Background: Achieving 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. Methods: We 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.
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This report shows that increased domestic revenues can and will cover only part of the necessary SDG budget spending of the LIDCs. Achieving the SDGs in the LIDCs will also require increases of both Official Development Assistance (ODA) and Private Development Assistance (PDA) to reach aggregate lev...els of SDG-directed development aid on the order of US$300-400 billion USD per year
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World Humanitarian Data and Trends presents global- and country-level data-and-trend analysis about humanitarian
crises and assistance. Its purpose is to consolidate this information and present it in an accessible way, providing policymakers, researchers and humanitarian practitioners with an evid...ence base to support humanitarian policy decisions and provide context for operational decisions.
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Examples of Donor Profiles
This paper introduces a new dataset of official financing—including foreign aid and other forms of concessional and non-concessional state financing—from China to 138 countries between 2000 and 2014. We use these data to investigate whether and to what extent Chinese aid affects economic growth ...in recipient countries. To account for the endogeneity of aid, we employ an instrumental-variables strategy that relies on exogenous variation in the supply of Chinese aid over time resulting from changes in Chinese steel production. Variation across recipient countries results from a country’s probability of receiving aid. Controlling for year- and recipient-fixed effects that capture the levels of these variables, their interaction provides a powerful and excludable instrument. Our results show that Chinese official development assistance (ODA) boosts economic growth in recipient countries. For the average recipient country, we estimate that one additional Chinese ODA project produces a 0.7 percentage point increase in economic growth two years after the project is committed. We also benchmark the effectiveness of Chinese aid vis-á-vis the World Bank, the United States, and all members of the OECD’s Development Assistance Committee (DAC).
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Background:Tracking aid fl ows helps to hold donors accountable and to compare the allocation of resources in relation to health need. With the use of data reported by donors in 2015, we provided estimates of offi cial development assistance and grants from the Bill & Melinda Gates Foundation (coll...ectively termed ODA+) to reproductive, maternal, newborn, and child health for 2013 and complete trends in reproductive, maternal, newborn, and child health support for the period 2003–13. Methods: We coded and analysed fi nancial disbursements to reproductive, maternal, newborn, and child health to all recipient countries from all donors reporting to the creditor reporting system database for the year 2013. We also revisited disbursement records for the years 2003–08 and coded disbursements relating to reproductive and sexual health activities resulting in the Countdown dataset for 2003–13. We matched this dataset to the 2015 creditor reporting system dataset and coded any unmatched creditor reporting system records. We analysed trends in ODA+ to reproductive, maternal, newborn, and child health for the period 2003–13, trends in donor contributions, disbursements to recipient countries, and targeting to need.
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This report seeks to uncover the extent to which global goals crowd in international financing, inform domestic policy priorities, and navigate progress toward development outcomes in low- and middle-income countries (LICs and MICs). Our report:
Provides a historical perspective on how ODA financin...g was aligned with the MDGs, and the perceived influence of global goals in shaping domestic priorities
Offers a baseline of ODA financing to the SDGs and a forward-looking perspective in translating past lessons learned from the MDGs era into actionable insights
Using a pilot methodology developed by AidData, we analyze ODA flows during the MDGs era (2000-2013) and approximate baseline financing for each goal prior to the adoption of Agenda 2030 in September 2015. The dataset used in the report, Financing to the SDGs, Version 1.0, provides project-level data on estimated Official Development Assistance (ODA) commitments to the 17 Sustainable Development Goals (SDGs) from 2000 to 2013. In this report, we also draw upon the responses of nearly 7,000 public, private, and civil society leaders from AidData’s novel 2014 Reform Efforts Survey to assess how national-level policymakers perceive the MDGs in light of their domestic reform priorities, and what this may mean for the SDGs.
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In an ambitious new era for health development under the 2030 Agenda for Sustainable Development, WHO and
its partners have a solid foundation of success on which to build. Health plays a fundamental role in development
and is the central focus of Sustainable Development Goal 3, “Ensure healthy ...lives and promote well-being for all
at all ages”. It is also relevant to all the Sustainable Development Goals. Understanding the significance of the
role of health is a prerequisite for successful collective action on the social, economic and environmental
determinants of health
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Donor financing to low- and middle-income countries for reproductive, maternal, newborn, and child health increased substantially from 2008 to 2013. However, increased spending by donors might not improve outcomes, if funds are delivered in ways that undermine countries’ public financial managemen...t systems and incur high transaction costs for project implementation
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Background: The need for sufficient and reliable funding to support health policy and systems research (HPSR) in low- and middle-income countries (LMICs) has been widely recognised. Currently, most resources to support such activities come from traditional development assistance for health (DAH) don...ors; however, few studies have examined the levels, trends, sources and national recipients of such support – a gap this research seeks to address. Method: Using OECD’s Creditor Reporting System database, we classified donor funding commitments using a keyword analysis of the project-level descriptions of donor supported projects to estimate total funding available for HPSR-related activities annually from bilateral and multilateral donors, as well as the Bill and Melinda Gates Foundation, to LMICs over the period 2000–2014.
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Background: 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 spendi...ng 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. Methods: 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.
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A System of Health Accounts 2011: Revised Edition provides an updated and systematic description of the financial flows related to the consumption of health care goods and services. As demands for information increase and more countries implement and institutionalise health accounts according to the... system, the data produced are expected to be more comparable, more detailed and more policy relevant. It builds on the original OECD Manual, published in 2000, and the Guide to Producing National Health Accounts to create a single global framework for producing health expenditure accounts that can help track resource flows from sources to uses. It is the result of a collaborative effort between the OECD, WHO and the European Commission, and sets out in more detail the boundaries, the definitions and the concepts – responding to health care systems around the globe – from the simplest to the more complicated.
