Authors
Mia E Martin, Juan A Insaurralde, Francisco F Ludueña-Almeida, Doriam Camacho-Rodríguez, Gabriel Parra-Henao, Alexander Salazar-Ceballos, Elizabet L Estallo
Published in
Science in One Health. Volume 5. Pages 100164. Epub Jun 06, 2026.
Abstract
Dengue fever is a major mosquito-borne disease whose transmission is influenced by climatic, environmental, and demographic factors. Colombia is a hyperendemic country, yet long-term local-scale studies remain limited. This study assessed the relationships between dengue incidence and environmental, climatic, and demographic predictors in Santa Marta, Colombia.
Weekly dengue case counts from 2009 to 2023 were analyzed using generalized linear mixed models with a negative binomial distribution. Epidemiological data were integrated with remotely sensed environmental variables, including vegetation indices (Normalized Difference Vegetation Index [NDVI] and Normalized Difference Water Index [NDWI]), daytime and nighttime Land Surface Temperature (LST), precipitation, and human population density. Lagged environmental effects (1-4 weeks) and biologically plausible interactions were evaluated.
A total of 9237 dengue cases were recorded during the study period. The best-fitting model identified significant positive associations between dengue incidence and NDVI (P < 0.001). Significant negative associations were observed for maximum daytime LST at a one-week lag (P < 0.001), minimum nighttime LST at a four-week lag (P < 0.001), NDWI at a one-week lag (P = 0.018), and precipitation at a four-week lag (P < 0.001). Population density significantly strengthened the positive effect of NDVI on dengue cases.
Dengue transmission in Santa Marta is shaped by complex and delayed interactions among environmental, climatic, and demographic factors. Vegetation cover increased dengue risk, particularly in densely populated areas, whereas excessive rainfall and high temperatures were associated with reduced incidence. These findings support the development of One Health-based surveillance and early-warning systems for dengue prevention.
PMID:
42382110
Bibliographic data and abstract were imported from PubMed on 01 Jul 2026.
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