TY - JOUR
T1 - The spatio-temporal analysis of the incidence of tuberculosis and the associated factors in mainland China, 2009-2015
AU - Li, Qihuan
AU - Liu, Mengyang
AU - Zhang, Yingjie
AU - Wu, Shangwu
AU - Yang, Yang
AU - Liu, Yue
AU - Amsalu, Endawoke
AU - Tao, L.
AU - Liu, Xiangtong
AU - Zhang, Feng
AU - Luo, Yanxia
AU - Yang, Xinghua
AU - Li, Weimin
AU - Li, Xia
AU - Wang, Wei
AU - Wang, Xiaonan
AU - Guo, Xiuhua
N1 - Publisher Copyright:
© 2019
PY - 2019/11
Y1 - 2019/11
N2 - Background: Tuberculosis is still one of the most infectious diseases in China. This study aimed to explore the spatio-temporal distribution of TB and the associated factors in mainland China from 2009 to 2015. Methods: A Bayesian spatio-temporal model was utilized to analyse the correlation of socio-economic, healthcare, demographic and meteorological factors with the population level number of TB. Results: The Bayesian spatio-temporal analysis showed that for the population level number of TB, the estimated parameters of the ratio of males to females, the number of beds in medical institutions, the population density, the proportion of the population that is rural, the amount of precipitation, the largest wind speed and the sunshine duration were 0.556, 0.197, 0.199, 29.03,0.1958, 0.0854 and 0.2117, respectively, demonstrating positive associations. However, health personnel, per capita annual gross domestic product, minimum temperature and humidity indicated negative associations, and the corresponding parameters were −0.050, −0.095, −0.0022 and −0.0070, respectively. Conclusions: Socio-economic, number of health personnel, demographic and meteorological factors could affect the case notification number of TB to different degrees and in different directions.
AB - Background: Tuberculosis is still one of the most infectious diseases in China. This study aimed to explore the spatio-temporal distribution of TB and the associated factors in mainland China from 2009 to 2015. Methods: A Bayesian spatio-temporal model was utilized to analyse the correlation of socio-economic, healthcare, demographic and meteorological factors with the population level number of TB. Results: The Bayesian spatio-temporal analysis showed that for the population level number of TB, the estimated parameters of the ratio of males to females, the number of beds in medical institutions, the population density, the proportion of the population that is rural, the amount of precipitation, the largest wind speed and the sunshine duration were 0.556, 0.197, 0.199, 29.03,0.1958, 0.0854 and 0.2117, respectively, demonstrating positive associations. However, health personnel, per capita annual gross domestic product, minimum temperature and humidity indicated negative associations, and the corresponding parameters were −0.050, −0.095, −0.0022 and −0.0070, respectively. Conclusions: Socio-economic, number of health personnel, demographic and meteorological factors could affect the case notification number of TB to different degrees and in different directions.
KW - Associated factors
KW - Bayesian spatio-temporal model
KW - Sputum smear positive/negative tuberculosis
KW - Tuberculosis
UR - http://www.scopus.com/inward/record.url?scp=85069639738&partnerID=8YFLogxK
U2 - 10.1016/j.meegid.2019.103949
DO - 10.1016/j.meegid.2019.103949
M3 - Article
C2 - 31279820
AN - SCOPUS:85069639738
SN - 1567-1348
VL - 75
JO - Infection, Genetics and Evolution
JF - Infection, Genetics and Evolution
M1 - 103949
ER -
