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1
Background: 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 e
...
stimates 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.
more
Global HIV control funding falls short of need. To maximize health outcomes, it is critical that national governments sustain reasonable commitments, and that international donor assistance be distributed according to country needs and funding gaps. We develop a country classification framework in t
...
erms of actual versus expected national domestic funding, considering resource needs and donor financing. With UNAIDS and World Bank data, we examine domestic and donor HIV program funding in relation to need in 84 low- and middle-income countries. We estimate expected domestic contributions per person living with HIV (PLWH) as a function of per capita income, relative size of the health sector, and per capita foreign debt service.
more
This report started with a simple question—“How can we tell how much funding is devoted to global health programs?”—and ended (more than two years later) with an answer that is far from simple. As those who have tried know well, tracking health-related funding is challenging in any setting,
...
given the range of public and private sources and the many types of services and programs that fall within the definition of “health sector.” It is made all the more complicated when significant external support from donors and private charities plus in-kind donations of drugs and other inputs are taken into account. The task is made yet harder by inadequate public expenditure management systems in countries where public agencies’ capacity is stretched very thin and by donor accounting structures that are not designed to respond in a timely way
more
The COVID-19 pandemic has resulted in a double shock - health and economic. As of March 1, 2021, COVID-19 has cost more than 2.5 million lives and triggered an economic recession surpassing any economic downturn since World War II.
Part I of this paper explores the impact of this current macro-fisc
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al outlook on the three primary sources of health spending. Drawing on experiences from previous economic crises, scenario analyses suggest a fall in government per capita spending on health in 2021 and 2022 unless governments make bold choices to increase the share of health in general government spending.
Part II of the paper discusses policy options to meet the spending needs in health. These options encompass strategies to make fiscal adjustments work and channel funds where they are most needed, as well as policies to stabilize the balance sheets of social health insurance (SHI) schemes. The paper explains how the health sector can play an active role in expanding fiscal space, contributing to tax reforms, most importantly pro-health taxes, and mobilizing and absorbing external financing, including debt relief.
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Guidelines for the Implementation of the SHA 2011 Framework for Accounting Health Care Financing
Organisation for Economic Co-operation and Development (OECD) and World Health Organization (WHO)
Organisation for Economic Co-operation and Development (OECD) and World Health Organization (WHO)
(2014)
CC
The accounting framework for health care financing is a key component of A System of Health Accounts 2011, published by OECD, Eurostat and WHO in October 2011.1 The framework makes health accounts more adaptable to rapidly evolving health financing systems, further enhances crosscountry comparabilit
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y of health expenditures and financing data, and ultimately improves the information base for the analytical use of national health accounts (NHAs). It is hoped that SHA 2011 – including its financing framework – will make health accounts a more useful assessment and monitoring tool for health systems and health expenditure in the economy as a whole.
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The majority of developing countries will fail to achieve their targets for Universal Health Coverage (UHC)1 and the health- and poverty-related Sustainable Development Goals (SDGs) unless they take urgent steps to strengthen their health financing. Just over a decade out from the SDG deadline of 20
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30, 3.6 billion people do not receive the most essential health services they need, and 100 million are pushed into poverty from paying out-of-pocket for health services. The evidence is strong that progress towards UHC, core to SDG 3, will spur inclusive and sustainable economic growth, yet this will not happen unless countries achieve high-performance health financing, defined here as funding levels that are adequate and sustainable; pooling that is sufficient to spread the financial risks of ill-health; and spending that is efficient and equitable to assure desired levels of health service coverage, quality, and financial protection for all people— with resilience and sustainability.
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The 2021 Report examines country health spending patterns and trends over the past 20 years, before the COVID-19 pandemic, with greater focus on public spending on health. The report also presents spending on primary health care, preliminary health expenditure in 2020 for a small set of countries (i
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ncluding their health spending on COVID-19) and an analysis of high-income countries spending patterns, in particular during the global financial crisis. The report also points out the need for more public investment in health to get progress towards UHC back on track and strong health security.
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The importance of robust mortality surveillance systems cannot be overstated in an era marked by increasing global health challenges where health threats loom large and population dynamics continue to evolve. Accurate and timely mortality data is essential for identifying trends and detecting emergi
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ng health threats, evaluating the impact of interventions, and guiding evidence-based policy decisions.
