The report covers: drivers of humanitarian crises in the region, particularly the intensification of violence in the DRC; manifestations of humanitarian needs, including record levels of displacement and food insecurity; and constraints to meeting humanitarian needs, including obstacles to humanitar
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ian access and inadequate funding
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In the post-colonial history of the Central African Republic, violence has often been the shortest way to presidential power. President Bozizé presented little deviation from this narrative after coming to power after a coup d’état in 2003. Whilst he faced armed opposition and a conflict-affecte
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d northwest from the outset, it is not until the rise of the Séléka, that the CAR entered into an era of unprecedented violence.
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The COVID-19 pandemic is a multiplier of vulnerability, compounding threats to food insecurity, while exposing weaknesses in food and health systems. It is severely undermining the capacity of communities to cope in times of crisis and has become a stress test for political and economic stability.
Six months in, the indirect impacts of COVID-19 take a toll on health, social and economic outcomes.
With about 24 million of Yemen’s 30 million people in need of some form of assistance, the United Nations calls Yemen the world’s worst humanitarian crisis. Cholera and other disease outbreaks are common, malnutrition is widespread, water is scarce, and the healthcare system is crumbling, with o
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nly half of the country’s 5,000 or so health facilities fully operational and with massive medical supply and staff shortages. In August 2020, the UN warned the country was again on the brink of full-scale famine.
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The well-being of children in sub-Saharan Africa is under siege from all directions since the advent of the COVID-19 pandemic. The region is now suffering its first-ever economic recession, pushing about 50 million people into extreme poverty, a majority of whom are children.
Joint EUAA, IOM and OECD report provides new insights on displacement from and within Ukraine
The European Union Agency for Asylum (EUAA), the International Organization for Migration (IOM) and the Organisation for Economic Co-operation and Development (OECD) have published a Joint Report on profil
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es, experiences, and aspirations of forcibly displaced people by the Russian invasion of Ukraine.
The Joint Report provides an in-depth study of the scale of displacement to EU countries and people seeking protection there, by building on initial findings derived from a June EUAA-OECD Survey.
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In our fourth year of producing The State of Open Humanitarian Data, we can report the highest levels yet for data availability across priority humanitarian operations. These gains can be attributed to the commitment of organizations to sharing and maintaining their data publicly. There was also str
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ong demand for data about the world's largest humanitarian crises, from the war in Ukraine to drought and food insecurity in the Horn of Africa.
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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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