Estimating total spending by source of funding on routine and supplementary immunisation activities in low-income and middle-income countries, 2000-17: a financial modelling study.

BACKGROUND: Childhood immunisation is one of the most cost-effective health interventions. However, despite its known value, global access to vaccines remains far from complete. Although supply-side constraints lead to inadequate vaccine coverage in many health systems, there is no comprehensive analysis of the funding for immunisation. We aimed to fill this gap by generating estimates of funding for immunisation disaggregated by the source of funding and the type of activities in order to highlight the funding landscape for immunisation and inform policy making. METHODS: For this financial modelling study, we estimated annual spending on immunisations for 135 low-income and middle-income countries (as determined by the World Bank) from 2000 to 2017, with a focus on government, donor, and out-of-pocket spending, and disaggregated spending for vaccines and delivery costs, and routine schedules and supplementary campaigns. To generate these estimates, we extracted data from National Health Accounts, the WHO-UNICEF Joint Reporting Forms, comprehensive multi-year plans, databases from Gavi, the Vaccine Alliance, and the Institute for Health Metrics and Evaluation's 2019 development assistance for health database. We estimated total spending on immunisation by aggregating the government, donor, prepaid private, and household spending estimates. FINDINGS: Between 2000 and 2017, funding for immunisation totalled US$112·4 billion (95% uncertainty interval 108·5-118·5). Aggregated across all low-income and middle-income countries, government spending consistently remained the largest source of funding, providing between 60·0% (57·7-61·9) and 79·3% (73·8-81·4) of total immunisation spending each year (corresponding to between $2·5 billion [2·3-2·8] and $6·4 billion [6·0-7·0] each year). Across income groups, immunisation spending per surviving infant was similar in low-income and lower-middle-income countries and territories, with average spending of $40 (38-42) in low-income countries and $42 (39-46) in lower-middle-income countries, in 2017. In low-income countries and territories, development assistance made up the largest share of total immunisation spending (69·4% [64·6-72·0]; $630·2 million) in 2017. Across the 135 countries, we observed higher vaccine coverage and increased government spending on immunisation over time, although in some countries, predominantly in Latin America and the Caribbean and in sub-Saharan Africa, vaccine coverage decreased over time, while spending increased. INTERPRETATION: These estimates highlight the progress over the past two decades in increasing spending on immunisation. However, many challenges still remain and will require dedication and commitment to ensure that the progress made in the previous decade is sustained and advanced in the next decade for the Immunization Agenda 2030. FUNDING: Bill & Melinda Gates Foundation.

Development assistance for human resources for health, 1990-2020.

BACKGROUND: Investing in the health workforce is key to achieving the health-related Sustainable Development Goals. However, achieving these Goals requires addressing a projected global shortage of 18 million health workers (mostly in low- and middle-income countries). Within that context, in 2016, the World Health Assembly adopted the WHO Global Strategy on Human Resources for Health: Workforce 2030. In the Strategy, the role of official development assistance to support the health workforce is an area of interest. The objective of this study is to examine progress on implementing the Global Strategy by updating previous analyses that estimated and examined official development assistance targeted towards human resources for health. METHODS: We leveraged data from IHME's Development Assistance for Health database, COVID development assistance database and the OECD's Creditor Reporting System online database. We utilized an updated keyword list to identify the relevant human resources for health-related activities from the project databases. When possible, we also estimated the fraction of human resources for health projects that considered and/or focused on gender as a key factor. We described trends, examined changes in the availability of human resources for health-related development assistance since the adoption of the Global Strategy and compared disease burden and availability of donor resources. RESULTS: Since 2016, development assistance for human resources for health has increased with a slight dip in 2019. In 2020, fueled by the onset of the COVID-19 pandemic, it reached an all-time high of $4.1 billion, more than double its value in 2016 and a 116.5% increase over 2019. The highest share (42.4%) of support for human resources for health-related activities has been directed towards training. Since the adoption of the Global Strategy, donor resources for health workforce-related activities have on average increased by 13.3% compared to 16.0% from 2000 through 2015. For 47 countries identified by the WHO as having severe workforce shortages, the availability of donor resources remains modest. CONCLUSIONS: Since 2016, donor support for health workforce-related activities has increased. However, there are lingering concerns related to the short-term nature of activities that donor funding supports and its viability for creating sustainable health systems.

