Health care worker occupational experiences during the COVID-19 outbreak: A cross-sectional study.

BACKGROUND: Health care workers treating coronavirus disease 2019 (COVID-19) patients experience burnout and stress due to overwork and poor working conditions. AIM: To investigate the work experiences of frontline health care workers in Wuhan city and Qinghai province, China, during the COVID-19 outbreak. METHODS: In this cross-sectional descriptive study, a self-reported questionnaire was designed to evaluate work experiences of medical staff throughout the course of the COVID-19 pandemic. A total of 178 health care workers responded to the questionnaire between February 19 and 29, 2020. Higher questionnaire dimen-sional score confirmed dimensional advantage. RESULTS: Of all dimensions evaluated by this questionnaire, the occupational value dimension had the highest mean score of 2.61 (0.59), followed by the support/security dimension score of 2.30 (0.74). Occupational protection scored lowest at 1.44 (0.75), followed by work environment at 1.97 (0.81). The social relationships dimension had an intermediate score of 2.06 (0.80). Significant differences in working conditions were observed across hospital departments, with the fever ward scoring lowest. Total scores also differed significantly across workplaces; the fever outpatient department scored lowest (P < 0.01). This phenomenon was likely due to the fact that work in the fever outpatient department, where many patients present to hospital, necessitates constant contact with a large number of individuals with insufficient provision of resources (such as protective equipment and social support). Medical workers in the fever outpatient department were burdened with a fear of COVID-19 infection and a lower sense of professional value as compared to workers in other hospital departments. Medical staff in Wuhan worked longer hours (P < 0.01) as compared to elsewhere. The mean support/security dimension score was higher for tertiary hospital as compared to secondary hospital medical staff as well as for Wuhan area as compared to Qinghai region staff (P < 0.01). Staff in Wuhan had a lower mean work environment score as compared to staff in Qinghai (P < 0.05). CONCLUSION: Medical staff treating COVID-19 patients in China report poor occupational experiences strongly affected by work environment, occupational protection and social relationships. Health care managers must address the occupational needs of medical staff by ensuring a supportive and safe work environment.

Deep learning for drug repurposing: methods, databases, and applications (preprint)

Drug development is time-consuming and expensive. Repurposing existing drugs for new therapies is an attractive solution that accelerates drug development at reduced experimental costs, specifically for Coronavirus Disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, comprehensively obtaining and productively integrating available knowledge and big biomedical data to effectively advance deep learning models is still challenging for drug repurposing in other complex diseases. In this review, we introduce guidelines on how to utilize deep learning methodologies and tools for drug repurposing. We first summarized the commonly used bioinformatics and pharmacogenomics databases for drug repurposing. Next, we discuss recently developed sequence-based and graph-based representation approaches as well as state-of-the-art deep learning-based methods. Finally, we present applications of drug repurposing to fight the COVID-19 pandemic, and outline its future challenges.

Assessing multiplex tiling PCR sequencing approaches for detecting genomic variants of SARS-CoV-2 in municipal wastewater (preprint)

Wastewater-based genomic surveillance of the SARS-CoV-2 virus shows promise to complement genomic epidemiology efforts. Multiplex tiled PCR is a desirable approach for targeted genome sequencing of SARS-CoV-2 in wastewater due to its low cost and rapid turnaround time. However, it is not clear how different multiplex tiled PCR primer schemes or wastewater sample matrices impact the resulting SARS-CoV-2 genome coverage. The objective of this work was to assess the performance of three different multiplex primer schemes, consisting of 150bp, 400bp, and 1200bp amplicons, as well as two wastewater sample matrices, influent wastewater and primary sludge, for targeted genome sequencing of SARS-CoV-2. Wastewater samples were collected weekly from five municipal wastewater treatment plants (WWTPs) in the Metro Vancouver region of British Columbia, Canada during a period of increased COVID-19 case counts from February to April, 2021. RNA extracted from clarified influent wastewater provided significantly higher genome coverage (breadth and median depth) than primary sludge samples across all primer schemes. Shorter amplicons appeared more resilient to sample RNA degradation, but were hindered by greater primer pool complexity in the 150bp scheme. The identified optimal primer scheme (400bp) and sample matrix (influent) was capable of detecting the emergence of mutations associated with genomic variants of concern, of which the daily wastewater load significantly correlated with clinical case counts. Taken together, these results provide guidance on best practices for implementing wastewater-based genomic surveillance, and demonstrate its ability to inform epidemiology efforts by detecting genomic variants of concern circulating within a geographic region. Importance Monitoring the genomic characteristics of the SARS-CoV-2 virus circulating in a population can shed important insights into epidemiological aspects of the COVID-19 outbreak. Sequencing every clinical patient sample in a highly populous area is a difficult feat, and thus sequencing SARS-CoV-2 RNA in municipal wastewater offers great promise to augment genomic surveillance by characterizing a pooled population sample matrix, particularly during an escalating outbreak. Here, we assess different approaches and sample matrices for rapid targeted genome sequencing of SARS-CoV-2 in municipal wastewater. We demonstrate that the optimal approach is capable of detecting the emergence of SARS-CoV-2 genomic variants of concern, with strong correlations to clinical case data in the province of British Columbia. These results provide guidance on best practices on, as well as further support for, the application of wastewater genomic surveillance as a tool to augment current genomic epidemiology efforts.

