Analysis of the spatial distribution of road accidents attended by the Mobile Emergency Service (SAMU-192) in a municipality of northeastern Brazil

Cristine Viera do Bonfim; Aline Galdino Soares da Silva; Weinar Maria de Araújo; Carmela Alencar; Betise Mery Alencar Furtado

doi:10.18294/sc.2018.1211

Analysis of the spatial distribution of road accidents attended by the Mobile Emergency Service (SAMU-192) in a municipality of northeastern Brazil

Cristine Viera do Bonfim PhD in Public Health. Full researcher at Fundación Joaquim Nabuco. Professor, Programa de Pós-Graduação en Saúde Coletiva [Postgraduate Program in Collective Health], Universidade Federal de Pernambuco. Recife, Pernambuco, Brazil. , Aline Galdino Soares da Silva Graphic designer. Geoprocessing Nucleus, Secretaria de Saúde [Health Secretariat]. Olinda, Pernambuco, Brazil. , Weinar Maria de Araújo Nursing Student. Universidade de Pernambuco. Recife, Pernambuco, Brazil. , Carmela Alencar Master´s degree student. Professor, Fundação de Ensino Superior de Olinda. Recife, Pernambuco, Brazil. , Betise Mery Alencar Furtado PhD in Sciences. Associate Professor, Universidade de Pernambuco. Recife, Pernambuco, Brazil.

Received: 1 November 2016, Accepted: 1 June 2017, Published: 11 April 2018

https://doi.org/10.18294/sc.2018.1211

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Abstract

This study describes the epidemiological characteristics of road accident victims attended by the Brazilian Mobile Emergency Service (SAMU-192) and located in the areas of highest accident density in the municipality of Olinda, (Pernambuco, Brazil). Kernel density estimation was used to detect spatial agglomerations of accidents. In 2015, 724 accidents occurred; of these, 73.48% of the victims were males aged 20-39 years. There was a predominance of accidents involving motorcycles (54.97%). Accident clusters were detected in the main traffic corridors, with run-over accidents located near bus terminals. Spatial analysis proved to be a relevant instrument for the identification of accident clusters and the application of effective prevention and traffic safety improvement measures.

Keywords: Traffic, Accidents, Emergency Medical Services, Spatial Analysis, Brazil

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