Containing COVID-19 Pandemic using Community Detection

Abstract Diseases such as COVID-19 that quickly spread through social contact where Infections remain undetected for long pose new kinds of challenges. Traditional epidemic models when applied to not only give highly alarmist predictions but also fail indicate any way target interventions. The do factor structure/context/dynamics.. To address this challenge we propose a novel Social Infection Analysis Model explain the intuition behind it and methodology factors structure while performing analysis. SIAM is particularly beneficial standard are dependent on wide-spread testing. Our includes (i) modelling society/localities using network paradigm analysis at macro level (ii) detecting communities (iii) infection within community over time. arrive an outlook make use NK solving complex, term problems coupled with agent based modeling member behavior. We NetLogo run simulations. intend validate our research in Indian context.