Geospatial and statistical modeling reveals infrastructure and municipal size drive disaster frequency across municipalities, highlighting exposure and urban resilience as critical targets for...
El Salvador’s geographic location, combined with socioeconomic inequalities and limited disaster risk reduction measures, renders it highly vulnerable to disasters. This study examines historical disaster occurrences at the national and municipal scale, leveraging data from the EM-DAT and DesInventar databases to explore disaster frequency, spatial distribution, and socioeconomic determinants. By analyzing both the previous 262 municipalities and the newly defined 46, the study offers a comprehensive assessment of disaster dynamics. Statistical and geospatial analyses identify road density, population size, and municipal area as the most significant predictors of disaster occurrences, whereas population density shows a negative correlation, suggesting improved urban resilience. Poisson regression and random forest models further validate these findings, underscoring the critical roles of exposure and infrastructure in shaping disaster vulnerability. Hydrometeorological disasters dominate the country records, accounting for over 40 percent of recorded events, with significant spatial disparities across municipalities. The study also highlights key risk factors, including unplanned urbanization and institutional weaknesses, while discussing future disaster risk reduction challenges such as climate adaptation and community resilience enhancement. The findings provide actionable insights for policymakers, offering a robust framework for developing targeted disaster risk reduction strategies to mitigate disaster impacts in El Salvador and similar conditions countries.
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Quesada-Román et al. (2026) studied this question.
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