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 re...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 smearnegative(SS-)reported TB were also detected at the prefecture level.Results:A total of 10200528 reported TB cases were collected from 2005 to 2015 in 340 prefectures,including 5283983 SS-TB cases and 4631734 SS+TB cases with specific sputum smear results,284811 cases without sputum smear test.Significantly TB clustering patterns in spatial,temporal and spatiotemporal 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<0.001)was mainly located in Xinjiang Uygur Autonomous Region of western China,covering five prefectures and clustering in the time frame from September 2012 to November 2015.The spatio-temporal clustering results of SS+TB and SS-TB also showed the most likely clusters distributed in the western China.However,the clustering time of SS+TB was concentrated before 2010 while SS-TB was mainly concentrated after 2010.Conclusions:This study identified the time and region of TB,SS+TB and SS-TB clustered easily in 340 prefectures in the mainland of China,which is helpful in prioritizing resource assignment in high-risk periods and high-risk areas,and to formulate powerful strategy to prevention and control TB.展开更多
基金The research was supported by the National S&T Major Project(Grant No.2014ZX10004005–001).
文摘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 smearnegative(SS-)reported TB were also detected at the prefecture level.Results:A total of 10200528 reported TB cases were collected from 2005 to 2015 in 340 prefectures,including 5283983 SS-TB cases and 4631734 SS+TB cases with specific sputum smear results,284811 cases without sputum smear test.Significantly TB clustering patterns in spatial,temporal and spatiotemporal 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<0.001)was mainly located in Xinjiang Uygur Autonomous Region of western China,covering five prefectures and clustering in the time frame from September 2012 to November 2015.The spatio-temporal clustering results of SS+TB and SS-TB also showed the most likely clusters distributed in the western China.However,the clustering time of SS+TB was concentrated before 2010 while SS-TB was mainly concentrated after 2010.Conclusions:This study identified the time and region of TB,SS+TB and SS-TB clustered easily in 340 prefectures in the mainland of China,which is helpful in prioritizing resource assignment in high-risk periods and high-risk areas,and to formulate powerful strategy to prevention and control TB.
