Epidemic spreading and control strategies in spatial modular network
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Epidemic spreading and control strategies in spatial modular network Bnaya Gross* and Shlomo Havlin *Correspondence: [email protected] Department of Physics, Bar-Ilan University, 52900 Ramat‑Gan, Israel
Abstract Epidemic spread on networks is one of the most studied dynamics in network science and has important implications in real epidemic scenarios. Nonetheless, the dynamics of real epidemics and how it is affected by the underline structure of the infection channels are still not fully understood. Here we apply the susceptible-infected-recovered model and study analytically and numerically the epidemic spread on a recently developed spatial modular model imitating the structure of cities in a country. The model assumes that inside a city the infection channels connect many different locations, while the infection channels between cities are less and usually directly connect only a few nearest neighbor cities in a two-dimensional plane. We find that the model experience two epidemic transitions. The first lower threshold represents a local epidemic spread within a city but not to the entire country and the second higher threshold represents a global epidemic in the entire country. Based on our analytical solution we proposed several control strategies and how to optimize them. We also show that while control strategies can successfully control the disease, early actions are essentials to prevent the disease global spread. Keywords: Epidemic spreading, Control strategies, Spatial networks, Community networks, Modular networks
Introduction Network science is becoming one of the most fruitful research fields in the last decades explaining variety of phenomena in many complex systems such as the human brain (Moretti and Muñoz 2013; Sporns 2010) the human microbiome (Smillie et al. 2011; Gibson et al. 2016; Layeghifard et al. 2017), protein-protein interactions (Kovács et al. 2019; De Domenico et al. 2015; Li et al. 2017), climate (Yamasaki et al. 2008; Fan et al. 2017; Ludescher et al. 2014), ecology (Paine 1966; Polis and Strong 1996) and infrastructures (Yang et al. 2017; Latora and Marchiori 2005; Li et al. 2015). Modelling of these systems and many others opened a new direction of studying many complex structures such as modular (community) networks (Palla et al. 2005; Rosvall and Bergstrom 2008; Gross et al. 2020b; Capocci et al. 2005; Shekhtman et al. 2015; Girvan and Newman 2002), multiplex networks (Nicosia et al. 2013; Gomez et al. 2013; Granell et al. 2013; Bianconi 2013), interdependent networks (Wang et al. 2013; Buldyrev et al. 2010; Brummitt et al. 2012; Baxter et al. 2012; Gao et al. 2012; Radicchi and Arenas 2013) and high © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to th
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