About: Optimizing antiviral treatment for seasonal influenza in the United States: A Mathematical Modeling Analysis

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Optimizing antiviral treatment for seasonal influenza in the United States: A Mathematical Modeling Analysis
Creator	Yamin, Dan Mbah, Ndeffo Ndeffo-Mbah, Martial Yechezkel, Matan
source	MedRxiv
abstract	Seasonal influenza remains a major health burden in the United States. Despite recommendations of early antiviral treatment of high-risk patients, the effective treatment coverage remains very low. We developed an influenza transmission model that incorporates data on infectious viral load, social contact, and healthcare-seeking behavior, to evaluate the population-level impact of increasing antiviral treatment timeliness and coverage among high-risk patients in the US. We found that increasing the rate of early treatment among high-risk patients who received treatment more than 48 hours after symptoms onset, would substantially avert infections and influenza-induced hospitalizations. We found that treatment of the elderly has the highest impact on reducing hospitalizations, whereas treating high-risk individuals aged 5-19 years old has the highest impact on transmission. The population-level impact of increased timeliness and coverage of treatment among high-risk patients was observed regardless of seasonal influenza vaccination coverage and the severity of the influenza season.
has issue date	2020-07-30(xsd:dateTime)
bibo:doi	10.1101/2020.07.28.20163741
has license	medrxiv
sha1sum (hex)	8cc230fc2a081ec1180da08e1ef95ef665208337
schema:url	https://doi.org/10.1101/2020.07.28.20163741
resource representing a document's title	Optimizing antiviral treatment for seasonal influenza in the United States: A Mathematical Modeling Analysis
resource representing a document's body	covid:8cc230fc2a081ec1180da08e1ef95ef665208337#body_text
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