Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China

作者:Cao, CX (Cao, Chunxiang)[ 1 ] ; Chen, W (Chen, Wei)[ 1 ] ; Zheng, S (Zheng, Sheng)[ 1 ] ; Zhao, J (Zhao, Jian)[ 1 ] ; Wang, JF (Wang, Jinfeng)[ 2 ] ; Cao, WC (Cao, Wuchun)[ 3 ]

BIOMED RESEARCH INTERNATIONAL

文献号: 7247983

DOI: 10.1155/2016/7247983

出版年: 2016

摘要

Severe acute respiratory syndrome (SARS) is one of the most severe emerging infectious diseases of the 21st century so far. SARS caused a pandemic that spread throughout mainland China for 7 months, infecting 5318 persons in 194 administrative regions. Using detailed mainland China epidemiological data, we study spatiotemporal aspects of this person-to-person contagious disease and simulate its spatiotemporal transmission dynamics via the Bayesian Maximum Entropy (BME) method. The BME reveals that SARS outbreaks show autocorrelation within certain spatial and temporal distances. We use BME to fit a theoretical covariance model that has a sine hole spatial component and exponential temporal component and obtain the weights of geographical and temporal autocorrelation factors. Using the covariance model, SARS dynamics were estimated and simulated under the most probable conditions. Our study suggests that SARS transmission varies in its epidemiological characteristics and SARS outbreak distributions exhibit palpable clusters on both spatial and temporal scales. In addition, the BME modelling demonstrates that SARS transmission features are affected by spatial heterogeneity, so we analyze potential causes. This may benefit epidemiological control of pandemic infectious diseases.

通讯作者地址: Chen, W (通讯作者)

  State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.

地址:

[ 1 ] State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

[ 2 ] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China

[ 3 ] Beijing Inst Microbiol & Epidemiol, Beijing 100101, Peoples R China