A Lagrangian Approach Towards Quantitative Analysis Of Flow-mediated Infection Transmission In Indoor Spaces With Application To SARS-COV-2 Journal Article uri icon



  • AbstractThe ongoing SARS-CoV-2 (Covid-19) pandemic has ushered an unforeseen level of global health and economic burden. As a respiratory infection, Covid-19 is known to have a dominant airborne transmission modality, wherein fluid flow plays a central role. Quantification of complex non-intuitive dynamics and transport of pathogen laden respiratory particles in indoor flows has been of specific interest. Here we present a Lagrangian computational approach towards quantification of human-to-human exposure quantifiers, and identification of pathways by which flow organizes transmission. We develop a Lagrangian viral exposure index in a parametric form, accounting for key parameters such as building and layout, ventilation, occupancy, biological variables. We also employ a Lagrangian computation of the Finite Time Lyapunov Exponent field to identify hidden patterns of transport. A systematic parametric study comprising a set of 120 simulations, yielding a total of 1,320 different exposure index computations are presented. Results from these simulations enable: (a) understanding the otherwise hidden ways in which air flow organizes the long-range transport of such particles; and (b) translating the micro-particle transport data into a quantifier for understanding infection exposure risks.

publication date

  • August 25, 2021

has restriction

  • green

Date in CU Experts

  • September 13, 2021 1:00 AM

Full Author List

  • Wilson J; Miller SL; Mukherjee D

author count

  • 3

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