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High-resolution climate-dengue modeling and mid-century projections under SSP5-8.5 in Costa Rica
Hugo G Hidalgo1, Eric J Alfaro2, Fabio Sanchez3
1School of Physics, Center for Geophysical Research and Center for Research in Pure and Applied Science, University of Costa Rica, San Pedro, San José, 11501-2060, Costa Rica.
Science in One Health
|June 3, 2026
Summary
Climate change will increase dengue cases in Costa Rica, with temperature and precipitation as key predictors. Projections show up to 42 additional cases per district by mid-century, informing adaptive health policies.
Area of Science:
- Environmental science
- Epidemiology
- Climate modeling
Background:
- Climate change is expanding dengue transmission globally.
- High-resolution, district-level climate-dengue assessments are needed in Costa Rica due to complex topography.
- Global climate models often miss local conditions crucial for dengue outbreak prediction.
Purpose of the Study:
- To model the climate-dengue relationship at Costa Rica's district level using high-resolution data.
- To identify the most significant climate predictors for dengue incidence.
- To project mid-century dengue cases under a pessimistic climate scenario (SSP5-8.5).
Main Methods:
- Used precipitation (CHIRPs) and temperature (CHIRTs) data with dengue diagnoses from public health centers.
- Employed a linear model and an objective algorithm with cross-validation to select climate predictors.
- Combined quasi-optimal models with downscaled General Circulation Model (GCM) projections for district-level future incidence.
Main Results:
- Temperature and precipitation significantly correlate with dengue counts.
- Temperature is the primary predictor during the dry season (December-June), precipitation during the rainy season (July-October).
- Mid-century projections indicate potential increases of up to 42 dengue cases per district, varying by month and location.
Conclusions:
- Projected dengue increases are driven by climate change under the SSP5-8.5 scenario, representing a potential upper bound of risk.
- Findings provide actionable guidance on high-risk areas and timeframes for dengue incidence.
- Results should inform adaptive health policies to mitigate climate change impacts on dengue transmission.
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