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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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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. |
format | Online Article Text |
id | pubmed-6497253 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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