About: Clustering model for transmission of the SARS virus: application to epidemic control and risk assessment

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Clustering model for transmission of the SARS virus: application to epidemic control and risk assessment
Creator	Small, Michael Tse, C
Source	Elsevier; Medline; PMC
abstract	Abstract We propose a new four state model for disease transmission and illustrate the model with data from the 2003 SARS epidemic in Hong Kong. The critical feature of this model is that the community is modelled as a small-world network of interconnected nodes. Each node is linked to a fixed number of immediate neighbors and a random number of geographically remote nodes. Transmission can only propagate between linked nodes. This model exhibits two features typical of SARS transmission: geographically localized outbreaks and “super-spreaders”. Neither of these features are evident in standard susceptible-infected-removed models of disease transmission. Our analysis indicates that “super-spreaders” may occur even if the infectiousness of all infected individuals is constant. Moreover, we find that nosocomial transmission in Hong Kong directly contributed to the severity of the outbreak and that by limiting individual exposure time to 3–5 days the extent of the SARS epidemic would have been minimal.
has issue date	2005-06-15(xsd:dateTime)
bibo:doi	10.1016/j.physa.2005.01.009
bibo:pmid	32288075
has license	els-covid
sha1sum (hex)	d42a95cf1d2da6101741a4a4e6d3deb571e13d93
schema:url	https://doi.org/10.1016/j.physa.2005.01.009
resource representing a document's title	Clustering model for transmission of the SARS virus: application to epidemic control and risk assessment
has PubMed Central identifier	PMC7126158
has PubMed identifier	32288075
schema:publication	Physica A: Statistical Mechanics and its Applications
resource representing a document's body	covid:d42a95cf1d2da6101741a4a4e6d3deb571e13d93#body_text
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