caa a22 4500 445299789 CHVBK 20180317142553.0 cr unu---uuuuu 170323e20100701xx s 000 0 eng 10.1007/s11430-010-0043-x doi (NATIONALLICENCE)springer-10.1007/s11430-010-0043-x Spatio-temporal evolution of Beijing 2003 SARS epidemic [Elektronische Daten] [ZhiDong Cao, DaJun Zeng, XiaoLong Zheng, QuanYi Wang, FeiYue Wang, JinFeng Wang, XiaoLi Wang] Studying spatio-temporal evolution of epidemics can uncover important aspects of interaction among people, infectious diseases, and the environment, providing useful insights and modeling support to facilitate public health response and possibly prevention measures. This paper presents an empirical spatio-temporal analysis of epidemiological data concerning 2321 SARS-infected patients in Beijing in 2003. We mapped the SARS morbidity data with the spatial data resolution at the level of street and township. Two smoothing methods, Bayesian adjustment and spatial smoothing, were applied to identify the spatial risks and spatial transmission trends. Furthermore, we explored various spatial patterns and spatio-temporal evolution of Beijing 2003 SARS epidemic using spatial statistics such as Moran's I and LISA. Part of this study is targeted at evaluating the effectiveness of public health control measures implemented during the SARS epidemic. The main findings are as follows. (1) The diffusion speed of SARS in the northwest-southeast direction is weaker than that in northeast-southwest direction. (2) SARS's spread risk is positively spatially associated and the strength of this spatial association has experienced changes from weak to strong and then back to weak during the lifetime of the Beijing SARS epidemic. (3) Two spatial clusters of disease cases are identified: one in the city center and the other in the eastern suburban area. These two clusters followed different evolutionary paths but interacted with each other as well. (4) Although the government missed the opportunity to contain the early outbreak of SARS in March 2003, the response strategies implemented after the mid of April were effective. These response measures not only controlled the growth of the disease cases, but also mitigated the spatial diffusion. Science China Press and Springer-Verlag Berlin Heidelberg, 2010 severe acute respiratory syndrome (SARS) nationallicence Beijing nationallicence morbidity rate nationallicence spatial analysis nationallicence spatio-temporal evolution nationallicence control measures nationallicence Cao ZhiDong Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut Zeng DaJun Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut Zheng XiaoLong Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut Wang QuanYi Beijing Center for Disease Control and Prevention, 100013, Beijing, China aut Wang FeiYue Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut Wang JinFeng State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China aut Wang XiaoLi Beijing Center for Disease Control and Prevention, 100013, Beijing, China aut Science China Earth Sciences SP Science China Press 53/7(2010-07-01), 1017-1028 1674-7313 53:7<1017 2010 53 11430 https://doi.org/10.1007/s11430-010-0043-x text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11430-010-0043-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cao ZhiDong Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut NATIONALLICENCE 700 1- Zeng DaJun Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut NATIONALLICENCE 700 1- Zheng XiaoLong Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut NATIONALLICENCE 700 1- Wang QuanYi Beijing Center for Disease Control and Prevention, 100013, Beijing, China aut NATIONALLICENCE 700 1- Wang FeiYue Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut NATIONALLICENCE 700 1- Wang JinFeng State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China aut NATIONALLICENCE 700 1- Wang XiaoLi Beijing Center for Disease Control and Prevention, 100013, Beijing, China aut NATIONALLICENCE 773 0- Science China Earth Sciences SP Science China Press 53/7(2010-07-01), 1017-1028 1674-7313 53:7<1017 2010 53 11430 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer