太阳成8722(中国)有限公司-GREEN NO.1

标题：Spatio-Temporal Distribution Characteristics and Trajectory Similarity Analysis of Tuberculosis in Beijing, China作者：Li, Lan; Xi, Yuliang; Ren, Fu

来源出版物：INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 卷：13 期：3 页码： DOI: 10.3390/ijerph13030291 出版年：MAR 2016

摘要：Tuberculosis (TB) is an infectious disease with one of the highest reported incidences in China. The detection of the spatio-temporal distribution characteristics of TB is indicative of its prevention and control conditions. Trajectory similarity analysis detects variations and loopholes in prevention and provides urban public health officials and related decision makers more information for the allocation of public health resources and the formulation of prioritized health-related policies. This study analysed the spatio-temporal distribution characteristics of TB from 2009 to 2014 by utilizing spatial statistics, spatial autocorrelation analysis, and space-time scan statistics. Spatial statistics measured the TB incidence rate (TB patients per 100,000 residents) at the district level to determine its spatio-temporal distribution and to identify characteristics of change. Spatial autocorrelation analysis was used to detect global and local spatial autocorrelations across the study area. Purely spatial, purely temporal and space-time scan statistics were used to identify purely spatial, purely temporal and spatio-temporal clusters of TB at the district level. The other objective of this study was to compare the trajectory similarities between the incidence rates of TB and new smear-positive (NSP) TB patients in the resident population (NSPRP)/new smear-positive TB patients in the TB patient population (NSPTBP)/retreated smear-positive (RSP) TB patients in the resident population (RSPRP)/retreated smear-positive TB patients in the TB patient population (RSPTBP) to detect variations and loopholes in TB prevention and control among the districts in Beijing. The incidence rates in Beijing exhibited a gradual decrease from 2009 to 2014. Although global spatial autocorrelation was not detected overall across all of the districts of Beijing, individual districts did show evidence of local spatial autocorrelation: Chaoyang and Daxing were Low-Low districts over the six-year period. The purely spatial scan statistics analysis showed significant spatial clusters of high and low incidence rates; the purely temporal scan statistics showed the temporal cluster with a three-year period from 2009 to 2011 characterized by a high incidence rate; and the space-time scan statistics analysis showed significant spatio-temporal clusters. The distribution of the mean centres (MCs) showed that the general distributions of the NSPRP MCs and NSPTBP MCs were to the east of the incidence rate MCs. Conversely, the general distributions of the RSPRP MCs and the RSPTBP MCs were to the south of the incidence rate MCs. Based on the combined analysis of MC distribution characteristics and trajectory similarities, the NSP trajectory was most similar to the incidence rate trajectory. Thus, more attention should be focused on the discovery of NSP patients in the western part of Beijing, whereas the northern part of Beijing needs intensive treatment for RSP patients.

入藏号：WOS:000373528600008

文献类型：Article

语种：English

作者关键词：spatial autocorrelation, trajectory similarity, tuberculosis (TB), Beijing, scan statistics

扩展关键词：CLUSTERS

通讯作者地址：Ren, F ;Wuhan Univ, Sch Resource & Environm Sci, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

Wuhan Univ, Key Lab GIS, Minist Educ, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

Wuhan Univ, Key Lab Digital Mapping & Land Informat Applicat, Natl Adm Surveying Mapping & Geoinformat, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

电子邮件地址：lilaninblue@whu.edu.cn; yuliangwhu@163.com; renfu@whu.edu.cn

地址：

[Li, Lan; Xi, Yuliang; Ren, Fu] Wuhan Univ, Sch Resource & Environm Sci, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

[Li, Lan; Xi, Yuliang; Ren, Fu] Wuhan Univ, Key Lab GIS, Minist Educ, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

[Li, Lan; Xi, Yuliang; Ren, Fu] Wuhan Univ, Key Lab Digital Mapping & Land Informat Applicat, Natl Adm Surveying Mapping & Geoinformat, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

[Ren, Fu] Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

研究方向：Environmental Sciences & Ecology

ISSN：1660-4601

影响因子（2014）：2.063