US Health Care Spending by Race and Ethnicity, 2002-2016.

Importance: Measuring health care spending by race and ethnicity is important for understanding patterns in utilization and treatment. Objective: To estimate, identify, and account for differences in health care spending by race and ethnicity from 2002 through 2016 in the US. Design, Setting, and Participants: This exploratory study included data from 7.3 million health system visits, admissions, or prescriptions captured in the Medical Expenditure Panel Survey (2002-2016) and the Medicare Current Beneficiary Survey (2002-2012), which were combined with the insured population and notified case estimates from the National Health Interview Survey (2002; 2016) and health care spending estimates from the Disease Expenditure project (1996-2016). Exposure: Six mutually exclusive self-reported race and ethnicity groups. Main Outcomes and Measures: Total and age-standardized health care spending per person by race and ethnicity for each year from 2002 through 2016 by type of care. Health care spending per notified case by race and ethnicity for key diseases in 2016. Differences in health care spending across race and ethnicity groups were decomposed into differences in utilization rate vs differences in price and intensity of care. Results: In 2016, an estimated $2.4 trillion (95% uncertainty interval [UI], $2.4 trillion-$2.4 trillion) was spent on health care across the 6 types of care included in this study. The estimated age-standardized total health care spending per person in 2016 was $7649 (95% UI, $6129-$8814) for American Indian and Alaska Native (non-Hispanic) individuals; $4692 (95% UI, $4068-$5202) for Asian, Native Hawaiian, and Pacific Islander (non-Hispanic) individuals; $7361 (95% UI, $6917-$7797) for Black (non-Hispanic) individuals; $6025 (95% UI, $5703-$6373) for Hispanic individuals; $9276 (95% UI, $8066-$10 601) for individuals categorized as multiple races (non-Hispanic); and $8141 (95% UI, $8038-$8258) for White (non-Hispanic) individuals, who accounted for an estimated 72% (95% UI, 71%-73%) of health care spending. After adjusting for population size and age, White individuals received an estimated 15% (95% UI, 13%-17%; P < .001) more spending on ambulatory care than the all-population mean. Black (non-Hispanic) individuals received an estimated 26% (95% UI, 19%-32%; P < .001) less spending than the all-population mean on ambulatory care but received 19% (95% UI, 3%-32%; P = .02) more on inpatient and 12% (95% UI, 4%-24%; P = .04) more on emergency department care. Hispanic individuals received an estimated 33% (95% UI, 26%-37%; P < .001) less spending per person on ambulatory care than the all-population mean. Asian, Native Hawaiian, and Pacific Islander (non-Hispanic) individuals received less spending than the all-population mean on all types of care except dental (all P < .001), while American Indian and Alaska Native (non-Hispanic) individuals had more spending on emergency department care than the all-population mean (estimated 90% more; 95% UI, 11%-165%; P = .04), and multiple-race (non-Hispanic) individuals had more spending on emergency department care than the all-population mean (estimated 40% more; 95% UI, 19%-63%; P = .006). All 18 of the statistically significant race and ethnicity spending differences by type of care corresponded with differences in utilization. These differences persisted when controlling for underlying disease burden. Conclusions and Relevance: In the US from 2002 through 2016, health care spending varied by race and ethnicity across different types of care even after adjusting for age and health conditions. Further research is needed to determine current health care spending by race and ethnicity, including spending related to the COVID-19 pandemic.

The G20 and development assistance for health: historical trends and crucial questions to inform a new era.

One of the most important gatherings of the world's economic leaders, the G20 Summit and ministerial meetings, takes place in June, 2019. The Summit presents a valuable opportunity to reflect on the provision and receipt of development assistance for health (DAH) and the role the G20 can have in shaping the future of health financing. The participants at the G20 Summit (ie, the world's largest providers of DAH, emerging donors, and DAH recipients) and this Summit's particular focus on global health and the Sustainable Development Goals offers a unique forum to consider the changing DAH context and its pressing questions. In this Health Policy perspective, we examined trends in DAH and its evolution over time, with a particular focus on G20 countries; pointed to persistent and emerging challenges for discussion at the G20 Summit; and highlighted key questions for G20 leaders to address to put the future of DAH on course to meet the expansive Sustainable Development Goals. Key questions include how to best focus DAH for equitable health gains, how to deliver DAH to strengthen health systems, and how to support domestic resource mobilisation and transformative partnerships for sustainable impact. These issues are discussed in the context of the growing effects of climate change, demographic and epidemiological transitions, and a global political shift towards increasing prioritisation of national interests. Although not all these questions are new, novel approaches to allocating DAH that prioritise equity, efficiency, and sustainability, particularly through domestic resource use and mobilisation are needed. Wrestling with difficult questions in a changing landscape is essential to develop a DAH financing system capable of supporting and sustaining crucial global health goals.

Global and regional spending on dementia care from 2000-2019 and expected future health spending scenarios from 2020-2050: An economic modelling exercise.

Background: The global burden of dementia is increasing. As diagnosis and treatment rates increase and populations grow and age, additional diagnosed cases will present a challenge to healthcare systems globally. Even modelled estimates of the current and future healthcare spending attributable to dementia are valuable for decision makers and advocates to prepare for growing demand. Methods: We modelled healthcare spending attributable to dementia from 2000 to 2019 and expected estimated future spending from 2020 to 2050 under multiple scenarios. Data were from the Global Burden of Diseases 2019 study and from two systematic literature reviews. We used meta-regression to estimate the fraction of dementia spending that is attributable to dementia for those receiving nursing home-based care and for those receiving community-based care. We used spatiotemporal Gaussian process regression to account for data missingness and model diagnosis and treatment rates, nursing home-based care and community-based care rates, and unit costs for the many countries without their own underlying estimates. Projections of future spending estimate a baseline scenario from 2020 to 2050 based on ongoing growth. Alternative scenarios assessed faster growth rates for dementia diagnosis and treatment rates, nursing home-based care, and healthcare costs. All spending is reported in 2019 United States dollars or 2019 purchasing-power parity-adjusted dollars. Findings: Based on observed and modelled inputs, we estimated that global spending on dementia increased by 4.5% (95% uncertainty interval: 3.4-5.4%) annually from 2000 to 2019, reaching $263 billion (95% uncertainty interval [UI] $199- $333) attributable to dementia in 2019. We estimated total healthcare spending on patients with dementia was $594 billion (95% UI $457-$843). Under the baseline scenario, we estimated that attributable dementia spending will reach $1.6 trillion (95% UI $0.9-$2.6) by 2050. We project it will represent 11% (95% UI 6-18%) of all expected health spending, although it could be as high as 17% (95% UI 10-26%) under alternative scenarios. Interpretation: Health systems will experience increases in the burden of dementia in the near future. These modelled direct cost estimates, built from a relatively small set of data and linear time trends, highlight the magnitude of health system resources expected to be used to provide care and ensure sufficient and adequate resources for aging populations and their caretakers. More data are needed to corroborate these important trends.

Tracking development assistance for health from India to low- and middle-income countries, 2009-2020.

