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

Area of Science:

• Epidemiology
• Environmental Health
• Spatial Analysis

Background:

• Dengue fever incidence is influenced by complex interactions between spatial and temporal factors.
• Understanding these determinants is crucial for effective public health strategies in endemic regions.

Purpose of the Study:

• To investigate the associations between dengue fever incidence and spatial (demographic, socioeconomic) and temporal (environmental) factors at multiple scales in Ibagué, Colombia.
• To identify key predictors and analyze spatio-temporal interactions for targeted interventions.

Main Methods:

• Utilized dengue incidence data (2013-2018) from Ibagué, Colombia.
• Employed geographically weighted regression (GWR) for spatial predictors and integrated nested Laplace approximation (INLA) for spatio-temporal modeling.
• Analyzed data at four levels of spatial aggregation, integrating census and satellite data.

Main Results:

• Significant spatial variables included population density, utility connections, demographics (women/children), and education levels.
• Lagged temporal variables showed higher temperatures and lower precipitation increased dengue risk.
• Intermediate spatial aggregation levels provided the most informative balance between spatial heterogeneity and case distribution.

Conclusions:

• Macro and micro-level factors are essential for accurate epidemiological modeling of dengue fever.
• Localized risk factor analysis can inform targeted public health interventions.
• Intermediate spatial scales are most effective for understanding dengue's spatial determinants.