Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic.
Identifieur interne : 000569 ( Main/Exploration ); précédent : 000568; suivant : 000570Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic.
Auteurs : Colin J. Worby [États-Unis] ; Hsiao-Han Chang [Taïwan]Source :
- Nature communications [ 2041-1723 ] ; 2020.
Descripteurs français
- KwdFr :
- Allocation des ressources (méthodes), Betacoronavirus (isolement et purification), Distance sociale (MeSH), Facteurs de risque (MeSH), Facteurs âges (MeSH), Humains (MeSH), Infections à coronavirus (prévention et contrôle), Infections à coronavirus (transmission), Infections à coronavirus (virologie), Infections à coronavirus (épidémiologie), Masques (ressources et distribution), Masques (statistiques et données numériques), Modèles théoriques (MeSH), Morbidité (MeSH), Pandémies (prévention et contrôle), Pneumopathie virale (prévention et contrôle), Pneumopathie virale (transmission), Pneumopathie virale (virologie), Pneumopathie virale (épidémiologie), Sujet âgé (MeSH).
- MESH :
- isolement et purification : Betacoronavirus.
- méthodes : Allocation des ressources.
- prévention et contrôle : Infections à coronavirus, Pandémies, Pneumopathie virale.
- ressources et distribution : Masques.
- statistiques et données numériques : Masques.
- virologie : Infections à coronavirus, Pneumopathie virale.
- épidémiologie : Infections à coronavirus, Pneumopathie virale.
- Distance sociale, Facteurs de risque, Facteurs âges, Humains, Modèles théoriques, Morbidité, Sujet âgé.
English descriptors
- KwdEn :
- Age Factors (MeSH), Aged (MeSH), Betacoronavirus (isolation & purification), Coronavirus Infections (epidemiology), Coronavirus Infections (prevention & control), Coronavirus Infections (transmission), Coronavirus Infections (virology), Humans (MeSH), Masks (statistics & numerical data), Masks (supply & distribution), Models, Theoretical (MeSH), Morbidity (MeSH), Pandemics (prevention & control), Pneumonia, Viral (epidemiology), Pneumonia, Viral (prevention & control), Pneumonia, Viral (transmission), Pneumonia, Viral (virology), Resource Allocation (methods), Risk Factors (MeSH), Social Distance (MeSH).
- MESH :
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- isolation & purification : Betacoronavirus.
- methods : Resource Allocation.
- prevention & control : Coronavirus Infections, Pandemics, Pneumonia, Viral.
- statistics & numerical data : Masks.
- supply & distribution : Masks.
- transmission : Coronavirus Infections, Pneumonia, Viral.
- virology : Coronavirus Infections, Pneumonia, Viral.
- Age Factors, Aged, Humans, Models, Theoretical, Morbidity, Risk Factors, Social Distance.
Abstract
The ongoing novel coronavirus disease (COVID-19) pandemic has already infected millions worldwide and, with no vaccine available, interventions to mitigate transmission are urgently needed. While there is broad agreement that travel restrictions and social distancing are beneficial in limiting spread, recommendations around face mask use are inconsistent. Here, we use mathematical modeling to examine the epidemiological impact of face masks, considering resource limitations and a range of supply and demand dynamics. Even with a limited protective effect, face masks can reduce total infections and deaths, and can delay the peak time of the epidemic. However, random distribution of masks is generally suboptimal; prioritized coverage of the elderly improves outcomes, while retaining resources for detected cases provides further mitigation under a range of scenarios. Face mask use, particularly for a pathogen with relatively common asymptomatic carriage, is an effective intervention strategy, while optimized distribution is important when resources are limited.
DOI: 10.1038/s41467-020-17922-x
PubMed: 32792562
PubMed Central: PMC7426871
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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While there is broad agreement that travel restrictions and social distancing are beneficial in limiting spread, recommendations around face mask use are inconsistent. Here, we use mathematical modeling to examine the epidemiological impact of face masks, considering resource limitations and a range of supply and demand dynamics. Even with a limited protective effect, face masks can reduce total infections and deaths, and can delay the peak time of the epidemic. However, random distribution of masks is generally suboptimal; prioritized coverage of the elderly improves outcomes, while retaining resources for detected cases provides further mitigation under a range of scenarios. Face mask use, particularly for a pathogen with relatively common asymptomatic carriage, is an effective intervention strategy, while optimized distribution is important when resources are limited.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Worby</LastName><ForeName>Colin J</ForeName><Initials>CJ</Initials><Identifier Source="ORCID">0000-0002-9132-7249</Identifier><AffiliationInfo><Affiliation>Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA. cworby@broadinstitute.org.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chang</LastName><ForeName>Hsiao-Han</ForeName><Initials>HH</Initials><Identifier Source="ORCID">0000-0001-8016-1530</Identifier><AffiliationInfo><Affiliation>Department of Life Science & Institute of Bioinformatics and Structural Biology, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Road, Hsinchu, 300044, Taiwan. 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Worby</name></noRegion></country><country name="Taïwan"><noRegion><name sortKey="Chang, Hsiao Han" sort="Chang, Hsiao Han" uniqKey="Chang H" first="Hsiao-Han" last="Chang">Hsiao-Han Chang</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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