Environmental contamination with SARS-CoV-2 in COVID-19 hospitals in Wuhan, China, 2020.

Coronavirus disease 2019 (COVID-19) pandemic has caused high number of infections and deaths of healthcare workers globally. Distribution and possible transmission route of SARS-CoV-2 in hospital environment should be clarified. We herein collected 431 environmental (391 surface and 40 air) samples in the intensive care unit (ICU) and general wards (GWs) of three hospitals in Wuhan, China from February 21 to March 4, 2020, and detected SARS-CoV-2 RNA by real-time quantitative PCR. The viral positive rate in the contaminated areas was 17.8% (28/157), whereas there was no virus detected in the clean areas. Higher positive rate (22/59, 37.3%) was found in ICU than that in GWs (3/63, 4.8%). The surfaces of computer keyboards and mouse in the ICU were the most contaminated (8/10, 80.0%), followed by the ground (6/9, 66.7%) and outer glove (2/5, 40.0%). From 17 air samples in the contaminated areas, only one sample collected at a distance of around 30 cm from the patient was positive. Enhanced surface disinfection and hand hygiene effectively decontaminated the virus from the environment. This finding might help understand the transmission route and contamination risk of SARS-CoV-2 and evaluate the effectiveness of infection prevention and control measures in healthcare facilities.

Comparison of the respiratory tract microbiome in hospitalized COVID-19 patients with different disease severity.

Little is known about the characteristics of respiratory tract microbiome in Coronavirus disease 2019 (COVID-19) inpatients with different severity. We conducted a study that expected to clarify these characteristics as much as possible. A cross-sectional study was conducted to characterize respiratory tract microbial communities of 69 COVID-19 inpatients from 64 nasopharyngeal swabs and 5 sputum specimens using 16S ribosomal RNA gene V3-V4 region sequencing. The bacterial profiles were analyzed to find potential biomarkers by the two-step method, the combination of random forest model and the linear discriminant analysis effect size, and explore the connections with clinical characteristics by Spearman's rank test. Compared with mild COVID-19 patients, severe patients had significantly decreased bacterial diversity (p-values were less than 0.05 in the alpha and beta diversity) and relative lower abundance of opportunistic pathogens, including Actinomyces, Prevotella, Rothia, Streptococcus, Veillonella. Eight potential biomarkers including Treponema, Leptotrichia, Lachnoanaerobaculum, Parvimonas, Alloprevotella, Porphyromonas, Gemella, and Streptococcus were found to distinguish the mild COVID-19 patients from the severe COVID-19 patients. The genera of Actinomyces and Prevotella were negatively correlated with age in two groups. Intensive care unit admission, neutrophil count, and lymphocyte count were significantly correlated with different genera in the two groups. In addition, there was a positive correlation between Klebsiella and white blood cell count in two groups. The respiratory tract microbiome had significant differences in COVID-19 patients with different severity. The value of the respiratory tract microbiome as predictive biomarkers for COVID-19 severity deserves further exploration.

Comparison of reverse-transcription qPCR and droplet digital PCR for the detection of SARS-CoV-2 in clinical specimens of hospitalized patients.

Accurate detection of severe acute respiratory syndrome coronavirus 2 is not only necessary for viral load monitoring to optimize treatment in hospitalized coronavirus disease 2019 patients, but also critical for deciding whether the patient could be discharged without any risk of viral shedding. Digital droplet PCR (ddPCR) is more sensitive than reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) and is usually considered the superior choice. In the current study, we compared the clinical performance of RT-qPCR and ddPCR using oropharyngeal swab samples from patients hospitalized in the temporary Huoshenshan Hospital, Wuhan, Hubei, China. Results demonstrated that ddPCR was indeed more sensitive than RT-qPCR. Negative results might be caused by poor sampling technique or recovered patients, as the range of viral load in these patients varied significantly. In addition, both methods were highly correlated in terms of their ability to detect all three target genes as well as the ratio of copies of viral genes to that of the IC gene. Furthermore, our results evidenced that both methods detected the N gene more easily than the ORF gene. Taken together, these findings imply that the use of ddPCR, as an alternative to RT-qPCR, is necessary for the accurate diagnosis of hospitalized coronavirus disease 2019 patients.

