What does this research mean for the field?

In El Salvador, road density, population size, and municipal area are the most significant positive predictors of disaster occurrences, whereas population density is negatively correlated, highlighting the critical role of exposure and infrastructure in shaping disaster vulnerability. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To examine historical disaster frequency, spatial patterns, and socioeconomic determinants at the national and municipal levels.

September 14, 2026Papers in Applied Geography

Socioeconomic drivers and historical patterns of disasters at the municipal scale in El Salvador

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Authors

AQAdolfo Quesada-Román APArmando Picado-Monge MHMiguel Hernández

Discussion

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Overview

Geospatial and statistical modeling reveals infrastructure and municipal size drive disaster frequency across municipalities, highlighting exposure and urban resilience as critical targets for...

Key Points

To examine historical disaster frequency, spatial patterns, and socioeconomic determinants at the national and municipal levels.
Extracted historical disaster occurrence data from the EM-DAT and DesInventar databases spanning 262 legacy and 46 newly organized municipalities in El Salvador.
Conducted geospatial evaluations alongside Poisson regression and random forest machine learning models to identify key infrastructural and demographic predictors of risk.
Hydrometeorological events constitute the majority of disaster occurrences, accounting for over 40% of all recorded events.
Road density, total population, and municipal land area demonstrate the strongest positive associations with disaster frequency, whereas higher population density correlates negatively.

Cite This Study

Quesada-Román et al. (2026) studied this question.

synapsesocial.com/papers/6aa7b3850926e14a848b2986 https://doi.org/10.1080/23754931.2026.2725606

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September 14, 2026Papers in Applied Geography

Socioeconomic drivers and historical patterns of disasters at the municipal scale in El Salvador

View Full Paper

Ask AI

Bookmark

Authors

AQAdolfo Quesada-Román APArmando Picado-Monge MHMiguel Hernández

Discussion

Member takes

Overview

Geospatial and statistical modeling reveals infrastructure and municipal size drive disaster frequency across municipalities, highlighting exposure and urban resilience as critical targets for...

Key Points

To examine historical disaster frequency, spatial patterns, and socioeconomic determinants at the national and municipal levels.
Extracted historical disaster occurrence data from the EM-DAT and DesInventar databases spanning 262 legacy and 46 newly organized municipalities in El Salvador.
Conducted geospatial evaluations alongside Poisson regression and random forest machine learning models to identify key infrastructural and demographic predictors of risk.
Hydrometeorological events constitute the majority of disaster occurrences, accounting for over 40% of all recorded events.
Road density, total population, and municipal land area demonstrate the strongest positive associations with disaster frequency, whereas higher population density correlates negatively.

Cite This Study

Quesada-Román et al. (2026) studied this question.

synapsesocial.com/papers/6aa7b3850926e14a848b2986 https://doi.org/10.1080/23754931.2026.2725606

View Full Paper

Ask AI

Bookmark