A Statistical Analysis of Impact of COVID19 on the Global Economy and Stock Index Returns

Market resilience of orthopaedic hip/knee arthroplasty sales during COVID-19

INTRODUCTION

The coronavirus 2019 (COVID-19) pandemic led to a marked decrease in elective surgical volume and orthopaedic device sales. The aim of this paper was to quantify this decrease and the related financial impact on the largest hip/knee arthroplasty companies by: (1) tracking individual hip/knee company valuations; (2) calculating aggregate changes in overall hip/knee arthroplasty market valuations; and (3) quantifying quarterly hip/knee revenues relative to prior years.

MATERIALS AND METHODS

Financial data on the top five hip/knee arthroplasty companies by size between January 1, 2019, and October 1, 2020, was collected from a Wall Street financial database, S&P Capital IQ. Changes in valuation of these companies were compared against benchmark market indices, the S&P500 and Vanguard Healthcare ETF. U.S. hip/knee arthroplasty-specific revenue for Q1 and Q2 of 2019 and 2020 was collected from Securities Exchange Commission 10-Q forms. Quarterly revenue changes were calculated using 1-2Q19 revenues as baselines and aggregate to approximate the overall hip/knee arthroplasty market.

RESULTS

The top five hip/knee companies lost $179.2 billion (32.7% loss) in market value from pre COVID-19 market highs to COVID-19 market lows (March 2020), while S&P500 and Vanguard Healthcare ETF decreased 36.1 and 33.2%, respectively. From market lows to October 2020, arthroplasty companies rallied 38.6% while the S&P500 and Vanguard Healthcare ETF regained 43.5 and 56.4% respectively. Notably, this occurred while aggregate 1Q/2Q20 revenue lagged 7.1/41.8% relative to 2019, with an overall decrease of $1.58B (24.8%).

CONCLUSIONS

Similar to the overall market and healthcare sector, the top five hip/knee arthroplasty companies have recovered from their COVID market lows. Our results reveal that the valuations of hip/knee companies remained robust during COVID, even as revenues fell, likely due to strong investor confidence in the industry outlook and the greater overall healthcare system utilization.

COVID-19 and financial performance: Pre and post effect of COVID-19 on organization performance; A study based on South Asian economy

The COVID-19 epidemic has damaged developing as well as developed economies and reduced the profitability of several companies. Technological advancement plays a vital role in the company's performance in this current situation. All activities carry on virtually. In this study, the financial performance of enterprises in the South Asian banking industry will be compared before and after the COVID-19 epidemic. Furthermore, the full influence of the pandemic will take place in the long run. This study also explains the technological effect on improving performance, especially during the period of the COVID-19 pandemic. It has an impact on people's social lives as well as the economic world. This study examined a sample of 34 banks from the South Asian region from 2016 to 2021. A Wilcox rank test was used to determine whether there was a significant difference before and after the epidemic era. The overall conclusion of this study is that the COVID-19 pandemic had a significant influence on the bank's financial performance, particularly in terms of profitability. But technological advancement has a positive effect on organizational performance, ultimately increasing the financial performance of South Asian banks. And there is a big difference between pre-pandemic and post-pandemic organizational performance. The findings of this study have significant policy implications since it is clear that cooperation among governments, banks, regulatory agencies, and central banks is necessary to address the financial and economic effects of the COVID-19 pandemic.

An empirical investigation of COVID-19 effects on herding behaviour in USA and UK stock markets using a quantile regression approach

This study investigates the effects of the COVID-19 pandemic on herding behaviour among investors in two well-developed markets. Utilizing daily prices of stock indexes from the period of December 5, 2017 to February 28, 2022 for USA and January 9, 2018 to February 28, 2022 for UK, we test for herding behaviour using the quantile regression approach in addition to the OLS model. We found no evidence of herding before the COVID-19 pandemic in both bullish and bearish markets for USA and UK. However, herding incidence was discovered in the USA and UK bullish market during the COVID-19 period. In the bearish market, herding behaviour was only found during the COVID-19 period in USA. The study provides policymakers and investors with information to draw significant measures in their investment portfolio management during crises and pandemics.

The COVID-19 pandemic's effects on SMEs and travel agencies: The critical role of corporate social responsibility

This study is based on the system resilience framework, which outlines the aspects of community behavior, employees, the environment, history, and corporate social responsibility. We used a partial least squares structural equation model to evaluate a sample of 300 Vietnamese SMEs and travel agencies. We discovered that SMEs' strategies positively influence performance and are co-created with corporate social responsibility. The dependability of internal integrity was then determined. The empirical results showed that the overall confidence index for all facilities ranged from 0.70 to 0.95, with values ranging from 0.809 to 0.931. Furthermore, the A and Cronbach's alpha reliability values ranged from 0.70 to 0.90. As a result, the reliability of internal consistency was established. The convergence validity of the configurations was assessed by comparing the extracted mean values of variance (AVE), which, for all configurations, exceeded the limit of 0.50. This approach emphasizes the impact of corporate social responsibility practices on communities, the environment, and heritage.

