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Analyzing the Role of Air-Transportation in COVID-19 Pandemic Disaster
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2023-04-01
[PDF-1.49 MB]
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Edition:Final Report FEB 2019-JUNE 2020
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Abstract:COVID-19 pandemic has resulted in an over 60% reduction in air travel worldwide according to some estimates. The high economic and public perception costs of potential superspreading during air travel necessitates research efforts that model, explain and mitigate disease spread. Here, we use a novel infection risk model that is linked with pedestrian dynamics to accurately capture these aspects of infection spread. The model is first parameterized through spatiotemporal analysis of a recent superspreading event in a restaurant in China. The passenger movement during boarding and deplaning, as well as the in-plane movement, are modeled with social force model and agent-based model respectively. We utilize the model to evaluate what-if scenarios on the relative effectiveness of policies and procedures such as masking and social distancing, as well as synergistic effects by combining different approaches in airplanes and other contexts. We then applied the dose response models to parametrically analyze the spread of infection and the effect of mask usage in generic transportation systems. We analyzed five empirical events of SARS-COV-2 transmission where the spatiotemporal details of the infected persons are known. We found that the dose level had a significant impact on the number of secondary infections. In general, mask usage reduced infections at all dose levels. High-quality N-95 masks are effective for all dose levels, while lower-quality masks exhibit a limited mitigation efficiency, especially for high-dose conditions. Sensitivity analysis indicated that the reduction in infection distance threshold is a critical factor in mask usage.
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