Aerosol exchange between pressure-equilibrium rooms induced by door motion and human movement.

It is now widely recognised that aerosol transport is major vector for transmission of diseases such as COVID-19, and quantification of aerosol transport in the built environment is critical to risk analysis and management. Understanding the effects of door motion and human movement on the dispersion of virus-laden aerosols under pressure-equilibrium conditions is of great significance to the evaluation of infection risks and development of mitigation strategies. This study uses novel numerical simulation techniques to quantify the impact of these motions upon aerosol transport and provides valuable insights into the wake dynamics of swinging doors and human movement. The results show that the wake flow of an opening swinging door delays aerosol escape, while that of a person walking out entrains aerosol out of the room. Aerosol escape caused by door motion mainly happens during the closing sequence which pushes the aerosols out. Parametric studies show that while an increased door swinging speed or human movement speed can enhance air exchange across the doorway, the cumulative aerosol exchange across the doorway is not clearly affected by the speeds.

Cross-sectional study of traumatic stress disorder in frontline nurses 6 mo after the outbreak of the COVID-19 in Wuhan.

BACKGROUND: Frontline nurses in Wuhan directly fighting severe acute respiratory syndrome coronavirus-2 diseases are at a high risk of infection and are extremely susceptible to psychological stress, especially due to the global coronavirus disease 2019 (COVID-19) pandemic. The psychological after-effects of this public health emergency on frontline nurses will last for years. AIM: To assess factors influencing post-traumatic stress disorder (PTSD) among frontline nurses in Wuhan 6 mo after the COVID-19 pandemic began. METHODS: A total of 757 frontline nurses from five hospitals in Wuhan, China, participated in an online survey from July 27 to August 13, 2020. This cross-sectional online study used a demographic information questionnaire, the PTSD Checklist for the Diagnostic and Statistical Manual of Mental Disorders, the Connor-Davidson Resilience Scale, and the Patient Health Questionnaire-4. The chi-square test and logistic regression were used to analyze the association of demographics, COVID-19-related variables, and PTSD. Logistic regression was also conducted to investigate which variables were associated with PTSD outcomes. RESULTS: A total of 13.5%, 24.3%, and 21.4% of the frontline nurses showed symptoms of PTSD, depression, and anxiety, respectively. The multivariate logistic regression analysis showed that the following factors were strongly associated with PTSD: Having a relative, friend, or colleague who died of COVID-19; experiencing stigma; or having psychological assistance needs, depressive symptoms or anxiety. Showing resilience and receiving praise after the COVID-19 outbreak were protective factors. CONCLUSION: Frontline nurses still experienced PTSD (13.5%) six months after the COVID-19 outbreak began. Peer support, social support, official recognition, reward mechanisms, exercise, better sleep, and timely provision of information (such as vaccine research progress) by the government via social media, and adequate protective supplies could mitigate the level of PTSD among nurses responding to COVID-19. Stigmatization, depression, and anxiety might be associated with a greater risk of PTSD among nurses.

Metabolomics Analysis of PK-15 Cells with Pseudorabies Virus Infection Based on UHPLC-QE-MS.

Viruses depend on the metabolic mechanisms of the host to support viral replication. We utilize an approach based on ultra-high-performance liquid chromatography/Q Exactive HF-X Hybrid Quadrupole-Orbitrap Mass (UHPLC-QE-MS) to analyze the metabolic changes in PK-15 cells induced by the infections of the pseudorabies virus (PRV) variant strain and Bartha K61 strain. Infections with PRV markedly changed lots of metabolites, when compared to the uninfected cell group. Additionally, most of the differentially expressed metabolites belonged to glycerophospholipid metabolism, sphingolipid metabolism, purine metabolism, and pyrimidine metabolism. Lipid metabolites account for the highest proportion (around 35%). The results suggest that those alterations may be in favor of virion formation and genome amplification to promote PRV replication. Different PRV strains showed similar results. An understanding of PRV-induced metabolic reprogramming will provide valuable information for further studies on PRV pathogenesis and the development of antiviral therapy strategies.

