Development and application of mathematical and statistical methods to estimate risk of mosquito-borne diseases and effectiveness of control interventions

Vector-borne diseases represent one of greatest health problem worldwide, accounting for >17% of all infectious diseases. Anopheles, Aedes and Culex mosquitoes are the insects most involved in the transmission of vector-borne human diseases. Some species of genus Anopheles are responsible for the transmission of malaria parasite. Aedes and Culex are instead vectors of human (es. Yellow Fever, Dengue, Zika, Chikungunya) and zoonotic (e.g. West Nile, Japanese encephalitis) arboviruses, and of filarial nematodes. Mosquito-borne diseases are disproportionally transmitted in tropical regions. However, in the last years, they increase their relevance also in temperate regions, previously considered at low risk. This is due to global invasion of Asian Aedes invasive vectors of human arboviruses and to climatic conditions favouring the transmission of zoonotic arboviruses by native Culex species. The goal of medical entomology is to understand and define vector species bionomics under specific eco-climatic conditions in order to feed model useful to predict the patterns of pathogen’s transmission, and to develop effective prevention and control interventions and methods to assess their efficacy. The latter are particularly crucial in non-endemic countries where sporadic pathogen’s circulation require assessment based on entomological parameters. Collaboration between medical entomologists, mathematicians and statisticians is instrumental to progress towards these goal. In fact, mathematical and statistical models provide a simplified representation of a complex system, which involves a variety of underlying factors, interactions, heterogeneity, random variations and fluctuations that have an impact on the prediction. The overarching objective of this thesis was to apply my mathematical background to research questions in the field of medical entomology - with specific reference to mosquito and mosquitoborne diseases - and to complement it with advanced statistical approaches. Under the tutoring of the Medical Entomology group of the Department of Public Health and Infectious Disease of Sapienza University in Rome, I became familiar with the research field of vector ecology and vector-borne disease and acquired data from field studies in Italy and Africa, on which I based my analyses. Under the tutoring by the Applied Ecology at the Research and Innovation Centre of Fondazione Edmund Mach, I exploited my background in mathematical modelling and I learned and applied basic and advanced statistical techniques to model mosquito dynamics and mosquito-borne pathogen transmission. More in detail during the first part of my PhD I learned and applied inferential statistic techniques based on frequentist approach to analyse field data from to two studies on species of the An. gambiae complex from Afro-tropical malaria-endemic regions. Afterwards, I exploited my mathematical background to develop advanced mathematical tools based on Partial Differential Equations to estimate epidemiologically relevant parameters (population size, survival rate and dispersal) of Ae. albopictus in Italy from Mark-Release-Recapture data. Finally, I enriched my knowledge on statistical inference by studying and applying the Bayesian framework in order to evaluate the effectiveness of traditional and innovative mosquito control tools. Results are summarized in 3 chapters, each of which introduces the specific entomological/epidemiological topic(s) and briefly describes the scientific questions addressed, the experimental field designs, the analytical approaches applied (discussed in the framework of conventional analytical tools) and the results obtained. At the end of each chapter, the scientific articles related to each specific topic are provided, in order to include all details of the individual studies, for a total of 5 published papers, and manuscript in preparation.