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Spatial and temporal clustering analysis of tuberculosis in the mainland of China at the prefecture level, 2005–2015

Authors :
Meng-Yang Liu
Qi-Huan Li
Ying-Jie Zhang
Yuan Ma
Yue Liu
Wei Feng
Cheng-Bei Hou
Endawoke Amsalu
Xia Li
Wei Wang
Wei-Min Li
Xiu-Hua Guo
Source :
Infectious Diseases of Poverty, Vol 7, Iss 1, Pp 1-10 (2018)
Publication Year :
2018
Publisher :
BMC, 2018.

Abstract

Abstract Background Tuberculosis (TB) is still one of the most serious infectious diseases in the mainland of China. So it was urgent for the formulation of more effective measures to prevent and control it. Methods The data of reported TB cases in 340 prefectures from the mainland of China were extracted from the China Information System for Disease Control and Prevention (CISDCP) during January 2005 to December 2015. The Kulldorff’s retrospective space-time scan statistics was used to identify the temporal, spatial and spatio-temporal clusters of reported TB in the mainland of China by using the discrete Poisson probability model. Spatio-temporal clusters of sputum smear-positive (SS+) reported TB and sputum smear-negative (SS-) reported TB were also detected at the prefecture level. Results A total of 10 200 528 reported TB cases were collected from 2005 to 2015 in 340 prefectures, including 5 283 983 SS- TB cases and 4 631 734 SS + TB cases with specific sputum smear results, 284 811 cases without sputum smear test. Significantly TB clustering patterns in spatial, temporal and spatio-temporal were observed in this research. Results of the Kulldorff’s scan found twelve significant space-time clusters of reported TB. The most likely spatio-temporal cluster (RR = 3.27, P

Details

Language :
English
ISSN :
20499957
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Infectious Diseases of Poverty
Publication Type :
Academic Journal
Accession number :
edsdoj.5e7cc05f6f7b4512853d2e0aa8627a63
Document Type :
article
Full Text :
https://doi.org/10.1186/s40249-018-0490-8