We investigate the effects of modular and temporal connectivity patterns on epidemic spreading. To this end, we introduce and analytically characterise a model of time-varying networks with tunable modularity. Within this framework, we study the epidemic size of Susceptible-Infected-Recovered, SIR, models and the epidemic threshold of Susceptible-Infected-Susceptible, SIS, models. Interestingly, we find that while the presence of tightly connected clusters inhibits SIR processes, it speeds up SIS phenomena. In this case, we observe that modular structures induce a reduction of the threshold with respect to time-varying networks without communities. We confirm the theoretical results by means of extensive numerical simulations both on synthetic graphs as well as on a real modular and temporal network.
Epidemic spreading in modular time-varying networks / Nadini, Matthieu; Sun, Kaiyuan; Ubaldi, Enrico; Starnini, Michele; Rizzo, Alessandro; Perra, Nicola. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 8:1(2018), pp. 1-11. [10.1038/s41598-018-20908-x]
Epidemic spreading in modular time-varying networks
Rizzo, Alessandro;
2018
Abstract
We investigate the effects of modular and temporal connectivity patterns on epidemic spreading. To this end, we introduce and analytically characterise a model of time-varying networks with tunable modularity. Within this framework, we study the epidemic size of Susceptible-Infected-Recovered, SIR, models and the epidemic threshold of Susceptible-Infected-Susceptible, SIS, models. Interestingly, we find that while the presence of tightly connected clusters inhibits SIR processes, it speeds up SIS phenomena. In this case, we observe that modular structures induce a reduction of the threshold with respect to time-varying networks without communities. We confirm the theoretical results by means of extensive numerical simulations both on synthetic graphs as well as on a real modular and temporal network.File | Dimensione | Formato | |
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2018 SciRep Rizzo.pdf
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https://hdl.handle.net/11583/2701756