About: Fitting to the UK COVID-19 outbreak, short-term forecasts and estimating the reproductive number.

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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	Fitting to the UK COVID-19 outbreak, short-term forecasts and estimating the reproductive number.
Creator	Keeling, Matt Semple, Malcolm Tildesley, Michael Dyson, Louise Hill, Edward Guyver-Fletcher, Glen Holmes, Alex
Source	MedRxiv; Medline; PMC
abstract	The COVID-19 pandemic has brought to the fore the need for policy makers to receive timely and ongoing scientific guidance in response to this recently emerged human infectious disease. Fitting mathematical models of infectious disease transmission to the available epidemiological data provides a key statistical tool for understanding the many quantities of interest that are not explicit in the underlying epidemiological data streams. Of these, the basic reproductive ratio, R, has taken on special significance in terms of the general understanding of whether the epidemic is under control (R < 1). Unfortunately, none of the epidemiological data streams are designed for modelling, hence assimilating information from multiple (often changing) sources of data is a major challenge that is particularly stark in novel disease outbreaks. Here, we present in some detail the inference scheme employed for calibrating the Warwick COVID-19 model to the available public health data streams, which span hospitalisations, critical care occupancy, mortality and serological testing. We then perform computational simulations, making use of the acquired parameter posterior distributions, to assess how the accuracy of short-term predictions varied over the timecourse of the outbreak. To conclude, we compare how refinements to data streams and model structure impact estimates of epidemiological measures, including the estimated growth rate and daily incidence.
has issue date	2020-08-12(xsd:dateTime)
bibo:doi	10.1101/2020.08.04.20163782
bibo:pmid	32817970
has license	cc-by
sha1sum (hex)	041647f81f38c5e5ac2d136d8a68f4cfcdc19450
schema:url	https://doi.org/10.1101/2020.08.04.20163782
resource representing a document's title	Fitting to the UK COVID-19 outbreak, short-term forecasts and estimating the reproductive number.
has PubMed Central identifier	PMC7430615
has PubMed identifier	32817970
schema:publication	medRxiv
resource representing a document's body	covid:041647f81f38c5e5ac2d136d8a68f4cfcdc19450#body_text
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