Informational inefficiency on bitcoin futures

This paper investigates the dynamics and drivers of informational inefficiency in the Bitcoin futures market. To quantify the adaptive pattern of informational inefficiency, we leverage two groups of statistics which measure long memory and fractal dimension to construct a global-local market inefficiency index. Our findings validate the adaptive market hypothesis, and the global and local inefficiency exhibits different patterns and contributions. Regarding the driving factors of the time-varying inefficiency, our results suggest that trading activity of retailers (hedgers) increases (decreases) informational inefficiency. Compared to hedgers and retailers, the role played by speculators is more likely to be affected by the COVID-19 crisis. Extremely bullish and bearish investor sentiment has more significant impact on the local inefficiency. Arbitrage potential, funding liquidity, and the pandemic exert impacts on the global and local inefficiency differently. No significant evidence is found for market liquidity and policy uncertainty related to cryptocurrency.

Urban Form and Spatiotemporal Vulnerability of Local Communities to Covid-19

This paper investigates spatiotemporal dynamics of the effects of urban form on the Covid-19 spread within local communities in Salt Lake County, Utah, in the United States. We identify three types of communities-minority, traditional urban and suburban, and new suburban-and three stages throughout March 2020-September 2021, reflecting the initial, outbreak, and recovery stages. While the traditional urban and suburban communities experience the least risk of Covid-19, minority communities are severely impacted in the initial and outbreak stages, and remote suburban communities are primarily affected in the outbreak and recovery stages. The regression further reveals the role of urban form in the pandemic. High-density urban land use is the main density factor contributing to the disease's spread. In the initial stage, mobility factors such as street connectivity and walkability contribute to the local spread, while land use mixture is the catalyst in the outbreak stage. A comprehensive compact development might offset these negative effects on local public health, and its contribution to local resilience in the recovery stage is also confirmed. Thus, compact development is still valuable for building urban resilience, and proper planning and policies can offset the potential adverse effects of pandemics.

[Epidemiological characteristics of COVID-19 caused by 2019-nCoV Delta variant in Shangyu district, Shaoxing of Zhejiang province].

Objective: To investigate the epidemiological characteristics of COVID-19 caused by 2019-nCoV Delta variant in Shangyu district, Shaoxing of Zhejiang province in 2021, and provide evidence for the improvement of COVID-19 control and prevention measures. Methods: The incidence data of COVID-19 in Shangyu from December 7 to 21, 2021 was obtained from Shangyu District Center for Disease Control and Prevention. The epidemiological characteristics of the cases, i.e. the population, time and space distributions, were analyzed, and the incubation period and time-varying reproduction numbers (Rt) were calculated. Results: From December 7 to 21, 2021, a total of 380 COVID-19 cases caused by 2019-nCoV Delta variant were detected in Shangyu, the median age of the cases was 52 years, M (Q1，Q3: 38, 61). The male to female ratio of the cases was 1∶1.25, and the cases were mainly workers (36.58%) and farmers (27.63%). The epidemic affected 9 townships (or community) of Shangyu, especially Caoe and Baiguan communities with the cases accounting for 57.10% and 31.53% respectively. The median incubation period of cases was 4.00 days, M (Q1，Q3: 3.00, 5.75). The basic reproduction number (R0) was 4.06, and the Rt was 5.62 in early phase of the outbreak (the highest) and continuously decreased to less than 1.00 within 10 days after the detection of the outbreak. The number of COVID-19 cases decreased to 0 within 14 days after the outbreak (December 7-21), and the main detection methods were screening in centralized isolation (55.53%) and home isolation (40.00%). The infection rates of close contacts and secondary close contacts were 2.06% and 0.46% respectively. Conclusion: The epidemic of COVID-19 in Shangyu characterized by short incubation period, large number of infected people, and case clustering, suggesting the strong transmission of Delta variant (B.1.617.2). Comprehensive prevention and control measures, such as management of close contacts and secondary close contacts, and high-risk area, are essential for the rapid control of the epidemic.

