About: Parameter Estimation in Epidemiology: from Simple to Complex Dynamics

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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
title	Parameter Estimation in Epidemiology: from Simple to Complex Dynamics
Creator	Stollenwerk, Nico Aguiar, Maíra Kooi, Bob Ballesteros, Sebastién Boto, João Mateus, Luís
source	PMC
abstract	We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models like multi‐strain dynamics to describe the virus‐host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.
has issue date	2011-09-14(xsd:dateTime)
bibo:doi	10.1063/1.3637843
bibo:pmid	32255869
has license	cc-by
sha1sum (hex)	354ae1dace6a05a3fbeb026027e8d98412897b2d
schema:url	https://doi.org/10.1063/1.3637843
resource representing a document's title	Parameter Estimation in Epidemiology: from Simple to Complex Dynamics
has PubMed Central identifier	PMC7108775
has PubMed identifier	32255869
schema:publication	AIP Conf Proc
resource representing a document's body	covid:354ae1dace6a05a3fbeb026027e8d98412897b2d#body_text
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