Large-scale emergencies, risks of social and biomedical consequences in the leading countries and globally (2012—2021)

Relevance: Large-scale emergencies (LSE) cause critical disruption in routine activities, while the elimination requires profound redeployment of workforce and resources.

The objective is to analyse the dynamics and risks of large-scale emergencies, as well as their social and biomedical consequences in a few individual countries and globally over the past 10 years (2012-2021).

Methods: The study is based on global large-scale emergency indicators as reported in the Emergency Events Database (EM-DAT: OFDA/CRED) [https://www.emdat.be/]. All emergencies are split in two generalized groups - natural (natural disasters) and man-made. Risks of social and biomedical consequences of emergencies were calculated for 1 million people (10^-6). Medians, upper and lower quartiles for LSE indicators and their consequences (Me [q₂₅; q₇₅]) are specified. The data is dynamically presented as a set of polynomial trends of the 2^nd order.

Results and discussion. According to EM-DAT, 5533 large-scale emergencies were recorded worldwide in 2012-2021, including 3807 (67.2%) natural and 1814 (32.8%) man-made events. It turned out that the global risks of exposure to emergencies, death, injury (illness) and homelessness were higher in natural emergencies than in man-made ones. The origin of large-scale natural emergencies was as follows: geophysical - 301 (7.9 %), meteorological - 1238 (32.5 %), climatological -272 (7.1 %), hydrological - 1780 (46.9 %) and biological - 215 (5.6 %). Most of the victims were observed during hydrological emergencies, median - 34.8 million people or 0.45 % of the world's population. The most serious bio-medical consequences were observed in meteorological emergencies (risk of death 0.55 • 10^-6, risk of injury or illness 2.38 • 10^-6), social consequences were most serious in case of hydrological and meteorological emergencies (risk of homelessness 35,8 • 10^-6 and 16.1 • 10^-6 respectively), economic consequences were most serious in climatological and meteorological emergencies (average economic loss of 1 large scale emergency makes 1 billion 727 million and 1 billion 600 million USA dollars respectively). Large-scale man-made emergencies included 225 industry-related (13.1%), 1206 transport (70%) and 291 domestic (16.9 %) events. The most serious bio-medical consequences were observed in transport emergencies (risk of death 0.54 • 10^-6, risk of injury or illness 0.25 • 10^-6), social consequences were most serious in domestic emergencies (risk of homelessness 1.12 • 10^-6). All large-scale emergencies included 648 (11.7 %) reported for Europe, 2281 (41.2 %) for Asia, 1167 (21.1 %) for the Americas, 1279 (23.1 %) for Africa and 158 (2.1 %) for Australia. As a rule, risks of biomedical and social consequences of large-scale emergencies in leading countries under consideration (China, Germany, India, Japan and the USA) were lower than global risks. Information on domestic large-scale emergencies obtained by Russian experts and EM-DAT staff requires further synchronisation.

Conclusion: The calculated indicators can be used to determine the need to develop measures to prevent emergencies or minimize their consequences regionally and globally.

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