 Using simulation modelling and systems science to help contain COVID‐19: A systematic reviewWeiwei Zhang, Shiyong Liu, Nathaniel Osgood, Hongli Zhu, Ying Qian and Peng Jia Systems Research and Behavioral Science, 2023, vol. 40, issue 1, 207-234 Abstract: This study systematically reviews applications of three simulation approaches, that is, system dynamics model (SDM), agent‐based model (ABM) and discrete event simulation (DES), and their hybrids in COVID‐19 research and identifies theoretical and application innovations in public health. Among the 372 eligible papers, 72 focused on COVID‐19 transmission dynamics, 204 evaluated both pharmaceutical and non‐pharmaceutical interventions, 29 focused on the prediction of the pandemic and 67 investigated the impacts of COVID‐19. ABM was used in 275 papers, followed by 54 SDM papers, 32 DES papers and 11 hybrid model papers. Evaluation and design of intervention scenarios are the most widely addressed area accounting for 55% of the four main categories, that is, the transmission of COVID‐19, prediction of the pandemic, evaluation and design of intervention scenarios and societal impact assessment. The complexities in impact evaluation and intervention design demand hybrid simulation models that can simultaneously capture micro and macro aspects of the socio‐economic systems involved. Date: 2023 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:srbeha:v:40:y:2023:i:1:p:207-234 Ordering information: This journal article can be ordered from Access Statistics for this article More articles in Systems Research and Behavioral Science from Wiley Blackwell |
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