Robust clustering and interpretation of scRNA-seq data using reference component analysis (preprint)

Motivation The transcriptomic diversity of the hundreds of cell types in the human body can be analysed in unprecedented detail using single cell (SC) technologies. Though clustering of cellular transcriptomes is the default technique for defining cell types and subtypes, single cell clustering can be strongly influenced by technical variation. In fact, the prevalent unsupervised clustering algorithms can cluster cells by technical, rather than biological, variation. Results Compared to de novo (unsupervised) clustering methods, we demonstrate using multiple benchmarks that supervised clustering, which uses reference transcriptomes as a guide, is robust to batch effects. To leverage the advantages of supervised clustering, we present RCA2, a new, scalable, and broadly applicable version of our RCA algorithm. RCA2 provides a user-friendly framework for supervised clustering and downstream analysis of large scRNA-seq data sets. RCA2 can be seamlessly incorporated into existing algorithmic pipelines. It incorporates various new reference panels for human and mouse, supports generation of custom panels and uses efficient graph-based clustering and sparse data structures to ensure scalability. We demonstrate the applicability of RCA2 on SC data from human bone marrow, healthy PBMCs and PBMCs from COVID-19 patients. Importantly, RCA2 facilitates cell-type-specific QC, which we show is essential for accurate clustering of SC data from heterogeneous tissues. In the era of cohort-scale SC analysis, supervised clustering methods such as RCA2 will facilitate unified analysis of diverse SC datasets. Availability RCA2 is implemented in R and is available at github.com/prabhakarlab/RCAv2

Long period dynamics of viral load and antibodies for SARS-CoV-2 infection: an observational cohort study (preprint)

ABSTRACT OBJECTIVE To investigate the dynamics of viral RNA, IgM, and IgG and their relationships in patients with SARS-CoV-2 pneumonia over an 8-week period. DESIGN Retrospective, observational case series. SETTING Wenzhou Sixth Peoples Hospital PARTICIPANTS Thirty-three patients with laboratory confirmed SARS-CoV-2 pneumonia admitted to hospital. Data were collected from January 27 to April 10, 2020. MAIN OUTCOME MEASURES Throat swabs, sputum, stool, and blood samples were collected, and viral load was measured by reverse transcription PCR (RT-PCR). Specific IgM and IgG against spike protein (S), spike protein receptor binding domain (RBD), and nucleocapsid (N) were analyzed. RESULTS At the early stages of symptom onset, SARS-CoV-2 viral load is higher in throat swabs and sputum, but lower in stool. The median (IQR) time of undetectable viral RNA in throat swab, sputum, and stool was 18.5 (13.25-22) days, 22 (18.5-27.5) days, and 17 (11.5-32) days, respectively. In sputum, 17 patients (51.5%) had undetectable viral RNA within 22 days (short persistence), and 16 (48.5%) had persistent viral RNA more than 22 days (long persistence). Three patients (9.1%) had a detectable relapse of viral RNA in sputum within two weeks of their discharge from the hospital. One patient had persistent viral RNA for 59 days or longer. The median (IQR) seroconversion time of anti-S IgM, anti-RBD IgM, and anti-N IgM was 10.5 (7.75-15.5) days, 14 (9-24) days, and 10 (7-14) days, respectively. The median (IQR) seroconversion time of anti-S IgG, anti-RBD IgG, and anti-N IgG was 10 (7.25-16.5) days, 13 (9-17) days, and 10 (7-14) days, respectively. By week 8 after symptom onset, IgM were negative in many of the previously positive patients, and IgG levels remained less than 50% of the peak levels in more than 20% of the patients. In about 40% of the patients, anti-RBD IgG levels were 4-times higher in convalescence than in acute phase. SARS-CoV-2 RNA coexisted with antibodies for more than 50 days. Anti-RBD IgM and IgG levels, including anti-RBD IgM levels at presentation and peak time, were significantly higher in viral RNA short persistence patients than in long persistence patients. CONCLUSION This study adds important new information about the features of viral load and antibody dynamics of SARS-CoV-2. It is clear from these results that the viral RNA persists in sputum and stool specimens for a relatively long time in many patients. Anti-RBD may also serve as a potential protective antibody against SARS-CoV-2 infection, as viral persistence appears to be related to anti-RBD levels. Earlier treatment intervention also appears to be a factor in viral persistence.