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

Tami C. Bond, Angela Bosco-Lauth, Delphine K. Farmer, Paul W. Francisco, Jeffrey R. Pierce, Kristen M. Fedak, Jay M. Ham, Shantanu H. Jathar, Sue VandeWoude

Research output: Working paper


The 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 transport in air. This measure distinguishes environmental transport from other factors in the chain of infection, thus allowing quantitative comparisons of the riskiness of different situations for any pathogens transported in air, including SARS-CoV-2. Particle size is a key factor in transport, removal onto surfaces, and elimination by mitigation measures, so ERBV is presented for a range of exhaled particle diameters: 1 μm, 10 μm, and 100 μm. Pathogen transport is enhanced by two separate but interacting effects: proximity and confinement. Confinement in enclosed spaces overwhelms proximity after 10-15 minutes for all but the largest particles. Therefore, we review plausible strategies to reduce the confinement effect. Changes in standard ventilation and filtration can reduce person-to-person transport of 1-μm particles (ERBV1) by 13-850-μm and 100-μm particles, so the same interventions reduce ERBV10 by only 3-50 and ERBV100 is unaffected. Determining transmission modes is critical to identify intervention effectiveness, and would be accelerated with prior knowledge of ERBV. When judiciously selected, the interventions examined can provide substantial reduction in risk, and the conditions for selection are identified. The framework of size-dependent ERBV supports analysis and mitigation decisions in an emerging situation, even before other infectious parameters are well known.Competing Interest StatementThe authors have declared no competing interest.Clinical TrialThis is a modeling study and literature review relevant to public health. Data were generated internally and computationally as relevant to humans.Funding StatementTCB acknowledges support from Walter Scott, Jr. Presidential Chair funds. DKF was supported by the Alfred P. Sloan Foundation (G-2019-12442)Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:This study relied on modeling, literature review and scientific synthesis for analysis relevant to public health.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll input data and equations are given in supporting information.
Original languageEnglish (US)
PublisherCold Spring Harbor Laboratory Press
Number of pages49
StateIn preparation - Sep 10 2020

Publication series

PublisherCold Spring Harbor Laboratory Press

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