Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China.
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 d...
| Publicado en: | BioMed Research International Vol. 2016; pp. 1 - 13 |
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| Autores principales: | , , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
8/15/2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=117447440&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 117447440 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 8/15/2016 vid: 2016 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 117447440 117447440 117447440 10.1155/2016/7247983 117447440 ppf: 1 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China. aug: au: Cao, Chunxiang Chen, Wei Zheng, Sheng Zhao, Jian Wang, Jinfeng Cao, Wuchun affil: State Key Laboratory of Remote Sensing Science, Beijing 100101, China sug: subj: Severe Acute Respiratory Syndrome Transmission Geographic Factors Disease Outbreaks China Time Factors China Human Probability Severe Acute Respiratory Syndrome Epidemiology Simulations Severe Acute Respiratory Syndrome Prevention and Control Descriptive Statistics Models, Statistical Data Analysis Software Severe Acute Respiratory Syndrome Etiology Funding Source ab: 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. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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