An Investigation into the Pressures Experienced by Medical Masters Students during the COVID-19 Pandemic Based on the Perceived Stress Scale-14 and Its Alleviation Methods.

The COVID-19 pandemic can be seen as a traumatic event during which time medical students have been required to perform dual roles both as students and as medical workers. In this study, we aimed to use the Perceived Stress Scale (PSS-14) to judge the pressures on medical students and to identify effective ways to relieve these pressures. In this cross-sectional study, the subjects were recruited under informed consent according to the Declaration of Helsinki. Students undertaking Masters degrees at the China-Japan Union Hospital of Jilin University were randomly selected and data were collected through questionnaire surveys. Our data showed significant differences in the levels of pressure experienced by Masters students (p < 0.05). In the student population that showed increased pressure, females were significantly more stressed than males (p < 0.05). In addition, the pressures persisted after a holiday period (p < 0.05) but were reduced by undertaking recreational activities. The psychological pressures resulting from the COVID-19 pandemic were higher in female medical students compared to males. We showed that recreational activities including chatting with friends reduced psychological pressures in female medical students.

A spatiotemporally resolved infection risk model for airborne transmission of COVID-19 variants in indoor spaces.

The classic Wells-Riley model is widely used for estimation of the transmission risk of airborne pathogens in indoor spaces. However, the predictive capability of this zero-dimensional model is limited as it does not resolve the highly heterogeneous spatiotemporal distribution of airborne pathogens, and the infection risk is poorly quantified for many pathogens. In this study we address these shortcomings by developing a novel spatiotemporally resolved Wells-Riley model for prediction of the transmission risk of different COVID-19 variants in indoor environments. This modelling framework properly accounts for airborne infection risk by incorporating the latest clinical data regarding viral shedding by COVID-19 patients and SARS-CoV-2 infecting human cells. The spatiotemporal distribution of airborne pathogens is determined via computational fluid dynamics (CFD) simulations of airflow and aerosol transport, leading to an integrated model of infection risk associated with the exposure to SARS-CoV-2, which can produce quantitative 3D infection risk map for a specific SARS-CoV-2 variant in a given indoor space. Application of this model to airborne COVID-19 transmission within a hospital ward demonstrates the impact of different virus variants and respiratory PPE upon transmission risk. With the emergence of highly contagious SARS-CoV-2 variants such as the Delta and Omicron strains, respiratory PPE alone may not provide effective protection. These findings suggest a combination of optimal ventilation and respiratory PPE must be developed to effectively control the transmission of COVID-19 in healthcare settings and indoor spaces in general. This generalised risk estimation framework has the flexibility to incorporate further clinical data as such becomes available, and can be readily applied to consider a wide range of factors that impact transmission risk, including location and movement of infectious persons, virus variant and stage of infection, level of PPE and vaccination of infectious and susceptible individuals, impacts of coughing, sneezing, talking and breathing, and natural and mechanised ventilation and filtration.

iCOVID: interpretable deep learning framework for early recovery-time prediction of COVID-19 patients.

Most prior studies focused on developing models for the severity or mortality prediction of COVID-19 patients. However, effective models for recovery-time prediction are still lacking. Here, we present a deep learning solution named iCOVID that can successfully predict the recovery-time of COVID-19 patients based on predefined treatment schemes and heterogeneous multimodal patient information collected within 48 hours after admission. Meanwhile, an interpretable mechanism termed FSR is integrated into iCOVID to reveal the features greatly affecting the prediction of each patient. Data from a total of 3008 patients were collected from three hospitals in Wuhan, China, for large-scale verification. The experiments demonstrate that iCOVID can achieve a time-dependent concordance index of 74.9% (95% CI: 73.6-76.3%) and an average day error of 4.4 days (95% CI: 4.2-4.6 days). Our study reveals that treatment schemes, age, symptoms, comorbidities, and biomarkers are highly related to recovery-time predictions.

