Explore the vast range of titles available.

Comparable estimates of health spending are crucial for the assessment of health systems and to optimally deploy health resources. The methods used to track health spending continue to evolve, but little is known about the distribution of spending across diseases. We developed improved estimates of health spending by source, including development assistance for health, and, for the first time, estimated HIV/AIDS spending on prevention and treatment and by source of funding, for 188 countries. We collected published data on domestic health spending, from 1995 to 2015, from a diverse set of international agencies. We tracked development assistance for health from 1990 to 2017. We also extracted 5385 datapoints about HIV/AIDS spending, between 2000 and 2015, from online databases, country reports, and proposals submitted to multilateral organisations. We used spatiotemporal Gaussian process regression to generate complete and comparable estimates for health and HIV/AIDS spending. We report most estimates in 2017 purchasing-power parity-adjusted dollars and adjust all estimates for the effect of inflation. Between 1995 and 2015, global health spending per capita grew at an annualised rate of 3·1% (95% uncertainty interval [UI] 3·1 to 3·2), with growth being largest in upper-middle-income countries (5·4% per capita [UI 5·3–5·5]) and lower-middle-income countries (4·2% per capita [4·2–4·3]). In 2015, $9·7 trillion (9·7 trillion to 9·8 trillion) was spent on health worldwide. High-income countries spent $6·5 trillion (6·4 trillion to 6·5 trillion) or 66·3% (66·0 to 66·5) of the total in 2015, whereas low-income countries spent $70·3 billion (69·3 billion to 71·3 billion) or 0·7% (0·7 to 0·7). Between 1990 and 2017, development assistance for health increased by 394·7% ($29·9 billion), with an estimated $37·4 billion of development assistance being disbursed for health in 2017, of which $9·1 billion (24·2%) targeted HIV/AIDS. Between 2000 and 2015, $562·6 billion (531·1 billion to 621·9 billion) was spent on HIV/AIDS worldwide. Governments financed 57·6% (52·0 to 60·8) of that total. Global HIV/AIDS spending peaked at 49·7 billion (46·2–54·7) in 2013, decreasing to $48·9 billion (45·2 billion to 54·2 billion) in 2015. That year, low-income and lower-middle-income countries represented 74·6% of all HIV/AIDS disability-adjusted life-years, but just 36·6% (34·4 to 38·7) of total HIV/AIDS spending. In 2015, $9·3 billion (8·5 billion to 10·4 billion) or 19·0% (17·6 to 20·6) of HIV/AIDS financing was spent on prevention, and $27·3 billion (24·5 billion to 31·1 billion) or 55·8% (53·3 to 57·9) was dedicated to care and treatment. From 1995 to 2015, total health spending increased worldwide, with the fastest per capita growth in middle-income countries. While these national disparities are relatively well known, low-income countries spent less per person on health and HIV/AIDS than did high-income and middle-income countries. Furthermore, declines in development assistance for health continue, including for HIV/AIDS. Additional cuts to development assistance could hasten this decline, and risk slowing progress towards global and national goals. The Bill & Melinda Gates Foundation.

Contrary to the hopes of policymakers, fossil fuel subsidy removal would have only a small impact on global energy demand and carbon dioxide emissions and would not increase renewable energy use by 2030. Limited benefits from banishing fuel subsidies Many governments use subsidies for fossil fuels to reduce the cost of energy for domestic consumption. This has led to the frequent argument that removing subsidies could play an important part in mitigating climate change. Now, Jessica Jewel and colleagues show that subsidy removal would indeed substantially lower emissions in fossil-fuel-exporting countries, but would reduce global carbon dioxide emissions by only a few per cent by 2030. This small reduction would largely be due to offsetting effects from international trade and fuel substitution. The authors also find that subsidy removal would not dramatically increase the use of renewable energy, adding to the suggestion that extensive revisions of subsidy policies would not produce a major benefit for climate mitigation. Hopes are high that removing fossil fuel subsidies could help to mitigate climate change by discouraging inefficient energy consumption and levelling the playing field for renewable energy 1 , 2 , 3 . In September 2016, the G20 countries re-affirmed their 2009 commitment (at the G20 Leaders’ Summit) to phase out fossil fuel subsidies 4 , 5 and many national governments are using today’s low oil prices as an opportunity to do so 6 , 7 , 8 , 9 . In practical terms, this means abandoning policies that decrease the price of fossil fuels and electricity generated from fossil fuels to below normal market prices 10 , 11 . However, whether the removal of subsidies, even if implemented worldwide, would have a large impact on climate change mitigation has not been systematically explored. Here we show that removing fossil fuel subsidies would have an unexpectedly small impact on global energy demand and carbon dioxide emissions and would not increase renewable energy use by 2030. Subsidy removal would reduce the carbon price necessary to stabilize greenhouse gas concentration at 550 parts per million by only 2–12 per cent under low oil prices. Removing subsidies in most regions would deliver smaller emission reductions than the Paris Agreement (2015) climate pledges and in some regions global subsidy removal may actually lead to an increase in emissions, owing to either coal replacing subsidized oil and natural gas or natural-gas use shifting from subsidizing, energy-exporting regions to non-subsidizing, importing regions. Our results show that subsidy removal would result in the largest CO 2 emission reductions in high-income oil- and gas-exporting regions, where the reductions would exceed the climate pledges of these regions and where subsidy removal would affect fewer people living below the poverty line than in lower-income regions.

