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Interrupted time series analysis using the ARIMA model of the impact of COVID-19 on the incidence rate of notifiable communicable diseases in China
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic in China is ongoing. Some studies have shown that the incidence of respiratory and intestinal infectious diseases in 2020 decreased significantly compared with previous years. Interrupted time series (ITS) is a time series analysis method...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266306/ https://www.ncbi.nlm.nih.gov/pubmed/37316780 http://dx.doi.org/10.1186/s12879-023-08229-5 |
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author | Zhou, Qin Hu, Junxian Hu, Wensui Li, Hailin Lin, Guo-zhen |
author_facet | Zhou, Qin Hu, Junxian Hu, Wensui Li, Hailin Lin, Guo-zhen |
author_sort | Zhou, Qin |
collection | PubMed |
description | BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic in China is ongoing. Some studies have shown that the incidence of respiratory and intestinal infectious diseases in 2020 decreased significantly compared with previous years. Interrupted time series (ITS) is a time series analysis method that evaluates the impact of intervention measures on outcomes and can control the original regression trend of outcomes before and after the intervention. This study aimed to analyse the impact of COVID-19 on the incidence rate of notifiable communicable diseases using ITS in China. METHODS: National data on the incidence rate of communicable diseases in 2009–2021 were obtained from the National Health Commission website. Interrupted time series analysis using autoregressive integrated moving average (ARIMA) models was used to analyse the changes in the incidence rate of infectious diseases before and after the COVID-19 epidemic. RESULTS: There was a significant short-term decline in the incidence rates of respiratory infectious diseases and enteric infectious diseases (step values of -29.828 and − 8.237, respectively), which remained at a low level for a long time after the decline. There was a short-term decline in the incidence rates of blood-borne and sexually transmitted infectious diseases (step = -3.638), which tended to recover to previous levels in the long term (ramp = 0.172). There was no significant change in the incidence rate of natural focus diseases or arboviral diseases before and after the epidemic. CONCLUSION: The COVID-19 epidemic had strong short-term and long-term effects on respiratory and intestinal infectious diseases and short-term control effects on blood-borne and sexually transmitted infectious diseases. Our methods for the prevention and control of COVID-19 can be used for the prevention and control of other notifiable communicable diseases, especially respiratory and intestinal infectious diseases. |
format | Online Article Text |
id | pubmed-10266306 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102663062023-06-14 Interrupted time series analysis using the ARIMA model of the impact of COVID-19 on the incidence rate of notifiable communicable diseases in China Zhou, Qin Hu, Junxian Hu, Wensui Li, Hailin Lin, Guo-zhen BMC Infect Dis Research BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic in China is ongoing. Some studies have shown that the incidence of respiratory and intestinal infectious diseases in 2020 decreased significantly compared with previous years. Interrupted time series (ITS) is a time series analysis method that evaluates the impact of intervention measures on outcomes and can control the original regression trend of outcomes before and after the intervention. This study aimed to analyse the impact of COVID-19 on the incidence rate of notifiable communicable diseases using ITS in China. METHODS: National data on the incidence rate of communicable diseases in 2009–2021 were obtained from the National Health Commission website. Interrupted time series analysis using autoregressive integrated moving average (ARIMA) models was used to analyse the changes in the incidence rate of infectious diseases before and after the COVID-19 epidemic. RESULTS: There was a significant short-term decline in the incidence rates of respiratory infectious diseases and enteric infectious diseases (step values of -29.828 and − 8.237, respectively), which remained at a low level for a long time after the decline. There was a short-term decline in the incidence rates of blood-borne and sexually transmitted infectious diseases (step = -3.638), which tended to recover to previous levels in the long term (ramp = 0.172). There was no significant change in the incidence rate of natural focus diseases or arboviral diseases before and after the epidemic. CONCLUSION: The COVID-19 epidemic had strong short-term and long-term effects on respiratory and intestinal infectious diseases and short-term control effects on blood-borne and sexually transmitted infectious diseases. Our methods for the prevention and control of COVID-19 can be used for the prevention and control of other notifiable communicable diseases, especially respiratory and intestinal infectious diseases. BioMed Central 2023-06-05 /pmc/articles/PMC10266306/ /pubmed/37316780 http://dx.doi.org/10.1186/s12879-023-08229-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Zhou, Qin Hu, Junxian Hu, Wensui Li, Hailin Lin, Guo-zhen Interrupted time series analysis using the ARIMA model of the impact of COVID-19 on the incidence rate of notifiable communicable diseases in China |
title | Interrupted time series analysis using the ARIMA model of the impact of COVID-19 on the incidence rate of notifiable communicable diseases in China |
title_full | Interrupted time series analysis using the ARIMA model of the impact of COVID-19 on the incidence rate of notifiable communicable diseases in China |
title_fullStr | Interrupted time series analysis using the ARIMA model of the impact of COVID-19 on the incidence rate of notifiable communicable diseases in China |
title_full_unstemmed | Interrupted time series analysis using the ARIMA model of the impact of COVID-19 on the incidence rate of notifiable communicable diseases in China |
title_short | Interrupted time series analysis using the ARIMA model of the impact of COVID-19 on the incidence rate of notifiable communicable diseases in China |
title_sort | interrupted time series analysis using the arima model of the impact of covid-19 on the incidence rate of notifiable communicable diseases in china |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266306/ https://www.ncbi.nlm.nih.gov/pubmed/37316780 http://dx.doi.org/10.1186/s12879-023-08229-5 |
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