Espinoza, SebastiánSebastiánEspinozaAnibal Enrique Vivaceta De la FuenteConstanza Andrea Machuca Contreras2025-12-072025-12-072016-09-1310.1017/dmp.2016.117https://cris-uv-2.scimago.es/handle/123456789/7319<jats:title>Abstract</jats:title><jats:sec id="S1935789316001178_abs1" sec-type="general"><jats:title>Objective</jats:title><jats:p>To describe and relate the main environmental risk factors in the emergency process after a large urban fire in Valparaiso, Chile, in April 2014.</jats:p></jats:sec><jats:sec id="S1935789316001178_abs2" sec-type="methods"><jats:title>Methods</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec id="S1935789316001178_abs3" sec-type="results"><jats:title>Results</jats:title><jats:p>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 (<jats:italic>P</jats:italic>value=0.00; model<jats:italic>P</jats:italic>value: 0.00; R<jats:sup>2</jats:sup>: 11.7%). The “garbage” category confirmed infrastructural damage (<jats:italic>P</jats:italic>value: 0.00), water (<jats:italic>P</jats:italic>value: 0.028), and vectors (P value: 0.00) as predictors (model<jats:italic>P</jats:italic>value: 0.00; R<jats:sup>2</jats:sup>: 23.09%).</jats:p></jats:sec><jats:sec id="S1935789316001178_abs4" sec-type="conclusions"><jats:title>Conclusions</jats:title><jats:p>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. (<jats:italic>Disaster Med Public Health Preparedness</jats:italic>. 2017;11:239–243)</jats:p></jats:sec>journal-article