Investigation and analysis of entry personnel’s mental health status under COVID-2019 quarantine in Shanghai, China (preprint)

Background To investigate the mental health status and stress coping of quarantined personnel entering Shanghai from abroad, identify the key influencing factors, and provide suggestions for improving the mental health of COVID-19 quarantined personnel.Methods We surveyed quarantined individuals to collect general demographic data and COVID-19-related information of 327 entry personnel at the quarantine medical observation point. PHQ-9, GAD-7, and Cope scale (simplified version) were used to assess depression, anxiety, and individual stress coping. We analyzed the independent individual variables for their relationship with mental health outcomes.Results Among the entry quarantined personnel, we found that 27.8% scored positively for depression and 20.5% for anxiety. Depressive symptoms were more likely in individuals with pre-existing health conditions (p = 0.003), lack of medical insurance (p = 0.012), worry about the impact of the epidemic on their studies / work (p = 0.020), worry about the lack of daily necessities during quarantine (p = 0.005), and worry about being rejected or discriminated against by the outside world after quarantine (p = 0.002). Anxiety symptoms were more likely in those without medical insurance (p = 0.008) and those worried about being rejected or discriminated against by the outside world after quarantine (p = 0.010). In terms of stress coping, those with higher scores in "denial (disapproval of events) (p = 0.025, P = 0.041), guilt and self-blame (p = 0.001, p = 0.009)" were more likely to score higher for depression and anxiety.Conclusion Attention should be paid to the negative psychological reactions of the entry quarantined personnel, especially those with pre-existing health conditions, those without medical insurance, and students studying abroad who are at high risk of negative emotions. Timely mental health support should be provided. Accurate and effective epidemic dynamic information and preventive and control measures can be provided to the public through media publicity to prevent fear and stigma against quarantined personnel.

Higher socioeconomic status strengthens confidence facing the COVID-19 pandemic for the males rather than females: the predictive role of left hippocampus (preprint)

Socioeconomic status (SES) has a large impact on the way individuals respond to environmental threats. However, less is known about how SES links to personal confidence in confronting COVID-19 and its underlying neural mechanisms. To this end, we assessed self-confidence in coping with pandemic on 606 participants during its peak in China from 21th, February, 2020 to 28th, February, 2020, who underwent magnetic resonance imaging (MRI) scanning before the outbreak from 17th, September, 2019 to 11th, January, 2020. We found that males, rather than females, showed heightened confidence levels as SES increased. Similarly, greater gray matter volumes (GMV) in the left hippocampus, which were identified as SES-related brain correlates using whole-brain voxel-based morphometry (VBM) method, predicted higher confidence level for males, whilst such association was not found among females. Moreover, an independent moderation analysis replicated the predictive role of GMV based on the pre-defined anatomical structure (i.e., left hippocampus). These findings suggested that relative to females, a less threat-biased evaluation style shaped by greater hippocampal volumes might account for the males’ adequate psychological resources for coping with the pandemic. Overall, evidence highlighted the importance to focus on specific populations like females, and people from lower SES in the era of pandemic.

Oridonin Inhibits SARS‐CoV‐2 by Targeting Its 3C‐Like Protease

Oridonin Inhibits SARS‐CoV‐2 Oridonin, a natural product extracted from Rabdosia rubescens, possesses a wide range of pharmacological properties, including anti‐inflammatory, anti‐cancer, anti‐microbial, neuroprotection, immunoregulation, etc. In article number 2100124, Baisen Zhong, Litao Sun, and co‐workers demonstrate that Oridonin targets the SARS‐CoV‐2 3CL protease by covalently binding to cysteine145 in its active pocket to exert an anti‐SARS‐CoV‐2 effect, which provides a novel candidate for the treatment of COVID‐19. © 2022 WILEY‐VCH GmbH

Dynamic Expedition of Leading Mutations in SARS-CoV-2 Spike Glycoproteins (preprint)

