About: Generalized Trapezoidal Ogive Curves for Fatality Rate Modeling

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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	Generalized Trapezoidal Ogive Curves for Fatality Rate Modeling
Creator	Mazzuchi, Thomas René Van Dorp, Johan Shittu, Ekundayo
Source	Elsevier; PMC
abstract	Abstract The construction of a continuous family of distributions on a compact (bounded) set is demonstrated by concatenating, in a continuous manner, three probability density functions with bound- ed support using a modified mixture technique. The construction technique is similar to that of generalized trapezoidal (GT) distributions, but contrary to GT distributions, the resulting density function is smooth within its bounded domain. The construction of Generalized Trapezoidal Ogive (GTO) distributions was motivated by the COVID-19 epidemic, where smoothness of an infection rate curve may be a desirable property combined with the ability to separately model three stages and their durations as the epidemic progresses, being: (1) an increasing infection rate stage, (2) an infection rate stage of some stability and (3) a decreasing infection rate stage. The resulting model allows for asymmetry of the infection rate curve opposite to, for example, the Gaussian Error Infection (GEI) rate curve utilized early on for COVID-19 epidemic projections by The Institute for Health Metrics and Evaluation. While other asymmetric distributions too allow for the modeling of asymmetry, the ability to separately model the above three stages of an epidemic’s progression is a distinct feature of the model proposed. The latter avoids unrealistic projections of an epidemic’s right-tail in the absence of right tail data, which is an artifact of any fatality rate model where a left-tail fit determines its right-tail behavior.
has issue date	2020-08-04(xsd:dateTime)
bibo:doi	10.1016/j.csfx.2020.100043
has license	els-covid
sha1sum (hex)	7e09d53ca09d0967d0f3a9050f4eba1d22a8904c
schema:url	https://doi.org/10.1016/j.csfx.2020.100043
resource representing a document's title	Generalized Trapezoidal Ogive Curves for Fatality Rate Modeling
has PubMed Central identifier	PMC7402242
resource representing a document's body	covid:7e09d53ca09d0967d0f3a9050f4eba1d22a8904c#body_text
is schema:about of	named entity 'Rate' named entity 'Curves' named entity 'Trapezoidal' named entity 'Journal' named entity 'log-normal' named entity 'least-squares' named entity 'risk communication' named entity 'epidemic' named entity 'Gaussian model' named entity 'Ogive' named entity 'epidemic' named entity 'fatality rate' named entity 'fatality rate' named entity 'infection' named entity 'infection rate' named entity 'Gaussian model' named entity 'fatality rate' named entity 'infection' named entity 'linear transformation' named entity 'epidemic' named entity 'objective function' named entity 'Spain' named entity 'epidemic' named entity 'risk mitigation measure' named entity 'global pandemic' named entity 'social distancing' named entity 'linear regression model' named entity 'financial markets' named entity 'epidemic' named entity 'ogive' named entity 'epidemic' named entity 'point in time' named entity 'epidemic' named entity 'fatality rate' named entity 'Italy' named entity 'epidemic' named entity 'epidemic' named entity 'epidemic' named entity 'infection' named entity 'fatality rate' named entity 'fatality rate' named entity 'infection' named entity 'time series forecasting' named entity 'COVID-19' named entity 'infection' named entity 'data reporting' named entity 'COVID-19' named entity 'fatality rate' named entity 'epidemic' named entity 'Italy' named entity 'Johns Hopkins University' named entity 'least-squares' named entity 'epidemic' named entity 'log-normal' named entity 'fatality rate' named entity 'curve fitting' named entity 'data reporting' named entity 'COVID-19' named entity 'COVID-19' named entity 'optimization algorithm' named entity 'objective function' named entity 'Italy' named entity 'fatality rate' named entity 'United Kingdom' named entity 'epidemic' named entity 'COVID-19' named entity 'ogive' named entity 'log-normal' named entity 'log-normal' named entity 'ogive' named entity 'fatality rate' named entity 'risk mitigation measure' named entity 'ogive' named entity 'Italy' named entity 'quantile function' named entity 'Wuhan' named entity 'infection rate' named entity 'Kerwan' named entity 'infection' named entity 'infection' named entity 'fatality rate' named entity 'fatality rate'

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