Analysis of Road Accidents in Colombia: Departmental Patterns and Trends from Vehicle Records - Mora Chacón, Karla Fernanda; Rosas López, Cristian David; Ulchur Ruíz, Mariana (Ingeniería, 2025)
Context: The high rate of road accidents in Colombia constitutes a serious public health issue. This study seeks to identify spatial patterns in the occurrence of traffic accidents at the departmental level. Based on these data, the aim is to better understand the factors that influence road accidents in order to propose more effective prevention strategies. Method: To this effect, a cluster analysis based on the K-means algorithm and binomial analysis was used. These statistical techniques allowed grouping Colombian departments according to their accident profile, considering variables such as geographical location, incidents, the validity of vehicle documents, and the presence of new road actors. Results: The results of the analysis revealed three groups of departments with different accident rates: high, medium, and low. This classification makes it possible to identify regions with a higher risk of suffering road accidents and determine their associated factors, such as population density and road conditions. This study demonstrates the usefulness of cluster analysis to identify spatial patterns in road accidents at the departmental level. Conclusions: The results obtained contribute to a better understanding of the factors that influence the occurrence of traffic accidents in Colombia, which enables the design of more focused and effective prevention strategies. Future research could delve into the analysis of the socioeconomic and cultural factors associated with road accidents, in addition to exploring the application of predictive models to anticipate the occurrence of accidents.