BACKGROUND: Development assistance for health (DAH) is an important source of financing for health for many low-income and some middle-income countries. Most DAH has predominantly been contributed by high-income countries. However, in the context of economic progress and changing global priorities, DAH contributions from countries of the Global South such as India have gained importance. In this paper, we estimate DAH contributed by India between 2009 and 2020. METHODS: We leveraged data from budgetary documents, databases, and financial reports of the Ministry of External Affairs and multilateral organizations to estimate DAH contributions. The proportions of development assistance that go towards health in major recipient countries were estimated and reported by recipient country and year. RESULTS: Between 2009 and 2020, DAH contributed by India to bilateral and multilateral partners totaled $206.0 million. South Asian countries including Bangladesh, Bhutan, Nepal, Sri Lanka, and Myanmar received the most DAH from India. DAH contributed relative to DAH received ranged from 1.42% in 2009 to 5.26% in 2018, the latest year with country-level data. Health focus areas prioritized by India included technical training and innovation, health care infrastructure support, and supply of medications and medical equipment. CONCLUSION: India is an important development partner to many countries-particularly to those in the South Asian region. India's DAH allocation strategy prioritizes contributions toward neighboring countries in the South Asia region in several health focus areas. Detailed project-level data are needed to estimate DAH contributions from India with greater precision and accuracy.

Varied Health Spending Growth Across US States Was Associated With Incomes, Price Levels, And Medicaid Expansion, 2000-19.

Little is known about health care spending variation across the US for recent years. To estimate health spending by state and payer, we combined data from the government's State Health Expenditure Accounts, which have estimates through 2014, with other primary data on spending. In 2019 state-specific per person spending ranged from $7,250 to $14,500. After adjustment for inflation, annualized per person spending growth for each state ranged from 1.0 percent in Washington, D.C., to 4.2 percent in South Dakota between 2013 and 2019. The factors that explained the most variation across states were incomes (25.3 percent) and consumer prices (21.7 percent). Medicaid expansion was associated with increases in total spending per person, although the median of spending in expansion states showed slower growth in out-of-pocket spending than the median in nonexpansion states. Contemporary estimates of state health spending are valuable for tracking divergent expenditure trajectories in the US and assessing the associated factors.

Factors associated with the disbursements of development assistance for health in low-income and middle-income countries, 2002-2017.

INTRODUCTION: In 2017, development assistance for health (DAH) comprised 5.3% of total health spending in low-income countries. Despite the key role DAH plays in global health-spending, little is known about the characteristics of assistance that may be associated with committed assistance that is actually disbursed. In this analysis, we examine associations between these characteristics and disbursement of committed assistance. METHODS: We extracted data from the Creditor Reporting System of the Organization for Economic Co-operation and Development, Institute for Health Metrics and Evaluation, and the WHO National Health Accounts database. Factors examined were off-budget assistance, administrative assistance, publicly sourced assistance and assistance to health systems strengthening. Recipient-country characteristics examined were perceived level of corruption, civil fragility and gross domestic product per capita (GDPpc). We used linear regression methods for panel of data to assess the proportion of committed aid that was disbursed for a given country-year, for each data source. RESULTS: Factors that were associated with a higher disbursement rates include off-budget aid (p<0.001), lower administrative expenses (p<0.01), lower perceived corruption in recipient country (p<0.001), lower fragility in recipient country (p<0.05) and higher GDPpc (p<0.05). CONCLUSION: Substantial gaps remain between commitments and disbursements. Characteristics of assistance (administrative, publicly sourced) and indicators of government transparency and fragility are also important drivers associated with disbursement of DAH. There remains a continued need for better aid flow reporting standards and clarity around aid types for better measurement of DAH.

Trends and outcomes in primary health care expenditures in low-income and middle-income countries, 2000-2017.

