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Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination
We developed a mechanism model which allows for simulating the novel coronavirus (COVID-19) transmission dynamics with the combined effects of human adaptive behaviours and vaccination, aiming at predicting the end time of COVID-19 infection in global scale. Based on the surveillance information (re...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10024953/ https://www.ncbi.nlm.nih.gov/pubmed/36803678 http://dx.doi.org/10.1017/S0950268823000274 |
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author | Zhou, Yuhao Li, Zhaowan Wu, Wei Xiao, Jianpeng Ma, Wenjun Zhu, Guanghu |
author_facet | Zhou, Yuhao Li, Zhaowan Wu, Wei Xiao, Jianpeng Ma, Wenjun Zhu, Guanghu |
author_sort | Zhou, Yuhao |
collection | PubMed |
description | We developed a mechanism model which allows for simulating the novel coronavirus (COVID-19) transmission dynamics with the combined effects of human adaptive behaviours and vaccination, aiming at predicting the end time of COVID-19 infection in global scale. Based on the surveillance information (reported cases and vaccination data) between 22 January 2020 and 18 July 2022, we validated the model by Markov Chain Monte Carlo (MCMC) fitting method. We found that (1) if without adaptive behaviours, the epidemic could sweep the world in 2022 and 2023, causing 3.098 billion of human infections, which is 5.39 times of current number; (2) 645 million people could be avoided from infection due to vaccination; and (3) in current scenarios of protective behaviours and vaccination, infection cases would increase slowly, levelling off around 2023, and it would end completely in June 2025, causing 1.024 billion infections, with 12.5 million death. Our findings suggest that vaccination and the collective protection behaviour remain the key determinants against the global process of COVID-19 transmission. |
format | Online Article Text |
id | pubmed-10024953 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-100249532023-03-20 Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination Zhou, Yuhao Li, Zhaowan Wu, Wei Xiao, Jianpeng Ma, Wenjun Zhu, Guanghu Epidemiol Infect Original Paper We developed a mechanism model which allows for simulating the novel coronavirus (COVID-19) transmission dynamics with the combined effects of human adaptive behaviours and vaccination, aiming at predicting the end time of COVID-19 infection in global scale. Based on the surveillance information (reported cases and vaccination data) between 22 January 2020 and 18 July 2022, we validated the model by Markov Chain Monte Carlo (MCMC) fitting method. We found that (1) if without adaptive behaviours, the epidemic could sweep the world in 2022 and 2023, causing 3.098 billion of human infections, which is 5.39 times of current number; (2) 645 million people could be avoided from infection due to vaccination; and (3) in current scenarios of protective behaviours and vaccination, infection cases would increase slowly, levelling off around 2023, and it would end completely in June 2025, causing 1.024 billion infections, with 12.5 million death. Our findings suggest that vaccination and the collective protection behaviour remain the key determinants against the global process of COVID-19 transmission. Cambridge University Press 2023-02-20 /pmc/articles/PMC10024953/ /pubmed/36803678 http://dx.doi.org/10.1017/S0950268823000274 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. |
spellingShingle | Original Paper Zhou, Yuhao Li, Zhaowan Wu, Wei Xiao, Jianpeng Ma, Wenjun Zhu, Guanghu Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination |
title | Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination |
title_full | Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination |
title_fullStr | Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination |
title_full_unstemmed | Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination |
title_short | Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination |
title_sort | transmission trends of the global covid-19 pandemic with combined effects of adaptive behaviours and vaccination |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10024953/ https://www.ncbi.nlm.nih.gov/pubmed/36803678 http://dx.doi.org/10.1017/S0950268823000274 |
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