About: Real-time Estimates in Early Detection of SARS

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Real-time Estimates in Early Detection of SARS
Creator	Boëlle, Pierre-Yves Ferguson, Neil Cauchemez, Simon Anderson, Roy Donnelly, Christl Valleron, Alain-Jacques Thomas, Guy Hedley, Anthony Leung, M Gabriel, †
Source	Medline; PMC
abstract	We propose a Bayesian statistical framework for estimating the reproduction number R early in an epidemic. This method allows for the yet-unrecorded secondary cases if the estimate is obtained before the epidemic has ended. We applied our approach to the severe acute respiratory syndrome (SARS) epidemic that started in February 2003 in Hong Kong. Temporal patterns of R estimated after 5, 10, and 20 days were similar. Ninety-five percent credible intervals narrowed when more data were available but stabilized after 10 days. Using simulation studies of SARS-like outbreaks, we have shown that the method may be used for early monitoring of the effect of control measures.
has issue date	2006-01-01(xsd:dateTime)
bibo:doi	10.3201/eid1201.050593
bibo:pmid	16494726
has license	no-cc
sha1sum (hex)	12c156dc659a9b4c3008ce4d6d10f464d60b5b65
schema:url	https://doi.org/10.3201/eid1201.050593
resource representing a document's title	Real-time Estimates in Early Detection of SARS
has PubMed Central identifier	PMC3293464
has PubMed identifier	16494726
schema:publication	Emerg Infect Dis
resource representing a document's body	covid:12c156dc659a9b4c3008ce4d6d10f464d60b5b65#body_text
is schema:about of	named entity 'STARTED' named entity 'METHOD' named entity 'NINETY' named entity 'EARLY' named entity 'HONG KONG' named entity 'MONITORING' named entity 'ESTIMATING' named entity 'NARROWED' named entity 'EPIDEMIC' named entity 'CASES' named entity 'PATTERNS' named entity 'OUTBREAKS' named entity 'DATA' named entity 'credible intervals' named entity 'started' named entity 'Estimates' named entity 'REAL-TIME' named entity 'USING' named entity 'DAYS' named entity 'EARLY DETECTION' named entity 'SARS' named entity 'STABILIZED' named entity 'TEMPORAL' named entity 'SIMILAR' named entity 'FEBRUARY' named entity 'SEVERE ACUTE RESPIRATORY SYNDROME' named entity 'MAY BE' named entity 'STATISTICAL' named entity 'ESTIMATES' named entity 'EFFECT' named entity 'OBTAINED' named entity 'ESTIMATE' named entity 'STUDIES' named entity 'CONTROL' named entity 'SECONDARY' named entity 'PERCENT' named entity 'SIMULATION' named entity 'ENDED' named entity '10%' named entity 'REPRODUCTION NUMBER' named entity 'APPLIED' named entity 'MEASURES' named entity 'ALLOWS' named entity 'INTERVALS' named entity 'HAVE' named entity 'ESTIMATED' named entity 'BUT' named entity 'AVAILABLE' named entity 'USED' covid:arg/12c156dc659a9b4c3008ce4d6d10f464d60b5b65 named entity 'stabilized' named entity 'credible intervals' named entity 'SARS' named entity 'Real-time' named entity 'Bayesian' named entity 'reproduction number' named entity 'reproduction number' named entity 'asymptomatic' named entity 'SARS' named entity 'reproduction number' named entity 'epidemic' named entity 'epidemic' named entity 'epidemiologists' named entity 'epidemic' named entity '95%' named entity 'symptom' named entity 'public health' named entity 'credible intervals' named entity 'credible intervals' named entity 'influenza' named entity 'SARS' named entity 'inference'

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