The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. We extracted GDP, government spending in 184 countries from 1980–2015, and health spend data from 1995–2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. We estimated that global spending on health will increase from US$9·21 trillion in 2014 to $24·24 trillion (uncertainty interval [UI] 20·47–29·72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5·3% (UI 4·1–6·8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4·2% (3·8–4·9). High-income countries are expected to grow at 2·1% (UI 1·8–2·4) and low-income countries are expected to grow at 1·8% (1·0–2·8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133–181) per capita in 2030 and $195 (157–258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157–258) per capita was available for health in 2040 in low-income countries. Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential. Bill & Melinda Gates Foundation.

In 2005, with the goal of reducing the numbers of maternal and neonatal deaths, the Government of India launched Janani Suraksha Yojana (JSY), a conditional cash transfer scheme, to incentivise women to give birth in a health facility. We independently assessed the effect of JSY on intervention coverage and health outcomes. We used data from the nationwide district-level household surveys done in 2002–04 and 2007–09 to assess receipt of financial assistance from JSY as a function of socioeconomic and demographic characteristics; and used three analytical approaches (matching, with-versus-without comparison, and differences in differences) to assess the effect of JSY on antenatal care, in-facility births, and perinatal, neonatal, and maternal deaths. Implementation of JSY in 2007–08 was highly variable by state—from less than 5% to 44% of women giving birth receiving cash payments from JSY. The poorest and least educated women did not always have the highest odds of receiving JSY payments. JSY had a significant effect on increasing antenatal care and in-facility births. In the matching analysis, JSY payment was associated with a reduction of 3·7 (95% CI 2·2–5·2) perinatal deaths per 1000 pregnancies and 2·3 (0·9–3·7) neonatal deaths per 1000 livebirths. In the with-versus-without comparison, the reductions were 4·1 (2·5–5·7) perinatal deaths per 1000 pregnancies and 2·4 (0·7–4·1) neonatal deaths per 1000 livebirths. The findings of this assessment are encouraging, but they also emphasise the need for improved targeting of the poorest women and attention to quality of obstetric care in health facilities. Continued independent monitoring and evaluations are important to measure the effect of JSY as financial and political commitment to the programme intensifies. Bill & Melinda Gates Foundation.

Head Start (HS) is the largest federally funded preschool program for disadvantaged children. Research has shown relatively small impacts on cognitive and social skills; therefore, some have questioned its effectiveness. Using data from the Head Start Impact Study (3-year-old cohort; N = 2,449), latent class analysis was used to (a) identify subgroups of children defined by baseline characteristics of their home environment and caregiver and (b) test whether the effects of HS on cognitive, and behavioral and relationship skills over 2 years differed across subgroups. The results suggest that the effectiveness of HS varies quite substantially. For some children there appears to be a significant, and in some cases, long-term, positive impact. For others there is little to no effect.

Adjustment for race is discouraged in lung-function testing, but the implications of adopting race-neutral equations have not been comprehensively quantified. We obtained longitudinal data from 369,077 participants in the National Health and Nutrition Examination Survey, U.K. Biobank, the Multi-Ethnic Study of Atherosclerosis, and the Organ Procurement and Transplantation Network. Using these data, we compared the race-based 2012 Global Lung Function Initiative (GLI-2012) equations with race-neutral equations introduced in 2022 (GLI-Global). Evaluated outcomes included national projections of clinical, occupational, and financial reclassifications; individual lung-allocation scores for transplantation priority; and concordance statistics (C statistics) for clinical prediction tasks. Among the 249 million persons in the United States between 6 and 79 years of age who are able to produce high-quality spirometric results, the use of GLI-Global equations may reclassify ventilatory impairment for 12.5 million persons, medical impairment ratings for 8.16 million, occupational eligibility for 2.28 million, grading of chronic obstructive pulmonary disease for 2.05 million, and military disability compensation for 413,000. These potential changes differed according to race; for example, classifications of nonobstructive ventilatory impairment may change dramatically, increasing 141% (95% confidence interval [CI], 113 to 169) among Black persons and decreasing 69% (95% CI, 63 to 74) among White persons. Annual disability payments may increase by more than $1 billion among Black veterans and decrease by $0.5 billion among White veterans. GLI-2012 and GLI-Global equations had similar discriminative accuracy with regard to respiratory symptoms, health care utilization, new-onset disease, death from any cause, death related to respiratory disease, and death among persons on a transplant waiting list, with differences in C statistics ranging from -0.008 to 0.011. The use of race-based and race-neutral equations generated similarly accurate predictions of respiratory outcomes but assigned different disease classifications, occupational eligibility, and disability compensation for millions of persons, with effects diverging according to race. (Funded by the National Heart Lung and Blood Institute and the National Institute of Environmental Health Sciences.).

