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Trajectory Data Analyses for Pedestrian Space-time Activity Study

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Traffic accident in Cuiabá-MT: an analysis through the data mining technology.

Noemi Dreyer Galvão¹, Heimar de Fátima Marin

¹Federal University of Mato Grosso-UFMT, Technician of the Health State Secretariat of Mato Grosso-MT, Brazil. noemidgalvao.mt@terra.com.br

Studies in Health Technology and Informatics

|September 16, 2010

Summary

Traffic road accidents (ATT) significantly impact urban areas globally. This study analyzed ATT victim data in Cuiabá, Brazil, revealing key characteristics and highlighting the need for targeted male collision accident prevention.

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Area of Science:

Public Health
Data Science
Epidemiology

Background:

Traffic road accidents (ATT) represent a significant global public health concern, particularly in urban environments.
Understanding the characteristics of ATT victims is crucial for developing effective prevention strategies.

Purpose of the Study:

To analyze data on traffic road accident victims in Cuiabá-MT, Brazil, for the year 2006.
To apply data mining techniques to identify patterns and characteristics of ATT victims.

Main Methods:

An observational, retrospective, and exploratory study utilizing secondary data from the Justice Secretariat and Public Security (SEJUSP).
Data linkage performed using the probabilistic method with RecLink software.
Data mining applied with WEKA software and the Apriori algorithm to identify associative rules.

Main Results:

139 pairs of ATT victims were identified and analyzed.
Data mining generated 10 association rules, with six deemed useful for characterizing victims.
Findings revealed specific patterns among road traffic accident victims in Cuiabá.

Conclusions:

The study identified unique characteristics of road traffic accident victims in Cuiabá.
Results underscore the necessity for targeted prevention measures, especially for male victims involved in collision accidents.