Time-lagged response of malaria transmission to climate and land use change in a Colombian Amazonian Municipality: Implications for Early Warning Systems and Control Strategies

Abstract

Malaria remains a significant public health problem worldwide, particularly in low-income regions with limited access to healthcare. Despite the use of antimalarial drugs, transmission remains an issue in Colombia, especially among indigenous populations in remote areas. In this study, we used an SIR Ross MacDonald model that considered land use changes, temperature, and precipitation to analyze eco epidemiological parameters and the impact of time lags on malaria transmission in La Pedrera - Amazonas municipality. We found changes in land use between 2007 and 2020, with increases in forested areas, urban infrastructure and water edges area resulting in a constant increase in mosquito carrying capacity. Temperature and precipitation variables exhibited a fluctuating pattern that corresponded to rainy and dry seasons, respectively and a marked influence of the El Niño climatic phenomenon. Our findings suggest that elevated precipitation and temperature increase malaria infection risk in the following two months influenced by the secondary vegetation and urban infrastructure near primary forest formation or water body edges. These results may be useful for public health officials and policymakers in developing effective malaria control strategies by monitoring precipitation, temperature, and land use variables to predict high-risk areas and periods, considering the time lag effect.

Malaria Risk Drivers in the Brazilian Amazon: Land Use—Land Cover Interactions and Biological Diversity

“…Despite interannual variations in precipitation and temperature, it could be possibly inadequate in influencing the risk of malaria at the regional scale. Instead, it is suggested that the occurrence of malaria cases is more likely influenced by intra-annual variations, which should be studied at a higher resolution by analyzing climatic variables on a monthly or two-month basis [61]. Furthermore, the differential sizes of municipalities, with some being considerably large, pose challenges in representing their climatic spatial variation with a single metric, consequently diminishing their significant impact on malaria risk.…”