Modeling the epidemic dynamics of COVID-19: Agent-based approach including molecular dynamics simulation and SEIR type methods

Fatemeh Aghaei,Amir Lohrasebi

doi:10.1142/s1793962321500574

Abstract

In this study, we developed a SEIR model, including social interactions and individual human mobility in everyday activities. For this purpose, daily mobility of people was considered by using the molecular dynamic method and the virus spreading was modeled employing the ordinary SEIR scheme. Utilizing this model, the variation of population size, density, and health strategy as well as the effect of busy places such as malls, were considered. The results show that our flexible model is able to consider the effects of different parameters such as distance between peoples, local population density and health strategy in the outbreak.

Highlights

In this study we developed a SEIR model, including social interactions and individual human mobility in everyday activities
We believe that more realistic models than the ordinary existing ones such as the normal forms of SEIR family models are needed to describe the virus epidemic in detail, due to some noticeable features of COVID-19 outbreak affected by the public situations such as social culture, local medical resources, health strategies and individual activities
Materials and Method We model the epidemiology of COVID-19 outbreak employing an agent-based models (ABMs) based on combination of the molecular dynamic (MD) simulation method and the ordinary SEIR model

Summary

Introduction

In this study we developed a SEIR model, including social interactions and individual human mobility in everyday activities For this purpose, daily mobility of people was considered by using the molecular dynamic method and the virus spreading was modeled employing the ordinary SEIR scheme. We believe that employing this simple model, based on well-defined assumptions can provide a practical approach to overcome the two important features of COVID-19 mentioned above This scheme can be used to model other kinds of similar infectious disease, and comparable complex systems such as animal herd dynamics and communication in social networks, by utilizing the proper parameters

Objectives

Methods

Results

Conclusion