Spatio-temporal evolution of Beijing 2003 SARS epidemic

被引:0
|
作者
ZhiDong Cao
DaJun Zeng
XiaoLong Zheng
QuanYi Wang
FeiYue Wang
JinFeng Wang
XiaoLi Wang
机构
[1] Chinese Academy of Sciences,Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation
[2] Beijing Center for Disease Control and Prevention,State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research
[3] Chinese Academy of Sciences,undefined
来源
Science China Earth Sciences | 2010年 / 53卷
关键词
severe acute respiratory syndrome (SARS); Beijing; morbidity rate; spatial analysis; spatio-temporal evolution; control measures;
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:1017 / 1028
页数:11
相关论文
共 50 条
  • [31] A predictive spatio-temporal model for bovine Babesiosis epidemic transmission
    Abdelheq, Mezouaghi
    Belhamiti, Omar
    Bouzid, Leila
    Trejos, Deccy Y.
    Valverde, Jose C.
    JOURNAL OF THEORETICAL BIOLOGY, 2019, 480 : 192 - 204
  • [32] Studying and approximating spatio-temporal models for epidemic spread and control
    Filipe, JAN
    Gibson, GJ
    PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 1998, 353 (1378) : 2153 - 2162
  • [33] Analyzing the dynamics of fractional spatio-temporal SEIR epidemic model
    Matouk, A. E.
    Ameen, Ismail Gad
    Gaber, Yasmeen Ahmed
    AIMS MATHEMATICS, 2024, 9 (11): : 30838 - 30863
  • [34] Numerical and bifurcation analysis of spatio-temporal delay epidemic model
    Jawaz, Muhammad
    Rehman, Muhammad Aziz Ur
    Ahmed, Nauman
    Baleanu, Dumitru
    Rafiq, Muhammad
    RESULTS IN PHYSICS, 2021, 22
  • [35] Multi-Agent Simulation of Epidemic Spatio-temporal Transmission
    Liu, Tao
    Li, Xia
    Ai, Bin
    Fu, Jing
    Zhang, XiaoHu
    ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 7, PROCEEDINGS, 2008, : 357 - +
  • [36] Spatio-temporal evolution and dynamic simulation of the urban resilience of Beijing-Tianjin-Hebei urban agglomeration
    MU Xufang
    FANG Chuanglin
    YANG Zhiqi
    JournalofGeographicalSciences, 2022, 32 (09) : 1766 - 1790
  • [37] Spatio-temporal evolution and dynamic simulation of the urban resilience of Beijing-Tianjin-Hebei urban agglomeration
    Xufang Mu
    Chuanglin Fang
    Zhiqi Yang
    Journal of Geographical Sciences, 2022, 32 : 1766 - 1790
  • [38] A spatio-temporal model for temporal evolution of spatial extremal dependence
    Maume-Deschamps, Veronique
    Ribereau, Pierre
    Zeidan, Manal
    SPATIAL STATISTICS, 2024, 64
  • [39] Spatio-temporal evolution and dynamic simulation of the urban resilience of Beijing-Tianjin-Hebei urban agglomeration
    Mu Xufang
    Fang Chuanglin
    Yang Zhiqi
    JOURNAL OF GEOGRAPHICAL SCIENCES, 2022, 32 (09) : 1766 - 1790
  • [40] Spatio-temporal evolution of urbanization and its relationship with regional climate change in Beijing over the past century
    Yang S.
    Wang J.
    Dou Y.
    Luan Q.
    Kuang W.
    Dili Xuebao/Acta Geographica Sinica, 2023, 78 (03): : 620 - 639