Original Articles
4 June 2025
Vol. 20 No. 1 (2025)
Dengue risk-mapping in an Amazonian locality in Colombia based on regression and multi-criteria analysis
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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The potential of dengue infection is of prime public health concern in tropical and subtropical countries. In Colombia, the management of this disease is based mainly on epidemiological monitoring and vector control. This study, covering the period 2015-2022, adds to this approach by investigating a tool that identifies dengue risk zones considering its environmental and sociodemographic determinants. For this purpose, an analytical, comparative, ecological study was carried out in three stages: i) selection of indicators associated with the occurrence of dengue through hierarchical analysis; ii) execution of a spatial-based Ordinary Least Squares (OLS) regression technique; and iii) multi-criteria analysis of the risk data obtained. Consequently, two optimal models, one for the rainy season (R2=0.5761; AIC=366.3929) and the other for the dry season (R2=0.8560; AIC=440.7557) were obtained for the Dengue Incidence Rate (DIR) during the study period mainly based on socio-demographic and environmental variables. A dengue risk map was generated, showing the impact on three neighbourhoods in the municipality of Piamonte in the Cauca Department covering both seasons. In conclusion, the dengue risk map made it possible to identify highrisk areas and also to identify the determinants of disease occurrence, which can contribute to improving disease management in tropical and subtropical regions.
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Dengue risk-mapping in an Amazonian locality in Colombia based on regression and multi-criteria analysis. (2025). Geospatial Health, 20(1). https://doi.org/10.4081/gh.2025.1292
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