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Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China

BACKGROUND: Guangxi is one of the provinces having the highest notification rate of tuberculosis in China. However, spatial and temporal patterns and the association between environmental diversity and tuberculosis notification are still unclear. OBJECTIVE: To detect the spatiotemporal pattern of tu...

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Autores principales: Cui, Zhezhe, Lin, Dingwen, Chongsuvivatwong, Virasakdi, Zhao, Jinming, Lin, Mei, Ou, Jing, Zhao, Jinghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6497253/
https://www.ncbi.nlm.nih.gov/pubmed/31048894
http://dx.doi.org/10.1371/journal.pone.0212051
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author Cui, Zhezhe
Lin, Dingwen
Chongsuvivatwong, Virasakdi
Zhao, Jinming
Lin, Mei
Ou, Jing
Zhao, Jinghua
author_facet Cui, Zhezhe
Lin, Dingwen
Chongsuvivatwong, Virasakdi
Zhao, Jinming
Lin, Mei
Ou, Jing
Zhao, Jinghua
author_sort Cui, Zhezhe
collection PubMed
description BACKGROUND: Guangxi is one of the provinces having the highest notification rate of tuberculosis in China. However, spatial and temporal patterns and the association between environmental diversity and tuberculosis notification are still unclear. OBJECTIVE: To detect the spatiotemporal pattern of tuberculosis notification rates from 2010 to 2016 and its potential association with ecological environmental factors in Guangxi Zhuang autonomous region, China. METHODS: We performed a spatiotemporal analysis with prediction using time series analysis, Moran’s I global and local spatial autocorrelation statistics, and space-time scan statistics to detect temporal and spatial clusters of tuberculosis notifications in Guangxi between 2010 and 2016. Spatial panel models were employed to identify potential associating factors. RESULTS: The number of reported cases peaked in spring and summer and decreased in autumn and winter. The predicted number of reported cases was 49,946 in 2017. Moran's I global statistics were greater than 0 (0.363–0.536) during the study period. The most significant hot spots were mainly located in the central area. The eastern area exhibited a low-low relation. By the space-time scanning, the clusters identified were similar to those of the local autocorrelation statistics, and were clustered toward the early part of 2016. Duration of sunshine, per capita gross domestic product, the treatment success rate of tuberculosis and participation rate of the new cooperative medical care insurance scheme in rural areas had a significant negative association with tuberculosis notification rates. CONCLUSION: The notification rate of tuberculosis in Guangxi remains high, with the highest notification cluster located in the central region. The notification rate is associated with economic level, treatment success rate and participation in the new cooperative medical care insurance scheme.
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spelling pubmed-64972532019-05-17 Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China Cui, Zhezhe Lin, Dingwen Chongsuvivatwong, Virasakdi Zhao, Jinming Lin, Mei Ou, Jing Zhao, Jinghua PLoS One Research Article BACKGROUND: Guangxi is one of the provinces having the highest notification rate of tuberculosis in China. However, spatial and temporal patterns and the association between environmental diversity and tuberculosis notification are still unclear. OBJECTIVE: To detect the spatiotemporal pattern of tuberculosis notification rates from 2010 to 2016 and its potential association with ecological environmental factors in Guangxi Zhuang autonomous region, China. METHODS: We performed a spatiotemporal analysis with prediction using time series analysis, Moran’s I global and local spatial autocorrelation statistics, and space-time scan statistics to detect temporal and spatial clusters of tuberculosis notifications in Guangxi between 2010 and 2016. Spatial panel models were employed to identify potential associating factors. RESULTS: The number of reported cases peaked in spring and summer and decreased in autumn and winter. The predicted number of reported cases was 49,946 in 2017. Moran's I global statistics were greater than 0 (0.363–0.536) during the study period. The most significant hot spots were mainly located in the central area. The eastern area exhibited a low-low relation. By the space-time scanning, the clusters identified were similar to those of the local autocorrelation statistics, and were clustered toward the early part of 2016. Duration of sunshine, per capita gross domestic product, the treatment success rate of tuberculosis and participation rate of the new cooperative medical care insurance scheme in rural areas had a significant negative association with tuberculosis notification rates. CONCLUSION: The notification rate of tuberculosis in Guangxi remains high, with the highest notification cluster located in the central region. The notification rate is associated with economic level, treatment success rate and participation in the new cooperative medical care insurance scheme. Public Library of Science 2019-05-02 /pmc/articles/PMC6497253/ /pubmed/31048894 http://dx.doi.org/10.1371/journal.pone.0212051 Text en © 2019 Cui et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Cui, Zhezhe
Lin, Dingwen
Chongsuvivatwong, Virasakdi
Zhao, Jinming
Lin, Mei
Ou, Jing
Zhao, Jinghua
Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China
title Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China
title_full Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China
title_fullStr Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China
title_full_unstemmed Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China
title_short Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China
title_sort spatiotemporal patterns and ecological factors of tuberculosis notification: a spatial panel data analysis in guangxi, china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6497253/
https://www.ncbi.nlm.nih.gov/pubmed/31048894
http://dx.doi.org/10.1371/journal.pone.0212051
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