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This paper presents an integrated computational modelling framework combining pedestrian dynamics and infection spread models, to analyse the infectious disease spread during the different stages of air-travel. While, commercial air travel is central to the global mobility of goods and people, it has also been identified as a leading factor in the spread of several epidemic diseases including influenza, SARS and Ebola. The mixing of susceptible and infectious individuals in these high people density locations like airports involves pedestrian movement which needs to be taken into account in the modeling studies of disease dynamics. We develop a Molecular Dynamics based social force modeling approach for pedestrian dynamics and combine it with a stochastic infection dynamics model to evaluate the spread of viral infectious diseases in airplanes and airports. We apply the multiscale model for various key components of air travel and suggest strategies to reduce the number of contacts and the spread of infectious diseases. We simulate pedestrian movement during boarding and deplaning of some typical commercial airplane models and movement of people through security check areas. We found specific boarding strategies that reduce the number of contacts. Further, we find that smaller airplanes are more effective in reducing the number of contacts compared to larger airplanes. We propose certain queue configuration that reduces contacts between people and mitigate disease spread. 

Molecular dynamics is an N-body method wherein dynamic evolution of interacting atoms and molecules is computationally simulated. It is a popular computational method for studying the mechanical and thermal behavior of nanomaterials and nanocomposites. Social force models [1] of pedestrian evolution utilize the same numerical framework for evolving the trajectories of moving pedestrians. In this paper, we propose an integrated model that merges a social force based pedestrian dynamics theory with a stochastic infection transmission framework to evaluate the propagation of Ebola infection aboard an airplane. Air travel has been identified as a leading factor in the spread of many different viruses [2]. Pedestrian motion through airports and airplanes leads to susceptible passengers coming into contact with infected passengers and contagion with harmful consequences. The objective of this study is to evaluate the effects of pedestrian movement during air-travel on the spread of infectious diseases. We do so borrowing numerical methods like molecular dynamics and Monte Carlo analysis from the field of computational materials science. 

This paper presents an integrated computational framework combining a molecular Dynamics (MD) based social force pedestrian movement model and a stochastic infection dynamics model to evaluate the spread of viral infectious diseases during air-transportation. We apply the multiscale model for three infectious (1) Ebola (2) Influenza (H1N1 strain) and (3) SARS pathogens with different transmission mechanisms and compare the pattern of propagation during an Airbus A320 carrier boarding and deplaning at an airport gate. The objective of this analysis is to assess the influence of pedestrian movement on infection spread during air travel