A rising number and variety of hazards has threatened local communities, possibly leading to disasters that are cause of important (human and economic) losses across regions and countries. As a consequence, both preparedness and management of hazard risk emerged as relevant issues in advanced economies. The present study proposes an original framework to estimate the number of future disasters in Greece using the Emergency Database (EM-DAT) as primary data. This information is vital to adopt precaution measures and design official plans for the protection of resident population. For this purpose, a logistic model based on Verhulst equations was tested here – using multinomial and exponential models as computational alternatives – on a complete database considering disasters occurred in Greece between 1904 and 2020. The outcomes of all models have documented the increasing frequency of all kinds of disasters over time. Predictions covering a time horizon that includes the 2020 s estimated the occurrence of 1 to 9 disasters per year as a whole (1 to 6 events per year for natural disasters and 1 to 3 events per year for technological disasters). These findings justify the urgent need of effective policies improving preparedness of local communities.

Predicting the occurrence of natural and technological disasters in Greece through Verhulst, multinomial and exponential models / Mavrakis, Anastasios; Lykoudis, Spyridon; Salvati, Luca. - In: SAFETY SCIENCE. - ISSN 0925-7535. - 166(2023).

Predicting the occurrence of natural and technological disasters in Greece through Verhulst, multinomial and exponential models

Luca Salvati
2023

Abstract

A rising number and variety of hazards has threatened local communities, possibly leading to disasters that are cause of important (human and economic) losses across regions and countries. As a consequence, both preparedness and management of hazard risk emerged as relevant issues in advanced economies. The present study proposes an original framework to estimate the number of future disasters in Greece using the Emergency Database (EM-DAT) as primary data. This information is vital to adopt precaution measures and design official plans for the protection of resident population. For this purpose, a logistic model based on Verhulst equations was tested here – using multinomial and exponential models as computational alternatives – on a complete database considering disasters occurred in Greece between 1904 and 2020. The outcomes of all models have documented the increasing frequency of all kinds of disasters over time. Predictions covering a time horizon that includes the 2020 s estimated the occurrence of 1 to 9 disasters per year as a whole (1 to 6 events per year for natural disasters and 1 to 3 events per year for technological disasters). These findings justify the urgent need of effective policies improving preparedness of local communities.
2023
disaster forecast; frequency; intensity; preparedness; Mediterranean; Europe
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Predicting the occurrence of natural and technological disasters in Greece through Verhulst, multinomial and exponential models / Mavrakis, Anastasios; Lykoudis, Spyridon; Salvati, Luca. - In: SAFETY SCIENCE. - ISSN 0925-7535. - 166(2023).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1693968
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