key demographic and socioeconomic determinants. We generated better and worse alternative future scenarios based on the global distribution of historic health spending growth rates. Last, we used stochastic frontier analysis to investigate the association between pooled health resources and UHC index, a measure of a country's UHC service coverage. Finally, we estimated future UHC performance and the number of people covered under the three future scenarios.FindingsIn the reference scenario, global health spending was projected to increase from US$10 trillion (95% uncertainty interval 10 trillion to 10 trillion) in 2015 to $20 trillion (18 trillion to 22 trillion) in 2040. Per capita health spending was projected to increase fastest in upper-middle-income countries, at 4·2% (3·4–5·1) per year, followed by lower-middle-income countries (4·0%, 3·6–4·5) and low-income countries (2·2%, 1·7–2·8). Despite global growth, per capita health spending was projected to range from only $40 (24–65) to $413 (263–668) in 2040 in low-income countries, and from $140 (90–200) to $1699 (711–3423) in lower-middle-income countries. Globally, the share of health spending covered by pooled resources would range widely, from 19·8% (10·3–38·6) in Nigeria to 97·9% (96·4–98·5) in Seychelles. Historical performance on the UHC index was significantly associated with pooled resources per capita. Across the alternative scenarios, we estimate UHC reaching between 5·1 billion (4·9 billion to 5·3 billion) and 5·6 billion (5·3 billion to 5·8 billion) lives in 2030.InterpretationWe chart future scenarios for health spending and its relationship with UHC. Ensuring that all countries have sustainable pooled health resources is crucial to the achievement of UHC.FundingThe Bill & Melinda Gates Foundation.

IntroductionThe rapid ageing of populations around the world is accompanied by increasing prevalence of multimorbidity. This study is one of the first to present the prevalence of multimorbidity that includes HIV in the complex epidemiological setting of South Africa, thus filling a gap in the multimorbidity literature that is dominated by studies in high-income or low-HIV prevalence settings.MethodsOut of the full sample of 5059 people aged 40+, we analysed cross-sectional data on 10 conditions from 3889 people enrolled in the Health and Ageing in Africa: A longitudinal study of an INDEPTH Community in South Africa (HAALSI) Programme. Two definitions of multimorbidity were applied: the presence of more than one condition and the presence of conditions from more than one of the following categories: cardiometabolic conditions, mental disorders, HIV and anaemia. We conducted descriptive and regression analyses to assess the relationship between prevalence of multimorbidity and sociodemographic factors. We examined the frequencies of the most prevalent combinations of conditions and assessed relationships between multimorbidity and physical and psychological functioning.Results69.4 per cent (95% CI 68.0 to 70.9) of the respondents had at least two conditions and 53.9% (52.4–55.5) of the sample had at least two categories of conditions. The most common condition groups and multimorbid profiles were combinations of cardiometabolic conditions, cardiometabolic conditions and depression, HIV and anaemia and combinations of mental disorders. The commonly observed positive relationships between multimorbidity and age and decreasing wealth were not observed in this population, namelydue to different epidemiological profiles in the subgroups, with higher prevalence of HIV and anaemia in the poorer and younger groups, and higher prevalence of cardiometabolic conditions in the richer and older groups. Both physical functioning and well-being negatively associated with multimorbidity.DiscussionMore coordinated, long-term integrated care management across multiple chronic conditions should be provided in rural South Africa.

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ObjectiveTo examine how multimorbidity might affect progression along the continuum of care among older adults with hypertension, diabetes and human immunodeficiency virus (HIV) infection in rural South Africa.MethodsWe analysed data from 4447 people aged 40 years or older who were enrolled in a longitudinal study in Agincourt sub-district. Household-based interviews were completed between November 2014 and November 2015. For hypertension and diabetes (2813 and 512 people, respectively), we defined concordant conditions as other cardiometabolic conditions, and discordant conditions as mental disorders or HIV infection. For HIV infection (1027 people) we defined any other conditions as discordant. Regression models were fitted to assess the relationship between the type of multimorbidity and progression along the care continuum and the likelihood of patients being in each stage of care for the index condition (four stages from testing to treatment).FindingsPeople with hypertension or diabetes plus other cardiometabolic conditions were more like to progress through the care continuum for the index condition than those without cardiometabolic conditions (relative risk, RR: 1.14, 95% confidence interval, CI: 1.09–1.20, and RR: 2.18, 95% CI: 1.52–3.26, respectively). Having discordant comorbidity was associated with greater progression in care for those with hypertension but not diabetes. Those with HIV infection plus cardiometabolic conditions had less progress in the stages of care compared with those without such conditions (RR: 0.86, 95% CI: 0.80–0.92).ConclusionPatients with concordant conditions were more likely to progress further along the care continuum, while those with discordant multimorbidity tended not to progress beyond diagnosis.