Untangling the changing impact of non-pharmaceutical interventions and vaccination on European COVID-19 trajectories
Untangling the changing impact of non-pharmaceutical interventions and vaccination on European COVID-19 trajectories
Non-pharmaceutical interventions (NPIs) and vaccination are two fundamental approaches for mitigating the coronavirus disease 2019 (COVID-19) pandemic. However, the real-world impact of NPIs versus vaccination, or a combination of both, on COVID-19 remains uncertain. To address this, we built a Bayesian inference model to assess the changing effect of NPIs and vaccination on reducing COVID-19 transmission, based on a large-scale dataset including epidemiological parameters, virus variants, vaccines, and climate factors in Europe from August 2020 to October 2021. We found that (1) the combined effect of NPIs and vaccination resulted in a 53% (95% confidence interval: 42–62%) reduction in reproduction number by October 2021, whereas NPIs and vaccination reduced the transmission by 35% and 38%, respectively; (2) compared with vaccination, the change of NPI effect was less sensitive to emerging variants; (3) the relative effect of NPIs declined 12% from May 2021 due to a lower stringency and the introduction of vaccination strategies. Our results demonstrate that NPIs were complementary to vaccination in an effort to reduce COVID-19 transmission, and the relaxation of NPIs might depend on vaccination rates, control targets, and vaccine effectiveness concerning extant and emerging variants.
Bayes Theorem, COVID-19/epidemiology, Humans, Pandemics/prevention & control, SARS-CoV-2, Vaccination
Ge, Yong
f22fa40c-9a6a-456c-bdad-b322c3fd24ee
Zhang, Wen-Bin
a4ab325c-e9cb-4369-959b-25a3320bb4e3
Wu, Xilin
58bc70e9-e062-4a74-8b9c-d3212e505436
Ruktanonchai, Corrine W.
44e6fcd0-246b-480e-8940-9557dbb7c0cc
Liu, Haiyan
aeca8fb6-ed13-471e-96ec-a33757a3b2e8
Wang, Jianghao
824eda0f-b65e-41c4-bb75-b0b604f96454
Song, Yongze
5b0e580c-c74f-49e2-a0a6-293e425c9b78
Liu, Mengxiao
71362048-644e-4deb-a2c0-dfb09382eb32
Yan, Wei
f5fa4872-fd83-4511-8478-8616d520c77d
Yang, Juan
a7a93a88-e671-435d-8845-9a32087cfe77
Cleary, Eimear
3cbf7016-269e-4517-ab4f-323e86db6e58
Qader, Sarchil H.
b1afb647-aeff-4bb8-84f2-56865c4eb9e4
Atuhaire, Fatumah
d55c841a-b029-47ea-bb9e-01ebbd851352
Ruktanonchai, Nick W.
fe68cb8d-3760-4955-99fa-47d43f86580a
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
3 June 2022
Ge, Yong
f22fa40c-9a6a-456c-bdad-b322c3fd24ee
Zhang, Wen-Bin
a4ab325c-e9cb-4369-959b-25a3320bb4e3
Wu, Xilin
58bc70e9-e062-4a74-8b9c-d3212e505436
Ruktanonchai, Corrine W.
44e6fcd0-246b-480e-8940-9557dbb7c0cc
Liu, Haiyan
aeca8fb6-ed13-471e-96ec-a33757a3b2e8
Wang, Jianghao
824eda0f-b65e-41c4-bb75-b0b604f96454
Song, Yongze
5b0e580c-c74f-49e2-a0a6-293e425c9b78
Liu, Mengxiao
71362048-644e-4deb-a2c0-dfb09382eb32
Yan, Wei
f5fa4872-fd83-4511-8478-8616d520c77d
Yang, Juan
a7a93a88-e671-435d-8845-9a32087cfe77
Cleary, Eimear
3cbf7016-269e-4517-ab4f-323e86db6e58
Qader, Sarchil H.
b1afb647-aeff-4bb8-84f2-56865c4eb9e4
Atuhaire, Fatumah
d55c841a-b029-47ea-bb9e-01ebbd851352
Ruktanonchai, Nick W.
fe68cb8d-3760-4955-99fa-47d43f86580a
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Ge, Yong, Zhang, Wen-Bin, Wu, Xilin, Ruktanonchai, Corrine W., Liu, Haiyan, Wang, Jianghao, Song, Yongze, Liu, Mengxiao, Yan, Wei, Yang, Juan, Cleary, Eimear, Qader, Sarchil H., Atuhaire, Fatumah, Ruktanonchai, Nick W., Tatem, Andrew J. and Lai, Shengjie
(2022)
Untangling the changing impact of non-pharmaceutical interventions and vaccination on European COVID-19 trajectories.
