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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
UNAIDS leads and inspires the world to achieve its shared vision of zero new HIV infections, zero discrimination and zero AIDS-related deaths. It unites the efforts of 11 UN Cosponsor organizations- UNHCR, UNICEF, WFP, UNDP,UNFPA, UNODC, UN Women, ILO, UNESCO, WHO and the World Bank- and a Secretari
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at.
more
There has been no systematic comparison of how the policy response to past infectious disease outbreaks and epidemics was funded. This study aims to collate and analyse funding for the Ebola epidemic and Zika outbreak between 2014 and 2019 in order to understand the shortcomings in funding reporting
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and suggest improvements. Methods: Data were collected via a literature review and analysis of financial reporting databases, including both amounts donated and received. Funding information from three financial databases was analysed: Institute of Health Metrics and Evaluation’s Development Assistance for Health database, the Georgetown Infectious Disease Atlas and the United Nations Financial Tracking Service. A systematic literature search strategy was devised and applied to seven databases: MEDLINE, EMBASE, HMIC, Global Health, Scopus, Web of Science and EconLit. Funding information was extracted from articles meeting the eligibility criteria and measures were taken to avoid double counting. Funding was collated, then amounts and purposes were compared within, and between, data sources.
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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.
more
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
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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.”
more
Unfortunately, current data available on SDG financing are not sufficient to quantify the distribution of financing for the SDGs.
AidData’s methodology for measuring financing to the SDGs attempts to fill this gap by analyzing development project documentation to estimate project-level contributi
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ons to the SDGs (and their associated targets). This methodology lets us see where development financing is targeted, allowing comparisons among SDG goals and individual SDG targets.
This methodology note describes two iterations of AidData’s methodology. The first, based on a crosswalk with existing aid reporting schemes, was employed for AidData’s 2017 flagship report Realizing Agenda 2030: Will donor dollars and country priorities align with global goals? and our brief Financing the SDGs in Colombia. The second iteration of the methodology employs a direct coding scheme, linking development projects directly to the SDGs through analysis and coding of project descriptions rather than through an intermediary classification system. This method was employed for our 2019 brief Financing the SDGs: Evidence in Four 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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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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Conformément aux recommandations de divers comités de l’Organisation mondiale de la Santé (OMS), le Bureau régional de l’OMS pour l’Afrique a mis en place trois initiatives phares afin de permettre aux États Membres de la Région africaine de se préparer aux urgences de santé publique,
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de les détecter et d’y riposter. Ces programmes sont le fruit de consultations approfondies avec plus de 30 Ministres africains, ainsi qu’avec des acteurs techniques, des partenaires à travers le continent et des institutions régionales telles que le Centre africain de contrôle et de prévention des maladies (CDC-Afrique), dont les contributions ont façonné les activités prioritaires. Le présent rapport est le quatrième rapport de synthèse trimestriel sur les progrès accomplis dans la mise en œuvre des initiatives phares.
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Le Ministère de la Santé Publique et de la Prévention en collaboration avec les partenaires techniques et financiers, a procédé à l’élaboration du Plan National de Développement Sanitaire quatrième de la Génération (PNDS4), couvrant la période 2022-2030. Ce PNDS4, contrairement aux PND
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S antérieurs couvre une période restante pour la mise en œuvre de la Politique Nationale de Santé 2016-2030. Le PNDS4 est le dernier segment du cycle de la planification stratégique de la mise en œuvre de la Politique Nationale de Santé (PSN) qui est alignée sur la vision du « Tchad que nous voulons » et l’atteinte des Objectifs de Développement Durable.
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Ending the epidemics of HIV, tuberculosis and malaria by 2030 is within reach, but not yet fully in our grasp.
With only 11 years left, we have no time to waste. We must step up the fight now.
The definition of Official Development Assistance (ODA) has for 40 years been the global standard for measuring donor efforts in supporting development co-operation objectives. It has provided the yardstick for documenting the volume and the terms of the concessional resources provided, assessing do
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nor performance against their aid pledges and enabling partner countries, civil society and others to hold donors to account. Yet for all its value, the ODA definition has always reflected a compromise between political expediency and statistical reality. It is based on interpretation and consensus and therefore allows for flexibility. It has evolved over the decades, while preserving the original concepts of a definition based on principal developmental motivation, official character and a degree of concessionality. While agreement on the ODA concept was a major achievement, discussion of the appropriateness of this measure has never ended. The paper documents the evolution of the ODA concept and proposes a possible new approach to measuring aid effort.
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Ebola disease and Marburg disease outbreaks continue to occur in Africa, with increased frequency. In addition to resulting in high mortality and morbidity, the outbreaks generate fear and mistrust about the response activities within the communities affected.
Infection prevention and control (IP
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C) is a key pillar in the outbreak response; adherence to IPC practices can prevent and control transmission of infections to health and care workers, patients and their family members.
During the 2014-2016 West African Ebola disease outbreak, there was an urgent need for rapid IPC guidance to help support ministries of health, health-care providers and non-governmental organizations (NGOs). In response, WHO produced several documents related to the outbreak based on expert opinion, including IPC-specific documents and documents on clinical management that also referenced key IPC principles and practices. Since that time, many practices in the field have become institutionalized.
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