This framework outlines a holistic approach to strengthening routine mortality surveillance systems, considering the unique contextual factors and challenges faced by African countries. It emphasizes the importance of establishing efficient data collection mechanisms, enhancing data quality and completeness, and promoting data sharing and collaboration among stakeholders.
Moreover, the framework recognizes the pivotal role of technology in the integration of data from fragmented mortality data sources. It highlights the potential of innovative data capture methods, advanced analytics, and real-time reporting systems to enhance mortality data’s accuracy, efficiency, and timeliness.
The continental framework for mortality surveillance aligns with Africa CDC’s mission and strategic goal by serving as a fundamental component in strengthening public health systems, enhancing disease surveillance capacities and capabilities, informing evidence-based policies and interventions, and promoting collaboration and coordination among African countries to address health challenges and improve health outcomes on the continent.
The successful implementation of this framework requires collective commitment and concerted efforts from governments, health institutions, and the international community. We hope this document will serve as a catalyst for transformative change, enabling countries to build resilient mortality surveillance systems that protect public health, save lives, and contribute to evidence-based decision-making.
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L'importance de systèmes de surveillance de la mortalité robustes ne peut être surestimée à une époque marquée par des défis sanitaires mondiaux croissants, où les menaces sanitaires pèsent lourd et la dynamique des populations continue d'évoluer. Des données précises et opportunes sur
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la mortalité sont essentielles pour identifier les tendances et détecter les menaces émergentes pour la santé, évaluer l'impact des interventions et orienter les décisions politiques fondées sur des données probantes.
Ce cadre décrit une approche holistique pour renforcer les systèmes de surveillance de routine de la mortalité, en tenant compte des facteurs contextuels uniques et des défis auxquels sont confrontés les pays africains. Il souligne l'importance d'établir des mécanismes de collecte de données efficaces, d'améliorer la qualité et l'exhaustivité des données et de promouvoir le partage des données et la collaboration entre les parties prenantes.
De plus, le cadre reconnaît le rôle central de la technologie dans l'intégration des données provenant de sources de données fragmentées sur la mortalité. Il met en évidence le potentiel des méthodes innovantes de capture de données, des analyses avancées et des systèmes de notification en temps réel pour améliorer la précision, l'efficacité et l'actualité des données sur la mortalité.
Le cadre continental de surveillance de la mortalité s'aligne sur la mission et l'objectif stratégique d'Africa CDC en servant d'élément fondamental dans le renforcement des systèmes de santé publique, l'amélioration des capacités et des capacités de surveillance des maladies, l'élaboration de politiques et d'interventions fondées sur des données probantes et la promotion de la collaboration et de la coordination entre les pays africains pour relever les défis sanitaires et améliorer les résultats sanitaires sur le continent.
La mise en œuvre réussie de ce cadre nécessite un engagement collectif et des efforts concertés de la part des gouvernements, des établissements de santé et de la communauté internationale. Nous espérons que ce document servira de catalyseur pour un changement transformateur, permettant aux pays de mettre en place des systèmes de surveillance de la mortalité résilients qui protègent la santé publique, sauvent des vies et contribuent à la prise de décision fondée sur des données probantes.
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The world has been turned on its head by the coronavirus disease 2019 (COVID-19) pandemic. This has provided a stark wakeup call on the severe under-financing of health systems around the world. It has laid bare the inequalities and limitations in the capacities of countries at all levels of develop
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ment to prevent major health crises or respond to them. But it doesn’t have to be this way.
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The 2021 Global monitoring report on financial protection in health shows that before the COVID-19 pandemic, the world was off-track to reduce financial hardship due to health expenditures because trends in catastrophic health spending were going in the wrong direction and the number of people incur
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ring impoverishing health spending remained unacceptably high (Chapter 1). Chapter 2 summarizes emerging evidence on the consequence of the pandemic and the related macroeconomic and fiscal crisis that points to the likely worsening of financial protection for households, particularly as a result of declining income and consumption, along with rising poverty and inequality
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The Mapping Antimicrobial Resistance and Antimicrobial Use Partnership (MAAP) project has conducted a multi-year, multi-country study that provides stark insights on the under-reported depth of the antimicrobial resistance (AMR) crisis across Africa and lays out urgent policy recommendations to addr
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ess the emergency.
