ABSTRACT
ObjectivesNo data were available about in-flight transmission of SARS-CoV-2. Here, we report an in-flight transmission cluster of COVID-19 and describe the clinical characteristics of these patients. MethodsAfter a flight, laboratory-confirmed COVID-19 was reported in 12 patients. Ten patients were admitted to the designated hospital. Data were collected from 25th January to 28th February 2020. Clinical information was retrospectively collected. ResultsAll patients are passengers without flight attendants. The median age was 33 years, and 70% were females. None was admitted to intensive care unit, and no patients succumbed through 28th February. The median incubation period was 3.0 days and from illness onset to hospital admission was 2 days. The most common symptom was fever. Two patients were asymptomatic and negative for chest CT scan throughout the disease courses. On admission, initial RT-PCR were positive in 9 patients, however initial chest CT were positive in only half patients. The median lung "total severity score" of chest CT was 6. Notably, "Crazy-Paving" pattern, pleural effusion, and ground-glass nodules were also seen. ConclusionIt is potential for COVID-19 transmission by airplane, but the symptoms are mild. Passengers and attendants must be protected during the flight.
ABSTRACT
To facilitate noninvasive diagnosis of anemia, high-performance and portable near infrared (NIR) spectrometer for human blood constituents was designed and fabricated based on linear variable filter (LVF).Meanwhile, the performance of support vector regression (SVR) model for quantitative analysis of human hemoglobin (Hb) was investigated.Spectral data were collected noninvasively from 100 volunteers by self-designed LVF-NIR spectrometer, then divided into calibration set, validation set 1 and 2.To establish a robust SVR model, grid search method was applied to optimize the penalty parameter and kernel function parameter c=5.28, g=0.33.Then, Hb levels in the validation 1 and 2 sets were quantitatively analyzed.The results showed that the root mean square error of prediction (RMSEP) were 10.20 g/L and 10.85 g/L, respectively, and the relative RMSEP (R-RMSEP) were 6.85% and 7.48%, respectively.The results indicated that the SVR model had high prediction accuracy to Hb level and adaptability to different samples, and could satisfy the requirements of clinical measurement.Based on the SVR algorithm, the self-designed LVF-NIR spectrometer has a wide application prospect in the field of non-invasive anemia diagnosis.
