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Characterizing the Risk of Infection from Mycobacterium tuberculosis in Commercial Passenger Aircraft Using Quantitative Microbial Risk Assessment

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  • Rachael M. Jones
  • Yoshifumi Masago
  • Timothy Bartrand
  • Charles N. Haas
  • Mark Nicas
  • Joan B. Rose

Abstract

Quantitative microbial risk assessment was used to predict the likelihood and spatial organization of Mycobacterium tuberculosis (Mtb) transmission in a commercial aircraft. Passenger exposure was predicted via a multizone Markov model in four scenarios: seated or moving infectious passengers and with or without filtration of recirculated cabin air. The traditional exponential (k = 1) and a new exponential (k = 0.0218) dose‐response function were used to compute infection risk. Emission variability was included by Monte Carlo simulation. Infection risks were higher nearer and aft of the source; steady state airborne concentration levels were not attained. Expected incidence was low to moderate, with the central 95% ranging from 10−6 to 10−1 per 169 passengers in the four scenarios. Emission rates used were low compared to measurements from active TB patients in wards, thus a “superspreader” emitting 44 quanta/h could produce 6.2 cases or more under these scenarios. Use of respiratory protection by the infectious source and/or susceptible passengers reduced infection incidence up to one order of magnitude.

Suggested Citation

  • Rachael M. Jones & Yoshifumi Masago & Timothy Bartrand & Charles N. Haas & Mark Nicas & Joan B. Rose, 2009. "Characterizing the Risk of Infection from Mycobacterium tuberculosis in Commercial Passenger Aircraft Using Quantitative Microbial Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 29(3), pages 355-365, March.
    • Handle: RePEc:wly:riskan:v:29:y:2009:i:3:p:355-365
    DOI: 10.1111/j.1539-6924.2008.01161.x
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    References listed on IDEAS

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    1. Mark Nicas, 1996. "An Analytical Framework for Relating Dose, Risk, and Incidence: An Application to Occupational Tuberculosis Infection," Risk Analysis, John Wiley & Sons, vol. 16(4), pages 527-538, August.
    2. Gwangpyo Ko & Kimberly M. Thompson & Edward A. Nardell, 2004. "Estimation of Tuberculosis Risk on a Commercial Airliner," Risk Analysis, John Wiley & Sons, vol. 24(2), pages 379-388, April.
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    Cited by:

    1. Gin Nam Sze‐To & Christopher Y. H. Chao, 2011. "Use of Risk Assessment and Likelihood Estimation to Analyze Spatial Distribution Pattern of Respiratory Infection Cases," Risk Analysis, John Wiley & Sons, vol. 31(3), pages 351-369, March.
    2. Siming You & Man Pun Wan, 2015. "A Risk Assessment Scheme of Infection Transmission Indoors Incorporating the Impact of Resuspension," Risk Analysis, John Wiley & Sons, vol. 35(8), pages 1488-1502, August.
    3. Li, Tao & Rong, Lili & Zhang, Anming, 2021. "Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail," Transport Policy, Elsevier, vol. 106(C), pages 226-238.
    4. Christos Nicolaides & Demetris Avraam & Luis Cueto‐Felgueroso & Marta C. González & Ruben Juanes, 2020. "Hand‐Hygiene Mitigation Strategies Against Global Disease Spreading through the Air Transportation Network," Risk Analysis, John Wiley & Sons, vol. 40(4), pages 723-740, April.
    5. Szu‐Chieh Chen & Chung‐Min Liao & Sih‐Syuan Li & Shu‐Han You, 2011. "A Probabilistic Transmission Model to Assess Infection Risk from Mycobacterium Tuberculosis in Commercial Passenger Trains," Risk Analysis, John Wiley & Sons, vol. 31(6), pages 930-939, June.

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