Changqiang Zhou, Tao Li, Jian Du, Dapeng Yin, Xiujun Li, Shixue Li
{"title":"通过了解中国海南省的流行病学特征和风险因素,努力消除结核病","authors":"Changqiang Zhou, Tao Li, Jian Du, Dapeng Yin, Xiujun Li, Shixue Li","doi":"10.1186/s40249-024-01188-2","DOIUrl":null,"url":null,"abstract":"The disease burden of tuberculosis (TB) was heavy in Hainan Province, China, and the information on transmission patterns was limited with few studies. This atudy aims to further explore the epidemiological characteristics and influencing factors of TB in Hainan Province, and thereby contribute valuable scientific evidences for TB elimination in Hainan Province. The TB notification data in Hainan Province from 2013 to 2022 were collected from the Chinese National Disease Control Information System Tuberculosis Surveillance System, along with socio-economic data. The spatial–temporal and population distributions were analyzed, and spatial autocorrelation analysis was conducted to explore TB notification rate clustering. In addition, the epidemiological characteristics of the cases among in-country migrants were described, and the delay pattern in seeking medical care was investigated. Finally, a geographically and temporally weighted regression (GTWR) model was adopted to analyze the relationship between TB notification rate and socio-economic indicators. The tailored control suggestions in different regions for TB elimination was provided by understanding epidemiological characteristics and risk factors obtained by GTWR. From 2013 to 2022, 64,042 cases of TB were notified in Hainan Province. The estimated annual percentage change of TB notification rate in Hainan Province from 2013 to 2020 was − 6.88% [95% confidence interval (CI): − 5.30%, − 3.69%], with higher rates in central and southern regions. The majority of patients were males (76.33%) and farmers (67.80%). Cases among in-country migrants primarily originated from Sichuan (369 cases), Heilongjiang (267 cases), Hunan (236 cases), Guangdong (174 cases), and Guangxi (139 cases), accounting for 53%. The majority (98.83%) of TB cases were notified through passive case finding approaches, with delay in seeking care. The GTWR analysis showed that gross domestic product per capita, the number of medical institutions and health personnel per 10,000 people were main factors affecting the high TB notification rates in some regions in Hainan Province. Different regional tailored measures such as more TB specialized hospitals were proposed based on the characteristics of each region. The notification rate of TB in Hainan Province has been declining overall but still remained high in central and southern regions. Particular attention should be paid to the prevalence of TB among males, farmers, and out-of-province migrant populations. The notification rate was also influenced by economic development and medical conditions, indicating the need of more TB specialized hospitals, active surveillance and other tailored prevention and control measures to promote the progress of TB elimination in Hainan Province.","PeriodicalId":13587,"journal":{"name":"Infectious Diseases of Poverty","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Toward tuberculosis elimination by understanding epidemiologic characteristics and risk factors in Hainan Province, China\",\"authors\":\"Changqiang Zhou, Tao Li, Jian Du, Dapeng Yin, Xiujun Li, Shixue Li\",\"doi\":\"10.1186/s40249-024-01188-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The disease burden of tuberculosis (TB) was heavy in Hainan Province, China, and the information on transmission patterns was limited with few studies. This atudy aims to further explore the epidemiological characteristics and influencing factors of TB in Hainan Province, and thereby contribute valuable scientific evidences for TB elimination in Hainan Province. The TB notification data in Hainan Province from 2013 to 2022 were collected from the Chinese National Disease Control Information System Tuberculosis Surveillance System, along with socio-economic data. The spatial–temporal and population distributions were analyzed, and spatial autocorrelation analysis was conducted to explore TB notification rate clustering. In addition, the epidemiological characteristics of the cases among in-country migrants were described, and the delay pattern in seeking medical care was investigated. Finally, a geographically and temporally weighted regression (GTWR) model was adopted to analyze the relationship between TB notification rate and socio-economic indicators. The tailored control suggestions in different regions for TB elimination was provided by understanding epidemiological characteristics and risk factors obtained by GTWR. From 2013 to 2022, 64,042 cases of TB were notified in Hainan Province. The estimated annual percentage change of TB notification rate in Hainan Province from 2013 to 2020 was − 6.88% [95% confidence interval (CI): − 5.30%, − 3.69%], with higher rates in central and southern regions. The majority of patients were males (76.33%) and farmers (67.80%). Cases among in-country migrants primarily originated from Sichuan (369 cases), Heilongjiang (267 cases), Hunan (236 cases), Guangdong (174 cases), and Guangxi (139 cases), accounting for 53%. The majority (98.83%) of TB cases were notified through passive case finding approaches, with delay in seeking care. The GTWR analysis showed that gross domestic product per capita, the number of medical institutions and health personnel per 10,000 people were main factors affecting the high TB notification rates in some regions in Hainan Province. Different regional tailored measures such as more TB specialized hospitals were proposed based on the characteristics of each region. The notification rate of TB in Hainan Province has been declining overall but still remained high in central and southern regions. Particular attention should be paid to the prevalence of TB among males, farmers, and out-of-province migrant populations. 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Toward tuberculosis elimination by understanding epidemiologic characteristics and risk factors in Hainan Province, China
The disease burden of tuberculosis (TB) was heavy in Hainan Province, China, and the information on transmission patterns was limited with few studies. This atudy aims to further explore the epidemiological characteristics and influencing factors of TB in Hainan Province, and thereby contribute valuable scientific evidences for TB elimination in Hainan Province. The TB notification data in Hainan Province from 2013 to 2022 were collected from the Chinese National Disease Control Information System Tuberculosis Surveillance System, along with socio-economic data. The spatial–temporal and population distributions were analyzed, and spatial autocorrelation analysis was conducted to explore TB notification rate clustering. In addition, the epidemiological characteristics of the cases among in-country migrants were described, and the delay pattern in seeking medical care was investigated. Finally, a geographically and temporally weighted regression (GTWR) model was adopted to analyze the relationship between TB notification rate and socio-economic indicators. The tailored control suggestions in different regions for TB elimination was provided by understanding epidemiological characteristics and risk factors obtained by GTWR. From 2013 to 2022, 64,042 cases of TB were notified in Hainan Province. The estimated annual percentage change of TB notification rate in Hainan Province from 2013 to 2020 was − 6.88% [95% confidence interval (CI): − 5.30%, − 3.69%], with higher rates in central and southern regions. The majority of patients were males (76.33%) and farmers (67.80%). Cases among in-country migrants primarily originated from Sichuan (369 cases), Heilongjiang (267 cases), Hunan (236 cases), Guangdong (174 cases), and Guangxi (139 cases), accounting for 53%. The majority (98.83%) of TB cases were notified through passive case finding approaches, with delay in seeking care. The GTWR analysis showed that gross domestic product per capita, the number of medical institutions and health personnel per 10,000 people were main factors affecting the high TB notification rates in some regions in Hainan Province. Different regional tailored measures such as more TB specialized hospitals were proposed based on the characteristics of each region. The notification rate of TB in Hainan Province has been declining overall but still remained high in central and southern regions. Particular attention should be paid to the prevalence of TB among males, farmers, and out-of-province migrant populations. The notification rate was also influenced by economic development and medical conditions, indicating the need of more TB specialized hospitals, active surveillance and other tailored prevention and control measures to promote the progress of TB elimination in Hainan Province.
期刊介绍:
Infectious Diseases of Poverty is a peer-reviewed, open access journal that focuses on essential public health questions related to infectious diseases of poverty. It covers a wide range of topics and methods, including the biology of pathogens and vectors, diagnosis and detection, treatment and case management, epidemiology and modeling, zoonotic hosts and animal reservoirs, control strategies and implementation, new technologies, and their application.
The journal also explores the impact of transdisciplinary or multisectoral approaches on health systems, ecohealth, environmental management, and innovative technologies. It aims to provide a platform for the exchange of research and ideas that can contribute to the improvement of public health in resource-limited settings.
In summary, Infectious Diseases of Poverty aims to address the urgent challenges posed by infectious diseases in impoverished populations. By publishing high-quality research in various areas, the journal seeks to advance our understanding of these diseases and contribute to the development of effective strategies for prevention, diagnosis, and treatment.