Corrigendum to: Do Stay at Home Orders and Cloth Face Coverings Control COVID-19 in New York City? Results From a SIER Model Based on Real-world Data.

[This corrects the article DOI: 10.1093/ofid/ofaa442.].

Metatranscriptomic Characterization of Coronavirus Disease 2019 Identified a Host Transcriptional Classifier Associated With Immune Signaling.

BACKGROUND: The recent identification of a novel coronavirus, also known as severe acute respiratory syndrome coronavirus 2, has caused a global outbreak of respiratory illnesses. The rapidly developing pandemic has posed great challenges to diagnosis of this novel infection. However, little is known about the metatranscriptomic characteristics of patients with coronavirus disease 2019 (COVID-19). METHODS: We analyzed metatranscriptomics in 187 patients (62 cases with COVID-19 and 125 with non-COVID-19 pneumonia). Transcriptional aspects of 3 core elements, pathogens, the microbiome, and host responses, were evaluated. Based on the host transcriptional signature, we built a host gene classifier and examined its potential for diagnosing COVID-19 and indicating disease severity. RESULTS: The airway microbiome in COVID-19 patients had reduced alpha diversity, with 18 taxa of differential abundance. Potentially pathogenic microbes were also detected in 47% of the COVID-19 cases, 58% of which were respiratory viruses. Host gene analysis revealed a transcriptional signature of 36 differentially expressed genes significantly associated with immune pathways, such as cytokine signaling. The host gene classifier built on such a signature exhibited the potential for diagnosing COVID-19 (area under the curve of 0.75-0.89) and indicating disease severity. CONCLUSIONS: Compared with those with non-COVID-19 pneumonias, COVID-19 patients appeared to have a more disrupted airway microbiome with frequent potential concurrent infections and a special trigger host immune response in certain pathways, such as interferon-gamma signaling. The immune-associated host transcriptional signatures of COVID-19 hold promise as a tool for improving COVID-19 diagnosis and indicating disease severity.

Do Stay at Home Orders and Cloth Face Coverings Control COVID-19 in New York City? Results From a SIER Model Based on Real-world Data.

BACKGROUND: Public health interventions have been implemented to contain the outbreak of coronavirus disease 2019 (COVID-19) in New York City. However, the assessment of those interventions-for example, social distancing and cloth face coverings-based on real-world data from published studies is lacking. METHODS: The Susceptible-Exposed-Infectious-Removed (SEIR) compartmental model was used to evaluate the effect of social distancing and cloth face coverings on the daily culminative laboratory confirmed cases in New York City (NYC) and COVID-19 transmissibility. The latter was measured by Rt reproduction numbers in 3 phases that were based on 2 interventions implemented during this timeline. RESULTS: Transmissibility decreased from phase 1 to phase 3. The initial R0 was 4.60 in phase 1 without any intervention. After social distancing, the Rt value was reduced by 68%, while after the mask recommendation, it was further reduced by ~60%. CONCLUSIONS: Interventions resulted in significant reduction of confirmed case numbers relative to predicted values based on the SEIR model without intervention. Our findings highlight the effectiveness of social distancing and cloth face coverings in slowing down the spread of severe acute respiratory syndrome coronavirus 2 in NYC.

Corticosteroid prevents COVID-19 progression within its therapeutic window: a multicentre, proof-of-concept, observational study.

Critically ill patients with coronavirus diseases 2019 (COVID-19) are of grave concern. Those patients usually underwent a stage of excessive inflammation before developing acute respiratory distress syndrome. In this study, we test the hypothesis that short-term, low-to-moderate-dose corticosteroids would benefit patients when used in the early phase of excessive inflammation, namely, the therapeutic window. Among a Shanghai cohort and a validation cohort, we enrolled COVID-19 patients showing marked radiographic progression. Short-term, low-to-moderate-dose corticosteroids were considered for them. After identifying the possible markers for the therapeutic window, we then divided the patients, based on whether they were treated with corticosteroids within the therapeutic window, into the early-start group and control group. We identified that the therapeutic window for corticosteroids was characterized by a marked radiographic progression and lactase dehydrogenase (LDH) less than two times the upper limit of normal (ULN). The Shanghai cohort comprised of 68 patients, including 47 in the early-start group and 21 in the control group. The proportion of patients requiring invasive mechanical ventilation was significantly lower in the early-start group than in the control group (10.6% vs. 33.3%, difference, 22.7%, 95% confidence interval 2.6-44.8%). Among the validation cohort of 51 patients, similar difference of the primary outcome was observed (45.0% vs. 74.2%, P = 0.035). Among COVID-19 patients with marked radiologic progression, short-term, low-to-moderate-dose corticosteroids benefits patients with LDH levels of less than two times the ULN, who may be in the early phase of excessive inflammation.

Lactate dehydrogenase and susceptibility to deterioration of mild COVID-19 patients: a multicenter nested case-control study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has infected more than 4 million people within 4 months. There is an urgent need to properly identify high-risk cases that are more likely to deteriorate even if they present mild diseases on admission. METHODS: A multicenter nested case-control study was conducted in four designated hospitals in China enrolling confirmed COVID-19 patients who were mild on admission. Baseline clinical characteristics were compared between patients with stable mild illness (stable mild group) and those who deteriorated from mild to severe illness (progression group). RESULTS: From Jan 17, 2020, to Feb 1, 2020, 85 confirmed COVID-19 patients were enrolled, including 16 in the progression group and 69 in the stable mild group. Compared to stable mild group (n = 69), patients in the progression group (n = 16) were more likely to be older, male, presented with dyspnea, with hypertension, and with higher levels of lactase dehydrogenase and c-reactive protein. In multivariate logistic regression analysis, advanced age (odds ratio [OR], 1.012; 95% confidence interval [CI], 1.020-1.166; P = 0.011) and the higher level of lactase dehydrogenase (OR, 1.012; 95% CI, 1.001-1.024; P = 0.038) were independently associated with exacerbation in mild COVID-19 patients. CONCLUSION: Advanced age and high LDH level are independent risk factors for exacerbation in mild COVID-19 patients. Among the mild patients, clinicians should pay more attention to the elderly patients or those with high LDH levels.

Era of molecular diagnosis for pathogen identification of unexplained pneumonia, lessons to be learned.

Unexplained pneumonia (UP) caused by a novel coronavirus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) emerged in China in late December 2019 and has infected more than 9000 cases by 31 January 2020. Shanghai reported the first imported case of COVID-19 (Coronavirus Disease 2019) in 20 January 2020. A combinative approach of real-time RT-PCR, CRISPR-based assay and metagenomic next-generation sequencing (mNGS) were used to diagnose this unexplained pneumonia patient. Real-time RT-PCR and CRISPR-based assay both reported positive. This sample belonged to Betacoronavirus and shared a more than 99% nucleotide (nt) identity with the Wuhan SARS-CoV-2 isolates. We further compared pros and cons of common molecular diagnostics in UP. In this study, we illustrated the importance of combining molecular diagnostics to rule out common pathogens and performed mNGS to obtain unbiased potential pathogen result for the diagnosis of UP.