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Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study

BACKGROUND: Non-pharmaceutical interventions (NPIs) have been implemented worldwide to suppress the spread of coronavirus disease 2019 (COVID-19). However, few studies have evaluated the effect of NPIs on other infectious diseases and none has assessed the avoided disease burden associated with NPIs...

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Autores principales: Zhang, Wenyi, Wu, Yao, Wen, Bo, Zhang, Yongming, Wang, Yong, Yin, Wenwu, Sun, Shanhua, Wei, Xianyu, Sun, Hailong, Zhang, Zhijie, Li, Shanshan, Guo, Yuming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996566/
https://www.ncbi.nlm.nih.gov/pubmed/36895021
http://dx.doi.org/10.1186/s40249-023-01066-3
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author Zhang, Wenyi
Wu, Yao
Wen, Bo
Zhang, Yongming
Wang, Yong
Yin, Wenwu
Sun, Shanhua
Wei, Xianyu
Sun, Hailong
Zhang, Zhijie
Li, Shanshan
Guo, Yuming
author_facet Zhang, Wenyi
Wu, Yao
Wen, Bo
Zhang, Yongming
Wang, Yong
Yin, Wenwu
Sun, Shanhua
Wei, Xianyu
Sun, Hailong
Zhang, Zhijie
Li, Shanshan
Guo, Yuming
author_sort Zhang, Wenyi
collection PubMed
description BACKGROUND: Non-pharmaceutical interventions (NPIs) have been implemented worldwide to suppress the spread of coronavirus disease 2019 (COVID-19). However, few studies have evaluated the effect of NPIs on other infectious diseases and none has assessed the avoided disease burden associated with NPIs. We aimed to assess the effect of NPIs on the incidence of infectious diseases during the COVID-19 pandemic in 2020 and evaluate the health economic benefits related to the reduction in the incidence of infectious diseases. METHODS: Data on 10 notifiable infectious diseases across China during 2010–2020 were extracted from the China Information System for Disease Control and Prevention. A two-stage controlled interrupted time-series design with a quasi-Poisson regression model was used to examine the impact of NPIs on the incidence of infectious diseases. The analysis was first performed at the provincial-level administrative divisions (PLADs) level in China, then the PLAD-specific estimates were pooled using a random-effect meta-analysis. RESULTS: A total of 61,393,737 cases of 10 infectious diseases were identified. The implementation of NPIs was associated with 5.13 million (95% confidence interval [CI] 3.45‒7.42) avoided cases and USD 1.77 billion (95% CI 1.18‒2.57) avoided hospital expenditures in 2020. There were 4.52 million (95% CI 3.00‒6.63) avoided cases for children and adolescents, corresponding to 88.2% of total avoided cases. The top leading cause of avoided burden attributable to NPIs was influenza [avoided percentage (AP): 89.3%; 95% CI 84.5‒92.6]. Socioeconomic status and population density were effect modifiers. CONCLUSIONS: NPIs for COVID-19 could effectively control the prevalence of infectious diseases, with patterns of risk varying by socioeconomic status. These findings have important implications for informing targeted strategies to prevent infectious diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40249-023-01066-3.
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spelling pubmed-99965662023-03-09 Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study Zhang, Wenyi Wu, Yao Wen, Bo Zhang, Yongming Wang, Yong Yin, Wenwu Sun, Shanhua Wei, Xianyu Sun, Hailong Zhang, Zhijie Li, Shanshan Guo, Yuming Infect Dis Poverty Research Article BACKGROUND: Non-pharmaceutical interventions (NPIs) have been implemented worldwide to suppress the spread of coronavirus disease 2019 (COVID-19). However, few studies have evaluated the effect of NPIs on other infectious diseases and none has assessed the avoided disease burden associated with NPIs. We aimed to assess the effect of NPIs on the incidence of infectious diseases during the COVID-19 pandemic in 2020 and evaluate the health economic benefits related to the reduction in the incidence of infectious diseases. METHODS: Data on 10 notifiable infectious diseases across China during 2010–2020 were extracted from the China Information System for Disease Control and Prevention. A two-stage controlled interrupted time-series design with a quasi-Poisson regression model was used to examine the impact of NPIs on the incidence of infectious diseases. The analysis was first performed at the provincial-level administrative divisions (PLADs) level in China, then the PLAD-specific estimates were pooled using a random-effect meta-analysis. RESULTS: A total of 61,393,737 cases of 10 infectious diseases were identified. The implementation of NPIs was associated with 5.13 million (95% confidence interval [CI] 3.45‒7.42) avoided cases and USD 1.77 billion (95% CI 1.18‒2.57) avoided hospital expenditures in 2020. There were 4.52 million (95% CI 3.00‒6.63) avoided cases for children and adolescents, corresponding to 88.2% of total avoided cases. The top leading cause of avoided burden attributable to NPIs was influenza [avoided percentage (AP): 89.3%; 95% CI 84.5‒92.6]. Socioeconomic status and population density were effect modifiers. CONCLUSIONS: NPIs for COVID-19 could effectively control the prevalence of infectious diseases, with patterns of risk varying by socioeconomic status. These findings have important implications for informing targeted strategies to prevent infectious diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40249-023-01066-3. BioMed Central 2023-03-09 /pmc/articles/PMC9996566/ /pubmed/36895021 http://dx.doi.org/10.1186/s40249-023-01066-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Zhang, Wenyi
Wu, Yao
Wen, Bo
Zhang, Yongming
Wang, Yong
Yin, Wenwu
Sun, Shanhua
Wei, Xianyu
Sun, Hailong
Zhang, Zhijie
Li, Shanshan
Guo, Yuming
Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study
title Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study
title_full Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study
title_fullStr Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study
title_full_unstemmed Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study
title_short Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study
title_sort non-pharmaceutical interventions for covid-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996566/
https://www.ncbi.nlm.nih.gov/pubmed/36895021
http://dx.doi.org/10.1186/s40249-023-01066-3
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