There is an urgent need for screening of patients having a communicable viral disease to cut infection chains. We could recently demonstrate that MCC-IMS of breath is able to identify In uenza-A infected patients. With decreasing In uenza epidemic and upcoming SARS-CoV-2 infections we went on and also analysed patients with suspected SARS-CoV-2 infections. 75 patients, 34m, 41f, aged 64.4 ± 15.4 years, 14 positive for In uenza-A, 16 positive for SARS-CoV-2, the remaining 44 patients were used as controls. In one patient RT-PCR was highly suspicious of SARS-CoV-2 but initially inconclusive Besides RT-PCR analysis of nasopharyngeal swabs all patients underwent MCC-IMS analysis of breath. There was no difference in gender or age according to the groups. 97.3% of the patients could be correctly classi ed to the respective group by discriminant analysis. Even the inconclusive patient could be mapped to the SARS-CoV-2 group applying the discrimination function. Conclusion MCC-IMS is able to detect SARS-CoV-2 infection and In uenza-A infection in breath. As this method provides exact, fast non-invasive diagnosis it should be further developed for screening of communicable viral diseases. Trial registration ClinicalTrial.gov, NCT04282135 Registered

There is an urgent need for screening patients of having a communicable viral disease to cut infection chains. We could recently demonstrate that MCC-IMS of breath is able to identify Influenza-A infected patients. With decreasing Influenza epidemic and upcoming SARS-CoV-2 infections we extended our study to the analysis of patients with suspected SARS-CoV-2 infections. 51 patients, 23m, 28f, aged 64 +/- 16 years, were included in this study. Besides RT-PCR analysis of nasopharyngeal swabs all patients underwent MCC-IMS analysis of breath. 16 patients, 7m, 9f, were positive for SARS-CoV-2 by RT-PCR. There was no difference in gender or age according to the groups. Stepwise canonical discriminant analysis could correctly classify the infected and non- infected subjects in 98% by cross-validation. Afterwards we combined the Influenza-A sub study and the SARS-CoV-2- sub study for a total of 75 patients, 34m, 41f, aged 64.8 +/- 1.8 years, 14 positive for Influenza-A, 16 positive for SARS-CoV-2, the remaining 44 patients were used as controls. In one patient RT-PCR was highly suspicious of SARS-CoV-2 but inconclusive. There was no imbalance between the groups for age or gender. 97.3% of the patients could be correctly classified to the respective group by discriminant analysis. Even the inconclusive patient could be mapped to the SARS-CoV-2 group applying the discrimination function. Conclusion: MCC-IMS is able to detect SARS-CoV-2 infection and Influenza-A infection in breath. As this method provides exact, fast non-invasive diagnosis it should be further developed for screening of communicable viral diseases. Study registration: NCT04282135

Infectious pathogens are a global issue. Global air travelling offers an easy and fast opportunity not only for people but also for infectious diseases to spread around the world within a few days. Also, large public events facilitate increasing infection numbers. Therefore, a rapid on-site screening for infected people is urgently needed.Due to the small size and easy handling, the ion mobility spectrometry coupled with a multicapillary column (MCC-IMS) is a very promising, sensitive method for the on-site identification of infectious pathogens based on scents, representing volatile organic compounds (VOCs).The purpose of this study was to prospectively assess whether identification of Influenza-Ainfection based on VOCs by MCC-IMS is possible in breath. Nasal breath was investigated in 24 consecutive persons with and without Influenza-A-infection by MCC-IMS. In 14 Influenza-A-infected patients, infection was proven by PCR of nasopharyngeal swabs. Four healthy staff members and six patients with negative PCR result served as controls. For picking up relevant VOCs in MCC-IMS spectra, software based on cluster analysis followed by multivariate statistical analysis was applied. With only four VOCs canonical discriminant analysis was able to distinguish Influenza-A-infected patients from not infected with 100% sensitivity and 100% specificity. This present proof-of-concept-study yields encouraging results showing a rapid diagnosis of viral infections in nasal breath within 5 minutes by MCC-IMS. The next step is to validate the results with a greater number of patients with Influenza-A-infection as well as other viral diseases, especially COVID-19. Registration number at ClinicalTrials.gov NCT04282135.

Rapid screening of infected people plays a crucial role in interrupting infection chains. However, the current methods for identification of bacteria are very tedious and labor intense. Fast on-site screening for pathogens based on volatile organic compounds (VOCs) by ion mobility spectrometry (IMS) could help to differentiate between healthy and potentially infected subjects. As a first step towards this, the feasibility of differentiating between seven different bacteria including resistant strains was assessed using IMS coupled to multicapillary columns (MCC-IMS). The headspace above bacterial cultures was directly drawn and analyzed by MCC-IMS after 90 min of incubation. A cluster analysis software and statistical methods were applied to select discriminative VOC clusters. As a result, 63 VOC clusters were identified, enabling the differentiation between all investigated bacterial strains using canonical discriminant analysis. These 63 clusters were reduced to 7 discriminative VOC clusters by constructing a hierarchical classification tree. Using this tree, all bacteria including resistant strains could be classified with an AUC of 1.0 by receiver-operating characteristic analysis. In conclusion, MCC-IMS is able to differentiate the tested bacterial species, even the non-resistant and their corresponding resistant strains, based on VOC patterns after 90 min of cultivation. Although this result is very promising, in vivo studies need to be performed to investigate if this technology is able to also classify clinical samples. With a short analysis time of 5 min, MCC-IMS is quite attractive for a rapid screening for possible infections in various locations from hospitals to airports.Key Points• Differentiation of bacteria by MCC-IMS is shown after 90-min cultivation.• Non-resistant and resistant strains can be distinguished.• Classification of bacteria is possible based on metabolic features.