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Modeling the resumption of work and production of enterprises during COVID-19: An SIR-based quantitative framework

The ongoing COVID-19 pandemic has evolved beyond being a public health crisis as it has exerted worldwide severe economic impacts, triggering cascading failures in the global industrial network. Although certain powerful enterprises can remain its normal operation during this global shock, what'...

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Autores principales: Zhao, Hongchao, Huang, Zili, Xu, Lei, Tang, Junqing, Chen, Yuang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801714/
https://www.ncbi.nlm.nih.gov/pubmed/36589974
http://dx.doi.org/10.3389/fpubh.2022.1066299
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author Zhao, Hongchao
Huang, Zili
Xu, Lei
Tang, Junqing
Chen, Yuang
author_facet Zhao, Hongchao
Huang, Zili
Xu, Lei
Tang, Junqing
Chen, Yuang
author_sort Zhao, Hongchao
collection PubMed
description The ongoing COVID-19 pandemic has evolved beyond being a public health crisis as it has exerted worldwide severe economic impacts, triggering cascading failures in the global industrial network. Although certain powerful enterprises can remain its normal operation during this global shock, what's more likely to happen for the majority, especially those small- and medium-sized firms, is that they are experiencing temporary suspension out of epidemic control requirement, or even permanent closure due to chronic business losses. For those enterprises that sustain the pandemic and only suspend for a relatively short period, they could resume work and production when epidemic control and prevention conditions are satisfied and production and operation are adjusted correspondingly. In this paper, we develop a novel quantitative framework which is based on the classic susceptible-infectious-recovered (SIR) epidemiological model (i.e., the SIR model), containing a set of differential equations to capture such enterprises' reactions in response to COVID-19 over time. We fit our model from the resumption of work and production (RWP) data on industrial enterprises above the designated size (IEDS). By modeling the dynamics of enterprises' reactions, it is feasible to investigate the ratio of enterprises' state of operation at given time. Since enterprises are major economic entities and take responsibility for most output, this study could potentially help policy makers better understand the economic impact caused by the pandemic and could be heuristic for future prevention and resilience-building strategies against suchlike outbreaks of public health crises.
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spelling pubmed-98017142022-12-31 Modeling the resumption of work and production of enterprises during COVID-19: An SIR-based quantitative framework Zhao, Hongchao Huang, Zili Xu, Lei Tang, Junqing Chen, Yuang Front Public Health Public Health The ongoing COVID-19 pandemic has evolved beyond being a public health crisis as it has exerted worldwide severe economic impacts, triggering cascading failures in the global industrial network. Although certain powerful enterprises can remain its normal operation during this global shock, what's more likely to happen for the majority, especially those small- and medium-sized firms, is that they are experiencing temporary suspension out of epidemic control requirement, or even permanent closure due to chronic business losses. For those enterprises that sustain the pandemic and only suspend for a relatively short period, they could resume work and production when epidemic control and prevention conditions are satisfied and production and operation are adjusted correspondingly. In this paper, we develop a novel quantitative framework which is based on the classic susceptible-infectious-recovered (SIR) epidemiological model (i.e., the SIR model), containing a set of differential equations to capture such enterprises' reactions in response to COVID-19 over time. We fit our model from the resumption of work and production (RWP) data on industrial enterprises above the designated size (IEDS). By modeling the dynamics of enterprises' reactions, it is feasible to investigate the ratio of enterprises' state of operation at given time. Since enterprises are major economic entities and take responsibility for most output, this study could potentially help policy makers better understand the economic impact caused by the pandemic and could be heuristic for future prevention and resilience-building strategies against suchlike outbreaks of public health crises. Frontiers Media S.A. 2022-12-16 /pmc/articles/PMC9801714/ /pubmed/36589974 http://dx.doi.org/10.3389/fpubh.2022.1066299 Text en Copyright © 2022 Zhao, Huang, Xu, Tang and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Zhao, Hongchao
Huang, Zili
Xu, Lei
Tang, Junqing
Chen, Yuang
Modeling the resumption of work and production of enterprises during COVID-19: An SIR-based quantitative framework
title Modeling the resumption of work and production of enterprises during COVID-19: An SIR-based quantitative framework
title_full Modeling the resumption of work and production of enterprises during COVID-19: An SIR-based quantitative framework
title_fullStr Modeling the resumption of work and production of enterprises during COVID-19: An SIR-based quantitative framework
title_full_unstemmed Modeling the resumption of work and production of enterprises during COVID-19: An SIR-based quantitative framework
title_short Modeling the resumption of work and production of enterprises during COVID-19: An SIR-based quantitative framework
title_sort modeling the resumption of work and production of enterprises during covid-19: an sir-based quantitative framework
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801714/
https://www.ncbi.nlm.nih.gov/pubmed/36589974
http://dx.doi.org/10.3389/fpubh.2022.1066299
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