Challenges with Disaster Mortality Data and Measuring Progress Towards the Implementation of the Sendai Framework

Abstract

Disasters exact a heavy toll globally. However, the degree to which we can accurately quantify their impact, in particular mortality, remains challenging. It is critical to ensure that disaster data reliably reflects the scale, type, and distribution of disaster impacts given the role of data in: (1) risk assessments; (2) developing disaster risk management programs; (3) determining the resources for response to emergencies; (4) the types of action undertaken in planning for prevention and preparedness; and (5) identifying research gaps. The Sendai Framework for Disaster Risk Reduction 2015–2030s seven global disaster-impact reduction targets represent the first international attempt to systematically measure the effectiveness of disaster-impact reduction as a means of better informing policy with evidence. Target A of the Sendai Framework aims to “substantially reduce global disaster mortality by 2030, aiming to lower the average per 100,000 global mortality rate in the decade 2020–2030 compared to the period 2005–2015.” This article provides an overview of the complexities associated with defining, reporting, and interpreting disaster mortality data used for gauging success in meeting Target A, acknowledging different challenges for different types of hazard events and subsequent disasters. It concludes with suggestions of how to address these challenges to inform the public health utility of monitoring through the Sendai Framework.

Keywords

Data / Disaster mortality / Disaster risk management / Disaster risk reduction / Mass casualty / Sendai Framework

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