About: To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic

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About: To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic Goto Sponge NotDistinct Permalink

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
title	To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic
Creator	Gumel, Abba Eikenberry, Keenan Eikenberry, Steffen Iboi, Enahoro Kostelich, Eric Kuang, Yang Mancuso, Marina Phan, Tin
source	ArXiv; Elsevier; Medline; PMC
abstract	Face mask use by the general public for limiting the spread of the COVID-19 pandemic is controversial, though increasingly recommended, and the potential of this intervention is not well understood. We develop a compartmental model for assessing the community-wide impact of mask use by the general, asymptomatic public, a portion of which may be asymptomatically infectious. Model simulations, using data relevant to COVID-19 dynamics in the US states of New York and Washington, suggest that broad adoption of even relatively ineffective face masks may meaningfully reduce community transmission of COVID-19 and decrease peak hospitalizations and deaths. Moreover, mask use decreases the effective transmission rate in nearly linear proportion to the product of mask effectiveness (as a fraction of potentially infectious contacts blocked) and coverage rate (as a fraction of the general population), while the impact on epidemiologic outcomes (death, hospitalizations) is highly nonlinear, indicating masks could synergize with other non-pharmaceutical measures. Notably, masks are found to be useful with respect to both preventing illness in healthy persons and preventing asymptomatic transmission. Hypothetical mask adoption scenarios, for Washington and New York state, suggest that immediate near universal (80%) adoption of moderately (50%) effective masks could prevent on the order of 17–45% of projected deaths over two months in New York, while decreasing the peak daily death rate by 34–58%, absent other changes in epidemic dynamics. Even very weak masks (20% effective) can still be useful if the underlying transmission rate is relatively low or decreasing: In Washington, where baseline transmission is much less intense, 80% adoption of such masks could reduce mortality by 24–65% (and peak deaths 15–69%), compared to 2–9% mortality reduction in New York (peak death reduction 9–18%). Our results suggest use of face masks by the general public is potentially of high value in curtailing community transmission and the burden of the pandemic. The community-wide benefits are likely to be greatest when face masks are used in conjunction with other non-pharmaceutical practices (such as social-distancing), and when adoption is nearly universal (nation-wide) and compliance is high.
has issue date	2020-04-21(xsd:dateTime)
bibo:doi	10.1016/j.idm.2020.04.001
bibo:pmid	32355904
has license	cc-by
sha1sum (hex)	d843c7173358c9cff118fbaf8f889677a08d6cfd
schema:url	https://doi.org/10.1016/j.idm.2020.04.001
resource representing a document's title	To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic
has PubMed Central identifier	PMC7186508
has PubMed identifier	32355904
schema:publication	Infect Dis Model
resource representing a document's body	covid:d843c7173358c9cff118fbaf8f889677a08d6cfd#body_text
is schema:about of	named entity 'adoption' named entity 'masks' named entity 'mortality' named entity 'prevent' named entity 'fraction' named entity 'adoption' named entity 'mask' named entity 'compartmental model' named entity 'coverage' named entity 'pandemic' named entity 'USED' named entity 'CONJUNCTION' named entity 'COMPARED' named entity 'FOUND' named entity 'USE' named entity 'PORTION' named entity 'PROJECTED' named entity 'LIKELY' named entity 'COVID-19' named entity 'transmission' named entity 'product' named entity 'preventing' named entity 'New York' named entity 'Face' named entity 'general' named entity 'Our' named entity 'conjunction' named entity 'asymptomatically' named entity 'simulations' named entity 'epidemic' named entity 'epidemic' named entity 'compartmental model' named entity 'pharmaceutical' named entity 'face masks' named entity 'asymptomatic' named entity 'face masks' named entity 'general population' named entity 'community transmission' named entity 'community transmission' named entity 'general public' named entity 'cloth masks' named entity 'cloth masks' named entity 'epidemic' named entity 'epidemiologic' named entity 'case-fatality ratios' named entity 'point of no return' named entity 'hospital discharge' named entity 'surgical mask' named entity 'clinical trials' named entity '2003 SARS epidemic' named entity 'homemade masks' named entity 'parameter estimation' named entity 'cystic fibrosis' named entity 'SARS-CoV-2' named entity '3, 4' named entity 'US Census' named entity 'N95 masks' named entity 'homemade masks' named entity 'epidemic' named entity 'aerosols' named entity 'healthcare workers' named entity 'respiratory infection' named entity 'epidemic' named entity 'Medical masks' named entity 'source control' named entity 'asymptomatic carriers' named entity 'transmission rate' named entity 'respiratory droplets' named entity 'surgical masks' named entity 'Wuhan' named entity 'general population' named entity 'general public' named entity 'transmission rate' named entity 'source control'

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