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Exploring Dengue Dynamics: Multi-Scale Analysis of Spatio-Temporal Trends in Ibagué, Colombia
Version 1
: Received: 12 March 2024 / Approved: 13 March 2024 / Online: 13 March 2024 (16:05:49 CET)
A peer-reviewed article of this Preprint also exists.
Otero, J.; Tabares, A.; Santos-Vega, M. Exploring Dengue Dynamics: A Multi-Scale Analysis of Spatio-Temporal Trends in Ibagué, Colombia. Viruses 2024, 16, 906. Otero, J.; Tabares, A.; Santos-Vega, M. Exploring Dengue Dynamics: A Multi-Scale Analysis of Spatio-Temporal Trends in Ibagué, Colombia. Viruses 2024, 16, 906.
Abstract
Our study examines how dengue incidence is associated with spatial (demographic and socioeconomic) alongside temporal (environmental) factors at multiple scales. We used the incidence of dengue in Ibagué, Colombia, from 2013 to 2018, to examine the associations with climate, socioeconomic and demographic factors from the census and satellite imagery at various levels of local spatial aggregation, including Manzanas, Secciones, Sectores, and Comunas. Our findings show a significant effect of spatial variables at finer levels of aggregation, showing varying degrees of correlation with dengue incidence. Temporal variables such as temperature and precipitation displayed consistent patterns across all spatial levels, with notable variations in Relative Risk (RR). Our study employs Geographically Weighted Regression (GWR) to identify relevant socioeconomic and demographic predictors. Then, these predictors were integrated into hierarchical models implemented in Integrated Nested Laplace Approximation (INLA) at each spatial level to assess spatiotemporal interactions. We comprehensively analyzed the three distinct models developed for each level: spatial, temporal, and spatiotemporal. A comparative evaluation of the models reveals that while higher aggregation levels often yield a better overall model fit, finer levels offer more detailed insights into the localized impacts of socioeconomic and demographic variables on dengue incidence. Our results underscore the importance of considering macro and micro-level factors in epidemiological modeling and highlight the potential for targeted public health interventions based on localized risk factor analysis. Notably, the intermediate level Secciones emerged as the most informative, balancing spatial heterogeneity and case distribution density, thereby providing a robust framework for understanding the spatial determinants of dengue.
Keywords
Dengue incidence; Spatio-temporal Analysis; Geographically Weighted Regression; Integrated Nested Laplace Approximation (INLA); Spatial Aggregation Levels (Manzanas, Secciones, Sectores, Comunas)
Subject
Medicine and Pharmacology, Epidemiology and Infectious Diseases
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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