# Lagged effect of temperature and rainfall on malaria incidence in Colombia (2013–2023): An approach with Bayesian spatiotemporal adjustment

## TL;DR

The study finds that malaria risk in Colombia increases with higher temperatures and lower rainfall, with effects delayed by up to six weeks, aiding early warning systems.

## Contribution

The novel use of Bayesian spatiotemporal models reveals specific temperature and rainfall thresholds linked to malaria transmission in Colombia.

## Key findings

- Malaria risk peaks at 28°C temperature with minimum risk at 16.43°C, showing non-linear effects.
- Lower rainfall (0.85 mm) is associated with higher malaria risk, likely due to persistent mosquito breeding sites.
- Temperature effects on malaria incidence are significant within 0–6 weeks, indicating accelerated transmission dynamics.

## Abstract

Malaria remains a major public health challenge in Colombia, with a significant increase in cases in recent years. Climate variables—particularly temperature and rainfall—are key drivers of malaria transmission, yet their lagged, non-linear effects across space and time are poorly characterized in the Colombian context. We conducted an ecological, spatiotemporal analysis using weekly malaria case data from 970 municipalities in Colombia (2013–2023) combined with satellite-derived climate data. We applied distributed lag non-linear models (DLNMs) embedded within a Bayesian hierarchical framework using integrated nested Laplace approximation (INLA) to estimate the delayed, non-linear associations between weekly temperature and rainfall and malaria incidence, while accounting for spatial and temporal autocorrelation, forest cover, multidimensional poverty, altitude, population size, and prior case counts. Our results show that malaria risk increases non-linearly with temperature, peaking around 28 °C, with a global exposure of minimum risk (EMR) at 16.43 °C, and significant effects observed at lags of 0–6 weeks. In contrast, lower weekly rainfall was associated with higher malaria risk, with an EMR at 0.85 mm. Sensitivity analyses confirmed the robustness of these findings. These results challenge previous studies about climate-driven malaria risk and highlight accelerated transmission dynamics in Colombia’s endemic zones. The identification of specific climate thresholds linked to elevated malaria incidence provides actionable evidence for climate-informed early warning systems and targeted interventions to support malaria elimination efforts in Colombia.

Malaria continues to threaten public health in Colombia, where cases have surged dramatically in recent years. While climate is known to influence malaria transmission, the exact timing and shape of these effects—especially how temperature and rainfall affect disease risk with delay—remain unclear in this setting. Using 11 years of municipal-level health and climate data, we applied statistical models that account for both spatial patterns and time lags in climate effects. We found that malaria risk rises with higher temperatures, peaking near 28 °C, and that drier conditions are linked to greater transmission—likely because persistent small water bodies during low rainfall support mosquito breeding without being washed away by heavy rains. Significant temperature effects were concentrated within 0–6 weeks after exposure, indicating faster transmission cycles than previously observed in cooler regions. These insights can help public health authorities design more responsive surveillance and control strategies that anticipate outbreaks based on observed weather patterns, ultimately supporting Colombia’s malaria elimination goals.