ABSTRACT
The COVID-19 outbreak has greatly impacted the stability of the global financial markets. In the post-COVID-19 pandemic era, the risk contagion patterns of the global financial markets may change. This paper utilizes the conditional value-at-risk (ΔCoVaR) model to measure the risk level of the financial markets in various economies and uses the TVP-VAR-CONNECTEDNESS approach to construct a time-varying spillover index. Based on the dimensions of time and space, we explored the contagion path, contagion status, and contagion structure characteristics of global financial market risk before and during the COVID-19 pandemic. The results entail several conclusions. (i) The COVID-19 pandemic increased the spillover level of global financial market risk and the risk connectedness of financial markets in different countries. In addition, during the concentrated outbreak period of COVID-19, the risk spillover level in developing countries rose rapidly, while the financial risk spillover level in developed countries decreased significantly. (ii) The impact of the COVID-19 pandemic on the spillover of the global financial market risk is time-varying, and there is a strong correlation between the risk spillover level of the financial markets of the world and the severity of the COVID-19 pandemic. (iii) Due to the impact of the COVID-19 pandemic, Brazil, Canada, and Russia have become new risk spillover centers;in the post-COVID-19 pandemic era, China's spillover to developed countries has increased, and the financial influence of China has also gradually increased. In addition, the risk contagion capacity of financial markets among European countries is gradually converging. (iv) During the concentrated outbreak of the COVID-19 pandemic, the Americas were the main exporter of global financial market risk, while Europe played a role in risk absorption.
ABSTRACT
SARS-CoV-2, which causes the current pandemic of respiratory illness, is evolving continuously and generating new variants. Nevertheless, most of the sequence analyses thus far focused on nucleotide substitutions despite the fact that insertions and deletions (indels) are equally important in the evolution of SARS-CoV-2. In this study, we analyzed 1,099,664 high-quality sequences of SARS-CoV-2 genomes to re-construct the evolutionary and epidemiological histories of indels. Our analysis revealed 289 circulating indel types (237 deletion and 52 insertion types, each represented by more than ten genomic sequences), among which eighteen were recurrent indel types, each represented by more than 500 genome sequences. Although indels were identified across the entire genome, most of them were identified in nsp6, S, ORF8, and N genes, among which ORF8 indel types had the highest frequencies of frameshift. Geographical and temporal analyses of these variants revealed a few alterations of dominant indel types, each accompanied by geographic expansion to different countries and continents, which resulted in the fixation of several types of indels in the field, including the current variants of concern. Evolutionary and structural analyses revealed that indels involving S N-terminal domain regions were linked to the 3/4 variants of concern, resulting in significantly altered S protein that might contribute to the selective advantage of the corresponding variant. In sum, our study highlights the important role of insertions and deletions in the evolution and spread of SARS-CoV-2.
ABSTRACT
Background: In China, mental health of frontline medical staff might be influenced by clinicians’ ability to handle the outbreak of coronavirus disease 2019 (COVID-19). Few studies to-date have addressed the association between clinicians’ competencies and mental health in this context. This cross-sectional study has examined the prevalence of mental health symptoms among frontline medical staff handling the COVID-19 outbreak, and explored the associations between their competencies, and separate and concurrent depressive and anxiety symptoms. Methods: A total of 623 frontline medical staff were included in this study, which took place from January 20, 2020 to February 20, 2020. Competencies, depressive symptoms, and anxiety symptoms were assessed using the short form of the Chinese clinical physicians’ competency model, Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7 questionnaire, respectively. Logistic regression models were used to estimate the associations between one standard deviation increase in competency scores and the prevalence of mental health problems. Multivariate-adjusted odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated.Results: Among 623 staff members, the prevalence of depressive, anxiety, and comorbid depressive and anxiety symptoms was 40.93%, 31.78%, and 26.00%, respectively. Among the medical staff with higher total competency scores, the prevalence of depressive (OR=0.67, 95% CI: 0.55-0.81), anxiety (OR=0.68, 95% CI: 0.56-0.83), and comorbid anxiety and depressive symptoms (OR=0.69, 95% CI: 0.55-0.83) was lower than among their lower-scoring counterparts. Subgroup analyses stratified by core competency scores revealed similar associations as the main analyses.Conclusions: The present findings highlight the association between high core competency scores and lower prevalence of depressive, anxiety, and comorbid anxiety and depressive symptoms. Improving medical staff’s core competencies might help prevent mental health problems among frontline medical staff responding to COVID-19.