Sustaining achievements in malaria control and making progress toward malaria elimination requires coordinated funding. We estimated domestic malaria spending by source in 106 countries that were malaria-endemic in 2000–16 or became malaria-free after 2000. We collected 36 038 datapoints reporting government, out-of-pocket (OOP), and prepaid private malaria spending, as well as malaria treatment-seeking, costs of patient care, and drug prices. We estimated government spending on patient care for malaria, which was added to government spending by national malaria control programmes. For OOP malaria spending, we used data reported in National Health Accounts and estimated OOP spending on treatment. Spatiotemporal Gaussian process regression was used to ensure estimates were complete and comparable across time and to generate uncertainty. In 2016, US$4·3 billion (95% uncertainty interval [UI] 4·2–4·4) was spent on malaria worldwide, an 8·5% (95% UI 8·1–8·9) per year increase over spending in 2000. Since 2000, OOP spending increased 3·8% (3·3–4·2) per year, amounting to $556 million (487–634) or 13·0% (11·6–14·5) of all malaria spending in 2016. Governments spent $1·2 billion (1·1–1·3) or 28·2% (27·1–29·3) of all malaria spending in 2016, increasing 4·0% annually since 2000. The source of malaria spending varied depending on whether countries were in the malaria control or elimination stage. Tracking global malaria spending provides insight into how far the world is from reaching the malaria funding target of $6·6 billion annually by 2020. Because most countries with a high burden of malaria are low income or lower-middle income, mobilising additional government resources for malaria might be challenging. The Bill & Melinda Gates Foundation.

is it more effective to give large grants to a few elite researchers, or small grants to many researchers? Large grants would be more effective only if scientific impact increases as an accelerating function of grant size. Here, we examine the scientific impact of individual university-based researchers in three disciplines funded by the Natural Sciences and Engineering Research Council of Canada (NSERC). We considered four indices of scientific impact: numbers of articles published, numbers of citations to those articles, the most cited article, and the number of highly cited articles, each measured over a four-year period. We related these to the amount of NSERC funding received. Impact is positively, but only weakly, related to funding. Researchers who received additional funds from a second federal granting council, the Canadian Institutes for Health Research, were not more productive than those who received only NSERC funding. Impact was generally a decelerating function of funding. Impact per dollar was therefore lower for large grant-holders. This is inconsistent with the hypothesis that larger grants lead to larger discoveries. Further, the impact of researchers who received increases in funding did not predictably increase. We conclude that scientific impact (as reflected by publications) is only weakly limited by funding. We suggest that funding strategies that target diversity, rather than \"excellence\", are likely to prove to be more productive.

Background Implementation of food taxes or subsidies may promote healthier and a more sustainable diet in a society. This study estimates the effects of a tax (15% or 30%) on meat and a subsidy (10%) on fruit and vegetables (F&V) consumption in the Netherlands using a social cost-benefit analysis with a 30-year time horizon. Methods Calculations with the representative Dutch National Food Consumption Survey (2012–2014) served as the reference. Price elasticities were applied to calculate changes in consumption and consumer surplus. Future food consumption and health effects were estimated using the DYNAMO-HIA model and environmental impacts were estimated using Life Cycle Analysis. The time horizon of all calculations is 30 year. All effects were monetarized and discounted to 2018 euros. Results Over 30-years, a 15% or 30% meat tax or 10% F&V subsidy could result in reduced healthcare costs, increased quality of life, and higher productivity levels. Benefits to the environment of a meat tax are an estimated €3400 million or €6300 million in the 15% or 30% scenario respectively, whereas the increased F&V consumption could result in €100 million costs for the environment. While consumers benefit from a subsidy, a consumer surplus of €10,000 million, the tax scenarios demonstrate large experienced costs of respectively €21,000 and €41,000 million. Overall, a 15% or 30% price increase in meat could lead to a net benefit for society between €3100–7400 million or €4100–12,300 million over 30 years respectively. A 10% F&V subsidy could lead to a net benefit to society of €1800–3300 million. Sensitivity analyses did not change the main findings. Conclusions The studied meat taxes and F&V subsidy showed net total welfare benefits for the Dutch society over a 30-year time horizon.