About: Quantifying the annual incidence and underestimation of seasonal influenza: A modelling approach

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About: Quantifying the annual incidence and underestimation of seasonal influenza: A modelling approach 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
title	Quantifying the annual incidence and underestimation of seasonal influenza: A modelling approach
Creator	Wu, Jianhong Nah, Kyeongah Arino, Julien Heffernan, Jane Stockdale, Jessica Agrawal, Nishant Alavinejad, Mahnaz Athar, Safia Chit, Ayman Chow, Christopher Coudeville, Laurent Jaber, Ahmed Jean, Danielle Keane, Laura Kong, Jude Lee, Jason Liu, Sam Mccarthy, Zachary Moyles, Iain Nahirniak, Myles Romanescu, Razvan Seet, Bruce Shin, Thomas Taurel, Anne-Frieda Thommes, Edward
source	PMC
abstract	BACKGROUND: Seasonal influenza poses a significant public health and economic burden, associated with the outcome of infection and resulting complications. The true burden of the disease is difficult to capture due to the wide range of presentation, from asymptomatic cases to non-respiratory complications such as cardiovascular events, and its seasonal variability. An understanding of the magnitude of the true annual incidence of influenza is important to support prevention and control policy development and to evaluate the impact of preventative measures such as vaccination. METHODS: We use a dynamic disease transmission model, laboratory-confirmed influenza surveillance data, and randomized-controlled trial (RCT) data to quantify the underestimation factor, expansion factor, and symptomatic influenza illnesses in the US and Canada during the 2011-2012 and 2012-2013 influenza seasons. RESULTS: Based on 2 case definitions, we estimate between 0.42−3.2% and 0.33−1.2% of symptomatic influenza illnesses were laboratory-confirmed in Canada during the 2011-2012 and 2012-2013 seasons, respectively. In the US, we estimate between 0.08−0.61% and 0.07−0.33% of symptomatic influenza illnesses were laboratory-confirmed in the 2011-2012 and 2012-2013 seasons, respectively. We estimated the symptomatic influenza illnesses in Canada to be 0.32−2.4 million in 2011-2012 and 1.8−8.2 million in 2012-2013. In the US, we estimate the number of symptomatic influenza illnesses to be 4.4−34 million in 2011-2012 and 23−102 million in 2012-2013. CONCLUSIONS: We illustrate that monitoring a representative group within a population may aid in effectively modelling the transmission of infectious diseases such as influenza. In particular, the utilization of RCTs in models may enhance the accuracy of epidemiological parameter estimation.
has issue date	2020-07-10(xsd:dateTime)
bibo:doi	10.1186/s12976-020-00129-4
bibo:pmid	32646444
has license	cc-by
sha1sum (hex)	1c9a399924214438f496bf8be49816be9b96cec3
schema:url	https://doi.org/10.1186/s12976-020-00129-4
resource representing a document's title	Quantifying the annual incidence and underestimation of seasonal influenza: A modelling approach
has PubMed Central identifier	PMC7347407
has PubMed identifier	32646444
schema:publication	Theor Biol Med Model
resource representing a document's body	covid:1c9a399924214438f496bf8be49816be9b96cec3#body_text
is schema:about of	named entity 'public health' named entity 'variability' named entity 'influenza transmission' named entity 'order of magnitude' named entity 'virologic' named entity 'RCT' named entity 'data sources' named entity 'influenza' named entity 'disease' named entity 'seasonal influenza' named entity 'separation of variables' named entity 'influenza' named entity 'RCT' named entity 'RCT' named entity 'sensitivity analysis' named entity 'RCT' named entity 'influenza' named entity 'transmission rate' named entity 'RCT' named entity 'influenza-like illness' named entity 'vaccine' named entity 'Mathematical modelling' named entity 'ILI' named entity 'wheezing' named entity 'RCT' named entity 'RCT' named entity 'parameter estimation' named entity 'sensitivity analysis' named entity 'influenza' named entity 'birth and death' named entity 'Statistical modelling' named entity 'influenza' named entity 'influenza' named entity 'influenza' named entity 'laboratory testing' named entity 'RCT' named entity 'virologic' named entity 'SVIR' named entity 'disease surveillance' named entity 'basic reproduction number' named entity 'infection' named entity 'sputum production' named entity 'RCT' named entity 'asymptomatic' named entity 'RCT' named entity 'epidemic' named entity 'general population' named entity 'Mexico' named entity 'Canadian' named entity 'RCT' named entity 'Matlab' named entity 'compartmental models' named entity 'influenza vaccine' named entity 'influenza vaccines' named entity 'RCT' named entity 'CDC' named entity 'epidemiological studies'

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