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The dose-response model has been widely used for quantifying the risk ofinfection of airborne diseases like COVID-19. The model has been used in theroom-average analysis of infection risk and analysis using passive scalars as aproxy for aerosol transport. However, it has not been employed for riskestimation in numerical simulations of droplet dispersion. In this work, wedevelop a framework for the evaluation of the probability of infection indroplet dispersion simulations using the dose-response model. We introduce aversion of the model that can incorporate the higher transmissibility ofvariant strains of SARS-CoV2 and the effect of vaccination in evaluating theprobability of infection. Numerical simulations of droplet dispersion duringspeech are carried out to investigate the infection risk over space and timeusing the model. The advantage of droplet dispersion simulations for riskevaluation is demonstrated through the analysis of the effect of humidity oninfection risk.

Quantifying the COVID19 infection risk due to droplet/aerosol inhalation