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A Systems Approach to Assess Transport and Diffusion of Hazardous Airborne Particles in a Large Surgical Suite: Potential Impacts on Viral Airborne Transmission

Author

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  • Marc Garbey

    (ORintelligence, Houston, TX 77021, USA
    LaSIE, UMR CNRS 7356, University of la Rochelle, 17000 La Rochelle, France
    Current address: 2450 Holcombe Blvd, Houston, TX 77021, USA.)

  • Guillaume Joerger

    (ORintelligence, Houston, TX 77021, USA
    GEPROVAS, 67000 Strasbourg, France
    Current address: 2450 Holcombe Blvd, Houston, TX 77021, USA.)

  • Shannon Furr

    (ORintelligence, Houston, TX 77021, USA
    Current address: 2450 Holcombe Blvd, Houston, TX 77021, USA.)

Abstract

Airborne transmission of viruses, such as the coronavirus 2 (SARS-CoV-2), in hospital systems are under debate: it has been shown that transmission of SARS-CoV-2 virus goes beyond droplet dynamics that is limited to 1 to 2 m, but it is unclear if the airborne viral load is significant enough to ensure transmission of the disease. Surgical smoke can act as a carrier for tissue particles, viruses, and bacteria. To quantify airborne transmission from a physical point of view, we consider surgical smoke produced by thermal destruction of tissue during the use of electrosurgical instruments as a marker of airborne particle diffusion-transportation. Surgical smoke plumes are also known to be dangerous for human health, especially to surgical staff who receive long-term exposure over the years. There are limited quantified metrics reported on long-term effects of surgical smoke on staff’s health. The purpose of this paper is to provide a mathematical framework and experimental protocol to assess the transport and diffusion of hazardous airborne particles in every large operating room suite. Measurements from a network of air quality sensors gathered during a clinical study provide validation for the main part of the model. Overall, the model estimates staff exposure to airborne contamination from surgical smoke and biological material. To address the clinical implication over a long period of time, the systems approach is built upon previous work on multi-scale modeling of surgical flow in a large operating room suite and takes into account human behavior factors.

Suggested Citation

  • Marc Garbey & Guillaume Joerger & Shannon Furr, 2020. "A Systems Approach to Assess Transport and Diffusion of Hazardous Airborne Particles in a Large Surgical Suite: Potential Impacts on Viral Airborne Transmission," IJERPH, MDPI, vol. 17(15), pages 1-23, July.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:15:p:5404-:d:390586
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    References listed on IDEAS

    as
    1. Francesco Romano & Jan Gustén & Stefano De Antonellis & Cesare M. Joppolo, 2017. "Electrosurgical Smoke: Ultrafine Particle Measurements and Work Environment Quality in Different Operating Theatres," IJERPH, MDPI, vol. 14(2), pages 1-13, January.
    2. Leonardo Setti & Fabrizio Passarini & Gianluigi De Gennaro & Pierluigi Barbieri & Alberto Pallavicini & Maurizio Ruscio & Prisco Piscitelli & Annamaria Colao & Alessandro Miani, 2020. "Searching for SARS-COV-2 on Particulate Matter: A Possible Early Indicator of COVID-19 Epidemic Recurrence," IJERPH, MDPI, vol. 17(9), pages 1-5, April.
    3. Luca Fiorillo & Gabriele Cervino & Marco Matarese & Cesare D’Amico & Giovanni Surace & Valeria Paduano & Maria Teresa Fiorillo & Antonio Moschella & Alessia La Bruna & Giovanni Luca Romano & Riccardo , 2020. "COVID-19 Surface Persistence: A Recent Data Summary and Its Importance for Medical and Dental Settings," IJERPH, MDPI, vol. 17(9), pages 1-10, April.
    4. Zaoli Yang & Xin Li & Harish Garg & Meng Qi, 2020. "Decision Support Algorithm for Selecting an Antivirus Mask over COVID-19 Pandemic under Spherical Normal Fuzzy Environment," IJERPH, MDPI, vol. 17(10), pages 1-27, May.
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    Cited by:

    1. Marc Garbey & Guillaume Joerger & Shannon Furr, 2020. "Gastroenterology Procedures Generate Aerosols: An Air Quality Turnover Solution to Mitigate COVID-19’s Propagation Risk," IJERPH, MDPI, vol. 17(23), pages 1-17, November.

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