Molecular epidemiology analysis of early variants of SARS-CoV-2 reveals the potential impact of mutations P504L and Y541C (NSP13) in the clinical COVID-19 outcomes.

Since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused global pandemic with alarming speed, comprehensively analyzing the mutation and evolution of early SARS-CoV-2 strains contributes to detect and prevent such virus. Here, we explored 1962 high-quality genomes of early SARS-CoV-2 strains obtained from 42 countries before April 2020. The changing trends of genetic variations in SARS-CoV-2 strains over time and country were subsequently identified. In addition, viral genotype mapping and phylogenetic analysis were performed to identify the variation features of SARS-CoV-2. Results showed that 57.89% of genetic variations involved in ORF1ab, most of which (68.85%) were nonsynonymous. Haplotype maps and phylogenetic tree analysis showed that amino acid variations in ORF1ab (p.5828P > L and p.5865Y > C, also NSP13: P504L and NSP13: Y541C) were the important characteristics of such clade. Furthermore, these variants showed more significant aggregation in the United States (P = 2.92E-66, 95%) than in Australia or Canada, especially in strains from Washington State (P = 1.56E-23, 77.65%). Further analysis demonstrated that the report date of the variants was associated with the date of increased infections and the date of recovery and fatality rate change in the United States. More importantly, the fatality rate in Washington State was higher (4.13%) and showed poorer outcomes (P = 4.12E-21 in fatality rate, P = 3.64E-29 in death and recovered cases) than found in other states containing a small proportion of strains with such variants. Using sequence alignment, we found that variations at the 504 and 541 sites had functional effects on NSP13. In this study, we comprehensively analyzed genetic variations in SARS-CoV-2, gaining insights into amino acid variations in ORF1ab and COVID-19 outcomes.

Factors associated with insomnia among Chinese front-line nurses fighting against COVID-19 in Wuhan: A cross-sectional survey.

AIM: To investigate the prevalence of insomnia among front-line nurses fighting against COVID-19 in Wuhan, China, and analyse its influencing factors. BACKGROUND: Insomnia is an important factor that can affect the health and work quality of nurses. However, there is a lack of big-sample studies exploring factors that affect the insomnia of nurses fighting against COVID-19. METHOD: This cross-sectional study using the Ascension Insomnia Scale, Fatigue Scale-14 and Perceived Stress Scale took place in March 2020. Participants were 1,794 front-line nurses from four tertiary-level general hospitals. RESULTS: The prevalence of insomnia among participants was 52.8%. Insomnia was predicted by gender, working experience, chronic diseases, midday nap duration, direct participation in the rescue of patients with COVID-19, frequency of night shifts, professional psychological assistance during the pandemic, negative experiences (such as family, friends or colleagues being seriously ill or dying due to COVID-19), the degree of fear of COVID-19, fatigue and perceived stress. CONCLUSION: The level of insomnia among participants was higher than the normal level. Interventions based on influencing factors should be implemented to ensure nurses' sleep quality. IMPLICATIONS FOR NURSING MANAGEMENT: An in-depth understanding of the influencing factors of insomnia among front-line nurses can help nurse managers develop solutions to improve front-line nurses' sleep quality, which will enhance the physical and mental conditions of nurses and promote the quality of care.

Prevalence and Influencing Factors on Fatigue of First-line Nurses Combating with COVID-19 in China: A Descriptive Cross-Sectional Study.

