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Assessing Infection Control Measures for Pandemic Influenza

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  • Lawrence M. Wein
  • Michael P. Atkinson

Abstract

We construct a mathematical model of aerosol (i.e., droplet‐nuclei) transmission of influenza within a household containing one infected and embed it into an epidemic households model in which infecteds occasionally infect someone from another household; in a companion paper, we argue that the contribution from contact transmission is trivial for influenza and the contribution from droplet transmission is likely to be small. Our model predicts that the key infection control measure is the use of N95 respirators, and that the combination of respirators, humidifiers, and ventilation reduces the threshold parameter (which dictates whether or not an epidemic breaks out) by ≈20% if 70% of households comply, and by ≈40% if 70% of households and workplaces comply (≈28% reduction would have been required to control the 1918 pandemic). However, only ≈30% of the benefits in the household are achieved if these interventions are used only after the infected develops symptoms. It is also important for people to sleep in separate bedrooms throughout the pandemic, space permitting. Surgical masks with a device (e.g., nylon hosiery) to reduce face‐seal leakage are a reasonable alternative to N95 respirators if the latter are in short supply.

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  • Lawrence M. Wein & Michael P. Atkinson, 2009. "Assessing Infection Control Measures for Pandemic Influenza," Risk Analysis, John Wiley & Sons, vol. 29(7), pages 949-962, July.
    • Handle: RePEc:wly:riskan:v:29:y:2009:i:7:p:949-962
    DOI: 10.1111/j.1539-6924.2009.01232.x
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    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Policy responses

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    Cited by:

    1. Rachael M. Jones, 2011. "Critical Review and Uncertainty Analysis of Factors Influencing Influenza Transmission," Risk Analysis, John Wiley & Sons, vol. 31(8), pages 1226-1242, August.
    2. Lawrence M. Wein, 2009. "OR Forum---Homeland Security: From Mathematical Models to Policy Implementation: The 2008 Philip McCord Morse Lecture," Operations Research, INFORMS, vol. 57(4), pages 801-811, August.
    3. Edward M. Fisher & John D. Noti & William G. Lindsley & Francoise M. Blachere & Ronald E. Shaffer, 2014. "Validation and Application of Models to Predict Facemask Influenza Contamination in Healthcare Settings," Risk Analysis, John Wiley & Sons, vol. 34(8), pages 1423-1434, August.
    4. Ana Carolina Carioca da Costa & Cláudia Torres Codeço & Elias Teixeira Krainski & Marcelo Ferreira da Costa Gomes & Aline Araújo Nobre, 2018. "Spatiotemporal diffusion of influenza A (H1N1): Starting point and risk factors," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-20, September.
    5. Martín López‐García & Marco‐Felipe King & Catherine J. Noakes, 2019. "A Multicompartment SIS Stochastic Model with Zonal Ventilation for the Spread of Nosocomial Infections: Detection, Outbreak Management, and Infection Control," Risk Analysis, John Wiley & Sons, vol. 39(8), pages 1825-1842, August.
    6. Rachael M. Jones & Elodie Adida, 2011. "Influenza Infection Risk and Predominate Exposure Route: Uncertainty Analysis," Risk Analysis, John Wiley & Sons, vol. 31(10), pages 1622-1631, October.
    7. Fatima‐Zohra Younsi & Salem Chakhar & Alessio Ishizaka & Djamila Hamdadou & Omar Boussaid, 2020. "A Dominance‐Based Rough Set Approach for an Enhanced Assessment of Seasonal Influenza Risk," Risk Analysis, John Wiley & Sons, vol. 40(7), pages 1323-1341, July.

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