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Airborne disease transmission during indoor gatherings over multiple time scales: Modeling framework and policy implications.
Dixit, Avinash K; Espinoza, Baltazar; Qiu, Zirou; Vullikanti, Anil; Marathe, Madhav V.
  • Dixit AK; Department of Economics, Princeton University, Princeton, NJ 08544.
  • Espinoza B; Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA 22904.
  • Qiu Z; Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA 22904.
  • Vullikanti A; Department of Computer Science, University of Virginia, Charlottesville, VA 22904.
  • Marathe MV; Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA 22904.
Proc Natl Acad Sci U S A ; 120(16): e2216948120, 2023 04 18.
Article en En | MEDLINE | ID: mdl-37036987
ABSTRACT
Indoor superspreading events are significant drivers of transmission of respiratory diseases. In this work, we study the dynamics of airborne transmission in consecutive meetings of individuals in enclosed spaces. In contrast to the usual pairwise-interaction models of infection where effective contacts transmit the disease, we focus on group interactions where individuals with distinct health states meet simultaneously. Specifically, the disease is transmitted by infected individuals exhaling droplets (contributing to the viral load in the closed space) and susceptible ones inhaling the contaminated air. We propose a modeling framework that couples the fast dynamics of the viral load attained over meetings in enclosed spaces and the slow dynamics of disease progression at the population level. Our modeling framework incorporates the multiple time scales involved in different setups in which indoor events may happen, from single-time events to events hosting multiple meetings per day, over many days. We present theoretical and numerical results of trade-offs between the room characteristics (ventilation system efficiency and air mass) and the group's behavioral and composition characteristics (group size, mask compliance, testing, meeting time, and break times), that inform indoor policies to achieve disease control in closed environments through different pathways. Our results emphasize the impact of break times, mask-wearing, and testing on facilitating the conditions to achieve disease control. We study scenarios of different break times, mask compliance, and testing. We also derive policy guidelines to contain the infection rate under a certain threshold.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Contaminación del Aire Interior / Contaminación del Aire Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Contaminación del Aire Interior / Contaminación del Aire Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article