Exhaled breath samples had the highest positive rate (26.9%, n=52), followed by surface swabs (5.4%, n=242), and air samples (3.8%, n=26). COVID-19 patients recruited in Beijing exhaled millions of SARS-CoV-2 RNA copies into the air per hour. Exhaled breath emission may play an important role in the COVID-19 transmission.

The COVID-19 pandemic has brought an unprecedented crisis to the global health sector. When discharging COVID-19 patients in accordance with throat or nasal swab protocols using RT-PCR, the potential risk of reintroducing the infection source to humans and the environment must be resolved. Here, 14 patients including 10 COVID-19 subjects were recruited; exhaled breath condensate (EBC), air samples and surface swabs were collected and analyzed for SARS-CoV-2 using reverse transcription-polymerase chain reaction (RT-PCR) in four hospitals with applied natural ventilation and disinfection practices in Wuhan. Here we discovered that 22.2% of COVID-19 patients (n = 9), who were ready for hospital discharge based on current guidelines, had SARS-CoV-2 in their exhaled breath (~10 5 RNA copies/m 3 ). Although fewer surface swabs (3.1%, n = 318) tested positive, medical equipment such as face shield frequently contacted/used by healthcare workers and the work shift floor were contaminated by SARS-CoV-2 (3–8 viruses/cm 2 ). Three of the air samples (n = 44) including those collected using a robot-assisted sampler were detected positive by a digital PCR with a concentration level of 9–219 viruses/m 3 . RT-PCR diagnosis using throat swab specimens had a failure rate of more than 22% in safely discharging COVID-19 patients who were otherwise still exhaling the SARS-CoV-2 by a rate of estimated ~1400 RNA copies per minute into the air. Direct surface contact might not represent a major transmission route, and lower positive rate of air sample (6.8%) was likely due to natural ventilation (1.6–3.3 m/s) and regular disinfection practices. While there is a critical need for strengthening hospital discharge standards in preventing re-emergence of COVID-19 spread, use of breath sample as a supplement specimen could further guard the hospital discharge to ensure the safety of the public and minimize the pandemic re-emergence risk.

Rapid screening of COVID-19 is key to controlling the pandemic. However, current nucleic acid amplification involves lengthy procedures in addition to the discomfort of taking throat/nasal swabs. Here we describe potential breath-borne volatile organic compound (VOC) biomarkers together with machine learning that can be used for point-of-care screening of COVID-19. Using a commercial gas chromatograph-ion mobility spectrometer, higher levels of propanol were detected in the exhaled breath of COVID-19 patients (N = 74) and non-COVID-19 respiratory infections (RI) (N = 30) than those of non-COVID-19 controls (NC)/health care workers (HCW) (N = 87), and backgrounds (N = 87). In contrast, breath-borne acetone was found to be significantly lower for COVID-19 patients than other subjects. Twelve key endogenous VOC species using supervised machine learning models (support vector machines, gradient boosting machines (GBMs), and Random Forests) were shown to exhibit strong capabilities in discriminating COVID-19 from (HCW + NC) and RI with a precision ranging from 91% to 100%. GBM and Random Forests models can also discriminate RI patients from healthy subjects with a precision of 100%. In addition, the developed models using breath-borne VOCs could also detect a confirmed COVID-19 patient but with a false negative throat swab polymerase chain reaction test. It takes 10 min to allow an entire breath test to finish, including analysis of the 12 key VOC species. The developed technology provides a novel concept for non-invasive rapid point-of-care-test screening for COVID-19 in various scenarios.