This tool is believed to be able to determine whether an uninfected person who later catches the virus will die from the disease with up to 90% certainty. It also claims to predict whether someone who’s admitted to hospital with COVID-19 will need a respirator with 80% accuracy.

It can also help identify who to prioritize for vaccines and how many respirators a hospital will need. Professor Mads Nielsen from University of Copenhagen added:

“We are working towards a goal that we should be able to predict the need for respirators five days ahead by giving the computer access to health data on all COVID positives in the region. The computer will never be able to replace a doctor’s assessment, but it can help doctors and hospitals see many COVID-19 infected patients at once and set ongoing priorities.”

The study showed that the most decisive indicators were unsurprisingly BMI and age. Males and people with high blood pressure or neurological disease also have an elevated risk. The other most influential factors were having chronic obstructive pulmonary disease (COPD), asthma, diabetes, and heart disease. Professor Nielsen also added:

“For those affected by one or more of these parameters, we have found that it may make sense to move them up in the vaccine queue, to avoid any risk of them becoming infected and eventually ending up on a respirator.”

You can check the whole study journal from Scientific Reports.