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Quantifying proximity, confinement, and interventions in disease outbreaks: a decision support framework for air-transported pathogens

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dc.contributor.authorBond, Tami C, author
dc.contributor.authorBosco-Lauth, Angela, author
dc.contributor.authorFarmer, Delphine K., author
dc.contributor.authorFrancisco, Paul W., author
dc.contributor.authorPierce, Jeffrey R., author
dc.contributor.authorFedak, Kristen M., author
dc.contributor.authorHam, Jay M., author
dc.contributor.authorJathar, Shantanu H., author
dc.contributor.authorVandeWoude, Sue, author
dc.contributor.authorEnvironmental Science & Technology, publisher
dc.date.accessioned2021-03-01T22:23:00Z
dc.date.available2021-03-01T22:23:00Z
dc.date.issued2021-02-19
dc.description.abstractThe inability to communicate how infectious diseases are transmitted in human environments has triggered avoidance of interactions during the COVID-19 pandemic. We define a metric, Effective ReBreathed Volume (ERBV), that encapsulates how infectious pathogens, including SARS-CoV-2, transport in air. ERBV separates environmental transport from other factors in the chain of infection, allowing quantitative comparisons among situations. Particle size affects transport, removal onto surfaces, and elimination by mitigation measures, so ERBV is presented for a range of exhaled particle diameters: 1, 10, and 100 μm. Pathogen transport depends on both proximity and confinement. If interpersonal distancing of 2 m is maintained, then confinement, not proximity, dominates rebreathing after 10–15 min in enclosed spaces for all but 100 μm particles. We analyze strategies to reduce this confinement effect. Ventilation and filtration reduce person-to-person transport of 1 μm particles (ERBV1) by 13–85% in residential and office situations. Deposition to surfaces competes with intentional removal for 10 and 100 μm particles, so the same interventions reduce ERBV10 by only 3–50%, and ERBV100 is unaffected. Prior knowledge of size-dependent ERBV would help identify transmission modes and effective interventions. This framework supports mitigation decisions in emerging situations, even before other infectious parameters are known.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationTami C. Bond, Angela Bosco-Lauth, Delphine K. Farmer, Paul W. Francisco, Jeffrey R. Pierce, Kristen M. Fedak, Jay M. Ham, Shantanu H. Jathar, and Sue VandeWoude. Quantifying proximity, confinement, and interventions in disease outbreaks: a decision support framework for air-transported pathogens. Environmental Science & Technology, 2021. https://doi.org/10.1021/acs.est.0c07721
dc.identifier.doihttps://doi.org/10.1021/acs.est.0c07721
dc.identifier.urihttps://hdl.handle.net/10217/225288
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights.licenseThis article is open access and distributed under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0).
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectinfectious diseases
dc.subjectredox reactions
dc.subjectatmospheric chemistry
dc.subjectdeposition
dc.subjectquantum confinement
dc.titleQuantifying proximity, confinement, and interventions in disease outbreaks: a decision support framework for air-transported pathogens
dc.typeText

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