INTRODUCTION: As the world responds to COVID-19 and aims for the Sustainable Development Goals, the potential for primary healthcare (PHC) is substantial, although the trends and effectiveness of PHC expenditure are unknown. We estimate PHC expenditure for each low-income and middle-income country between 2000 and 2017 and test which health outputs and outcomes were associated with PHC expenditure. METHODS: We used three data sources to estimate PHC expenditures: recently published health expenditure estimates for each low-income and middle-income country, which were constructed using 1662 country-reported National Health Accounts; proprietary data from IQVIA to estimate expenditure of prescribed pharmaceuticals for PHC; and household surveys and costing estimates to estimate inpatient vaginal delivery expenditures. We employed regression analyses to measure the association between PHC expenditures and 15 health outcomes and intermediate health outputs. RESULTS: PHC expenditures in low-income and middle-income countries increased between 2000 and 2017, from $41 per capita (95% uncertainty interval $33-$49) to $90 ($73-$105). Expenditures for low-income countries plateaued since 2014 at $17 per capita ($15-$19). As national income increased, the proportion of health expenditures on PHC generally decrease; however, the fraction of PHC expenditures spent via ambulatory care providers grew. Increases in the fraction of health expenditures on PHC was associated with lower maternal mortality rate (p value≤0.001), improved coverage of antenatal care visits (p value≤0.001), measles vaccination (p value≤0.001) and an increase in the Health Access and Quality index (p value≤0.05). PHC expenditure was not systematically associated with all-age mortality, communicable and non-communicable disease (NCD) burden. CONCLUSION: PHC expenditures were associated with maternal and child health but were not associated with reduction in health burden for other key causes of disability, such as NCDs. To combat changing disease burdens, policy-makers and health professionals need to adapt primary healthcare to ensure continued impact on emerging health challenges.

Health expenditures by services and providers for 195 countries, 2000-2017.

INTRODUCTION: National Health Accounts are a significant source of health expenditure data, designed to be comprehensive and comparable across countries. However, there is currently no single repository of this data and even when compiled major gaps persist. This research aims to provide policymakers and researchers with a single repository of available national health expenditures by healthcare functions (ie, services) and providers of such services. Leveraging these data within statistical methods, a complete set of detailed health expenditures is estimated. METHODS: A methodical compilation and synthesis of all available national health expenditure reports including disaggregation by healthcare functions and providers was conducted. Using these data, a Bayesian multivariate regression analysis was implemented to estimate national-level health expenditures by the cross-classification of functions and providers for 195 countries, from 2000 to 2017. RESULTS: This research used 1662 country-years and 110 070 data points of health expenditures from existing National Health Accounts. The most detailed country-year had 52% of the categories of interest reported. Of all health functions, curative care and medical goods were estimated to make up 51.4% (uncertainty interval (UI) 33.2% to 59.4%) and 17.5% (UI 13.0% to 26.9%) of total global health expenditures in 2017, respectively. Three-quarters of the global health expenditures are allocated to three categories of providers: hospital providers (35.4%, UI 30.3% to 38.9%), providers of ambulatory care (25.5%, UI 21.1% to 28.8%) and retailers of medical goods (14.4%, UI 12.4% to 16.3%). As gross domestic product increases, countries spend more on long-term care and less on preventive care. CONCLUSION: Disaggregated estimates of health expenditures are often unavailable and unable to provide policymakers and researchers a holistic understanding of how expenditures are used. This research aggregates reported data and provides a complete time-series of estimates, with uncertainty, of health expenditures by health functions and providers between 2000 and 2017 for 195 countries.

Tracking government spending on immunization: The joint reporting forms, national health accounts, comprehensive multi-year plans and co-financing data.

BACKGROUND: Coverage rates for immunization have dropped in lower income countries during the COVID-19 pandemic, raising concerns regarding potential outbreaks and premature death. In order to re-invigorate immunization service delivery, sufficient financing must be made available from all sources, and particularly from government resources. This study utilizes the most recent data available to provide an updated comparison of available data sources on government spending on immunization. METHODS: We examined data from WHO/UNICEF's Joint Reporting Form (JRF), country Comprehensive Multi-Year Plan (cMYP), country co-financing data for Gavi, and WHO National Health Accounts (NHA) on government spending on immunization for consistency by comparing routine and vaccine spending where both values were reported. We also examined spending trends across time, quantified underreporting and utilized concordance analyses to assess the magnitude of difference between the data sources. RESULTS: Routine immunization spending reported through the cMYP was nearly double that reported through the JRF (rho = 0.64, 95% 0.53 to 0.77) and almost four times higher than that reported through the NHA on average (rho = 3.71, 95% 1.00 to 13.87). Routine immunization spending from the JRF was comparable to spending reported in the NHA (rho = 1.30, 95% 0.97 to 1.75) and vaccine spending from the JRF was comparable to that from the cMYP data (rho = 0.97, 95% 0.84 to 1.12). Vaccine spending from both the JRF and cMYP was higher than Gavi co-financing by a at least two (rho = 2.66, 95% 2.45 to 2.89) and (rho = 2.66, 95% 2.15 to 3.30), respectively. IMPLICATIONS: Overall, our comparative analysis provides a degree of confidence in the validity of existing reporting mechanisms for immunization spending while highlighting areas for potential improvements. Users of these data sources should factor these into consideration when utilizing the data. Additionally, partners should work with governments to encourage more reliable, comprehensive, and accurate reporting of vaccine and immunization spending.

