Abstract
Dengue is a vector-borne disease that has increased over the past two decades, becoming a global public health emergency. The transmission of dengue is contingent upon various factors, among which climate variability plays a significant role. However, there remains substantial uncertainty regarding the underlying mechanisms. This study aims to investigate the spatial and temporal patterns of dengue risk and to quantify the associated risk factors in Valle del Cauca, Colombia, from 2001 to 2019. To achieve this, a spatio-temporal Bayesian hierarchical model was developed, integrating delayed and non-linear effects of climate variables, socio-economic factors, along with spatio-temporal random effects to account for unexplained variability. The results indicate that average temperature is positively associated with dengue risk 0-2 months later, showing a 35% increase in the risk. Similarly, high precipitation levels lead to increased risk approximately 2-3 months later, while relative humidity showed a constant risk within a 6 months-lag. These findings could be valuable for local health authorities interested in developing early warning systems to predict future risks in advance.
Original language | English (US) |
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Article number | e0311607 |
Journal | PloS one |
Volume | 19 |
Issue number | 10 October |
DOIs | |
State | Published - Oct 2024 |
Bibliographical note
Publisher Copyright:© 2024 Ortega-Lenis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
ASJC Scopus subject areas
- General