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Board of Directors Report 2016-2017 of the Coalition for Epidemic Preparedness Innovations (CEPI) outlining financial information about CEPI regarding investors and accounts.
Background: A recent report by the Institute for Health Metrics and Evaluation (IHME) highlights that mental health receives little attention despite being a major cause of disease burden. This paper extends previous assessments of development assistance for mental health (DAMH) in two significant w...ays; first by contrasting DAMH against that for other disease categories, and second by benchmarking allocated development assistance against the core disease burden metric (disability-adjusted life year) as estimated by the Global Burden of Disease Studies. Methods: In order to track DAH, IHME collates information from audited financial records, project level data, and budget information from the primary global health channels. The diverse set of data were standardised and put into a single inflation adjusted currency (2015 US dollars) and each dollar disbursed was assigned up to one health focus areas from 1990 through 2015. We tied these health financing estimates to disease burden estimates (DALYs) produced by the Global Burden of Disease 2015 Study to calculated a standardised measure across health focus areas—development assistance for health (in US Dollars) per DALY.
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An adequate amount of prepaid resources for health is important to ensure access to health services and for the pursuit of universal health coverage. Previous studies on global health financing have described the relationship between economic development and health financing. In this study, we furth...er explore global health financing trends and examine how the sources of funds used, types of services purchased, and development assistance for health disbursed change with economic development. We also identify countries that deviate from the trends.
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How do the global goals crowd in international financing and inform domestic priorities? A new AidData report assesses the historical baseline for funding to the SDGs.
We created a dataset to generate estimates of donor-reported ‘official development assistance’ and private grants (ODA+) to reproductive, maternal, newborn and child health (RMNCH) by donor, recipient country and activity type over the period 2003–2013. We collected disbursement information fr...om the Organisation for Economic Co-operation and Development Creditor Reporting System (CRS) in January 2015. All 2.1 million records across all sectors were coded based on donor name, project title, short and long descriptions, and CRS code describing the purpose of the disbursement. We classified records according to the degree to which they would promote attainment of Millennium Development Goals 4 and 5 (reproductive and sexual health, maternal and newborn health, and child health). We also classified records according to whether they supported prenatal and neonatal health (PNH). The dataset includes project funding as well as allocating shares of general budget support, health sector support and basket funding. The data can be used to analyse resource flows to RMNCH or to other purposes or beneficiaries of ODA+.
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The majority of Countdown countries did not reach the fourth Millennium Development Goal (MDG 4) on reducing child mortality, despite the fact that donor funding to the health sector has drastically increased. When tracking aid invested in child survival, previous studies have exclusively focused on... aid targeting reproductive, maternal, newborn, and child health (RMNCH). We take a multi-sectoral approach and extend the estimation to the four sectors that determine child survival: health (RMNCH and non-RMNCH), education, water and sanitation, and food and humanitarian assistance (Food/HA). Methods and findings: Using donor reported data, obtained mainly from the OECD Creditor Reporting System and Development Assistance Committee, we tracked the level and trends of aid (in grants or loans) disbursed to each of the four sectors at the global, regional, and country levels. We performed detailed analyses on missing data and conducted imputation with various methods. To identify aid projects for RMNCH, we developed an identification strategy that combined keyword searches and manual coding. To quantify aid for RMNCH in projects with multiple purposes, we adopted an integrated approach and produced the lower and upper bounds of estimates for RMNCH, so as to avoid making assumptions or using weak evidence for allocation. We checked the sensitivity of trends to the estimation methods and compared our estimates to that produced by other studies. Our study yielded time-series and recipient-specific annual estimates of aid disbursed to each sector, as well as their lower- and upper-bounds in 134 countries between 2000 and 2014, with a specific focus on Countdown countries. We found that the upper-bound estimates of total aid disbursed to the four sectors in 134 countries rose from US$ 22.62 billion in 2000 to US$ 59.29 billion in
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Background: In 2015, 5.3 million babies died in the third trimester of pregnancy and first month following birth. Progress in reducing neonatal mortality and stillbirth rates has lagged behind the substantial progress in reducing postneonatal and maternal mortality rates. The benefits to prenatal an...d neonatal health (PNH) from maternal and child health investments cannot be assumed. Methods: We analysed donor funding for PNH over the period 2003–2013. We used an exhaustive key term search followed by manual review and classification to identify official development assistance and private grant (ODA+) disbursement records in the Countdown to 2015 ODA+ Database.
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This codebook outlines the set of TUFF procedures that have been developed, tested, refined, and implemented by AidData staff and affiliated faculty at the College of William & Mary. We initially employed these methods to achieve a specific objective: documenting the known universe of officially fin...anced Chinese projects in Africa (Strange et al. 2013, 2017). We have since then employed these methods to track Chinese official finance to five major world regions: Africa, the Middle East, Asia and the Pacific, Latin America and the Caribbean, and Central and Eastern Europe (Dreher et al. 2017). Additionally, other social scientists have adapted and applied the TUFF methodology to identify grants and loans from Gulf Cooperation Council (GCC) members (Minor et al. 2014), under-reported humanitarian assistance flows from traditional and non-traditional sources (Ghose 2017), foreign direct investment from Western and non-Western sources (Bunte et al. 2017), and pre-2000 foreign aid flows from China (Morgan and Zheng 2017). However, this codebook focuses specifically on TUFF data collection and quality assurance procedures to track Chinese official finance between 2000 and 2014.
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