Effect Of Human Movement On Airborne Disease Transmission In An Airplane Cabin: Study Using Numerical Modeling And Quantitative Risk Analysis. - Info and Reading Options

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This article is from <a href="//archive.org/search.php?query=journaltitle%3A%28BMC%20Infectious%20Diseases%29" rel="nofollow">BMC Infectious Diseases</a>, <a href="//archive.org/search.php?query=journaltitle%3A%28BMC%20Infectious%20Diseases%29%20AND%20volume%3A%2814%29" rel="nofollow">volume 14</a>.<h2>Abstract</h2>Background: Airborne transmission of respiratory infectious disease in indoor environment (e.g. airplane cabin, conference room, hospital, isolated room and inpatient ward) may cause outbreaks of infectious diseases, which may lead to many infection cases and significantly influences on the public health. This issue has received more and more attentions from academics. This work investigates the influence of human movement on the airborne transmission of respiratory infectious diseases in an airplane cabin by using an accurate human model in numerical simulation and comparing the influences of different human movement behaviors on disease transmission. Methods: The Eulerian–Lagrangian approach is adopted to simulate the dispersion and deposition of the expiratory aerosols. The dose–response model is used to assess the infection risks of the occupants. The likelihood analysis is performed as a hypothesis test on the input parameters and different human movement pattern assumptions. An in-flight SARS outbreak case is used for investigation. A moving person with different moving speeds is simulated to represent the movement behaviors. A digital human model was used to represent the detailed profile of the occupants, which was obtained by scanning a real thermal manikin using the 3D laser scanning system. Results: The analysis results indicate that human movement can strengthen the downward transport of the aerosols, significantly reduce the overall deposition and removal rate of the suspended aerosols and increase the average infection risk in the cabin. The likelihood estimation result shows that the risk assessment results better fit the outcome of the outbreak case when the movements of the seated passengers are considered. The intake fraction of the moving person is significantly higher than most of the seated passengers. Conclusions: The infection risk distribution in the airplane cabin highly depends on the movement behaviors of the passengers and the index patient. The walking activities of the crew members and the seated passengers can significantly increase their personal infection risks. Taking the influence of the movement of the seated passengers and the index patient into consideration is necessary and important. For future studies, investigations on the behaviors characteristics of the passengers during flight will be useful and helpful for infection control. Electronic supplementary material: The online version of this article (doi:10.1186/1471-2334-14-434) contains supplementary material, which is available to authorized users.

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