Abstract

About three quarters of human emerging infectious diseases are caused by zoonotic pathogens, and many of them are spread by vectors such as mosquitoes. Mathematical models nowadays represent very powerful tools to make investigations and predictions for biological dynamical systems, providing helpful insights that can be extremely valuable for several aims. In this thesis, we will focus on a particular mosquito-borne zoonosis, West Nile virus (WNV), a flavivirus of emerging public health relevance in Europe and North America, and its main European vector, Culex pipiens mosquitoes. As the transmission of mosquito-borne diseases is largely driven by the abundance of the vector, to design appropriate control strategies it is crucial to understand the population dynamics of existing vector populations and evaluate how it depends on biotic and environmental factors. This thesis presents some new mathematical models that provide insights on several aspects of mosquito population dynamics by using different statistical and computational approaches, including for instance Linear Models and Markov chain Monte Carlo technique. Specifically, they aim to study the effect of biotic and abiotic factors on Cx. pipiens dynamics by using adult mosquito trapping data, gathered over several years in Northern Italy, to feed theoretical models. Furthermore, the effects of host competition and vector feeding preferences on the dynamics of a vector-borne infection (such as WNV) are investigated through a more theoretical study.