Effects of climate variability on the spatio-temporal distribution of Dengue in Valle del Cauca, Colombia, from 2001 to 2019

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...

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Published in:PloS one 2024-10, Vol.19 (10), p.e0311607
Main Authors: Ortega-Lenis, Delia, Arango-Londoño, David, Hernández, Freddy, Moraga, Paula
Format: Article
Language:English
Subjects:
Bayes Theorem
Bayesian analysis
Binomial distribution
Biology and Life Sciences
Care and treatment
Climate
Climate Change
Climate effects
Climate variability
Colombia - epidemiology
Dengue
Dengue - epidemiology
Dengue - transmission
Dengue fever
Diagnosis
Disease transmission
Early warning systems
Earth Sciences
Ecology and Environmental Sciences
Economic factors
Eggs
Environmental aspects
Health aspects
Households
Humans
Humidity
Medicine and Health Sciences
Mosquitoes
Municipalities
People and places
Precipitation
Prevention
Public health
Relative humidity
Risk Factors
Socioeconomic factors
Socioeconomics
Spatial distribution
Spatio-Temporal Analysis
Temperature
Temporal distribution
Urban areas
Variability
Variables
Vector-borne diseases
Vectors (Biology)
Warning systems
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description 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.
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subjects Bayes Theorem
Bayesian analysis
Binomial distribution
Biology and Life Sciences
Care and treatment
Climate
Climate Change
Climate effects
Climate variability
Colombia - epidemiology
Dengue
Dengue - epidemiology
Dengue - transmission
Dengue fever
Diagnosis
Disease transmission
Early warning systems
Earth Sciences
Ecology and Environmental Sciences
Economic factors
Eggs
Environmental aspects
Health aspects
Households
Humans
Humidity
Medicine and Health Sciences
Mosquitoes
Municipalities
People and places
Precipitation
Prevention
Public health
Relative humidity
Risk Factors
Socioeconomic factors
Socioeconomics
Spatial distribution
Spatio-Temporal Analysis
Temperature
Temporal distribution
Urban areas
Variability
Variables
Vector-borne diseases
Vectors (Biology)
Warning systems
title Effects of climate variability on the spatio-temporal distribution of Dengue in Valle del Cauca, Colombia, from 2001 to 2019
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