Modeling of the Small-Scale Outbreak of COVID-19

With the improvement of treatment and prevention methods, many countries have the pandemic under control. Different from the globally large-scale outbreak of COVID-19 in 2020, now the outbreak in these countries shows new characteristics, which calls for an effective epidemic model to describe the t...

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Bibliographic Details
Published inFrontiers in public health Vol. 10; p. 907814
Main Authors Wu, Ze-Yang, Zhang, Hong-Bo, Zhao, Hong-Fei
Format Journal Article
LanguageEnglish
Published Frontiers Media S.A 01.07.2022
Subjects
cellular automata
COVID-19
Public Health
simulation
small-scale outbreak
time matrix
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Summary:With the improvement of treatment and prevention methods, many countries have the pandemic under control. Different from the globally large-scale outbreak of COVID-19 in 2020, now the outbreak in these countries shows new characteristics, which calls for an effective epidemic model to describe the transmission dynamics. Meeting this need, first, we extensively investigate the small-scale outbreaks in different provinces of China and use classic compartmental models, which have been widely used in predictions, to forecast the outbreaks. Additionally, we further propose a new version of cellular automata with a time matrix, to simulate outbreaks. Finally, the experimental results show that the proposed cellular automata could effectively simulate the small-scale outbreak of COVID-19, which provides insights into the transmission dynamics of COVID-19 in China and help countries with small-scale outbreaks to determine and implement effective intervention measures. The countries with relatively small populations will also get useful information about the epidemic from our research.
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Edited by: Gopi Battineni, University of Camerino, Italy
This article was submitted to Infectious Diseases - Surveillance, Prevention and Treatment, a section of the journal Frontiers in Public Health
Reviewed by: Muhammad Imran Khan, The University of Haripur, Pakistan; Lin Wang, University of Cambridge, United Kingdom
ISSN:2296-2565
2296-2565
DOI:10.3389/fpubh.2022.907814