Quantifying the COVID19 infection risk due to droplet/aerosol inhalation

Abstract

The dose-response model has been widely used for quantifying the risk of infection of airborne diseases like COVID-19. The model has been used in the room-average analysis of infection risk and analysis using passive scalars as a proxy for aerosol transport. However, it has not been employed for risk estimation in numerical simulations of droplet dispersion. In this work, we develop a framework for the evaluation of the probability of infection in droplet dispersion simulations using the dose-response model. We introduce a version of the model that can incorporate the higher transmissibility of variant strains of SARS-CoV2 and the effect of vaccination in evaluating the probability of infection. Numerical simulations of droplet dispersion during speech are carried out to investigate the infection risk over space and time using the model. The advantage of droplet dispersion simulations for risk evaluation is demonstrated through the analysis of the effect of humidity on infection risk.

Digital transformation of droplet/aerosol infection risk assessment realized on "Fugaku" for the fight against COVID-19

“…where v0 d is the quasi-steady state rate of droplet ejection volume entering the breathing zone. Further details of the model can be found in the work of [1] We are currently working to refine this model to deal with aerosols that are directly generated inside the lung, exhaled, and then inhaled into the lung and actually infection the cells. The results from such work will be reported in our future publications.…”