About: Consistency and reliability of COVID-19 projection models as a means to save lives

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About: Consistency and reliability of COVID-19 projection models as a means to save lives Goto Sponge NotDistinct Permalink

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	Consistency and reliability of COVID-19 projection models as a means to save lives
Creator	Elkbuli, Adel Mckenney, Mark Sen-Crowe, Brendon
Source	Elsevier; Medline; PMC
abstract	covid:57fb77d2e93730a15a4815d9bf7ac1372b481f02#abstract
has issue date	2020-07-12(xsd:dateTime)
bibo:doi	10.1016/j.ajem.2020.07.020
bibo:pmid	32713604
has license	no-cc
sha1sum (hex)	57fb77d2e93730a15a4815d9bf7ac1372b481f02
schema:url	https://doi.org/10.1016/j.ajem.2020.07.020
resource representing a document's title	Consistency and reliability of COVID-19 projection models as a means to save lives
has PubMed Central identifier	PMC7354274
has PubMed identifier	32713604
schema:publication	Am J Emerg Med
resource representing a document's body	covid:57fb77d2e93730a15a4815d9bf7ac1372b481f02#body_text
is schema:about of	named entity 'turning point' named entity 'Save' named entity 'forecasting' named entity 'effects' named entity 'transparency' named entity 'projection' named entity 'public health' named entity 'short-term' named entity 'predictive models' named entity 'IHME' named entity 'sensitivity analysis' named entity 'predictive models' named entity 'margin of error' named entity 'data collected' named entity 'California' named entity 'ICU' named entity 'contact tracing' named entity 'ICL' named entity 'ICU' named entity 'COVID-19' named entity 'social distancing' named entity 'predictive models' named entity 'Imperial College of London' named entity 'public health' named entity 'ICU' named entity 'COVID-19' named entity 'Texas' named entity 'COVID-19' named entity 'IHME' named entity 'sampling' named entity 'New York' named entity 'ICL' named entity 'sampling' named entity 'confounding variables' named entity 'ICU beds' named entity 'reproducibility' named entity 'COVID-19' named entity 'May 20' named entity 'COVID-19 tests' named entity 'risk of transmission' named entity 'social distancing' named entity 'United States' named entity 'May 8' named entity 'COVID-19' named entity 'COVID-19 pandemic' named entity 'travel behavior' named entity 'COVID-19' named entity 'predictive model' named entity 'types of data' named entity 'real-world' named entity 'projections' named entity 'Journal' named entity '27S' named entity 'LIVES' named entity 'ALLOW' named entity 'PUBLIC' named entity 'OUR' named entity 'PREDICTIVE MODELS' named entity 'REAL' named entity 'COVID-19' named entity 'PREDICTIVE MODEL' named entity 'MODELS' named entity 'MAINTENANCE' named entity 'COVID-19' named entity 'PROOF' named entity 'TRANSPARENCY' named entity 'OTHER TYPES OF DATA' named entity 'PROOF' named entity 'MEANS' named entity 'flaws' named entity 'methodology' named entity 'normalcy' named entity 'driven' named entity 'criticism' named entity 'types' named entity 'Journal' named entity 'travel behavior' named entity 'mitigation' named entity 'reliability'

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