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Analysis and predication of tuberculosis registration rates in Henan Province, China: an exponential smoothing model study

BACKGROUND: The World Health Organization End TB Strategy meant that compared with 2015 baseline, the reduction in pulmonary tuberculosis (PTB) incidence should be 20 and 50% in 2020 and 2025, respectively. The case number of PTB in China accounted for 9% of the global total in 2018, which ranked th...

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Autores principales: Zhang, Yan-Qiu, Li, Xin-Xu, Li, Wei-Bin, Jiang, Jian-Guo, Zhang, Guo-Long, Zhuang, Yan, Xu, Ji-Ying, Shi, Jie, Sun, Ding-Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7457775/
https://www.ncbi.nlm.nih.gov/pubmed/32867846
http://dx.doi.org/10.1186/s40249-020-00742-y
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author Zhang, Yan-Qiu
Li, Xin-Xu
Li, Wei-Bin
Jiang, Jian-Guo
Zhang, Guo-Long
Zhuang, Yan
Xu, Ji-Ying
Shi, Jie
Sun, Ding-Yong
author_facet Zhang, Yan-Qiu
Li, Xin-Xu
Li, Wei-Bin
Jiang, Jian-Guo
Zhang, Guo-Long
Zhuang, Yan
Xu, Ji-Ying
Shi, Jie
Sun, Ding-Yong
author_sort Zhang, Yan-Qiu
collection PubMed
description BACKGROUND: The World Health Organization End TB Strategy meant that compared with 2015 baseline, the reduction in pulmonary tuberculosis (PTB) incidence should be 20 and 50% in 2020 and 2025, respectively. The case number of PTB in China accounted for 9% of the global total in 2018, which ranked the second high in the world. From 2007 to 2019, 854 672 active PTB cases were registered and treated in Henan Province, China. This study was to assess whether the WHO milestones could be achieved in Henan Province. METHODS: The active PTB numbers in Henan Province from 2007 to 2019, registered in Chinese Tuberculosis Information Management System were analyzed to predict the active PTB registration rates in 2020 and 2025, which is conductive to early response measures to ensure the achievement of the WHO milestones. The time series model was created by monthly active PTB registration rates from 2007 to 2016, and the optimal model was verified by data from 2017 to 2019. The Ljung-Box Q statistic was used to evaluate the model. The statistically significant level is α = 0.05. Monthly active PTB registration rates and 95% confidence interval (CI) from 2020 to 2025 were predicted. RESULTS: High active PTB registration rates in March, April, May and June showed the seasonal variations. The exponential smoothing winter’s multiplication model was selected as the best-fitting model. The predicted values were approximately consistent with the observed ones from 2017 to 2019. The annual active PTB registration rates were predicted as 49.1 (95% CI: 36.2–62.0) per 100 000 population and 34.4 (95% CI: 18.6–50.2) per 100 000 population in 2020 and 2025, respectively. Compared with the active PTB registration rate in 2015, the reduction will reach 23.7% (95% CI, 3.2–44.1%) and 46.8% (95% CI, 21.4–72.1%) in 2020 and 2025, respectively. CONCLUSIONS: The high active PTB registration rates in spring and early summer indicate that high risk of tuberculosis infection in late autumn and winter in Henan Province. Without regard to the CI, the first milestone of WHO End TB Strategy in 2020 will be achieved. However, the second milestone in 2025 will not be easily achieved unless there are early response measures in Henan Province, China.
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spelling pubmed-74577752020-09-02 Analysis and predication of tuberculosis registration rates in Henan Province, China: an exponential smoothing model study Zhang, Yan-Qiu Li, Xin-Xu Li, Wei-Bin Jiang, Jian-Guo Zhang, Guo-Long Zhuang, Yan Xu, Ji-Ying Shi, Jie Sun, Ding-Yong Infect Dis Poverty Research Article BACKGROUND: The World Health Organization End TB Strategy meant that compared with 2015 baseline, the reduction in pulmonary tuberculosis (PTB) incidence should be 20 and 50% in 2020 and 2025, respectively. The case number of PTB in China accounted for 9% of the global total in 2018, which ranked the second high in the world. From 2007 to 2019, 854 672 active PTB cases were registered and treated in Henan Province, China. This study was to assess whether the WHO milestones could be achieved in Henan Province. METHODS: The active PTB numbers in Henan Province from 2007 to 2019, registered in Chinese Tuberculosis Information Management System were analyzed to predict the active PTB registration rates in 2020 and 2025, which is conductive to early response measures to ensure the achievement of the WHO milestones. The time series model was created by monthly active PTB registration rates from 2007 to 2016, and the optimal model was verified by data from 2017 to 2019. The Ljung-Box Q statistic was used to evaluate the model. The statistically significant level is α = 0.05. Monthly active PTB registration rates and 95% confidence interval (CI) from 2020 to 2025 were predicted. RESULTS: High active PTB registration rates in March, April, May and June showed the seasonal variations. The exponential smoothing winter’s multiplication model was selected as the best-fitting model. The predicted values were approximately consistent with the observed ones from 2017 to 2019. The annual active PTB registration rates were predicted as 49.1 (95% CI: 36.2–62.0) per 100 000 population and 34.4 (95% CI: 18.6–50.2) per 100 000 population in 2020 and 2025, respectively. Compared with the active PTB registration rate in 2015, the reduction will reach 23.7% (95% CI, 3.2–44.1%) and 46.8% (95% CI, 21.4–72.1%) in 2020 and 2025, respectively. CONCLUSIONS: The high active PTB registration rates in spring and early summer indicate that high risk of tuberculosis infection in late autumn and winter in Henan Province. Without regard to the CI, the first milestone of WHO End TB Strategy in 2020 will be achieved. However, the second milestone in 2025 will not be easily achieved unless there are early response measures in Henan Province, China. BioMed Central 2020-08-31 /pmc/articles/PMC7457775/ /pubmed/32867846 http://dx.doi.org/10.1186/s40249-020-00742-y Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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, Yan-Qiu
Li, Xin-Xu
Li, Wei-Bin
Jiang, Jian-Guo
Zhang, Guo-Long
Zhuang, Yan
Xu, Ji-Ying
Shi, Jie
Sun, Ding-Yong
Analysis and predication of tuberculosis registration rates in Henan Province, China: an exponential smoothing model study
title Analysis and predication of tuberculosis registration rates in Henan Province, China: an exponential smoothing model study
title_full Analysis and predication of tuberculosis registration rates in Henan Province, China: an exponential smoothing model study
title_fullStr Analysis and predication of tuberculosis registration rates in Henan Province, China: an exponential smoothing model study
title_full_unstemmed Analysis and predication of tuberculosis registration rates in Henan Province, China: an exponential smoothing model study
title_short Analysis and predication of tuberculosis registration rates in Henan Province, China: an exponential smoothing model study
title_sort analysis and predication of tuberculosis registration rates in henan province, china: an exponential smoothing model study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7457775/
https://www.ncbi.nlm.nih.gov/pubmed/32867846
http://dx.doi.org/10.1186/s40249-020-00742-y
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