During the ongoing CoVID-19 epidemic, the continuous genomic evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been generating new variants with enhanced transmissibility and immune escape. Being one key target of antibodies, mutations of the spike glycoprotein play a vital role in the trajectory of virus evasion. Here, we present a time-resolved statistical method, dynamic expedition of leading mutations (deLemus), to analyze the evolution dynamics of the spike protein. Together with analysis on single amino-acid polymorphism (SAP), we proposed one L-index to quantify the mutation strength of each amino acid for unravelling mutation pattern of spike glycoprotein. The sites of interest (SOI) with high L-index hold great promise to detect potential signal of emergent variants.

Single-shot rAAV5-based Vaccine Provides Long-term Protective Immunity against SARS-CoV-2 and Its Variants (preprint)

The COVID-19 pandemic and the SARS-CoV-2 with its variants have posed unprecedented challenges worldwide. Existing vaccines have limited effectiveness against the SARS-CoV-2 variants. Therefore, novel vaccines to match current mutated viral lineages with long-term protective immunity are urgently in demand. In the current study, we for the first time designed a recombinant Adeno-Associated Virus 5 (rAAV5)-based vaccine named as rAAV-COVID-19 vaccine (Covacinplus) by using RBD-plus of spike protein with both the single-stranded and the self-complementary AAV5 delivering vectors (ssAAV5 and scAAAV5), which provides excellent protection from SARS-CoV-2 infection. A single dose vaccination induced the strong immune response against SARS-CoV-2. The induced neutralizing antibodies (NAs) titers were maintained at a high peak level of over 1:1024 even after more than one year of injection and accompanied with functional T-cells responses in mice. Importantly, both ssAAV- and scAAV-based RBD-plus vaccines exhibited high levels of serum NAs against current circulating variants including variants Alpha, Beta, Gamma and Delta. SARS-CoV-2 virus challenge test showed that ssAAV5-RBD-plus vaccine protected both young and old age mice from SARS-CoV-2 infection in the upper and the lower respiratory tracts. Moreover, whole genome sequencing demonstrated that AAV vector DNA sequences were not found in the genome of the vaccinated mice after one year vaccination, demonstrating excellent safety of the vaccine. Taken together, this study suggests that rAAV5-based vaccine is powerful against SARS-CoV-2 and its variants with long-term protective immunity and excellent safety, which has great potential for development into prophylactic vaccination in human to end this global pandemic.

Combat COVID-19 Infodemic Using Explainable Natural Language Processing Models (preprint)

Misinformation of COVID-19 is prevalent on social media as the pandemic unfolds, and the associated risks are extremely high. Thus, it is critical to detect and combat such misinformation. Recently, deep learning models using natural language processing techniques, such as BERT (Bidirectional Encoder Representations from Transformers), have achieved great successes in detecting misinformation. In this paper, we proposed an explainable natural language processing model based on DistilBERT and SHAP (Shapley Additive exPlanations) to combat misinformation about COVID-19 due to their efficiency and effectiveness. First, we collected a dataset of 984 claims about COVID-19 with fact checking. By augmenting the data using back-translation, we doubled the sample size of the dataset and the DistilBERT model was able to obtain good performance (accuracy: 0.972; areas under the curve: 0.993) in detecting misinformation about COVID-19. Our model was also tested on a larger dataset for AAAI2021 - COVID-19 Fake News Detection Shared Task and obtained good performance (accuracy: 0.938; areas under the curve: 0.985). The performance on both datasets was better than traditional machine learning models. Second, in order to boost public trust in model prediction, we employed SHAP to improve model explainability, which was further evaluated using a between-subjects experiment with three conditions, i.e., text (T), text+SHAP explanation (TSE), and text+SHAP explanation+source and evidence (TSESE). The participants were significantly more likely to trust and share information related to COVID-19 in the TSE and TSESE conditions than in the T condition. Our results provided good implications in detecting misinformation about COVID-19 and improving public trust.

