Literature DB >> 33737676

Influential factors and spatial-temporal distribution of tuberculosis in mainland China.

Siyu Bie1, Xijian Hu2, Huiguo Zhang1, Kai Wang3, Zhihui Dou4.   

Abstract

Tuberculosis (TB) is an infectious disease that threatens human safety. Mainland China is an area with a high incidence of tuberculosis, and the task of tuberculosis prevention and treatment is arduous. This paper aims to study the impact of seven influencing factors and spatial-temporal distribution of the relative risk (RR) of tuberculosis in mainland China using the spatial-temporal distribution model and INLA algorithm. The relative risks and confidence intervals (CI) corresponding to average relative humidity, monthly average precipitation, monthly average sunshine duration and monthly per capita GDP were 1.018 (95% CI 1.001-1.034), 1.014 (95% CI 1.006-1.023), 1.026 (95% CI 1.014-1.039) and 1.025 (95% CI 1.011-1.040). The relative risk for average temperature and pressure were 0.956 (95% CI 0.942-0.969) and 0.767 (95% CI 0.664-0.875). Spatially, the two provinces with the highest relative risks are Xinjiang and Guizhou, and the remaining provinces with higher relative risks were mostly concentrated in the Northwest and South China regions. Temporally, the relative risk decreased year by year from 2013 to 2015. It was higher from February to May each year and was most significant in March. It decreased from June to December. Average relative humidity, monthly average precipitation, monthly average sunshine duration and monthly per capita GDP had positive effects on the relative risk of tuberculosis. The average temperature and pressure had negative effects. The average wind speed had no significant effect. Mainland China should adapt measures to local conditions and develop tuberculosis prevention and control strategies based on the characteristics of different regions and time.

Entities:  

Year:  2021        PMID: 33737676     DOI: 10.1038/s41598-021-85781-7

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  1 in total

1.  Estimates of tuberculosis mortality rates in China using the disease surveillance point system, 2004-2010.

Authors:  Hui Zhang; Fei Huang; Wei Chen; Xin DU; Mai Geng Zhou; Jia Hu; Li Xia Wang
Journal:  Biomed Environ Sci       Date:  2012-08       Impact factor: 3.118

  1 in total
  2 in total

1.  Identifying spatiotemporal patterns of COVID-19 transmissions and the drivers of the patterns in Toronto: a Bayesian hierarchical spatiotemporal modelling.

Authors:  Nushrat Nazia; Jane Law; Zahid Ahmad Butt
Journal:  Sci Rep       Date:  2022-06-07       Impact factor: 4.996

2.  Modeling and Predicting Pulmonary Tuberculosis Incidence and Its Association with Air Pollution and Meteorological Factors Using an ARIMAX Model: An Ecological Study in Ningbo of China.

Authors:  Yun-Peng Chen; Le-Fan Liu; Yang Che; Jing Huang; Guo-Xing Li; Guo-Xin Sang; Zhi-Qiang Xuan; Tian-Feng He
Journal:  Int J Environ Res Public Health       Date:  2022-04-28       Impact factor: 4.614

  2 in total

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