Cargando…

Identification and Prediction of Tuberculosis in Eastern China: Analyses from 10-year Population-based Notification Data in Zhejiang Province, China

Tuberculosis, a severe infectious disease caused by the Mycobacterium tuberculosis, arouses huge concerns globally. In this study, a total of 331,594 TB cases in Zhejiang Province were notified during the period of 2009–2018 with the gender ratio of male to female 2.16:1. The notified TB incidences...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Kui, Li, Tao, Vongpradith, Avina, Wang, Fei, Peng, Ying, Wang, Wei, Chai, Chengliang, Chen, Songhua, Zhang, Yu, Zhou, Lin, Chen, Xinyi, Bian, Qiao, Chen, Bin, Wang, Xiaomeng, Jiang, Jianmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7198485/
https://www.ncbi.nlm.nih.gov/pubmed/32367050
http://dx.doi.org/10.1038/s41598-020-64387-5
_version_ 1783528994783625216
author Liu, Kui
Li, Tao
Vongpradith, Avina
Wang, Fei
Peng, Ying
Wang, Wei
Chai, Chengliang
Chen, Songhua
Zhang, Yu
Zhou, Lin
Chen, Xinyi
Bian, Qiao
Chen, Bin
Wang, Xiaomeng
Jiang, Jianmin
author_facet Liu, Kui
Li, Tao
Vongpradith, Avina
Wang, Fei
Peng, Ying
Wang, Wei
Chai, Chengliang
Chen, Songhua
Zhang, Yu
Zhou, Lin
Chen, Xinyi
Bian, Qiao
Chen, Bin
Wang, Xiaomeng
Jiang, Jianmin
author_sort Liu, Kui
collection PubMed
description Tuberculosis, a severe infectious disease caused by the Mycobacterium tuberculosis, arouses huge concerns globally. In this study, a total of 331,594 TB cases in Zhejiang Province were notified during the period of 2009–2018 with the gender ratio of male to female 2.16:1. The notified TB incidences demonstrated a continuously declining trend from 75.38/100,000 to 52.25/100,000. Seasonally, the notified TB cases presented as low in January and February closely followed an apparent rise in March and April. Further stratification analysis by both genders demonstrated the double peak phenomenon in the younger population (“15–35”) and the elders (“>55”) of the whole group. Results from the rate difference (RD) analysis showed that the rising TB incidence mainly presented in the young group of “15–20” and elder group of “65–70”, implying that some implementations such as the increased frequency of checkup in specific student groups and strengthening of elder health examination could be explored and integrated into available health policy. Finally, the SARIMA (2,0,2) (0,1,1)12 was determined as the optimal prediction model, which could be used in the further prediction of TB in Zhejiang Province.
format Online
Article
Text
id pubmed-7198485
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-71984852020-05-08 Identification and Prediction of Tuberculosis in Eastern China: Analyses from 10-year Population-based Notification Data in Zhejiang Province, China Liu, Kui Li, Tao Vongpradith, Avina Wang, Fei Peng, Ying Wang, Wei Chai, Chengliang Chen, Songhua Zhang, Yu Zhou, Lin Chen, Xinyi Bian, Qiao Chen, Bin Wang, Xiaomeng Jiang, Jianmin Sci Rep Article Tuberculosis, a severe infectious disease caused by the Mycobacterium tuberculosis, arouses huge concerns globally. In this study, a total of 331,594 TB cases in Zhejiang Province were notified during the period of 2009–2018 with the gender ratio of male to female 2.16:1. The notified TB incidences demonstrated a continuously declining trend from 75.38/100,000 to 52.25/100,000. Seasonally, the notified TB cases presented as low in January and February closely followed an apparent rise in March and April. Further stratification analysis by both genders demonstrated the double peak phenomenon in the younger population (“15–35”) and the elders (“>55”) of the whole group. Results from the rate difference (RD) analysis showed that the rising TB incidence mainly presented in the young group of “15–20” and elder group of “65–70”, implying that some implementations such as the increased frequency of checkup in specific student groups and strengthening of elder health examination could be explored and integrated into available health policy. Finally, the SARIMA (2,0,2) (0,1,1)12 was determined as the optimal prediction model, which could be used in the further prediction of TB in Zhejiang Province. Nature Publishing Group UK 2020-05-04 /pmc/articles/PMC7198485/ /pubmed/32367050 http://dx.doi.org/10.1038/s41598-020-64387-5 Text en © The Author(s) 2020 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Liu, Kui
Li, Tao
Vongpradith, Avina
Wang, Fei
Peng, Ying
Wang, Wei
Chai, Chengliang
Chen, Songhua
Zhang, Yu
Zhou, Lin
Chen, Xinyi
Bian, Qiao
Chen, Bin
Wang, Xiaomeng
Jiang, Jianmin
Identification and Prediction of Tuberculosis in Eastern China: Analyses from 10-year Population-based Notification Data in Zhejiang Province, China
title Identification and Prediction of Tuberculosis in Eastern China: Analyses from 10-year Population-based Notification Data in Zhejiang Province, China
title_full Identification and Prediction of Tuberculosis in Eastern China: Analyses from 10-year Population-based Notification Data in Zhejiang Province, China
title_fullStr Identification and Prediction of Tuberculosis in Eastern China: Analyses from 10-year Population-based Notification Data in Zhejiang Province, China
title_full_unstemmed Identification and Prediction of Tuberculosis in Eastern China: Analyses from 10-year Population-based Notification Data in Zhejiang Province, China
title_short Identification and Prediction of Tuberculosis in Eastern China: Analyses from 10-year Population-based Notification Data in Zhejiang Province, China
title_sort identification and prediction of tuberculosis in eastern china: analyses from 10-year population-based notification data in zhejiang province, china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7198485/
https://www.ncbi.nlm.nih.gov/pubmed/32367050
http://dx.doi.org/10.1038/s41598-020-64387-5
work_keys_str_mv AT liukui identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT litao identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT vongpradithavina identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT wangfei identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT pengying identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT wangwei identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT chaichengliang identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT chensonghua identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT zhangyu identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT zhoulin identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT chenxinyi identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT bianqiao identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT chenbin identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT wangxiaomeng identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina
AT jiangjianmin identificationandpredictionoftuberculosisineasternchinaanalysesfrom10yearpopulationbasednotificationdatainzhejiangprovincechina