Development and New Thinking on Covid-19 Vaccine

The COVID-19 (2019 Novel Coronavirus Pneumonia) outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the most severe challenge facing mankind in a century. After Wuhan, a city in China became the epicenter of the outbreak of COVID-19 in December 2019, multiple countries have experienced multiple waves of the disease. Scientific experts have been working on the characteristics of COVID-19 with the aim of finding the most appropriate way to control the virus. This phenomenon has reinforced the strong need to develop a vaccine to control the rate and spread of infection. In view of the global importance attached to COVID-19, this article mainly reviews the basic biological characteristics, sources and transmission routes of SARS-CoV-2, and provides an overview of the current clinical trials of representative new coronavirus vaccines (including inactivated vaccines, live attenuated vaccines, recombinant vector vaccines, subunit vaccines and nucleic acid vaccines) to summarize and analyze the advantages and disadvantages of various COVID-19 vaccines on the market today, and provide reference suggestions for the design and optimization of COVID-19 vaccines. © 2021, Editorial Board of Pharmaceutical Biotechnology. All right reserved.

The challenge of COVID-19 for adult men and women in the United States: disparities of psychological distress by gender and age.

OBJECTIVES: During the COVID-19 pandemic, the prevalence of psychological distress rose from 11% in 2019 to more than 40% in 2020. This study aims to examine the disparities among US adult men and women. STUDY DESIGN: We used 21 waves of cross-sectional data from the Household Pulse Survey that were collected between April and December 2020 for the study. The Household Pulse Survey was developed by the U.S. Census Bureau to document the social and economic impact of COVID-19. METHODS: The study population included four groups of adults: emerging adults (18-24 years); young adults (25-44 years); middle-aged adults (45-64 years); and older adults (65-88 years). Psychological distress was measured by their Generalized Anxiety Disorder score and the Patient Health Questionnaire. The prevalence of psychological stress was calculated using logistic models adjusted for socio-demographic variables including race/ethnicity, education, household income, and household structure. All descriptive and regression analysis considered survey weights. RESULTS: Younger age groups experienced higher prevalence of psychological distress than older age groups. Among emerging adults, the prevalence of anxiety (42.6%) and depression (39.5%) was more than twice as high as older adults who experienced prevalence of anxiety at 20% and depression at 16.6%. Gender differences were also more apparent in emerging adults. Women between 18 and 24 years reported higher differential rates of anxiety and depression than those with men (anxiety: 43.9% vs. 28.3%; depression: 33.3% vs. 24.9%). CONCLUSION: Understanding the complex dynamics between COVID-19 and psychological distress has emerged as a public health priority. Mitigating the negative mental health consequences associated with the COVID-19 pandemic, for younger generations and females in particular, will require local efforts to rebuild capacity for social integration and social connection.

[Clinical features and outcome of treatment for novel coronavirus pneumonia: a meta-analysis].

Objective: To investigate the clinical features and outcome of treatment for novel coronavirus pneumonia. Methods: Literature on novel coronavirus pneumonia was retrieved from PubMed and EMBASE databases. The relevant data was extracted and a meta-analysis was performed using StatsDirect statistical software V.2.8.0 to calculate the combined odds ratio. Results: Seven studies were included, consisting of 1594 cases. The meta-analysis result showed that the most common clinical symptoms of the novel coronavirus pneumonia were fever (91.6%) and cough (64.5%), followed by dyspnea (32.8%) and sputum (28.1%). Headache (10.5%), sore throat (11.2%), hemoptysis (3.2%), diarrhea (6.6%) and the other symptoms were relatively rare. Aspartate aminotransferase (29%), alanine transaminase (22.7%), and total bilirubin (11.7%) levels were elevated, except for serum albumin levels (80.4%). The common therapeutic agents used were antibiotics (87.7%), antiviral drugs (75.5%), and glucocorticoids (26.6%), while antifungal agents (7.7%) were used in few. Mechanical ventilation (13.4%), extracorporeal membrane oxygenation (1.9%), and continuous renal replacement therapy (3.8%) were used in severe cases. The rate of mortality in hospital was 7.7%, respectively. Heterogeneity between studies was significant; however, subgroup and sensitivity analysis had failed to identify clear sources of heterogeneity. Conclusion: Fever, cough and liver dysfunction are the main clinical manifestations of this disease and the mortality rate is low.