Linked Life Data

16222170

Source:http://linkedlifedata.com/resource/pubmed/id/16222170

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2005-10-13
pubmed:abstractText
The emergence and rapid global spread of the severe acute respiratory syndrome (SARS) coronavirus in 2002-2003 prompted efforts by modelers to characterize SARS epidemiology and inform control policies. We overview and discuss models for emerging infectious diseases (EIDs), provide a critical survey of SARS modeling literature, and discuss promising future directions for research. We reconcile discrepancies between published estimates of the basic reproductive number R0 for SARS (a crucial epidemiologic parameter), discuss insights regarding SARS control measures that have emerged uniquely from a modeling approach, and argue that high priorities for future modeling of SARS and similar respiratory EIDs should include informing quarantine policy and better understanding the impact of population heterogeneity on transmission patterns.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1044-3983
pubmed:author
pubmed:issnType
Print
pubmed:volume
16
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
791-801
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Dynamically modeling SARS and other newly emerging respiratory illnesses: past, present, and future.
pubmed:affiliation
Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada. cbauch@uoguelph.ca
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't, Meta-Analysis, Research Support, N.I.H., Extramural