The neutrophil-to-lymphocyte ratio determines clinical efficacy of corticosteroids therapy in patients with COVID-19 (preprint)

Preliminary results from the RECOVERY trial indicated that dexamethasone usage markedly reduced death rate in COVID-19 patients receiving invasive mechanical ventilation. However, the overall reduction for the entire patient cohort in that trial was much more modest, indicating highly variable effects of corticosteroid usage among COVID-19 patients. While steroid treatment is known to have both clinical efficacy and detrimental adverse-effects, defining a clinic parameter that could guide the beneficial corticosteroid usage for treating COVID-19 remains an elusive, urgent, and critical unmet need in COVID-19 therapy. Here, we undertook a multicentered retrospective study on a cohort of 12,862 confirmed COVID-19 cases from 21 hospitals in Hubei Province, China, including 3,254 received corticosteroid treatment and 9,608 received usual care without corticosteroid. We uncovered that the clinical benefits of corticosteroid use were closely associated with the neutrophil-to-lymphocyte ratio (NLR) measured at admission. Among participants with NLR > 6.12 at admission, corticosteroid treatment was significantly associated with a lower risk of 60-day all-cause mortality of COVID-19 based on both Cox model with time-varying exposure and Marginal Structural Model. However, in patients with NLR ≤ 6.12 at admission, corticosteroid treatment was no longer associated with reduced risk of all-cause death, but rather with increased risks of severe adverse effects, particularly in hyperglycemia and infection. In diabetic patients with COVID-19, corticosteroid treatment was associated with increased glycemia, but not with a higher risk of 60-day mortality. Therefore, our study has uncovered NLR as a clinical indicator to stratify COVID-19 patients in their response to corticosteroid therapy. This finding may assist clinical evaluation and future randomized controlled trials to establish proper guidelines for corticosteroid therapy in COVID-19 patients.

Do not forget interaction: Predicting fatality of COVID-19 patients using logistic regression (preprint)

Amid the ongoing COVID-19 pandemic, whether COVID-19 patients with high risks can be recovered or not depends, to a large extent, on how early they will be treated appropriately before irreversible consequences are caused to the patients by the virus. In this research, we reported an explainable, intuitive, and accurate machine learning model based on logistic regression to predict the fatality rate of COVID-19 patients using only three important blood biomarkers, including lactic dehydrogenase, lymphocyte (%) and high-sensitivity C-reactive protein, and their interactions. We found that when the fatality probability produced by the logistic regression model was over 0.8, the model had the optimal performance in that it was able to predict patient fatalities more than 11.30 days on average with maximally 34.91 days in advance, an accumulative f1-score of 93.76% and and an accumulative accuracy score of 93.92%. Such a model can be used to identify COVID-19 patients with high risks with three blood biomarkers and help the medical systems around the world plan critical medical resources amid this pandemic.

Estimation of the Time-Varying Reproduction Number of 2019-nCoV Outbreak in China (preprint)

Background: The 2019-nCoV outbreak in Wuhan, China has attracted world-wide attention. As of February 11, 2020, a total of 44730 cases of novel coronavirus-infected pneumonia associated with COVID-19 were confirmed by the National Health Commission of China. Methods: Three approaches, namely Poisson likelihood-based method (ML), exponential growth rate-based method (EGR) and stochastic Susceptible-Infected-Removed dynamic model-based method (SIR), were implemented to estimate the basic and controlled reproduction numbers. Results: A total of 71 chains of transmission together with dates of symptoms onset and 67 dates of infections were identified among 5405 confirmed cases outside Hubei as reported by February 2, 2020. Based on this information, we find the serial interval having an average of 4.41 days with a standard deviation of 3.17 days and the infectious period having an average of 10.91 days with a standard deviation of 3.95 days. Conclusions: The controlled reproduction number is declining. It is lower than one in most regions of China, but is still larger than one in Hubei Province. Sustained efforts are needed to further reduce the Rc to below one in order to end the current epidemic.