Tracking total spending on tuberculosis by source and function in 135 low-income and middle-income countries, 2000-17: a financial modelling study.

BACKGROUND: Estimates of government spending and development assistance for tuberculosis exist, but less is known about out-of-pocket and prepaid private spending. We aimed to provide comprehensive estimates of total spending on tuberculosis in low-income and middle-income countries for 2000-17. METHODS: We extracted data on tuberculosis spending, unit costs, and health-care use from the WHO global tuberculosis database, Global Fund proposals and reports, National Health Accounts, the WHO-Choosing Interventions that are Cost-Effective project database, and the Institute for Health Metrics and Evaluation Development Assistance for Health Database. We extracted data from at least one of these sources for all 135 low-income and middle-income countries using the World Bank 2019 definitions. We estimated tuberculosis spending by source and function for notified (officially reported) and non-notified tuberculosis cases separately and combined, using spatiotemporal Gaussian process regression to fill in for missing data and estimate uncertainty. We aggregated estimates of government, out-of-pocket, prepaid private, and development assistance spending on tuberculosis to estimate total spending in 2019 US$. FINDINGS: Total spending on tuberculosis in 135 low-income and middle-income countries increased annually by 3·9% (95% CI 3·0 to 4·6), from $5·7 billion (5·2 to 6·5) in 2000 to $10·9 billion (10·3 to 11·8) in 2017. Government spending increased annually by 5·1% (4·4 to 5·7) between 2000 and 2017, and reached $6·9 billion (6·5 to 7·5) or 63·5% (59·2 to 66·8) of all tuberculosis spending in 2017. Of government spending, $5·8 billion (5·6 to 6·1) was spent on notified cases. Out-of-pocket spending decreased annually by 0·8% (-2·9 to 1·3), from $2·4 billion (1·9 to 3·1) in 2000 to $2·1 billion (1·6 to 2·7) in 2017. Development assistance for country-specific spending on tuberculosis increased from $54·6 million in 2000 to $1·1 billion in 2017. Administrative costs and development assistance for global projects related to tuberculosis care increased from $85·3 million in 2000 to $576·2 million in 2017. 30 high tuberculosis burden countries of low and middle income accounted for 73·7% (71·8-75·8) of tuberculosis spending in 2017. INTERPRETATION: Despite substantial increases since 2000, funding for tuberculosis is still far short of global financing targets and out-of-pocket spending remains high in resource-constrained countries, posing a barrier to patient's access to care and treatment adherence. Of the 30 countries with a high-burden of tuberculosis, just over half were primarily funded by government, while others, especially lower-middle-income and low-income countries, were still primarily dependent on development assistance for tuberculosis or out-of-pocket health spending. FUNDING: Bill & Melinda Gates Foundation.

Potential for additional government spending on HIV/AIDS in 137 low-income and middle-income countries: an economic modelling study.

