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2
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
...
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
...
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
...
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
...
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
...
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
Since the 1970s, voluntary contributions have become an increasingly important component of WHO's budget. As voluntary contributions tend to be earmarked for donor-specified programmes and projects, there are concerns that this trend has diverted focus away from WHO's strategic priorities, made coor
...
dination and attaining coherence more difficult, undermined WHO's democratic structures and given undue power to a handful of wealthy donors. In the past few years, the WHO Secretariat has pushed for donors to increase the amount of flexible funding they provide.
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
...
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
...
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
...
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
...
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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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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WHO’s total revenue in 2020 was US$ 4299 million and total expenses were US$ 3561 million, resulting in a surplus of US$ 824 million, which includes finance revenue (e.g. interest and investment income) of US$ 86 million, representing increases of 38% and 15% in revenue and expenses respectively.
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10. The financial statements report all the Organization’s revenue and expenses. The Organization’s operations are managed under three fund groups: (1) the General Fund, which supports the programme budget, (2) Member States – other, and (3) the Fiduciary Fund (Note 2.18 gives particulars of each of the funds). This segregation of resources facilitates clearer reporting of WHO’s revenues and expenses.
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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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Achieving the Sustainable Development Goals (SDGs) will require the international community to mobilize significant additional financing over the next decade. Tracking and analyzing this funding is central to measuring progress and making more informed choices to direct financial flows where they wi
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ll have the greatest impact. This brief highlights AidData’s updated methodology to track financing to the SDGs, providing a baseline of funding for the years immediately before and after their launch. To track SDG-related financing, we build on our 2017 pilot methodology. Using data from the OECD CRS database on all official development assistance between 2010 and 2016, we identify individual projects that are linked to specific SDG goals or targets and then quantify total financing by SDG. This brief highlights four countries that represent different development contexts and trajectories, exploring how a country’s individual context impacts its SDG-related donor funding by examining the composition of funding and financing trends. We also look at SDG financing from the perspective of donors to see how their own interests are reflected in development portfolios across different countries.
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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
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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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Development finance institutions owned by European governments and the World Bank Group are spending hundreds of millions of dollars on expensive for-profit hospitals in the Global South that block patients from getting care, or bankrupt them, with some even imprisoning patients who cannot afford th
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eir bills. At the height of the COVID-19 pandemic, some of these same hospitals denied entry to patients suffering from the virus or sold intensive care beds at eyewatering prices to the highest bidder. These development institutions have woefully inadequate safeguards, invest via a complex web of tax-avoiding financial intermediaries, and offer little to zero evidence on the impacts their investments are having. Oxfam is calling on rich-country governments and the World Bank Group to immediately halt their spending on for-profit private healthcare, and for an urgent independent investigation to be conducted into all active and historic investments.
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We combine data on Chinese development projects with data from Demographic and Health Surveys to study the impact of Chinese aid on household welfare in sub-Saharan Africa. We use a novel methodology to test the effect of Chinese aid on three important development outcomes: education, health, and nu
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trition. For each outcome, we use difference-in-difference estimations to compare household areas near Chinese project sites to control areas located farther away, before and after receiving Chinese aid. This empirical strategy rules out many confounding factors that can bias measuring the impact of Chinese aid on our outcome variables. First, we find that Chinese projects significantly improve education and child mortality in treatment areas, but do not significantly affect nutrition. Second, social sector projects have a larger effect on outcomes than economic projects. Third, we do not find significant effects for projects that ended more than five years before the post-treatment survey wave. Our results are robust to a host of robustness checks.
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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
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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 report examines the support to private healthcare provision in India by the World Bank’s private sector arm, the International Finance Corporation (IFC). Despite supporting private healthcare in the country since 1997, no healthcare results for lending and investments have been disclosed sinc
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e the start of these operations over twenty-five years ago. The IFC has overwhelmingly invested in high-end urban hospitals which are out of reach for the majority of Indians. Several have consistently failed to provide free healthcare to poor patients despite this being a condition under which free or subsidized public land was allotted to these hospitals. Supporting private healthcare in a context where 37% of Indians experience catastrophic health expenditures in private hospitals appears to run counter to the World Bank Group’s focus on poverty reduction. These investments do not contribute to the building of stronger healthcare infrastructure or respond to unmet healthcare needs. Only 14% of IFC-financed hospitals are located in the 10 states ranked lowest in terms of the overall performance of the health system. Furthermore, we found many instances where regulators upheld complaints pertaining to violations of patients’ rights by these hospitals including overcharging, denial of healthcare, price rigging, financial conflict of interest and medical negligence.
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