Cargando…
Epidemic modeling for the resurgence of COVID-19 in Chinese local communities
COVID-19 is a constantly challenging global health issue due to its strong intensity, rapid mutation and high infectiousness. The new Delta and Omicron variants have triggered massive outbreaks worldwide. Even China, which has done a good job in outbreak prevention, is still heavily affected by the...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9085441/ http://dx.doi.org/10.1016/j.jnlssr.2022.03.005 |
_version_ | 1784703818357800960 |
---|---|
author | Peng, Min Zhang, Jianing Gong, Jingrui Ran, Xingqi Liu, Jvlu Zhang, Lin |
author_facet | Peng, Min Zhang, Jianing Gong, Jingrui Ran, Xingqi Liu, Jvlu Zhang, Lin |
author_sort | Peng, Min |
collection | PubMed |
description | COVID-19 is a constantly challenging global health issue due to its strong intensity, rapid mutation and high infectiousness. The new Delta and Omicron variants have triggered massive outbreaks worldwide. Even China, which has done a good job in outbreak prevention, is still heavily affected by the virus. The long-term fight against multiple COVID-19 outbreaks is ongoing. In this study, we propose an SEIQR model that considers the incubation period and quarantine measurement. We verified our model using actual outbreak data from four Chinese cities. Numerical simulations show that a five-day delay results in a double resurgence scale. Our model can be used as a tool to understand the spread of the virus quantitatively and provide a reference for policymaking accordingly. |
format | Online Article Text |
id | pubmed-9085441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90854412022-05-10 Epidemic modeling for the resurgence of COVID-19 in Chinese local communities Peng, Min Zhang, Jianing Gong, Jingrui Ran, Xingqi Liu, Jvlu Zhang, Lin Journal of Safety Science and Resilience Article COVID-19 is a constantly challenging global health issue due to its strong intensity, rapid mutation and high infectiousness. The new Delta and Omicron variants have triggered massive outbreaks worldwide. Even China, which has done a good job in outbreak prevention, is still heavily affected by the virus. The long-term fight against multiple COVID-19 outbreaks is ongoing. In this study, we propose an SEIQR model that considers the incubation period and quarantine measurement. We verified our model using actual outbreak data from four Chinese cities. Numerical simulations show that a five-day delay results in a double resurgence scale. Our model can be used as a tool to understand the spread of the virus quantitatively and provide a reference for policymaking accordingly. China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. 2022-09 2022-05-10 /pmc/articles/PMC9085441/ http://dx.doi.org/10.1016/j.jnlssr.2022.03.005 Text en © 2022 China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Peng, Min Zhang, Jianing Gong, Jingrui Ran, Xingqi Liu, Jvlu Zhang, Lin Epidemic modeling for the resurgence of COVID-19 in Chinese local communities |
title | Epidemic modeling for the resurgence of COVID-19 in Chinese local communities |
title_full | Epidemic modeling for the resurgence of COVID-19 in Chinese local communities |
title_fullStr | Epidemic modeling for the resurgence of COVID-19 in Chinese local communities |
title_full_unstemmed | Epidemic modeling for the resurgence of COVID-19 in Chinese local communities |
title_short | Epidemic modeling for the resurgence of COVID-19 in Chinese local communities |
title_sort | epidemic modeling for the resurgence of covid-19 in chinese local communities |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9085441/ http://dx.doi.org/10.1016/j.jnlssr.2022.03.005 |
work_keys_str_mv | AT pengmin epidemicmodelingfortheresurgenceofcovid19inchineselocalcommunities AT zhangjianing epidemicmodelingfortheresurgenceofcovid19inchineselocalcommunities AT gongjingrui epidemicmodelingfortheresurgenceofcovid19inchineselocalcommunities AT ranxingqi epidemicmodelingfortheresurgenceofcovid19inchineselocalcommunities AT liujvlu epidemicmodelingfortheresurgenceofcovid19inchineselocalcommunities AT zhanglin epidemicmodelingfortheresurgenceofcovid19inchineselocalcommunities |