Exploring Dengue Dynamics: A Multi-Scale Analysis of Spatio-Temporal Trends in Ibagué, Colombia.

dengue geographically weighted regression integrated nested Laplace approximation spatial aggregation levels spatio-temporal analysis

Journal

Viruses
ISSN: 1999-4915
Titre abrégé: Viruses
Pays: Switzerland
ID NLM: 101509722

Informations de publication

Date de publication:
03 Jun 2024
Historique:
received: 09 03 2024
revised: 23 04 2024
accepted: 23 04 2024
medline: 27 6 2024
pubmed: 27 6 2024
entrez: 27 6 2024
Statut: epublish

Résumé

Our study examines how dengue fever incidence is associated with spatial (demographic and socioeconomic) alongside temporal (environmental) factors at multiple scales in the city of Ibagué, located in the Andean region of Colombia. We used the dengue incidence in Ibagué from 2013 to 2018 to examine the associations with climate, socioeconomic, and demographic factors from the national census and satellite imagery at four levels of local spatial aggregation. We used geographically weighted regression (GWR) to identify the relevant socioeconomic and demographic predictors, and we then integrated them with environmental variables into hierarchical models using integrated nested Laplace approximation (INLA) to analyze the spatio-temporal interactions. Our findings show a significant effect of spatial variables across the different levels of aggregation, including human population density, gas and sewage connection, percentage of woman and children, and percentage of population with a higher education degree. Lagged temporal variables displayed consistent patterns across all levels of spatial aggregation, with higher temperatures and lower precipitation at short lags showing an increase in the relative risk (RR). A comparative evaluation of the models at different levels of aggregation revealed 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 they highlight the potential for targeted public health interventions based on localized risk factor analyses. Notably, the intermediate levels emerged as the most informative, thereby balancing spatial heterogeneity and case distribution density, as well as providing a robust framework for understanding the spatial determinants of dengue.

Identifiants

pubmed: 38932198
pii: v16060906
doi: 10.3390/v16060906
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Julian Otero (J)

Centro Para los Objetivos de Desarrollo Sostenible, Universidad de Los Andes, Bogotá 111711, Colombia.
Grupo Biología Matemática y Computacional (BIOMAC), Universidad de Los Andes, Bogotá 111711, Colombia.

Alejandra Tabares (A)

Departamento de Ingeniería Industrial, Universidad de los Andes, Bogotá 111711, Colombia.

Mauricio Santos-Vega (M)

Grupo Biología Matemática y Computacional (BIOMAC), Universidad de Los Andes, Bogotá 111711, Colombia.
Departamento de Ciencias Biológicas, Universidad de Los Andes, Bogotá 111711, Colombia.

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Classifications MeSH