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The influence of meteorological factors on tuberculosis incidence in Southwest China from 2006 to 2015.


ABSTRACT: The influence of meteorological determinants on tuberculosis (TB) incidence remains severely under-discussed, especially through the perspective of time series analysis. In the current study, we used a distributed lag nonlinear model (DLNM) to analyze a 10-year series of consecutive surveillance data. We found that, after effectively controlling for autocorrelation, the changes in meteorological factors related to temperature, humidity, wind and sunshine were significantly associated with subsequent fluctuations in TB incidence: average temperature was inversely associated with TB incidence at a lag period of 2 months; total precipitation and minimum relative humidity were also inversely associated with TB incidence at lag periods of 3 and 4 months, respectively; average wind velocity and total sunshine hours exhibited an instant rather than lagged influence on TB incidence. Our study results suggest that preceding meteorological factors may have a noticeable effect on future TB incidence; informed prevention and preparedness measures for TB can therefore be constructed on the basis of meteorological variations.

SUBMITTER: Xiao Y 

PROVIDER: S-EPMC6030127 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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The influence of meteorological factors on tuberculosis incidence in Southwest China from 2006 to 2015.

Xiao Yuanyuan Y   He Limei L   Chen Ying Y   Wang Qinying Q   Meng Qiong Q   Chang Wei W   Xiong Lifen L   Yu Zhen Z  

Scientific reports 20180703 1


The influence of meteorological determinants on tuberculosis (TB) incidence remains severely under-discussed, especially through the perspective of time series analysis. In the current study, we used a distributed lag nonlinear model (DLNM) to analyze a 10-year series of consecutive surveillance data. We found that, after effectively controlling for autocorrelation, the changes in meteorological factors related to temperature, humidity, wind and sunshine were significantly associated with subseq  ...[more]

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