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Journal article
Parameter space exploration in pedestrian queue design to mitigate infectious disease spread
Journal of the Indian Institute of Science, Vol.101(3), pp.329-339
2021
PMCID: PMC8329629
PMID: 34366585
Web of Science ID: WOS:000680760700001
Abstract
Reducing the interactions between pedestrians in crowded environments can potentially curb the spread of infectious diseases including COVID-19. The mixing of susceptible and infectious individuals in many high-density man-made environments such as waiting queues
involves pedestrian movement, which is generally not taken into account in modeling studies of disease dynamics. In this paper, a social force-based pedestrian-dynamics approach is used to evaluate the contacts among proximate pedestrians which are then integrated with a stochastic epidemiological model to estimate the infectious disease spread in a localized outbreak. Practical application of such multiscale models to real-life scenarios can be limited by the uncertainty in human behavior, lack of data during early stage epidemics, and inherent stochasticity in the problem. We parametrize the sources of uncertainty and explore the associated parameter space using a novel high-efficiency parameter sweep algorithm. We show the effectiveness of a low-discrepancy sequence (LDS) parameter sweep in reducing the number of simulations required for effective parameter space exploration in this multiscale problem. The algorithms are applied to a model problem of infectious disease spread in a pedestrian queue similar to that at an airport security check point. We find that utilizing the low-discrepancy sequence-based parameter sweep, even for one component of the multiscale model, reduces the computational requirement by an order of magnitude.
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Details
- Title
- Parameter space exploration in pedestrian queue design to mitigate infectious disease spread
- Publication Details
- Journal of the Indian Institute of Science, Vol.101(3), pp.329-339
- Resource Type
- Journal article
- Publisher
- Indian Institute of Science; India
- Copyright
- © Indian Institute of Science 2021
- Identifiers
- WOS:000680760700001; 99380090598906600
- Academic Unit
- Computer Science; Hal Marcus College of Science and Engineering
- Language
- English