Background: Aedes albopictus, the Asian tiger mosquito, has become a prevalent pest in Italy, causing severe nuisance and posing a threat of transmission of arboviruses introduced by infected travelers. In this study, we investigated the influence of weather parameters on the seasonal population density of Aedes albopictus.
Methods: A Bayesian approach was employed to identify the best meteorological predictors of species trend, using the eggs collected monthly from 2010 to 2022 by the Emilia-Romagna regional monitoring network.
Results: The findings show that the winter-spring period (January to May) plays a crucial role in the size of the first generation and seasonal development of the species.
Conclusions: A temperate winter and a dry and cold March, followed by a rainy and hot spring and a rainy July, seem to favor the seasonal development of Ae. albopictus.
Keywords: Aedes albopictus; Bayesian model; MCMC; ovitraps; predictive models.