An interaction-oriented multi-agent SIR model to assess the spread of SARS-CoV-2


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Altun K., ALTUNTAŞ S. , Dereli T.

HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, vol.50, no.5, pp.1548-1559, 2021 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 50 Issue: 5
  • Publication Date: 2021
  • Doi Number: 10.15672/hujms.751734
  • Journal Name: HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
  • Journal Indexes: Science Citation Index Expanded, Scopus, zbMATH
  • Page Numbers: pp.1548-1559
  • Keywords: SARS-CoV-2 (COVID-19), agent-based simulation, multi-agent SIR model, COMPUTATION

Abstract

It is important to recognize that the dynamics of each country are different. Therefore, the SARS-CoV-2 (COVID-19) pandemic necessitates each country to act locally, but keep thinking globally. Governments have a responsibility to manage their limited resources optimally while struggling with this pandemic. Managing the trade-offs regarding these dynamics requires some sophisticated models. "Agent-based simulation" is a powerful tool to create such kind of models. Correspondingly, this study addresses the spread of COVID-19 employing an interaction-oriented multi-agent SIR (Susceptible Infected-Recovered) model. This model is based on the scale-free networks (incorporating 10,000 nodes) and it runs some experimental scenarios to analyze the main effects and the interactions of "average-node-degree", "initial-outbreak-size", "spread-chance", "recovery-chance", and "gain-resistance" factors on "average-duration (of the pandemic last)", "average-percentage of infected", "maximum-percentage of infected", and "the expected peak-time". Obtained results from this work can assist determining the correct tactical responses of partial lockdown.