In the era of coronavirus disease 2019 (COVID-19) pandemic, imported COVID-19 cases pose great challenges to many countries. Chest CT examination is considered to be complementary to nucleic acid test for COVID-19 detection and diagnosis. We report the first community infected COVID-19 patient by an imported case in Beijing, which manifested as nodular lesions on chest CT imaging at the early stage. Deep Learning (DL)-based diagnostic systems quantitatively monitored the progress of pulmonary lesions in 6 days and timely made alert for suspected pneumonia, so that prompt medical isolation was taken. The patient was confirmed as COVID-19 case after nucleic acid test, for which the community transmission was prevented timely. The roles of DL-assisted diagnosis in helping radiologists screening suspected COVID cases were discussed.
Adult ; Beijing ; COVID-19/diagnostic imaging* ; COVID-19 Testing/methods* ; Community-Acquired Infections/diagnostic imaging* ; Deep Learning ; Humans ; Lung/diagnostic imaging* ; Male ; Tomography, X-Ray Computed/methods*

Objective: To establish a rapid and specific quantitative real-time PCR (qPCR) method for the detection of SARS-CoV-2 subgenomic nucleocapsid RNA (SgN) in patients with COVID-19 or environmental samples. Methods: The qPCR assay was established by designing specific primers and TaqMan probe based on the SARS-CoV-2 genomic sequence in Global Initiative of Sharing All Influenza Data (GISAID) database. The reaction conditions were optimized by using different annealing temperature, different primers and probe concentrations and the standard curve was established. Further, the specificity, sensitivity and repeatability were also assessed. The established SgN and genomic RNA (gRNA) qPCR assays were both applied to detect 21 environmental samples and 351 clinical samples containing 48 recovered patients. In the specimens with both positive gRNA and positive SgN, 25 specimens were inoculated on cells. Results: The primers and probes of SgN had good specificity for SARS-CoV-2. The minimum detection limit of the preliminarily established qPCR detection method for SgN was 1.5×10² copies/ml, with a coefficient of variation less than 1%. The positive rate of gRNA in 372 samples was 97.04% (361/372). The positive rates of SgN in positive environmental samples and positive clinical samples were 36.84% (7/19) and 49.42% (169/342), respectively. The positive rate and copy number of SgN in Wild strain were lower than those of SARS-CoV-2 Delta strain. Among the 25 SgN positive samples, 12 samples within 5 days of sampling time were all isolated with virus; 13 samples sampled for more than 12 days had no cytopathic effect. Conclusion: A qPCR method for the detection of SARS-CoV-2 SgN has been successfully established. The sensitivity, specificity and repeatability of this method are good.
Humans ; SARS-CoV-2/genetics* ; COVID-19/diagnosis* ; Subgenomic RNA ; Real-Time Polymerase Chain Reaction/methods* ; RNA, Viral/genetics* ; Sensitivity and Specificity ; Nucleocapsid/chemistry* ; COVID-19 Testing

COVID-19/transmission* ; COVID-19 Testing ; Humans ; Infection Control ; Infectious Disease Transmission, Patient-to-Professional/prevention & control* ; Intraoperative Care ; Pandemics ; Personal Protective Equipment ; Postoperative Care ; Preoperative Care ; Tracheostomy/methods*

Adolescent ; Adult ; Aged ; COVID-19/virology* ; COVID-19 Nucleic Acid Testing/methods* ; Child ; Coronavirus Nucleocapsid Proteins/genetics* ; Feces/virology* ; Female ; Humans ; Male ; Middle Aged ; Phosphoproteins/genetics* ; RNA, Viral/genetics* ; SARS-CoV-2/isolation & purification* ; Young Adult

COVID-19 Nucleic Acid Testing/methods* ; Clinical Laboratory Techniques ; Containment of Biohazards ; Disinfection ; Environmental Monitoring ; Humans ; Nucleic Acids/isolation & purification* ; SARS-CoV-2/isolation & purification* ; Specimen Handling