An interaction-oriented multi-agent SIR model to assess the spread of SARS-CoV-2
HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, vol.50, no.5, pp.1548-1559, 2021 (SCI-Expanded, Scopus, TRDizin)
- 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 (SCI-EXPANDED), Scopus, zbMATH, TR DİZİN (ULAKBİM)
- Page Numbers: pp.1548-1559
- Keywords: SARS-CoV-2 (COVID-19), agent-based simulation, multi-agent SIR model, COMPUTATION
- Open Archive Collection: AVESIS Open Access Collection
- Yıldız Technical University Affiliated: Yes
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.