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Impact of COVID-19 prevention and control on tuberculosis and scarlet fever in China’s Guizhou
China has implemented a series of long-term measures to control the spread of COVID-19, however, the effects of these measures on other chronic and acute respiratory infectious diseases remain unclear. Tuberculosis (TB) and scarlet fever (SF) serve as representatives of chronic and acute respiratory...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258764/ https://www.ncbi.nlm.nih.gov/pubmed/37308561 http://dx.doi.org/10.1038/s41598-023-36263-5 |
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author | Zhou, Jian Chen, Hui-Juan Lu, Ting-Jia Chen, Pu Zhuang, Yan Li, Jin-Lan |
author_facet | Zhou, Jian Chen, Hui-Juan Lu, Ting-Jia Chen, Pu Zhuang, Yan Li, Jin-Lan |
author_sort | Zhou, Jian |
collection | PubMed |
description | China has implemented a series of long-term measures to control the spread of COVID-19, however, the effects of these measures on other chronic and acute respiratory infectious diseases remain unclear. Tuberculosis (TB) and scarlet fever (SF) serve as representatives of chronic and acute respiratory infectious diseases, respectively. In China’s Guizhou province, an area with a high prevalence of TB and SF, approximately 40,000 TB cases and hundreds of SF cases are reported annually. To assess the impact of COVID-19 prevention and control on TB and SF in Guizhou, the exponential smoothing method was employed to establish a prediction model for analyzing the influence of COVID-19 prevention and control on the number of TB and SF cases. Additionally, spatial aggregation analysis was utilized to describe spatial changes in TB and SF before and after the COVID-19 outbreak. The parameters of the TB and SF prediction models are R(2) = 0.856, BIC = 10.972 and R(2) = 0.714, BIC = 5.325, respectively. TB and SF cases declined rapidly at the onset of COVID-19 prevention and control measures, with the number of SF cases decreasing for about 3–6 months and the number of TB cases remaining in decline for 7 months after the 11th month. The spatial aggregation of TB and SF did not change significantly before and after the COVID-19 outbreak but exhibited a marked decrease. These findings suggest that China’s COVID-19 prevention and control measures also reduced the prevalence of TB and SF in Guizhou. These measures may have a long-term positive impact on TB, but a short-term effect on SF. Areas with high TB prevalence may continue to experience a decline due to the implementation of COVID-19 preventive measures in the future. |
format | Online Article Text |
id | pubmed-10258764 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102587642023-06-14 Impact of COVID-19 prevention and control on tuberculosis and scarlet fever in China’s Guizhou Zhou, Jian Chen, Hui-Juan Lu, Ting-Jia Chen, Pu Zhuang, Yan Li, Jin-Lan Sci Rep Article China has implemented a series of long-term measures to control the spread of COVID-19, however, the effects of these measures on other chronic and acute respiratory infectious diseases remain unclear. Tuberculosis (TB) and scarlet fever (SF) serve as representatives of chronic and acute respiratory infectious diseases, respectively. In China’s Guizhou province, an area with a high prevalence of TB and SF, approximately 40,000 TB cases and hundreds of SF cases are reported annually. To assess the impact of COVID-19 prevention and control on TB and SF in Guizhou, the exponential smoothing method was employed to establish a prediction model for analyzing the influence of COVID-19 prevention and control on the number of TB and SF cases. Additionally, spatial aggregation analysis was utilized to describe spatial changes in TB and SF before and after the COVID-19 outbreak. The parameters of the TB and SF prediction models are R(2) = 0.856, BIC = 10.972 and R(2) = 0.714, BIC = 5.325, respectively. TB and SF cases declined rapidly at the onset of COVID-19 prevention and control measures, with the number of SF cases decreasing for about 3–6 months and the number of TB cases remaining in decline for 7 months after the 11th month. The spatial aggregation of TB and SF did not change significantly before and after the COVID-19 outbreak but exhibited a marked decrease. These findings suggest that China’s COVID-19 prevention and control measures also reduced the prevalence of TB and SF in Guizhou. These measures may have a long-term positive impact on TB, but a short-term effect on SF. Areas with high TB prevalence may continue to experience a decline due to the implementation of COVID-19 preventive measures in the future. Nature Publishing Group UK 2023-06-12 /pmc/articles/PMC10258764/ /pubmed/37308561 http://dx.doi.org/10.1038/s41598-023-36263-5 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/) . |
spellingShingle | Article Zhou, Jian Chen, Hui-Juan Lu, Ting-Jia Chen, Pu Zhuang, Yan Li, Jin-Lan Impact of COVID-19 prevention and control on tuberculosis and scarlet fever in China’s Guizhou |
title | Impact of COVID-19 prevention and control on tuberculosis and scarlet fever in China’s Guizhou |
title_full | Impact of COVID-19 prevention and control on tuberculosis and scarlet fever in China’s Guizhou |
title_fullStr | Impact of COVID-19 prevention and control on tuberculosis and scarlet fever in China’s Guizhou |
title_full_unstemmed | Impact of COVID-19 prevention and control on tuberculosis and scarlet fever in China’s Guizhou |
title_short | Impact of COVID-19 prevention and control on tuberculosis and scarlet fever in China’s Guizhou |
title_sort | impact of covid-19 prevention and control on tuberculosis and scarlet fever in china’s guizhou |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258764/ https://www.ncbi.nlm.nih.gov/pubmed/37308561 http://dx.doi.org/10.1038/s41598-023-36263-5 |
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