Dengue is a vector-borne disease that is endemic to several countries, including the Dominican Republic, which has experienced dengue outbreaks for over four decades. With outbreaks
growing in incidence in recent years, it is becoming increasingly important to develop better tools to
understand drivers of dengue transmission. Such tools are critical for providing timely information
to assist healthcare authorities in preparing human, material, and medical resources for outbreaks.
Here, we investigate associations between meteorological variables and dengue transmission in the
Dominican Republic in 2019, the year in which the country’s largest outbreak to date ocurred. We
apply generalized linear mixed modelling with gamma family and log link to model the weekly
dengue incidence rate. Because correlations in lags between climate variables and dengue cases
exhibited different behaviour among provinces, a backward-type selection method was executed to
find a final model with lags in the explanatory variables. We find that in the best models, meteorological conditions such as temperature and rainfall have an impact with a delay of 2–5 weeks in the
development of an outbreak, ensuring breeding conditions for mosquitoes.publishe
