About: Improved inference of time-varying reproduction numbers during infectious disease outbreaks

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About: Improved inference of time-varying reproduction numbers during infectious disease outbreaks Goto Sponge NotDistinct Permalink

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

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Improved inference of time-varying reproduction numbers during infectious disease outbreaks
Creator	Miguel, E Cauchemez, S Lessler, J Li, S Thompson, R Cori, A Dahlqwist, E Demarsh, P Jombart, T Kamvar, Z Polonsky, J Stockwin, J Van Gaalen, R
Source	Elsevier; Medline; PMC
abstract	Accurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. A valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. This quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). Some methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. Here we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) up-to-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. We demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of H1N1 influenza, Ebola virus disease and Middle-East Respiratory Syndrome. We present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an R software package (EpiEstim 2.2). It is also accessible as an interactive, user-friendly online interface (EpiEstim App), permitting its use by non-specialists. Our tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.
has issue date	2019-08-26(xsd:dateTime)
bibo:doi	10.1016/j.epidem.2019.100356
bibo:pmid	31624039
has license	no-cc
sha1sum (hex)	54394b3d09418b2fbd79dbf8c04f6d18b2f96262
schema:url	https://doi.org/10.1016/j.epidem.2019.100356
resource representing a document's title	Improved inference of time-varying reproduction numbers during infectious disease outbreaks
has PubMed Central identifier	PMC7105007
has PubMed identifier	31624039
schema:publication	Epidemics
resource representing a document's body	covid:54394b3d09418b2fbd79dbf8c04f6d18b2f96262#body_text
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