Persistent Somatic Symptom Burden and Sleep Disturbance in Patients with COVID-19 During Hospitalization and After Discharge: A Prospective Cohort Study.

BACKGROUND The present study was designed to reveal the trajectory of self-reported somatic symptom burden and sleep quality over time in patients with COVID-19 and to identify prognostic factors for greater somatic symptom burden and sleep disturbance. MATERIAL AND METHODS Seventy-four patients with COVID-19 were prospectively followed for longitudinal assessment of somatic symptom burden and sleep quality. We used the 8-item Somatic Symptom Scale (SSS-8) and the modified Medical Research Council (mMRC) scale for somatic symptom burden and the Pittsburgh Sleep Quality Index for sleep quality investigation. Univariate and multivariate analyses were performed to identify independent factors associated with somatic symptom burden and sleep quality. RESULTS Although the degree of physical discomfort and sleep quality issues tended to decline during self-quarantine, patients still experienced these problems to a certain degree. Univariate and multivariate analyses showed that SSS-8 scores at admission (relative risk [RR] 1.234, 95% CI 1.075-1.417, P=0.003) and mMRC scores at discharge (RR 2.420, 95% CI 1.251-4.682, P=0.009) were 2 independent prognostic indicators of somatic symptom burden. In addition, muscle pain as a chief complaint (RR 4.682, 95% CI 1.247-17.580, P<0.022) and history of use of hypnotic drugs (RR 0.148, 95% CI 0.029-0.749, P<0.019) were 2 independent indicators of patient sleep quality during hospitalization. CONCLUSIONS To the best of our knowledge, the present study was the first dynamic assessment of the somatic symptom burden and sleep quality in patients with COVID-19 during hospitalization and quarantine after discharge. Patients with high somatic symptom burden at admission, especially muscle pain as the chief complaint, are prone to having a higher physical burden and more sleep disturbance at discharge.

Impact of the shift to a fibrinolysis-first strategy on care and outcomes of patients with ST-segment-elevation myocardial infarction during the COVID-19 pandemic-The experience from the largest cardiovascular-specific centre in China.

BACKGROUND: The impact of fibrinolysis-first strategy on outcomes of patients with ST-segment-elevation myocardial infarction (STEMI) during the COVID-19 pandemic was unknown. METHODS: Data from STEMI patients presenting to Fuwai Hospital from January 23 to April 30, 2020 were compared with those during the equivalent period in 2019. The primary end-point was net adverse clinical events (NACE; a composite of death, non-fatal myocardial reinfarction, stroke, emergency revascularization, and bleeding over BARC type 3). The secondary outcome was a composite of recurrent ischaemia, cardiogenic shock, and exacerbated heart failure. RESULTS: The final analysis included 164 acute STEMI patients from 2020 and 240 from 2019. Eighteen patients (20.2% of those with indications) received fibrinolysis therapy in 2020 with a median door-to-needle time of 60.0 (43.5, 92.0) minutes. Patients in 2020 underwent primary PCI less frequently than their counterparts (14 [14.2%] vs. 144 [86.8%] in 2019, P < 0.001), and had a longer median door-to-balloon time (175 [121,213] minutes vs. 115 [83, 160] minutes in 2019, P = 0.009). Patients were more likely to undergo elective PCI (86 [52.4%] vs. 28 [11.6%] in 2019, P < 0.001). The in-hospital NACE was similar between 2020 and 2019 (14 [8.5%] vs. 25 [10.4%], P = 0.530), while more patients developed a secondary outcome in 2020 (20 [12.2%] vs. 12 [5.0%] in 2019, P = 0.009). CONCLUSIONS: The fibrinolysis-first strategy during the COVID-19 pandemic was associated with a lower rate of timely coronary reperfusion and increased rates of recurrent ischaemia, cardiogenic shock, and exacerbated heart failure. However, the in-hospital NACE remained similar to that in 2019.