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Valparaiso’s 2014 Fire: Evaluation of Environmental and Epidemiological Risk Factors During the Emergency Through a Crowdsourcing Tool

Published online by Cambridge University Press:  13 September 2016

Sebastián Eduardo Espinoza Espinoza*
Affiliation:
School of Dentistry, Public Health Department, Universidad de Valparaíso, Valparaíso, Chile
Anibal Enrique Vivaceta De la Fuente
Affiliation:
School of Medicine, Public Health Department, Universidad de Valparaíso, Valparaíso, Chile.
Constanza Andrea Machuca Contreras
Affiliation:
School of Dentistry, Public Health Department, Universidad de Valparaíso, Valparaíso, Chile
*
Correspondence and reprint requests to Sebastián Espinoza E, #211, Subida Carvallo, Valparaíso, Chile (e-mail: [email protected]).

Abstract

Objective

To describe and relate the main environmental risk factors in the emergency process after a large urban fire in Valparaiso, Chile, in April 2014.

Methods

An observational, cross-sectional descriptive study was performed. All 243 reports from an ad hoc web/mobile website created on the Ushahidi/Crowdmap platform were reviewed. Reports were recorded in a new database with dichotomist variables based on either the presence or absence of the relevant category in each report.

Results

Almost one-third of the reports presented data about garbage (30%) and chemical toilets (29%). Reports related to water, infrastructural damage, and garbage had significant associations with 4 categories by chi-square test. In the logistic regression model for chemical toilets, only the variable of water was significant (P value=0.00; model P value: 0.00; R2: 11.7%). The “garbage” category confirmed infrastructural damage (P value: 0.00), water (P value: 0.028), and vectors (P value: 0.00) as predictors (model P value: 0.00; R2: 23.09%).

Conclusions

Statistically significant evidence was found for the statistical dependence of 7 out of 10 studied variables. The most frequent environmental risk factors in the reports were garbage, chemical toilets, and donation centers. The highest correlation found was for damaged infrastructure, vectors, and garbage. (Disaster Med Public Health Preparedness. 2017;11:239–243)

Type
Original Research
Copyright
Copyright © Society for Disaster Medicine and Public Health, Inc. 2016 

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