An easy-to-use algorithm can now be used to determine the risk of being infected by SARS-CoV-2 via aerosol particles from patients in indoor environments. It also estimates how protective measures such as wearing masks and ventilation reduce the risk. The model, developed by researchers at the Max Planck Institute in Chemistry in Mainz, uses parameters such as the size of the room, the number of people in it and their activity to estimate both the individual risk of COVID-19 infection and the risk of anyone in the room. The algorithm is publicly available via an input mask on the institute’s website. It calculates infection risk by micrometer size aerosol particles, but not by larger droplets in case of close contact with an infected person. The approach complements standard protection measures.
Even though experts have not yet reached full agreement, many assume that aerosol particles play an important role in the transmission of SARS-CoV-2 viruses. The aerosols are created when breathing, talking and singing. Unlike droplets, they don’t fall to the ground quickly, but can stay in the air for a long time and spread throughout the room. Indoor situations where many people are together for an extended period are particularly critical for infection with COVID-19. But how high is the risk of infection really? And how much can it be reduced by wearing face masks and active ventilation?
Researchers at the Max Planck Institute for Chemistry and the Cyprus Institute (Cyprus) have now published a study in which they present an easy-to-use spreadsheet algorithm to estimate the probability of COVID-19 infections through indoor aerosol transmission. The algorithm is publicly available, and can also be