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Activity Number:
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90
- Novel Statistical Methods for COVID Pandemic and Other Current Health Policy Issues
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Type:
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Contributed
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Date/Time:
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Monday, August 9, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Health Policy Statistics Section
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Abstract #319019
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Title:
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Boeing Confident Travel Initiative Passenger Screening Model
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Author(s):
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Lindsay Waite Jones* and Ahmad Nahhas and Jan Irvahn and Grace S Garden and William Ferng and Elizabeth Killelea and Jason W Armstrong and Thomas Austin and Stephen Jones and Joshua J Cummins
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Companies:
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Boeing and Boeing and Boeing and Boeing and Boeing and Boeing and Boeing and Boeing and Boeing and Boeing
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Keywords:
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COVID-19;
air travel;
screening;
COVID-19 testing
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Abstract:
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Air travel volume, particularly international travel volume, has decreased dramatically as a result of the COVID-19 pandemic. The Boeing Confident Travel Initiative (CTI) has responded by using a data-driven modeling approach to inform decisions in order to make air travel safer and to increase passenger confidence in the safety of air travel amidst the pandemic. The CTI passenger screening model was developed to compare different screening approaches through one or more COVID-19 tests in order to provide safe options that will allow the reopening of international travel. We use a Monte Carlo approach to simulate a group of COVID-19 infected travelers, each with an individual infection timeline, and model test performance as a function of that timeline to compare the effectiveness of different screening strategies. Moreover, we incorporate disease prevalence data from countries around the world in order to provide tailored results for specific travel journeys. Our model provides an avenue to compare the relative performance of screening and quarantine practices and to determine which approaches may be best for specific country-to-country travel journeys.
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Authors who are presenting talks have a * after their name.
