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Assessing the spatial heterogeneity of tuberculosis in a population with internal migration in China: a retrospective population-based study

BACKGROUND: Internal migrants pose a critical threat to eliminating Tuberculosis (TB) in many high-burden countries. Understanding the influential pattern of the internal migrant population in the incidence of tuberculosis is crucial for controlling and preventing the disease. We used epidemiologica...

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Autores principales: Lin, Honghua, Zhang, Rui, Wu, Zheyuan, Li, Minjuan, Wu, Jiamei, Shen, Xin, Yang, Chongguang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266412/
https://www.ncbi.nlm.nih.gov/pubmed/37325311
http://dx.doi.org/10.3389/fpubh.2023.1155146
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author Lin, Honghua
Zhang, Rui
Wu, Zheyuan
Li, Minjuan
Wu, Jiamei
Shen, Xin
Yang, Chongguang
author_facet Lin, Honghua
Zhang, Rui
Wu, Zheyuan
Li, Minjuan
Wu, Jiamei
Shen, Xin
Yang, Chongguang
author_sort Lin, Honghua
collection PubMed
description BACKGROUND: Internal migrants pose a critical threat to eliminating Tuberculosis (TB) in many high-burden countries. Understanding the influential pattern of the internal migrant population in the incidence of tuberculosis is crucial for controlling and preventing the disease. We used epidemiological and spatial data to analyze the spatial distribution of tuberculosis and identify potential risk factors for spatial heterogeneity. METHODS: We conducted a population-based, retrospective study and identified all incident bacterially-positive TB cases between January 1st, 2009, and December 31st, 2016, in Shanghai, China. We used Getis-Ord Gi* statistics and spatial relative risk methods to explore spatial heterogeneity and identify regions with spatial clusters of TB cases, and then used logistic regression method to estimate individual-level risk factors for notified migrant TB and spatial clusters. A hierarchical Bayesian spatial model was used to identify the attributable location-specific factors. RESULTS: Overall, 27,383 bacterially-positive tuberculosis patients were notified for analysis, with 42.54% (11,649) of them being migrants. The age-adjusted notification rate of TB among migrants was much higher than among residents. Migrants (aOR, 1.85; 95%CI, 1.65-2.08) and active screening (aOR, 3.13; 95%CI, 2.60-3.77) contributed significantly to the formation of TB high-spatial clusters. With the hierarchical Bayesian modeling, the presence of industrial parks (RR, 1.420; 95%CI, 1.023-1.974) and migrants (RR, 1.121; 95%CI, 1.007-1.247) were the risk factors for increased TB disease at the county level. CONCLUSION: We identified a significant spatial heterogeneity of tuberculosis in Shanghai, one of the typical megacities with massive migration. Internal migrants play an essential role in the disease burden and the spatial heterogeneity of TB in urban settings. Optimized disease control and prevention strategies, including targeted interventions based on the current epidemiological heterogeneity, warrant further evaluation to fuel the TB eradication process in urban China.
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spelling pubmed-102664122023-06-15 Assessing the spatial heterogeneity of tuberculosis in a population with internal migration in China: a retrospective population-based study Lin, Honghua Zhang, Rui Wu, Zheyuan Li, Minjuan Wu, Jiamei Shen, Xin Yang, Chongguang Front Public Health Public Health BACKGROUND: Internal migrants pose a critical threat to eliminating Tuberculosis (TB) in many high-burden countries. Understanding the influential pattern of the internal migrant population in the incidence of tuberculosis is crucial for controlling and preventing the disease. We used epidemiological and spatial data to analyze the spatial distribution of tuberculosis and identify potential risk factors for spatial heterogeneity. METHODS: We conducted a population-based, retrospective study and identified all incident bacterially-positive TB cases between January 1st, 2009, and December 31st, 2016, in Shanghai, China. We used Getis-Ord Gi* statistics and spatial relative risk methods to explore spatial heterogeneity and identify regions with spatial clusters of TB cases, and then used logistic regression method to estimate individual-level risk factors for notified migrant TB and spatial clusters. A hierarchical Bayesian spatial model was used to identify the attributable location-specific factors. RESULTS: Overall, 27,383 bacterially-positive tuberculosis patients were notified for analysis, with 42.54% (11,649) of them being migrants. The age-adjusted notification rate of TB among migrants was much higher than among residents. Migrants (aOR, 1.85; 95%CI, 1.65-2.08) and active screening (aOR, 3.13; 95%CI, 2.60-3.77) contributed significantly to the formation of TB high-spatial clusters. With the hierarchical Bayesian modeling, the presence of industrial parks (RR, 1.420; 95%CI, 1.023-1.974) and migrants (RR, 1.121; 95%CI, 1.007-1.247) were the risk factors for increased TB disease at the county level. CONCLUSION: We identified a significant spatial heterogeneity of tuberculosis in Shanghai, one of the typical megacities with massive migration. Internal migrants play an essential role in the disease burden and the spatial heterogeneity of TB in urban settings. Optimized disease control and prevention strategies, including targeted interventions based on the current epidemiological heterogeneity, warrant further evaluation to fuel the TB eradication process in urban China. Frontiers Media S.A. 2023-05-30 /pmc/articles/PMC10266412/ /pubmed/37325311 http://dx.doi.org/10.3389/fpubh.2023.1155146 Text en Copyright © 2023 Lin, Zhang, Wu, Li, Wu, Shen and Yang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Lin, Honghua
Zhang, Rui
Wu, Zheyuan
Li, Minjuan
Wu, Jiamei
Shen, Xin
Yang, Chongguang
Assessing the spatial heterogeneity of tuberculosis in a population with internal migration in China: a retrospective population-based study
title Assessing the spatial heterogeneity of tuberculosis in a population with internal migration in China: a retrospective population-based study
title_full Assessing the spatial heterogeneity of tuberculosis in a population with internal migration in China: a retrospective population-based study
title_fullStr Assessing the spatial heterogeneity of tuberculosis in a population with internal migration in China: a retrospective population-based study
title_full_unstemmed Assessing the spatial heterogeneity of tuberculosis in a population with internal migration in China: a retrospective population-based study
title_short Assessing the spatial heterogeneity of tuberculosis in a population with internal migration in China: a retrospective population-based study
title_sort assessing the spatial heterogeneity of tuberculosis in a population with internal migration in china: a retrospective population-based study
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266412/
https://www.ncbi.nlm.nih.gov/pubmed/37325311
http://dx.doi.org/10.3389/fpubh.2023.1155146
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