Modelling Singapore COVID-19 pandemic with a SEIR multiplex network model

Abstract

Abstract In this paper, we have implemented a large-scale agent-based model to study the outbreak of coronavirus infectious diseases (COVID-19) in Singapore, taking into account complex human interaction pattern. In particular, the concept of multiplex network is utilized to differentiate between social interactions that happen in households and workplaces. In addition, weak interactions among crowds, transient interactions within social gatherings, and dense human contact between foreign workers in dormitories are also taken into consideration. Such a categorization in terms of a multiplex of social network connections together with the Susceptible-Exposed-Infectious-Removed (SEIR) epidemic model have enabled a more precise study of the feasibility and efficacy of control measures such as social distancing, work from home, and lockdown, at different moments and stages of the pandemics. Using this model, we study an epidemic outbreak that occurs within densely populated residential areas in Singapore. Our simulations show that residents in densely populated areas could be infected easily, even though they constitute a very small fraction of the whole population. Once infection begins in these areas, disease spreading is uncontrollable if appropriate control measures are not implemented.