Multifactorial influences underpinning a decision on COVID-19 vaccination among healthcare workers: a qualitative analysis

COVID-19 vaccination in healthcare workers (HCW) is essential for improved patient safety and resilience of health systems. Despite growing body of literature on the perceptions of COVID vaccines in HCWs, existing studies tend to focus on reasons for 'refusing' the vaccines, using surveys almost exclusively. To gain a more nuanced understanding, we explored multifactorial influences underpinning a decision on vaccination and suggestions for decision support to improve vaccine uptake among HCWs in the early phase of vaccination rollout. Semi-structured interviews were undertaken with thirty-three HCWs in Singapore. Transcribed data was thematically analyzed. Decisions to accept vaccines were underpinned by a desire to protect patients primarily driven by a sense of professional integrity, collective responsibility to protect others, confidence in health authorities and a desire to return to a pre-pandemic way of life. However, there were prevailing concerns with respect to the vaccines, including long-term benefits, safety and efficacy, that hampered a decision. Inadequate information and social media representation of vaccination appeared to add to negative beliefs, impeding a decision to accept while low perceived susceptibility played a moderate role in the decision to delay or decline vaccination. Participants made valuable suggestions to bolster vaccination. Our findings support an approach to improving vaccine uptake in HCWs that features routine tracking and transparent updates on vaccination status, use of institutional platforms for sharing of experience, assuring contingency management plans and tailored communications to emphasize the duty of care and positive outlook associated with vaccination.

Artificial Intelligence and Deep Learning Assisted Rapid Diagnosis of COVID-19 from Chest Radiographical Images: A Survey

Artificial Intelligence (AI) has been applied successfully in many real-life domains for solving complex problems. With the invention of Machine Learning (ML) paradigms, it becomes convenient for researchers to predict the outcome based on past data. Nowadays, ML is acting as the biggest weapon against the COVID-19 pandemic by detecting symptomatic cases at an early stage and warning people about its futuristic effects. It is observed that COVID-19 has blown out globally so much in a short period because of the shortage of testing facilities and delays in test reports. To address this challenge, AI can be effectively applied to produce fast as well as cost-effective solutions. Plenty of researchers come up with AI-based solutions for preliminary diagnosis using chest CT Images, respiratory sound analysis, voice analysis of symptomatic persons with asymptomatic ones, and so forth. Some AI-based applications claim good accuracy in predicting the chances of being COVID-19-positive. Within a short period, plenty of research work is published regarding the identification of COVID-19. This paper has carefully examined and presented a comprehensive survey of more than 110 papers that came from various reputed sources, that is, Springer, IEEE, Elsevier, MDPI, arXiv, and medRxiv. Most of the papers selected for this survey presented candid work to detect and classify COVID-19, using deep-learning-based models from chest X-Rays and CT scan images. We hope that this survey covers most of the work and provides insights to the research community in proposing efficient as well as accurate solutions for fighting the pandemic.

Pediatric Residency Training amid the COVID-19 Pandemic: Exploring the Impact of Supervision and Clinical Practice Guidelines on Clinical and Financial Outcomes

Objective

This study is aimed at calculating the magnitude of the effect of clinical practice guidelines (CPG) and supervision in inhibiting the negative impact of the COVID-19 pandemic on clinical and financial outcomes of non-COVID-19 inpatient care by pediatric residents in academic medical center (AMC) hospitals during the COVID-19 pandemic.

Methods

The cohort retrospective study was conducted. This study collected patient data from pediatric residency programs. A research cohort consisted of non-COVID-19 pediatric patients at Dr. Soetomo General Academic Hospital. This study compared the subgroup of patients treated during the pandemic with those treated before the pandemic. The results were analyzed using SPSS 26.0 and Smart-PLS.

Results

There was a 41.4% decrease in pediatric inpatients during the pandemic with an increased severity level and complexity level, a reduction of 7.46% availability of supervisors, an increase of 0.4% in readmission < 30 days, an increase of 0.31% in-hospital mortality, an increase the total costs of care, and a decrease of insurance claim profit. CPG did not moderate the effect of the COVID-19 pandemic on the clinical outcomes (β = −0.006, P = 0.083) but moderated the financial outcomes (β = −0.022, P = 0.000), by reducing the total cost of care and increasing insurance claim profit. Supervision moderated the effect of the COVID-19 pandemic on the clinical outcomes (β = 0.040, P = 0.000) by increasing aLOS and on the financial outcomes (β = −0.031, P = 0.000) by reducing the total cost of care and increasing insurance claim profit. This study model had a 24.0% variance of explanatory power for clinical outcomes and 49.0% for financial outcomes. This study's structural model effectively predicted clinical outcomes (Q² = 0.238) and financial outcomes (Q² = 0.413).

