TY  - JOUR
TI  - An interaction-oriented multi-agent SIR model to assess the spread of SARS-CoV-2
AB  - 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.
AU  - Altuntas, Serkan
AU  - Dereli, Türkay
AU  - Altun, Koray
DO  - 10.15672/hujms.751734
PY  - 2021
JO  - Hacettepe Journal of Mathematics and Statistics
VL  - 50
IS  - 5
SN  - 1303-5010
SP  - 1548
EP  - 1559
DB  - TRDizin
UR  - http://search/yayin/detay/495053
ER  -