Nurses' work-related fatigue has been recognized as a threat to nurse health and patient safety. The aim of this study was to assess the prevalence of fatigue among first-line nurses combating with COVID-19 in Wuhan, China, and to analyze its influencing factors on fatigue. A multi-center, descriptive, cross-sectional design with a convenience sample was used. The statistical population consisted of the first-line nurses in 7 tertiary general hospitals from March 3, 2020 to March 10, 2020 in Wuhan of China. A total of 2667 samples from 2768 contacted participants completed the investgation, with a response rate of 96.35%. Social-demographic questionnaire, work-related questionnaire, Fatigue Scale-14, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, and Chinese Perceived Stress Scale were used to conduct online survey. The descriptive statistic of nurses' social-demographic characteristics was conducted, and the related variables of work, anxiety, depression, perceived stress and fatigue were analyzed by t-tests, nonparametric test and Pearson's correlation analysis. The significant factors which resulted in nurses' fatigue were further analyzed by multiple linear regression analysis. The median score for the first-line nurses' fatigue in Wuhan was 4 (2, 8). The median score of physical and mental fatigue of them was 3 (1, 6) and 1 (0, 3) respectively. According to the scoring criteria, 35.06% nurses (n=935) of all participants were in the fatigue status, their median score of fatigue was 10 (8, 11), and the median score of physical and mental fatigue of them was 7 (5, 8) and 3 (2, 4) respectively. Multiple linear regression analysis revealed the participants in the risk groups of anxiety, depression and perceived stress had higher scores on physical and mental fatigue and the statistically significant positive correlation was observed between the variables and nurses' fatigue, the frequency of exercise and nurses' fatigue had a statistically significant negative correlation, and average daily working hours had a significantly positive correlation with nurses' fatigue, and the frequency of weekly night shift had a low positive correlation with nurses' fatigue (P<0.01). There was a moderate level of fatigue among the first-line nurses fighting against COVID-19 pandemic in Wuhan, China. Government and health authorities need to formulate and take effective intervention strategies according to the relevant risk factors, and undertake preventive measures aimed at reducing health hazards due to increased work-related fatigue among first-line nurses, and to enhance their health status and provide a safe occupational environment worldwide. Promoting both medical and nursing safety while combating with the pandemic currently is warranted.

Amino acid variation analysis of surface spike glycoprotein at 614 in SARS-CoV-2 strains.

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to disperse globally with worrisome speed, identifying amino acid variations in the virus could help to understand the characteristics of it. Here, we studied 489 SARS-CoV-2 genomes obtained from 32 countries from the Nextstrain database and performed phylogenetic tree analysis by clade, country, and genotype of the surface spike glycoprotein (S protein) at site 614. We found that virus strains from mainland China were mostly distributed in Clade B and Clade undefined in the phylogenetic tree, with very few found in Clade A. In contrast, Clades A2 (one case) and A2a (112 cases) predominantly contained strains from European regions. Moreover, Clades A2 and A2a differed significantly from those of mainland China in age of infected population (P = 0.0071, mean age 40.24 to 46.66), although such differences did not exist between the US and mainland China. Further analysis demonstrated that the variation of the S protein at site 614 (QHD43416.1: p.614D>G) was a characteristic of stains in Clades A2 and A2a. Importantly, this variation was predicted to have neutral or benign effects on the function of the S protein. In addition, global quality estimates and 3D protein structures tended to be different between the two S proteins. In summary, we identified different genomic epidemiology among SARS-CoV-2 strains in different clades, especially in an amino acid variation of the S protein at 614, revealing potential viral genome divergence in SARS-CoV-2 strains.

Sex-specific clinical characteristics and prognosis of coronavirus disease-19 infection in Wuhan, China: A retrospective study of 168 severe patients.

To confirm the relationship between sex and the progression of Coronavirus Disease-19 (COVID-19), and its potential mechanism, among severe patients. For this retrospective study, we included 168 consecutive severe patients with pathogen-confirmed COVID-19 who were hospitalized between January 16th and February 4th, 2020, at Tongji Hospital in Wuhan, China. Clinical characteristics, laboratory parameters, and outcomes were compared and analyzed between males and females. In the present study, we analyzed 168 severe patients with COVID-19, including 86 males and 82 females, and 48 patients (28.6%) were diagnosed as critically ill. Of 86 male patients, 12.8% (11/86) died and 75.6% (65/86) were discharged; of 82 female patients, 7.3% (6/82) died and 86.6% (71/82) were discharged. Eleven laboratory parameters showed significant differences between male and female patients, and six of them were higher during the whole clinical course in patients who died than in patients who were discharged. In adjusted logistic regression analysis, males with comorbidities presented a higher risk of being critically ill than males without comorbidities (OR = 3.824, 95% CI = 1.279-11.435). However, this association attenuated to null in female patients (OR = 2.992, 95% CI = 0.937-9.558). A similar sex-specific trend was observed in the relation between age and critically ill conditions. We highlighted sex-specific differences in clinical characteristics and prognosis. Male patients appeared to be more susceptible to age and comorbidities. Sex is an important biological variable that should be considered in the prevention and treatment of COVID-19.