Cristiano Marinelli
Interplay of Health Interventions in Time-Varying contact Networks.
Rel. Luca Dall'Asta, Nicolò Gozzi. Politecnico di Torino, Corso di laurea magistrale in Physics Of Complex Systems (Fisica Dei Sistemi Complessi), 2024
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Abstract
Throughout history, humanity has recurrently faced epidemics of infectious diseases, which have spread both within and between populations. From ancient pandemics like the Antonine Plague to the contemporary COVID-19 pandemic, understanding and controlling the spread of diseases has always been crucial. Mathematical modeling of epidemics plays a key role in this understanding. Over the years, epidemic modeling has evolved, incorporating interdisciplinary elements, particularly from network science. Health interventions, including non-pharmaceutical measures and pharmaceutical solutions like vaccines, have historically been crucial in mitigating disease spread. During the COVID-19 pandemic, for example, measures such as social distancing, lockdowns, mask usage, hygiene, and vaccinations were key in controlling the virus spread.
This thesis proposes a mathematical framework to model three distinct health interventions—social distancing, mask usage, and vaccination—on activity-driven networks (ADN), a mathematical framework that models the dynamic nature of individual contacts and the heterogeneity in sociability
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