MAAP reviewed 819,584 AMR records from 2016-2019, from 205 laboratories across Burkina Faso, Cameroon, Eswatini, Gabon, Ghana, Kenya, Malawi, Nigeria, Senegal, Sierra Leone, Tanzania, Uganda, Zambia, and Zimbabwe. MAAP also reviewed data from 327 hospital and community pharmacies and 16 national-level AMC datasets.
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Past quantitative research on health financing has focused mostly on the level and distribution of total expenditure, with little emphasis on the specific role of public funds, despite their known importance for universal health coverage (UHC). Health Accounts data do not disaggregate public expendi
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ture on health by source of funding. Achieving a better understanding of public financing for health in the context of the macro-fiscal and health financing environment is of fundamental importance to the development of future health financing policy, particularly in low- and middle-income countries (LMICs).
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The Mapping Antimicrobial Resistance and Antimicrobial Use Partnership (MAAP) project has conducted a multi-year, multi-country study that provides stark insights on the under-reported depth of the antimicrobial resistance (AMR) crisis across Africa and lays out urgent policy recommendations to addr
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ess the emergency.
MAAP reviewed 819,584 AMR records from 2016-2019, from 205 laboratories across Burkina Faso, Cameroon, Eswatini, Gabon, Ghana, Kenya, Malawi, Nigeria, Senegal, Sierra Leone, Tanzania, Uganda, Zambia, and Zimbabwe. MAAP also reviewed data from 327 hospital and community pharmacies and 16 national-level AMC datasets.
more
The Mapping Antimicrobial Resistance and Antimicrobial Use Partnership (MAAP) project has conducted a multi-year, multi-country study that provides stark insights on the under-reported depth of the antimicrobial resistance (AMR) crisis across Africa and lays out urgent policy recommendations to addr
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ess the emergency.
MAAP reviewed 819,584 AMR records from 2016-2019, from 205 laboratories across Burkina Faso, Cameroon, Eswatini, Gabon, Ghana, Kenya, Malawi, Nigeria, Senegal, Sierra Leone, Tanzania, Uganda, Zambia, and Zimbabwe. MAAP also reviewed data from 327 hospital and community pharmacies and 16 national-level AMC datasets.
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This results report for the biennium 2020–2021 presents the progress towards the triple billion targets, outcomes and outputs, based on the GPW 13 results framework and indicators. It uses structured methodologies, both quantitative and qualitative, for measuring and analysing the achievements and
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challenges to achieving them, and includes country and impact case studies to exemplify how the Organization’s work is driving health impacts at the country level, where it matters most. For the first time, the WHO Secretariat is reporting on its investments, results and performance through a scorecard methodology for every country or territory it serves.
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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
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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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AidData has developed a set of open source data collection methods to track project-level data on suppliers of official finance who do not participate in global reporting systems. This codebook outlines the version 1.1 set of TUFF procedures that have been developed, tested, refined, and implemented
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by AidData researchers and affiliated faculty at the College of William & Mary and Brigham Young University.
In the first iteration of this codebook, AidData's Media-Based Data Collection Methodology, Version 1.0, we referred to our data collection procedures as a “media-based data collection” (MBDC) methodology. The term “media-based” was misleading, as the methodology does not rely exclusively on media reports; rather, media reports are used only as a departure point, and are supplemented with case studies undertaken by scholars and non-governmental organizations, project inventories supplied through Chinese embassy websites, and grants and loan data published by recipient governments. In the interest of providing greater clarity, we now refer to our methodology for systematically gathering open source development finance information as the Tracking Underreported Financial Flows (TUFF) methodology. 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 and Brigham Young University.
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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
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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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I examine the effectiveness of donors in targeting the highest burden of malaria in the Democratic Republic of Congo when health information structure is fragmented. I exploit local variations in the burden of malaria induced by mining activities as well as financial and epidemiological data from he
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alth facilities to estimate how local aid is matching local health needs. Using a regression discontinuity design, I find significant but quantitatively small variations in aid to health facilities located within mining areas. Comparing local aid with the additional cost of treatment and prevention associated with the increased risk of malaria transmission, I find suggestive evidence that local populations with the highest burden of the disease receive a proportionately lower share of aid compared to neighbouring areas with reduced exposure to malaria infection. The evidence of disparities in the allocation of aid for malaria supports the view that donors may have inaccurate information about local population needs.
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