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Trends in respiratory diseases before and after the COVID-19 pandemic in China from 2010 to 2021

BACKGROUND: The ongoing benefits of coronavirus disease 2019 (COVID-19) nonpharmaceutical interventions (NPIs) for respiratory infectious diseases in China are still unclear. We aimed to explore the changes in seven respiratory infectious diseases before, during, and after COVID-19 in China from 201...

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Autores principales: Zuo, Zhongbao, Yang, Chunli, Ye, Fei, Wang, Miaochan, Wu, Jing, Tao, Chengjiang, Xun, Yunhao, Li, Zhaoyi, Liu, Shourong, Huang, Jinsong, Xu, Aifang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889952/
https://www.ncbi.nlm.nih.gov/pubmed/36721137
http://dx.doi.org/10.1186/s12889-023-15081-4
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author Zuo, Zhongbao
Yang, Chunli
Ye, Fei
Wang, Miaochan
Wu, Jing
Tao, Chengjiang
Xun, Yunhao
Li, Zhaoyi
Liu, Shourong
Huang, Jinsong
Xu, Aifang
author_facet Zuo, Zhongbao
Yang, Chunli
Ye, Fei
Wang, Miaochan
Wu, Jing
Tao, Chengjiang
Xun, Yunhao
Li, Zhaoyi
Liu, Shourong
Huang, Jinsong
Xu, Aifang
author_sort Zuo, Zhongbao
collection PubMed
description BACKGROUND: The ongoing benefits of coronavirus disease 2019 (COVID-19) nonpharmaceutical interventions (NPIs) for respiratory infectious diseases in China are still unclear. We aimed to explore the changes in seven respiratory infectious diseases before, during, and after COVID-19 in China from 2010 to 2021. METHODS: The monthly case numbers of seven respiratory infectious diseases were extracted to construct autoregressive integrated moving average (ARIMA) models. Eight indicators of NPIs were chosen from the COVID-19 Government Response Tracker system. The monthly case numbers of the respiratory diseases and the eight indicators were used to establish the Multivariable generalized linear model (GLM) to calculate the incidence rate ratios (IRRs). RESULTS: Compared with the year 2019, the percentage changes in 2020 and 2021 were all below 100% ranging from 3.81 to 84.71%. Pertussis and Scarlet fever started to increase in 2021 compared with 2020, with a percentage change of 183.46 and 171.49%. The ARIMA model showed a good fit, and the predicted data fitted well with the actual data from 2010 to 2019, but the predicted data was bigger than the actual number in 2020 and 2021. All eight indicators could negatively affect the incidence of respiratory diseases. The seven respiratory diseases were significantly reduced during the COVID-19 pandemic in 2020 and 2021 compared with 2019, with significant estimated IRRs ranging from 0.06 to 0.85. In the GLM using data for the year 2020 and 2021, the IRRs were not significant after adjusting for the eight indicators in multivariate analysis. CONCLUSION: Our study demonstrated the incidence of the seven respiratory diseases decreased rapidly during the COVID-19 pandemic in 2020 and 2021. At the end of 2021, we did see a rising trend for the seven respiratory diseases compared to the year 2020 when the NPIs relaxed in China, but the rising trend was not significant after adjusting for the NPIs indicators. Our study showed that NPIs have an effect on respiratory diseases, but Relaxation of NPIs might lead to the resurgence of respiratory diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-15081-4.
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spelling pubmed-98899522023-02-01 Trends in respiratory diseases before and after the COVID-19 pandemic in China from 2010 to 2021 Zuo, Zhongbao Yang, Chunli Ye, Fei Wang, Miaochan Wu, Jing Tao, Chengjiang Xun, Yunhao Li, Zhaoyi Liu, Shourong Huang, Jinsong Xu, Aifang BMC Public Health Research BACKGROUND: The ongoing benefits of coronavirus disease 2019 (COVID-19) nonpharmaceutical interventions (NPIs) for respiratory infectious diseases in China are still unclear. We aimed to explore the changes in seven respiratory infectious diseases before, during, and after COVID-19 in China from 2010 to 2021. METHODS: The monthly case numbers of seven respiratory infectious diseases were extracted to construct autoregressive integrated moving average (ARIMA) models. Eight indicators of NPIs were chosen from the COVID-19 Government Response Tracker system. The monthly case numbers of the respiratory diseases and the eight indicators were used to establish the Multivariable generalized linear model (GLM) to calculate the incidence rate ratios (IRRs). RESULTS: Compared with the year 2019, the percentage changes in 2020 and 2021 were all below 100% ranging from 3.81 to 84.71%. Pertussis and Scarlet fever started to increase in 2021 compared with 2020, with a percentage change of 183.46 and 171.49%. The ARIMA model showed a good fit, and the predicted data fitted well with the actual data from 2010 to 2019, but the predicted data was bigger than the actual number in 2020 and 2021. All eight indicators could negatively affect the incidence of respiratory diseases. The seven respiratory diseases were significantly reduced during the COVID-19 pandemic in 2020 and 2021 compared with 2019, with significant estimated IRRs ranging from 0.06 to 0.85. In the GLM using data for the year 2020 and 2021, the IRRs were not significant after adjusting for the eight indicators in multivariate analysis. CONCLUSION: Our study demonstrated the incidence of the seven respiratory diseases decreased rapidly during the COVID-19 pandemic in 2020 and 2021. At the end of 2021, we did see a rising trend for the seven respiratory diseases compared to the year 2020 when the NPIs relaxed in China, but the rising trend was not significant after adjusting for the NPIs indicators. Our study showed that NPIs have an effect on respiratory diseases, but Relaxation of NPIs might lead to the resurgence of respiratory diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-15081-4. BioMed Central 2023-02-01 /pmc/articles/PMC9889952/ /pubmed/36721137 http://dx.doi.org/10.1186/s12889-023-15081-4 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
Zuo, Zhongbao
Yang, Chunli
Ye, Fei
Wang, Miaochan
Wu, Jing
Tao, Chengjiang
Xun, Yunhao
Li, Zhaoyi
Liu, Shourong
Huang, Jinsong
Xu, Aifang
Trends in respiratory diseases before and after the COVID-19 pandemic in China from 2010 to 2021
title Trends in respiratory diseases before and after the COVID-19 pandemic in China from 2010 to 2021
title_full Trends in respiratory diseases before and after the COVID-19 pandemic in China from 2010 to 2021
title_fullStr Trends in respiratory diseases before and after the COVID-19 pandemic in China from 2010 to 2021
title_full_unstemmed Trends in respiratory diseases before and after the COVID-19 pandemic in China from 2010 to 2021
title_short Trends in respiratory diseases before and after the COVID-19 pandemic in China from 2010 to 2021
title_sort trends in respiratory diseases before and after the covid-19 pandemic in china from 2010 to 2021
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889952/
https://www.ncbi.nlm.nih.gov/pubmed/36721137
http://dx.doi.org/10.1186/s12889-023-15081-4
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