Genome-wide association study of COVID-19 severity among the Chinese population.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes a broad clinical spectrum of coronavirus disease 2019 (COVID-19). The development of COVID-19 may be the result of a complex interaction between the microbial, environmental, and host genetic components. To reveal genetic determinants of susceptibility to COVID-19 severity in the Chinese population, we performed a genome-wide association study on 885 severe or critical COVID-19 patients (cases) and 546 mild or moderate patients (controls) from two hospitals, Huoshenshan and Union hospitals at Wuhan city in China. We identified two loci on chromosome 11q23.3 and 11q14.2, which are significantly associated with the COVID-19 severity in the meta-analyses of the two cohorts (index rs1712779: odds ratio [OR] = 0.49; 95% confidence interval [CI], 0.38-0.63 for T allele; P = 1.38 × 10-8; and index rs10831496: OR = 1.66; 95% CI, 1.38-1.98 for A allele; P = 4.04 × 10-8, respectively). The results for rs1712779 were validated in other two small COVID-19 cohorts in the Asian populations (P = 0.029 and 0.031, respectively). Furthermore, we identified significant eQTL associations for REXO2, C11orf71, NNMT, and CADM1 at 11q23.3, and CTSC at 11q14.2, respectively. In conclusion, our findings highlight two loci at 11q23.3 and 11q14.2 conferring susceptibility to the severity of COVID-19, which might provide novel insights into the pathogenesis and clinical treatment of this disease.

Development and evaluation of a serological test for diagnosis of COVID-19 with selected recombinant spike proteins.

Serological test is a valuable diagnostic tool for coronavirus disease 2019 (COVID-19). However, considerable improvements to these tests are needed, especially in the detection sensitivity. In this study, six recombinant nucleocapsid and spike proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were prepared and evaluated, including three prokaryotic expression nucleocapsid proteins (rN, rN1, rN2) and three eukaryotic expression spike proteins (rS1, rS-RBD, rS-RBD-mFc). The recombinant proteins with the highest ELISA titers (rS1 and rS-RBD-mFc) were selected to develop a double-antigen sandwich colloidal gold immunochromatography assay (GICA) to detect total antibodies against SARS-CoV-2. The clinical evaluation results showed that the sensitivity and specificity of GICA were 92.09% (419/455) and 99.44% (706/710), respectively. Moreover, a significant number (65.63%, 21/32) of COVID-19 patients with undetectable viral RNA were correctly diagnosed by the GICA method. In conclusion, the eukaryotic expression spike proteins (rS1 and rS-RBD-mFc) are more suitable than the prokaryotic expression nucleocapsid proteins for serological diagnosis of SARS-CoV-2. The proposed GICA for detection of total antibodies could be a powerful complement to the current RNA tests for COVID-19.

Clinical features and antibody response of patients from a COVID-19 treatment hospital in Wuhan, China.

Coronavirus disease 2019 (COVID-19) has rapidly evolved into a global pandemic. A total of 1578 patients admitted into a newly built hospital specialized for COVID-19 treatment in Wuhan, China, were enrolled. Clinical features and the levels of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin (Ig)M and IgG were analyzed. In total, 1532 patients (97.2%) were identified as laboratory-confirmed cases. Seventy-seven patients were identified as asymptomatic carriers (n = 64) or SARS-CoV-2 RNA positive before symptom onset (n = 13). The positive rates of SARS-CoV-2 IgM and IgG were 80.4% and 96.8%, respectively. The median of IgM and IgG titers were 37.0A U/ml (interquartile range [IQR]: 13.4-81.1 AU/ml) and 156.9 AU/ml (IQR: 102.8-183.3 AU/ml), respectively. The IgM and IgG levels of asymptomatic patients (median titers, 8.3 AU/ml and 100.3 AU/ml) were much lower than those in symptomatic patients (median titers, 38.0 AU/ml and 158.2 AU/ml). A much lower IgG level was observed in critically ill patients 42-60 days after symptom onset. There were 153 patients with viral RNA shedding after IgG detection. These patients had a higher proportion of critical illness during hospitalization (p < .001) and a longer hospital stay (p < .001) compared to patients with viral clearance after IgG detection. Coronary heart disease (odds ratio [OR], 1.89 [95% confidence interval [CI], 1.11-3.24]; p = .020), and intensive care unit admission (OR, 2.47 [95% CI, 1.31-4.66]; p = .005) were independent risk factors associated with viral RNA shedding after IgG detection. Symptomatic patients produced more antibodies than asymptomatic patients. The patients who had SARS-CoV-2 RNA shedding after developing IgG were more likely to be sicker patients.