Altun, KorayAltuntas S.Dereli T.2022-04-012022-04-0120212651477Xhttps://hdl.handle.net/20.500.12885/1834It is important to recognize that the dynamics of each country are different. There-fore, 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 re-garding 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 (incorporat-ing 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.trinfo:eu-repo/semantics/openAccessAgent-based simulationMulti-agent SIR modelSARS-CoV-2 (COVID-19)Article10.15672/HUJMS.75173450515481559N/AN/A