Nature Communications, 13 (1), [3106].
(doi:10.1038/s41467-022-30897-1).
Abstract
Non-pharmaceutical interventions (NPIs) and vaccination are two fundamental approaches for mitigating the coronavirus disease 2019 (COVID-19) pandemic. However, the real-world impact of NPIs versus vaccination, or a combination of both, on COVID-19 remains uncertain. To address this, we built a Bayesian inference model to assess the changing effect of NPIs and vaccination on reducing COVID-19 transmission, based on a large-scale dataset including epidemiological parameters, virus variants, vaccines, and climate factors in Europe from August 2020 to October 2021. We found that (1) the combined effect of NPIs and vaccination resulted in a 53% (95% confidence interval: 42–62%) reduction in reproduction number by October 2021, whereas NPIs and vaccination reduced the transmission by 35% and 38%, respectively; (2) compared with vaccination, the change of NPI effect was less sensitive to emerging variants; (3) the relative effect of NPIs declined 12% from May 2021 due to a lower stringency and the introduction of vaccination strategies. Our results demonstrate that NPIs were complementary to vaccination in an effort to reduce COVID-19 transmission, and the relaxation of NPIs might depend on vaccination rates, control targets, and vaccine effectiveness concerning extant and emerging variants.
Text
s41467-022-30897-1
- Version of Record
More information
Submitted date: 30 October 2021
Accepted/In Press date: 24 May 2022
Published date: 3 June 2022
Additional Information:
Funding Information:
We thank the researchers who generated and publicly shared the epidemiological, intervention and sequencing data used in this research. This study was supported by the National Natural Science Foundation for Distinguished Young Scholars of China (No. 41725006), the Bill & Melinda Gates Foundation (INV-024911), and the National Institutes of Health (R01AI160780). YG is supported by funding from the National Natural Science Foundation for Distinguished Young Scholars of China (No. 41725006). AJT is supported by funding from the Bill & Melinda Gates Foundation (OPP1106427, OPP1032350, OPP1134076, OPP1094793), the Clinton Health Access Initiative, the UK Foreign, Commonwealth and Development Office (UK-FCDO), the Wellcome Trust (106866/Z/15/Z, 204613/Z/16/Z), the National Institutes of Health (R01AI160780), and the EU H2020 (MOOD 874850). SL is supported by funding from the Bill & Melinda Gates Foundation (INV-024911) and the National Natural Science Foundation of China (81773498). JY is supported by funding from the Shanghai Municipal Science and Technology Major Project (ZD2021CY001). The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. The views expressed in this article are those of the authors and do not represent any official policy.
Publisher Copyright:
© 2022, The Author(s).
Keywords:
Bayes Theorem, COVID-19/epidemiology, Humans, Pandemics/prevention & control, SARS-CoV-2, Vaccination
Identifiers
Local EPrints ID: 458194
URI: http://eprints.soton.ac.uk/id/eprint/458194
ISSN: 2041-1723
PURE UUID: 465a35c8-571b-42aa-9eb9-4b0d5daaf56e
Catalogue record
Date deposited: 30 Jun 2022 17:07
Last modified: 22 May 2024 02:05
Export record
Altmetrics
Contributors
Author:
Yong Ge
Author:
Wen-Bin Zhang
Author:
Xilin Wu
Author:
Corrine W. Ruktanonchai
Author:
Haiyan Liu
Author:
Jianghao Wang
Author:
Yongze Song
Author:
Mengxiao Liu
Author:
Wei Yan
Author:
Juan Yang
Author:
Eimear Cleary
Author:
Fatumah Atuhaire
Author:
Nick W. Ruktanonchai
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics