ID:
publications-4484
Type:
article
Year:
2022
Authors:
Tang, Jing and Tang, Jing and Vinayavekhin, Sukrit and Vinayavekhin, Sukrit and Weeramongkolkul, Manapat and Weeramongkolkul, Manapat and Suksanon, Chanakan and Suksanon, Chanakan and Pattarapremcharoen, Kantapat and Pattarapremcharoen, Kantapat and Thiwathittayanuphap, Sasinat and Thiwathittayanuphap, Sasinat and Leelawat, Natt and Leelawat, Natt
Title:
Agent-Based Simulation and Modeling of COVID-19 Pandemic: A Bibliometric Analysis
Venue/Journal:
Journal of disaster research
DOI:
10.20965/jdr.2022.p0093
Research type:
Water System:
Technical Focus:
Abstract:
The coronavirus disease has caused an ongoing pandemic worldwide since 2019. To slow the rapid spread of the virus, many countries have adopted lockdown measures. To scientifically determine the most appropriate measures and policies, agent-based simulation and modeling techniques have been employed. It can be challenging for researchers to select the appropriate tools and techniques as well as the input and output parameters. This study conducted a bibliometric analysis, especially a co-word network analysis, to classify relevant research articles into five clusters: conceptual, economic-based, organizational, policy-based, and statistical modeling. It then explained each approach and point of concern. Through this, researchers and modelers can identify the optimal approaches for their agent-based models.
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