About: Relatedness of the Incidence Decay with Exponential Adjustment (IDEA) Model,%22Farr's Law%22and Compartmental Difference Equation SIR Models

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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	Relatedness of the Incidence Decay with Exponential Adjustment (IDEA) Model,%22Farr's Law%22and Compartmental Difference Equation SIR Models
Creator	Fisman, David Santillana, Mauricio Tuite, Ashleigh Dushoff, Jonathan Nasserie, Tahmina Champredon, David Chindelevitch, Leonid Fine, Paul
Source	ArXiv
abstract	Mathematical models are often regarded as recent innovations in the description and analysis of infectious disease outbreaks and epidemics, but simple models have been in use for projection of epidemic trajectories for more than a century. We recently described a single equation model (the incidence decay with exponential adjustment, or IDEA, model) that can be used for short term forecasting. In the mid-19th century, Dr. William Farr developed a single equation approach (Farr's law) for epidemic forecasting. We show here that the two models are in fact identical, and can be expressed in terms of one another, and also in terms of a susceptible-infectious-removed (SIR) compartmental model with improving control. This demonstrates that the concept of the reproduction number, R0, is implicit to Farr's (pre-microbial era) work, and also suggests that control of epidemics, whether via behavior change or intervention, is as integral to the natural history of epidemics as is the dynamics of disease transmission.
has issue date	2016-03-03(xsd:dateTime)
has license	arxiv
sha1sum (hex)	c43f5ba6a7960c9b6040d761fc8e539520e93247
resource representing a document's title	Relatedness of the Incidence Decay with Exponential Adjustment (IDEA) Model,%22Farr's Law%22and Compartmental Difference Equation SIR Models
resource representing a document's body	covid:c43f5ba6a7960c9b6040d761fc8e539520e93247#body_text
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