Conclusion

Direct supervision inhibited the negative impact of the COVID-19 pandemic on both clinical and financial outcomes of non-COVID-19 inpatient care by pediatric residents, while CPG only inhibited the negative impact on financial outcomes. Implication of This Study. In a disaster, the availability of CPG and direct supervision makes AMC hospitals able to inhibit the negative impact of disasters on clinical and financial outcomes.

Adoption of telehealth technologies: an approach to improving healthcare system

BACKGROUND

Globally, the healthcare industry is well known to be one of the strongest drivers of economic growth and development. The sector has gained substantial attention to deal with the fallout of COVID-19, leading to improvement in the quality observed in developed and developing nations. With the advent of the twenty-first century, globalization an ever-growing populace, and environmental changes prompted the more noteworthy spread of irresistible diseases, highlighting the association between wellbeing and future health security. The massive spread of COVID-19 paralyzed the global economy and took a toll on health governance and wellbeing. The present review aims to map the harrowing impacts of COVID-19 on the QoL (quality of life) observed. Particularly the post-pandemic era is likely to boot-strap the healthcare sector. Hence in post COVID era, there is a dire need to strengthen the healthcare system and understand the evolving challenges to answer calls in recovery in the wake of COVID-19.

CONCLUSION

There is a flurry of research highlighting the implications faced due to the rise of the pandemic, resulting in the wrecking growth and development. However, the massive potential of telehealth is still largely underexplored with scarce research on countless evolving technologies. The current crisis highlighted the need to develop emerging frameworks and facilitate multilateral cooperation. The present research can serve as the baseline for better future strategies to improve global health initiatives. Further, this can help to focus on wider health determinants, redesign strategies and policies for the healthcare industry and to mitigate/deal better with future pandemics.

Unsuppressed HIV infection impairs T cell responses to SARS-CoV-2 infection and abrogates T cell cross-recognition

In some instances, unsuppressed HIV has been associated with severe COVID-19 disease, but the mechanisms underpinning this susceptibility are still unclear. Here, we assessed the impact of HIV infection on the quality and epitope specificity of SARS-CoV-2 T cell responses in the first wave and second wave of the COVID-19 epidemic in South Africa. Flow cytometry was used to measure T cell responses following peripheral blood mononuclear cell stimulation with SARS-CoV-2 peptide pools. Culture expansion was used to determine T cell immunodominance hierarchies and to assess potential SARS-CoV-2 escape from T cell recognition. HIV-seronegative individuals had significantly greater CD4+ T cell responses against the Spike protein compared to the viremic people living with HIV (PLWH). Absolute CD4 count correlated positively with SARS-CoV-2-specific CD4+ and CD8+ T cell responses (CD4 r=0.5, p=0.03; CD8 r=0.5, p=0.001), whereas T cell activation was negatively correlated with CD4+ T cell responses (CD4 r=-0.7, p=0.04). There was diminished T cell cross-recognition between the two waves, which was more pronounced in individuals with unsuppressed HIV infection. Importantly, we identify four mutations in the Beta variant that resulted in abrogation of T cell recognition. Taken together, we show that unsuppressed HIV infection markedly impairs T cell responses to SARS-Cov-2 infection and diminishes T cell cross-recognition. These findings may partly explain the increased susceptibility of PLWH to severe COVID-19 and also highlights their vulnerability to emerging SARS-CoV-2 variants of concern.

A novel method to detect the early warning signal of COVID-19 transmission

Background

Infectious illness outbreaks, particularly the corona-virus disease 2019 (COVID-19) pandemics in recent years, have wreaked havoc on human society, and the growing number of infected patients has put a strain on medical facilities. It’s necessary to forecast early warning signals of potential outbreaks of COVID-19, which would facilitate the health ministry to take some suitable control measures timely to prevent or slow the spread of COVID-19. However, since the intricacy of COVID-19 transmission, which connects biological and social systems, it is a difficult task to predict outbreaks of COVID-19 epidemics timely.

Results

In this work, we developed a new model-free approach, called, the landscape network entropy based on Auto-Reservoir Neural Network (ARNN-LNE), for quantitative analysis of COVID-19 propagation, by mining dynamic information from regional networks and short-term high-dimensional time-series data. Through this approach, we successfully identified the early warning signals in six nations or areas based on historical data of COVID-19 infections.

Conclusion

Based on the newly published data on new COVID-19 disease, the ARNN-LNE method can give early warning signals for the outbreak of COVID-19. It’s worth noting that ARNN-LNE only relies on small samples data. Thus, it has great application potential for monitoring outbreaks of infectious diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07603-z.

