Ongoing projects


Emergency Events Database (EM-DAT)

Duration January, 1999 to September, 2025

The Emergency Events Database (EM-DAT) is a free and fully searchable database that contains worldwide data on the occurrence and impact of over 20,000 natural and technological disasters from 1900 to the present dayEM-DAT provides an objective basis for vulnerability assessments and rational decision-making in disaster situations. More specifically, it helps policymakers identify the most common disaster types in a given country and the associated impacts on human populations.  

For more information, contact Regina Below or


Mortality estimates in complex emergencies

Duration October, 2022

Mortality is one of the major key indicators used in assessing the level of needs in conflict-affected areas. This helps to better target humanitarian aid to the most vulnerable population. Recently, the global humanitarian sector has shown a great interest in finding improved ways to produce robust estimates of mortality in countries severely affected by armed conflicts. The project aims to employ the use of Bayesian methods in understanding the evolution of mortality in crisis-affected by utilization of data from small-scale surveys.

This research will contribute towards improving the tools that health providers use, enhancing the understanding of mortality patterns and better targeting aid for the populations at risk.

For more information, contact Thomas Jideofor Ogbu 



DAMOCLES (Understanding and Modelling Compound Climate and Weather Events)

Funding European Cooperation in Science and Technology (COST)
Duration May, 2018 to September, 2022
DAMOCLES is a project funded by the European Cooperation in Science and Technology (COST). Compound Events are high-impact events whose causes or effects show a complex combination of factors and pose major challenges to risk assessment and management. Current climate and impact modelling efforts are very limited in their ability to model Compound Events, making it difficult to design appropriate adaptation strategies. DAMOCLES will (a) identify key process and variable combinations underpinning Compound Events; (b) describe the available statistical methods for modelling dependence in time, space, and between multiple variables; (c) identify data requirements needed to document, understand, and simulate Compound Events, and (d) propose an analysis framework to improve the assessment of Compound Events.

For more information, contact Joris van Loenhout

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