BACKGROUND: Between 2012 and 2016, development assistance for HIV/AIDS decreased by 20·0%; domestic financing is therefore critical to sustaining the response to HIV/AIDS. To understand whether domestic resources could fill the financing gaps created by declines in development assistance, we aimed to track spending on HIV/AIDS and estimated the potential for governments to devote additional domestic funds to HIV/AIDS. METHODS: We extracted 8589 datapoints reporting spending on HIV/AIDS. We used spatiotemporal Gaussian process regression to estimate a complete time series of spending by domestic sources (government, prepaid private, and out-of-pocket) and spending category (prevention, and care and treatment) from 2000 to 2016 for 137 low-income and middle-income countries (LMICs). Development assistance data for HIV/AIDS were from Financing Global Health 2018, and HIV/AIDS prevalence, incidence, and mortality were from the Global Burden of Disease study 2017. We used stochastic frontier analysis to estimate potential additional government spending on HIV/AIDS, which was conditional on the current government health budget and other finance, economic, and contextual factors associated with HIV/AIDS spending. All spending estimates were reported in 2018 US$. FINDINGS: Between 2000 and 2016, total spending on HIV/AIDS in LMICs increased from $4·0 billion (95% uncertainty interval 2·9-6·0) to $19·9 billion (15·8-26·3), spending on HIV/AIDS prevention increased from $596 million (258 million to 1·3 billion) to $3·0 billion (1·5-5·8), and spending on HIV/AIDS care and treatment increased from $1·1 billion (458·1 million to 2·2 billion) to $7·2 billion (4·3-11·8). Over this time period, the share of resources sourced from development assistance increased from 33·2% (21·3-45·0) to 46·0% (34·2-57·0). Care and treatment spending per year on antiretroviral therapy varied across countries, with an IQR of $284-2915. An additional $12·1 billion (8·4-17·5) globally could be mobilised by governments of LMICs to finance the response to HIV/AIDS. Most of these potential resources are concentrated in ten middle-income countries (Argentina, China, Colombia, India, Indonesia, Mexico, Nigeria, Russia, South Africa, and Vietnam). INTERPRETATION: Some governments could mobilise more domestic resources to fight HIV/AIDS, which could free up additional development assistance for many countries without this ability, including many low-income, high-prevalence countries. However, a large gap exists between available financing and the funding needed to achieve global HIV/AIDS goals, and sustained and coordinated effort across international and domestic development partners is required to end AIDS by 2030. FUNDING: The Bill & Melinda Gates Foundation.

Tracking development assistance for health from China, 2007-2017.

INTRODUCTION: In recent years, China has increased its international engagement in health. Nonetheless, the lack of data on contributions has limited efforts to examine contributions from China. Existing estimates that track development assistance for health (DAH) from China have relied primarily on one dataset. Furthermore, little is known about the disbursing agencies especially the multilaterals through which contributions are disbursed and how these are changing across time. In this study, we generated estimates of DAH from China from 2007 through 2017 and disaggregated those estimates by disbursing agency and health focus area. METHODS: We identified the major government agencies providing DAH. To estimate DAH provided by each agency, we leveraged publicly available development assistance data in government agencies' budgets and financial accounts, as well as revenue statements from key international development agencies such as the WHO. We reported trends in DAH from China, disaggregated contributions by disbursing bilateral and multilateral agencies, and compared DAH from China with other traditional donors. We also compared these estimates with existing estimates. RESULTS: DAH provided by China grew dramatically, from US$323.1 million in 2007 to $652.3 million in 2017. During this period, 91.8% of DAH from China was disbursed through its bilateral agencies, including the Ministry of Commerce ($3.7 billion, 64.1%) and the National Health Commission ($917.1 million, 16.1%); the other 8.2% was disbursed through multilateral agencies including the WHO ($236.5 million, 4.1%) and the World Bank ($123.1 million, 2.2%). Relative to its level of economic development, China provided substantially more DAH than would be expected. However, relative to population size and government spending, China's contributions are modest. CONCLUSION: In the current context of plateauing in the growth rate of DAH contributions, China has the potential to contribute to future global health financing, especially financing for health system strengthening.

Tracking spending on malaria by source in 106 countries, 2000-16: an economic modelling study.

BACKGROUND: 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. METHODS: 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. FINDINGS: 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. INTERPRETATION: 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. FUNDING: The Bill & Melinda Gates Foundation.