Researchers have developed a hydroalcoholic gel with a QR code that enables people to access a test that assesses their ability to identify the smell of the product and eight symptoms of COVID, instantly evaluating the risk of having the deadly respiratory disease.

The team from Spain's Universitat Rovira i Virgili, in conjunction with the Pere Virgili Health Research Institute, developed this method, which is based on artificial intelligence (AI) techniques.

The AI model instantly determines which people have a low, medium or high risk of having the disease at that moment with a sensitivity of 97 per cent.

The first prototype of this device has been installed at the entrance to the Sant Joan University Hospital in Reus and the research results were published in the journal Scientific Reports.

Citrus fruits and apples are two of the first aromas that people with the SARS-CoV-2 virus stop detecting. Also, a high temperature, a headache, a cough, discomfort and a sore throat are all signs of the coronavirus but also of a cold or flu.

The AI system that has been patented is based on a hydroalcoholic gel to which a particular concentration of citrus essence has been added.

"We knew from the results of previous research that this aroma is one of the first that COVID sufferers cannot perceive when they lose their sense of smell," said Eduard Llobet, a researcher from the URV's Department of Electronic, Electrical and Automatic Engineering.

"We did tests with different concentrations until we determined the one we needed," he added.

This test was performed on approximately 500 patients, because they had COVID-like symptoms or because they were asymptomatic but had been in close contact with a positive case.

They had to rub their hands with the gel and then smell them after three seconds. The result was considered negative if they recognised a citrus fruit, and positive if they couldn't smell the gel or could not detect a citrus aroma.

Once this had been done, the participants in the study had to fill in a short questionnaire with the result of the smell test and other data such as age, gender and the presence or absence of different symptoms.

"We gave each symptom a diagnostic value based on our calculations, and there were eight that we regarded as statistically significant for detecting the disease," explained Youcef Aceli, a researcher at the IISPV, who headed the research.

Once the participants had their answers given, they were given a PCR test to check the result. The data ensured almost total sensitivity (97 per cent), which makes it useful as a method for screening the population.

"The antigen tests on the market have an average sensitivity of 80 per cent, which means that the number of false negatives is 20 per cent. What we have developed is not a diagnostic test, but a screening system that aims to detect the maximum possible number of positives and prevent false negatives," the researchers said.