AbstractObjectives Arboviral diseases—including dengue, Zika, and chikungunya—cause an estimated 100–400 million infections annually. This study modeled associations between mosquito larval density, human arboviral cases, and climatic factors (temperature and precipitation) in Aruba (2019–2020) using routine surveillance data. Methods Multiple linear regression examined relationships between the monthly Breteau Index (BI) and climatic variables. Monthly arboviral case counts were analyzed using a negative binomial generalized linear model including BI and climatic predictors. Models incorporated lag structures and interaction terms. Results Monthly BI was positively associated with precipitation days (β = 1.33, 95% confidence interval CI: 1.105–1.595, P = 0.007). Arboviral case counts were positively associated with BI (incidence rate ratio=1.41, 95% CI: 1.03–1.94, P = 0.03) and negatively associated with the number of precipitation days at a three-month lag (incidence rate ratio=0.86, 95% CI: 0.77–0.97, P = 0.02). Thus, higher BI values corresponded to a 41% increase in arboviral case occurrence, while precipitation occurring three months earlier was associated with a 14% decrease in case numbers. Conclusion Despite limitations, including overdispersion and data constraints, the BI—interpreted alongside precipitation lags—may support early-warning surveillance for arboviral transmission in Aruba using a One Health framework. Future work should address entomological surveillance gaps, apply spatial risk analyses, explore threshold values, and integrate socio-environmental determinants using a One Health approach.
Melchers et al. (Sat,) studied this question.