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...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...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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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.
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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...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.
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The increasing amounts of official development assistance (ODA) for health have been aimed primarily at fighting HIV/AIDS, malaria and tuberculosis. Neglected tropical diseases (NTD), one of the most serious public health burdens among the most deprived communities, have only recently drawn the atte...ntion of major donors. While frequently stated, the low share
of funding for NTD control projects has not been calculated empirically. Our analysis of ODA commitments for infectious disease control for the years 2003 to 2007 confirms that Development Assistance Committee (DAC)-countries and multilateral donors have largely ignored funding NTD control projects. On average, only 0.6% of total annual health ODA was dedicated
to the fight against NTDs while the average share of control projects for HIV/AIDS was 36.3%, for malaria 3.6%, and for tuberculosis 2.2%. This allocation of health ODA does not reflect the diseases’ respective health burdens.
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This report analyses the intersection of HIV, COVID-19 and public debt in developing countries. The collision between COVID-19 and a crippling debt crisis have reversed decades of progress - putting present and future investments in health and HIV at risk. Pragmatic options to address the pandemic t...riad are proposed.
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The Creditor Reporting System was analysed for official development assistance funding disbursements towards TB control in 11 conflict-affectedstates, 17 non-conflict-affected fragile states and 38 comparable non-fragile states. The amounts of funding, funding relative to burden, funding relative to... malaria and human immunodeficiency virus (HIV) control, disbursements relative to commitments, sources of funding as well as funding activities were extracted and analysed.
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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 ...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... 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...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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Little is known about foreign aid provided by private donors. This paper contributes to closing this research gap by comparing the allocation of private humanitarian aid to that of official humanitarian aid awarded to 140 recipient countries over the 2000-2016 period. We construct a new database tha...t offers information on the country in which the headquarters of private donors are located to test whether private donors follow the aid allocation pattern of their home country. Our empirical results confirm that private aid “follows the flag.” This finding is robust against the inclusion of various fixed effects, estimating instrumental variables models, and disaggregating private aid into corporate aid and NGO aid. Donor country-specific estimations reveal that private aid from China, Sweden, the United Kingdom, and the United States “follow the flag.”
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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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Background: Mental health has recently gained increasing attention on global health and development agendas, including calls for an increase in international funding. Few studies have previously characterized official development assistance for mental health (DAMH) in a nuanced and differentiated ma...nner in order to support future funding efforts. Methods: Data from the Organisation for Economic Cooperation and Development Creditor Reporting System were obtained through keyword searches. Projects were manually reviewed and categorized into projects dedicated entirely to mental health and projects that mention mental health (as one of many aims). Analysis of donor, recipient, and sector characteristics within and between categories was undertaken cumulatively and yearly.
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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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