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Assessing the medical resources in COVID-19 based on evolutionary game.

Authors :
Guo, Keyu
Lu, Yikang
Geng, Yini
Lu, Jun
Shi, Lei
Source :
PLoS ONE. 1/11/2023, Vol. 17 Issue 1, p1-17. 17p.
Publication Year :
2023

Abstract

COVID-19 has brought a great challenge to the medical system. A key scientific question is how to make a balance between home quarantine and staying in the hospital. To this end, we propose a game-based susceptible-exposed-asymptomatic -symptomatic- hospitalized-recovery-dead model to reveal such a situation. In this new framework, time-varying cure rate and mortality are employed and a parameter m is introduced to regulate the probability that individuals are willing to go to the hospital. Through extensive simulations, we find that (1) for low transmission rates (β < 0.2), the high value of m (the willingness to stay in the hospital) indicates the full use of medical resources, and thus the pandemic can be easily contained; (2) for high transmission rates (β > 0.2), large values of m lead to breakdown of the healthcare system, which will further increase the cumulative number of confirmed cases and death cases. Finally, we conduct the empirical analysis using the data from Japan and other typical countries to illustrate the proposed model and to test how our model explains reality. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19326203
Volume :
17
Issue :
1
Database :
Academic Search Index
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
161249493
Full Text :
https://doi.org/10.1371/journal.pone.0280067