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Assessing dengue fever risk in Costa Rica by using climate variables and machine learning techniques
Luis A Barboza1, Shu-Wei Chou-Chen2, Paola Vásquez3
1Centro de Investigación en Matemática Pura y Aplicada - Escuela de Matemática, Universidad de Costa Rica, San José, Costa Rica.
Plos Neglected Tropical Diseases
|January 13, 2023
Summary
Climate variables significantly impact dengue fever risk in Costa Rica. This study uses advanced modeling to forecast dengue outbreaks, aiding public health decision-making and resource allocation for better disease surveillance.
Area of Science:
- Environmental Science
- Epidemiology
- Public Health
Background:
- Dengue fever is a growing global health concern, particularly in tropical and subtropical regions.
- Climate change and socio-environmental factors are driving increased dengue incidence and geographic spread.
- Effective dengue outbreak prediction is crucial for public health planning and resource management.
Purpose of the Study:
- To investigate the influence of climate variables on dengue fever risk in Costa Rica.
- To develop predictive models for forecasting relative dengue risk across 32 key cantons.
- To provide actionable insights for public health authorities to enhance dengue surveillance and response.
Main Methods:
- Utilized Generalized Additive Models (GAM) and Random Forest (RF) approaches for risk forecasting.
- Employed a vector auto-regressive (VAR) model to predict climatic variables.
- Trained models on data from 2000 to 2020 for robust analysis.
Main Results:
- The study achieved reliable projections of relative dengue risk.
- Identified key climate variables influencing dengue transmission dynamics.
- Demonstrated the utility of predictive climate modeling for prospective dengue risk assessment.
Conclusions:
- Climate variables are significant predictors of dengue outbreaks in Costa Rica.
- Predictive modeling offers a valuable tool for proactive public health interventions.
- This research supports improved dengue surveillance and targeted resource allocation.
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