Litcius/Paper detail

Detecting COVID-19 from Breath: A Game Changer for a Big Challenge

Giorgia Giovannini, Hossam Haick, Denis Garoli

2021ACS Sensors128 citationsDOIOpen Access PDF

Abstract

Coronavirus disease 2019 (COVID-19) is probably the most commonly heard word of the last 12 months. The outbreak of this virus (SARS-CoV-2) is strongly compromising worldwide healthcare systems, social behavior, and everyone's lives. The early diagnosis of COVID-19 and isolation of positive cases has proven to be fundamental in containing the spread of the infection. Even though the polymerase chain reaction (PCR) based methods remain the gold standard for SARS-CoV-2 detection, the urgent demand for rapid and wide-scale diagnosis precipitated the development of alternative diagnostic approaches. The millions of tests performed every day worldwide are still insufficient to achieve the desired goal, that of screening the population during daily life. Probably the most appealing approach to consistently monitor COVID-19 spread is the direct detection of SARS-CoV-2 from exhaled breath. For instance, the challenging incorporation of reliable, highly sensitive, and cost-efficient detection methods in masks could represent a breakthrough in the development of portable and noninvasive point-of-care diagnosis for COVID-19. In this perspective paper, we discuss the critical technical aspects related to the application of breath analysis in the diagnosis of viral infection. We believe that, if achieved, it could represent a game-changer in containing the pandemic spread.

Topics & Concepts

Coronavirus disease 2019 (COVID-19)Gold standard (test)PandemicIsolation (microbiology)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Intensive care medicineMedicinePopulation2019-20 coronavirus outbreakVirologyOutbreakComputer scienceDiseasePathologyBioinformaticsBiologyInfectious disease (medical specialty)Environmental healthInternal medicineAdvanced Chemical Sensor TechnologiesSARS-CoV-2 detection and testingBiosensors and Analytical Detection