Revisiting the complex time-varying effect of non-pharmaceutical interventions on COVID-19 transmission in the United States
Copyright © 2024 Wu, Zhang, Wu, Wang, Huang, Wu, Li, Zhang, Du and Hao..
Introduction: Although the global COVID-19 emergency ended, the real-world effects of multiple non-pharmaceutical interventions (NPIs) and the relative contribution of individual NPIs over time were poorly understood, limiting the mitigation of future potential epidemics.
Methods: Based on four large-scale datasets including epidemic parameters, virus variants, vaccines, and meteorological factors across 51 states in the United States from August 2020 to July 2022, we established a Bayesian hierarchical model with a spike-and-slab prior to assessing the time-varying effect of NPIs and vaccination on mitigating COVID-19 transmission and identifying important NPIs in the context of different variants pandemic.
Results: We found that (i) the empirical reduction in reproduction number attributable to integrated NPIs was 52.0% (95%CI: 44.4, 58.5%) by August and September 2020, whereas the reduction continuously decreased due to the relaxation of NPIs in following months; (ii) international travel restrictions, stay-at-home requirements, and restrictions on gathering size were important NPIs with the relative contribution higher than 12.5%; (iii) vaccination alone could not mitigate transmission when the fully vaccination coverage was less than 60%, but it could effectively synergize with NPIs; (iv) even with fully vaccination coverage >60%, combined use of NPIs and vaccination failed to reduce the reproduction number below 1 in many states by February 2022 because of elimination of above NPIs, following with a resurgence of COVID-19 after March 2022.
Conclusion: Our results suggest that NPIs and vaccination had a high synergy effect and eliminating NPIs should consider their relative effectiveness, vaccination coverage, and emerging variants.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:12 |
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| Enthalten in: |
Frontiers in public health - 12(2024) vom: 29., Seite 1343950 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Wu, Gonghua [VerfasserIn] |
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| Links: |
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| Themen: |
Bayesian hierarchical model |
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| Anmerkungen: |
Date Completed 08.03.2024 Date Revised 08.03.2024 published: Electronic-eCollection Citation Status MEDLINE |
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| doi: |
10.3389/fpubh.2024.1343950 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Copyright © 2024 Wu, Zhang, Wu, Wang, Huang, Wu, Li, Zhang, Du and Hao. | ||
| 520 | |a Introduction: Although the global COVID-19 emergency ended, the real-world effects of multiple non-pharmaceutical interventions (NPIs) and the relative contribution of individual NPIs over time were poorly understood, limiting the mitigation of future potential epidemics | ||
| 520 | |a Methods: Based on four large-scale datasets including epidemic parameters, virus variants, vaccines, and meteorological factors across 51 states in the United States from August 2020 to July 2022, we established a Bayesian hierarchical model with a spike-and-slab prior to assessing the time-varying effect of NPIs and vaccination on mitigating COVID-19 transmission and identifying important NPIs in the context of different variants pandemic | ||
| 520 | |a Results: We found that (i) the empirical reduction in reproduction number attributable to integrated NPIs was 52.0% (95%CI: 44.4, 58.5%) by August and September 2020, whereas the reduction continuously decreased due to the relaxation of NPIs in following months; (ii) international travel restrictions, stay-at-home requirements, and restrictions on gathering size were important NPIs with the relative contribution higher than 12.5%; (iii) vaccination alone could not mitigate transmission when the fully vaccination coverage was less than 60%, but it could effectively synergize with NPIs; (iv) even with fully vaccination coverage >60%, combined use of NPIs and vaccination failed to reduce the reproduction number below 1 in many states by February 2022 because of elimination of above NPIs, following with a resurgence of COVID-19 after March 2022 | ||
| 520 | |a Conclusion: Our results suggest that NPIs and vaccination had a high synergy effect and eliminating NPIs should consider their relative effectiveness, vaccination coverage, and emerging variants | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Bayesian hierarchical model | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a NPIs | |
| 650 | 4 | |a shrinkage prior | |
| 650 | 4 | |a vaccination | |
| 700 | 1 | |a Zhang, Wanfang |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Wenjing |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Pengyu |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Zitong |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Yueqian |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Junxi |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Wangjian |e verfasserin |4 aut | |
| 700 | 1 | |a Du, Zhicheng |e verfasserin |4 aut | |
| 700 | 1 | |a Hao, Yuantao |e verfasserin |4 aut | |
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