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      From bad to worse: airline boarding changes in response to COVID-19

      research-article
      1 , 2 , 1 , , 3 , 4 , 4
      Royal Society Open Science
      The Royal Society
      pedestrian dynamics, COVID-19, aeroplane boarding

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          Abstract

          Airlines have introduced a back-to-front boarding process in response to the COVID-19 pandemic. It is motivated by the desire to reduce passengers' likelihood of passing close to seated passengers when they take their seats. However, our prior work on the risk of Ebola spread in aeroplanes suggested that the driving force for increased exposure to infection transmission risk is the clustering of passengers while waiting for others to stow their luggage and take their seats. In this work, we examine whether the new boarding processes lead to increased or decreased risk of infection spread. We also study the reasons behind the risk differences associated with different boarding processes. We accomplish this by simulating the new boarding processes using pedestrian dynamics and compare them against alternatives. Our results show that back-to-front boarding roughly doubles the infection exposure compared with random boarding. It also increases exposure by around 50% compared to a typical boarding process prior to the outbreak of COVID-19. While keeping middle seats empty yields a substantial reduction in exposure, our results show that the different boarding processes have similar relative strengths in this case as with middle seats occupied. We show that the increased exposure arises from the proximity between passengers moving in the aisle and while seated. Such exposure can be reduced significantly by prohibiting the use of overhead bins to stow luggage. Our results suggest that the new boarding procedures increase the risk of exposure to COVID-19 compared with prior ones and are substantially worse than a random boarding process.

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          Most cited references25

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          Simulating dynamical features of escape panic.

          One of the most disastrous forms of collective human behaviour is the kind of crowd stampede induced by panic, often leading to fatalities as people are crushed or trampled. Sometimes this behaviour is triggered in life-threatening situations such as fires in crowded buildings; at other times, stampedes can arise during the rush for seats or seemingly without cause. Although engineers are finding ways to alleviate the scale of such disasters, their frequency seems to be increasing with the number and size of mass events. But systematic studies of panic behaviour and quantitative theories capable of predicting such crowd dynamics are rare. Here we use a model of pedestrian behaviour to investigate the mechanisms of (and preconditions for) panic and jamming by uncoordinated motion in crowds. Our simulations suggest practical ways to prevent dangerous crowd pressures. Moreover, we find an optimal strategy for escape from a smoke-filled room, involving a mixture of individualistic behaviour and collective 'herding' instinct.
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            Transmission of infectious diseases during commercial air travel

            Summary Because of the increasing ease and affordability of air travel and mobility of people, airborne, food-borne, vector-borne, and zoonotic infectious diseases transmitted during commercial air travel are an important public health issue. Heightened fear of bioterrorism agents has caused health officials to re-examine the potential of these agents to be spread by air travel. The severe acute respiratory syndrome outbreak of 2002 showed how air travel can have an important role in the rapid spread of newly emerging infections and could potentially even start pandemics. In addition to the flight crew, public health officials and health care professionals have an important role in the management of infectious diseases transmitted on airlines and should be familiar with guidelines provided by local and international authorities.
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              Review and comparison between the Wells–Riley and dose‐response approaches to risk assessment of infectious respiratory diseases

              Abstract  Infection risk assessment is very useful in understanding the transmission dynamics of infectious diseases and in predicting the risk of these diseases to the public. Quantitative infection risk assessment can provide quantitative analysis of disease transmission and the effectiveness of infection control measures. The Wells–Riley model has been extensively used for quantitative infection risk assessment of respiratory infectious diseases in indoor premises. Some newer studies have also proposed the use of dose‐response models for such purpose. This study reviews and compares these two approaches to infection risk assessment of respiratory infectious diseases. The Wells–Riley model allows quick assessment and does not require interspecies extrapolation of infectivity. Dose‐response models can consider other disease transmission routes in addition to airborne route and can calculate the infectious source strength of an outbreak in terms of the quantity of the pathogen rather than a hypothetical unit. Spatial distribution of airborne pathogens is one of the most important factors in infection risk assessment of respiratory disease. Respiratory deposition of aerosol induces heterogeneous infectivity of intake pathogens and randomness on the intake dose, which are not being well accounted for in current risk models. Some suggestions for further development of the risk assessment models are proposed. Practical Implications This review article summarizes the strengths and limitations of the Wells–Riley and the dose‐response models for risk assessment of respiratory diseases. Even with many efforts by various investigators to develop and modify the risk assessment models, some limitations still persist. This review serves as a reference for further development of infection risk assessment models of respiratory diseases. The Wells–Riley model and dose‐response model offer specific advantages. Risk assessors can select the approach that is suitable to their particular conditions to perform risk assessment.
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                Author and article information

                Contributors
                Journal
                R Soc Open Sci
                RSOS
                royopensci
                Royal Society Open Science
                The Royal Society
                2054-5703
                April 28, 2021
                April 2021
                : 8
                : 4
                : 201019
                Affiliations
                [ 1 ]Department of Computer Science, University of West Florida, , Pensacola, FL, USA
                [ 2 ]Department of Computer Science, Florida State University, , Tallahassee, FL, USA
                [ 3 ]Department of Aerospace Engineering, Embry-Riddle Aeronautical University, , Daytona Beach, FL, USA
                [ 4 ]Arizona State University, , Tempe, AZ, USA
                Author information
                http://orcid.org/0000-0003-0408-2886
                http://orcid.org/0000-0003-1487-9573
                http://orcid.org/0000-0003-3936-3055
                http://orcid.org/0000-0001-5100-9724
                Article
                rsos201019
                10.1098/rsos.201019
                8080014
                34007455
                bd76889d-1f60-424f-b41d-a7143683cc94
                © 2021 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : June 10, 2020
                : April 13, 2021
                Funding
                Funded by: National Science Foundation, http://dx.doi.org/10.13039/100000001;
                Award ID: 1931511
                Award ID: 2027514
                Award ID: 2027518
                Award ID: 2027529
                Categories
                1003
                1004
                50
                44
                Computer Science and Artificial Intelligence
                Research Articles

                pedestrian dynamics,covid-19,aeroplane boarding
                pedestrian dynamics, covid-19, aeroplane boarding

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