About: Estimating a Markovian Epidemic Model Using Household Serial Interval Data from the Early Phase of an Epidemic

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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	Estimating a Markovian Epidemic Model Using Household Serial Interval Data from the Early Phase of an Epidemic
Creator	Black, A Ross, J
Source	PMC
abstract	The clinical serial interval of an infectious disease is the time between date of symptom onset in an index case and the date of symptom onset in one of its secondary cases. It is a quantity which is commonly collected during a pandemic and is of fundamental importance to public health policy and mathematical modelling. In this paper we present a novel method for calculating the serial interval distribution for a Markovian model of household transmission dynamics. This allows the use of Bayesian MCMC methods, with explicit evaluation of the likelihood, to fit to serial interval data and infer parameters of the underlying model. We use simulated and real data to verify the accuracy of our methodology and illustrate the importance of accounting for household size. The output of our approach can be used to produce posterior distributions of population level epidemic characteristics.
has issue date	2013-08-30(xsd:dateTime)
bibo:doi	10.1371/journal.pone.0073420
bibo:pmid	24023679
has license	cc-by
sha1sum (hex)	b2fde3b77f54db50b124bca17aaba10069e4424b
schema:url	https://doi.org/10.1371/journal.pone.0073420
resource representing a document's title	Estimating a Markovian Epidemic Model Using Household Serial Interval Data from the Early Phase of an Epidemic
has PubMed Central identifier	PMC3758268
has PubMed identifier	24023679
schema:publication	PLoS One
resource representing a document's body	covid:b2fde3b77f54db50b124bca17aaba10069e4424b#body_text
is schema:about of	named entity 'DATA' named entity 'illustrate' named entity 'model' named entity 'policy' named entity 'fit' named entity 'calculating' named entity 'mathematical modelling' named entity 'SERIAL' named entity 'TIME' named entity 'INDEX CASE' named entity 'INTERVAL' named entity 'MODEL OF' named entity 'QUANTITY' named entity 'USE OF' named entity 'PANDEMIC' named entity 'CALCULATING' named entity 'LIKELIHOOD' named entity 'MATHEMATICAL MODELLING' named entity 'PUBLIC HEALTH POLICY' named entity 'USED' named entity 'ONE OF' named entity 'METHODS' named entity 'DISTRIBUTION' named entity 'LEVEL' named entity 'USE' named entity 'HOUSEHOLD' named entity 'HOUSEHOLD SIZE' named entity 'DATE' named entity 'TO PRODUCE' named entity 'PRESENT' named entity 'ALLOWS' named entity 'OUR' named entity 'REAL' named entity 'VERIFY' named entity 'PAPER' named entity 'ACCOUNTING' named entity 'IS A' named entity 'POPULATION' named entity 'DATA' named entity 'MARKOVIAN MODEL' named entity 'SECONDARY' named entity 'EVALUATION' named entity 'EPIDEMIC' named entity 'POSTERIOR' named entity 'INFER' named entity 'HOUSEHOLD' named entity 'USING' named entity 'PHASE' named entity 'EPIDEMIC MODEL' named entity 'INTERVAL' named entity 'ITS' named entity 'CLINICAL' named entity 'UNDERLYING' named entity 'EPIDEMIC' named entity 'TRANSMISSION' named entity 'INFECTIOUS DISEASE' named entity 'SERIAL' named entity 'METHODOLOGY' named entity 'CASES' named entity 'DYNAMICS' named entity 'OUTPUT' named entity 'METHOD' named entity 'EARLY' named entity 'ESTIMATING' named entity 'PARAMETERS' named entity 'COLLECTED' named entity 'ACCURACY' named entity 'SYMPTOM ONSET' named entity 'CHARACTERISTICS' named entity 'MODEL' named entity 'FIT' named entity 'DISTRIBUTIONS' named entity 'NOVEL' named entity 'SIMULATED' named entity 'evaluation' named entity 'onset' named entity 'This' named entity 'Bayesian MCMC' named entity 'infectious disease' named entity 'Markovian'

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