Multiscale model for pedestrian and infection dynamics during air travel

Sirish Namilae, Pierrot Derjany, Anuj Mubayi, Mathew Scotch, and Ashok Srinivasan
Phys. Rev. E 95, 052320 – Published 31 May 2017

Abstract

In this paper we develop a multiscale model combining social-force-based pedestrian movement with a population level stochastic infection transmission dynamics framework. The model is then applied to study the infection transmission within airplanes and the transmission of the Ebola virus through casual contacts. Drastic limitations on air-travel during epidemics, such as during the 2014 Ebola outbreak in West Africa, carry considerable economic and human costs. We use the computational model to evaluate the effects of passenger movement within airplanes and air-travel policies on the geospatial spread of infectious diseases. We find that boarding policy by an airline is more critical for infection propagation compared to deplaning policy. Enplaning in two sections resulted in fewer infections than the currently followed strategy with multiple zones. In addition, we found that small commercial airplanes are better than larger ones at reducing the number of new infections in a flight. Aggregated results indicate that passenger movement strategies and airplane size predicted through these network models can have significant impact on an event like the 2014 Ebola epidemic. The methodology developed here is generic and can be readily modified to incorporate the impact from the outbreak of other directly transmitted infectious diseases.

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  • Received 30 November 2016
  • Revised 7 March 2017

DOI:https://doi.org/10.1103/PhysRevE.95.052320

©2017 American Physical Society

Physics Subject Headings (PhySH)

Statistical Physics & ThermodynamicsInterdisciplinary PhysicsNetworksPhysics of Living Systems

Authors & Affiliations

Sirish Namilae1,*, Pierrot Derjany1, Anuj Mubayi2, Mathew Scotch3,4, and Ashok Srinivasan5

  • 1Department of Aerospace Engineering, Embry-Riddle Aeronautical University, Daytona Beach, Florida 32114, USA
  • 2SAL Mathematical, Computational and Modeling Science Center, School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona 85287, USA
  • 3Department of Biomedical Informatics, Arizona State University, Scottsdale, Arizona 85259, USA
  • 4Biodesign Center for Environmental Security, Arizona State University, Tempe, Arizona 85257, USA
  • 5Department of Computer Science, Florida State University, Tallahassee, Florida 32306, USA

  • *Corresponding author: namilaes@erau.edu

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Issue

Vol. 95, Iss. 5 — May 2017

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