Modeling the Impact of Environmental and Immunity Heterogeneity on Infectious Disease Transmission Risk

Mathematical modeling represents an essential tool to analyze the transmission of infectious diseases, interpret epidemiological trends, monitor the disease circulation, and support public health decisions. This thesis presents a collection of modeling approaches applied to different infectious diseases – including COVID-19, respiratory syncytial virus (RSV), measles, chikungunya, dengue, and Zika - unravel to quantitatively assess how heterogeneities in population’s immunity and environmental conditions shape the individuals’ risk of infection. In the first chapter, a secondary data analysis on vaccine effectiveness (VE) against SARS-CoV-2 showed that VE against symptomatic disease and laboratory-confirmed infection with Omicron variant was lower than 20% at 6 months from last dose administration. The study presented in the second chapter quantified the immunity gap associated with the risk of RSV infection and severe disease led by COVID-19 restrictions in Lombardy, Italy. The proportion of the population susceptible to RSV infection at the start of the season was estimated to increase on average from 1.4% in 2018-2019 to 2.3% before the 2021-22 season, returning to 1.5% at the beginning of the following 2022–2023 season. The third chapter showed that the administration of the monoclonal antibody nirsevimab to 80% of infants can avert about 50% of RSV-associated hospitalizations in the overall population. In the fourth chapter, the analysis on measles epidemiology in Italy revealed that, as of 2023, about 9.4% of the Italian population was still susceptible to measles, and that measles transmissibility potential was consistent with the one estimated for national epidemics and local outbreaks occurred in the last decade. The fifth chapter presents a new framework to provide detailed spatiotemporal estimates of Aedes albopictus and Aedes aegypti absolute abundance and of the consequent risk of transmission of chikungunya, dengue, and Zika in Europe and the Americas. The sixth chapter focused on the analysis of the risk for arboviral infections in Italy as resulting from combining evidence based on entomological and human surveillance. Results suggested that while local dengue transmission may become more frequent, chikungunya outbreaks could be larger and more intense due to higher transmissibility and shorter generation time. The last chapter illustrates a new approach to robustly estimate the likelihood of experiencing a major outbreak of vector-borne diseases following the importation of cases major outbreak, considering the spatial heterogeneities in the human density and short-distance mobility patterns.