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

How Mobility and Sociality Reshape the Context: A Decade of Experience in Mobile CrowdSensing

“…Our opinion is that the quality of the data set, the demographic, the duration and the performed analysis are all factors that can contribute to limiting the inaccuracy of the predictability. A further step to support the prevention of COVID-19 disease consists of determining communities of users to analyse the spread of infection spread within a community over time, as suggested in [ 57 ]. Moreover, understanding the membership of humans to communities, the spatial scale of their human interactions, and how the network of human communities’ changes over time is a powerful tool to target interventions to at-risk areas without unnecessarily restricting areas at low risk of resurgence [ 58 ].…”

Global Experiences of Community Responses to COVID-19: A Systematic Literature Review

“…According to the definition of the WHO, community is “a group of individuals who live together in a specific geographical place, which maintains social relations among its members who recognize that they belong to such a community” ( 6 ). Thus, activities that require the community to cluster can facilitate the spread of the epidemic within the community and expose residents to the dangers of the pandemic ( 7 , 8 ). Group gathering and intimate contact are widespread due to often high population density in communities, providing a high possibility for the spread of the epidemic ( 9 ).…”