COVID-19 Detection from Mass Spectra of Exhaled Breath

Abstract

According to the World Health Organization, the SARS-CoV-2 virus generated a global emergency between 2020 and 2023 resulting in about 7 million deaths out of more than 750 million individuals diagnosed with COVID-19. During these years, polymerase-chain-reaction and antigen testing played a prominent role in disease control. In this study, we propose a fast and non-invasive detection system exploiting a proprietary mass spectrometer to measure ions in exhaled breath. We demonstrated that infected individuals, even if asymptomatic, exhibit characteristics in the air expelled from the lungs that can be detected by a nanotech-based technology and then recognized by soft-computing algorithms. A clinical trial was ran on about 300 patients: the mass spectra in the 10-351 mass-to-charge range were measured, suitably pre-processed, and analyzed by different classification models; eventually, the system shown an accuracy of 95% and a recall of 94% in identifying cases of COVID-19. With performances comparable to traditional methodologies, the proposed system could play a significant role in both routine examination for common diseases and emergency response for new epidemics.