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.

翻译：根据世界卫生组织的数据，SARS-CoV-2病毒在2020至2023年间引发了全球紧急状态，导致超过7.5亿确诊的COVID-19患者中约700万人死亡。在此期间，聚合酶链反应检测和抗原检测在疾病控制中发挥了关键作用。本研究提出了一种快速、非侵入性的检测系统，利用专有质谱仪测量呼出气体中的离子。我们证实，即使是无症状感染者，其肺部呼出的气体也会呈现特征性变化，这些变化可通过纳米技术基检测设备捕获，并由软计算算法识别。一项针对约300名患者的临床试验显示：在10-351质荷比范围内的质量谱经过适当预处理后，采用多种分类模型进行分析，最终该系统的COVID-19识别准确率达到95%，召回率达到94%。其性能与传统检测方法相当，所提出的系统既可在常规疾病筛查中发挥作用，也能为新发疫情的应急响应提供重要支持。