Modeling the Consequences of Social Distancing Over Epidemics Spreading in Complex Social Networks: From Link Removal Analysis to SARS-CoV-2 Prevention - Bellingeri, M.; Turchetto, M.; Bevacqua, D.; Scotognella, F.; Alfieri, R.; Nguyen, Q.; Cassi, D. (Frontiers in Physics, 2021)
In this Perspective we describe how link removal (LR) analysis in social complex networks may be a promising tool to model Non-Pharmaceutical Interventions (NPIs) and social distancing to prevent epidemics spreading. First we show how the extent of the epidemic spreading and the NPIs effectiveness over complex social networks may be evaluated with a static indicator, i.e. the classic largest connected component (LCC). Then, we explain how coupling the LR analysis and type SIR epidemiological models (EM), provide further information by including the temporal dynamics of the epidemic spreading. This is a promising approach to investigate important aspects of the recent NPIs applied by government to contain SARS-CoV-2, such as modelling the effect of the social distancing severity and timing over different network topologies. Further, implementing different link removal strategies to halt epidemics spreading provides information to individuate more effective NPIs, representing an important tool to offer a rationale sustaining policies to prevent SARS-CoV-2 and others epidemic spreading.