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High-Quality Masks Can Reduce Infections and Deaths in the US
Erik Rosenstrom; Buse Oruc Aglar; Nathaniel Hupert; Julie S. Ivy; Pinar Keskinocak; Maria Mayorga; Julie L Swann.
Afiliação
  • Erik Rosenstrom; North Carolina State University
  • Buse Oruc Aglar; Georgia Institute of Technology
  • Nathaniel Hupert; Cornell University
  • Julie S. Ivy; North Carolina State University
  • Pinar Keskinocak; Georgia Institute of Technology
  • Maria Mayorga; North Carolina State University
  • Julie L Swann; North Carolina State University
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20199737
ABSTRACT
ObjectivesTo evaluate the effectiveness of widespread adoption of masks or face coverings to reduce community transmission of the SARS-CoV-2 virus that causes Covid-19. MethodsWe employed an agent-based stochastic network simulation model, where Covid-19 progresses across census tracts according to a variant of SEIR. We considered a mask order that was initiated 3.5 months after the first confirmed Covid-19 case. We evaluated scenarios where wearing a mask reduces transmission and susceptibility by 50% or 80%; an individual wears a mask with a probability of 0%, 20%, 40%, 60%, 80%, or 100%. ResultsIf 60% of the population wears masks that are 50% effective, this decreases the cumulative infection attack rate (CAR) by 25%, the peak prevalence by 51%, and the population mortality by 25%. If 100% of people wear masks (or 60% wear masks that are 80% effective), this decreases the CAR by 38%, the peak prevalence by 67%, and the population mortality by 40%. ConclusionsAfter community transmission is present, masks can significantly reduce infections.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo observacional Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo observacional Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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