Personal Economic Worries in Response to COVID-19 Pandemic: A Cross Sectional Study

Objectives

The emergence of the COVID-19 pandemic worsened Lebanon’s economic situation and generated worries about living conditions. This study aimed to explain personal economic worries patterns among Lebanese young adults while accounting for demographics and mental health characteristics.

Methods

A total sample of 988 Lebanese responses were collected, using an online survey. The analysis was conducted using regression-based methods.

Results

Men exhibited higher economic worries than women. Lower levels of economic worries among people with higher wages were more pronounced. Lebanese retirees experience the highest economic worries compared to other employment status groups. Individuals with higher life satisfaction are less concerned about the economy. Mental wellbeing factors were positively associated with personal economic worries.

Conclusion

The current study presents a seminal insight into the differences in economic worries caused by COVID-19 pandemic among individuals in a developing country context.

Effects of Multiple Financial News Shocks on Tourism Demand Volatility Modelling and Forecasting

Even though both symmetric and asymmetric conceptions of news impacts are well-established in the disciplines of economics and financial markets, the effects of combining multiple news shocks on the volatility of tourism demand have not yet been delved into or gauged in any tourist destination. This work hypothesises and verifies that the news impact curve (NIC), conditional heteroscedastic volatility models, and multiple news shocks are suitable for forecasting the volatility of the Malaysian tourist industry. Among them, three primarily volatility models (GARCH, EGARCH, and GJRGARCH) are used in conjunction with five financial news shocks (FFNSs), namely the Kuala Lumpur Composite Index (KLCI), the United States Dollar Index (DXY), the stock performance of 500 large companies listed on stock exchanges (S&P500), Crude Oil (CO), and Gold Price (GP). Among the most significant findings of this study are the demonstration of monthly seasonality using conditional mean equations, asymmetry effects in EGARCH-FFNSs, and GJRGARCH-FFNSs models in conditional variance equations and 50 NICs, and the GARCH-FFNSs model’s evaluation of the persistence influence of news shocks on monthly visitor arrivals in Malaysia. The GJRGARCH-FFNSs model is the best model for Malaysian tourism demand volatility forecasting accuracy. Furthermore, KLCI and Gold Price have the most substantial impact on the number of tourists to Malaysia. In addition, it should be emphasised that the methodological framework utilised in this study can be a useful tool for creating and forecasting the performance of symmetry and asymmetry impacts on tourism demand volatility.

Recent Chronology of COVID-19 Pandemic

COVID-19 is highly contagious and is caused by severe acute respiratory syndrome coronavirus 2. It spreads by means of respiratory droplets and close contact with infected persons. With the progression of disease, numerous complications develop, particularly among persons with chronic illnesses. Pathological investigations indicate that it affects multiple organs and can induce acute respiratory distress syndrome. Prevention is vital and self-isolation is the best means of containing this virus. Good community health practices like maintaining sufficient distance from other people, wearing protective face masks and regular hand washing should be adopted. Convalescent plasma transfusion and the administration of the antiviral Remdesivir have been found to be effective. Vaccines offer lifesaving protecting against COVID-19 which has killed millions and our best bet for staying safe. Screening, suppression/containment as well as mitigation are the strategies implemented for controlling COVID-19 pandemic. Vaccination is essential to end the COVID-19 pandemic and everyone should have an access to them. The current COVID-19 pandemic brought the global economy to a standstill and has exacted an enormous human and financial toll.

The interconnection between independent reactive control policies drives the stringency of local containment

The lack of medical treatments and vaccines upon the arrival of the SARS-CoV-2 virus has made non-pharmaceutical interventions the best allies in safeguarding human lives in the face of the COVID-19 pandemic. Here we propose a self-organized epidemic model with multi-scale control policies that are relaxed or strengthened depending on the extent of the epidemic outbreak. We show that optimizing the balance between the effects of epidemic control and the associated socio-economic cost is strongly linked to the stringency of control measures. We also show that non-pharmaceutical interventions acting at different spatial scales, from creating social bubbles at the household level to constraining mobility between different cities, are strongly interrelated. We find that policy functionality changes for better or worse depending on network connectivity, meaning that some populations may allow for less restrictive measures than others if both have the same resources to respond to the evolving epidemic.

The Dynamic Impact of COVID-19 Pandemic on Stock Returns: A TVP-VAR-SV Estimation for G7 Countries

The COVID-19 pandemic has profoundly and negatively impacted the global stock markets. Hence, we investigated the time-varying impact of the COVID-19 pandemic on stock returns during the period from January 27, 2020 to December 23, 2021 using the TVP-VAR-SV model and used G7 countries as our research sample. Our results imply that (i) the spread of the COVID-19 pandemic has a significant negative impact on stock returns, but the impact decreases as the time window increases; (ii) the timeliness, compulsoriness, and effectiveness of anti-epidemic policies implemented by governments are the important adjustment factors for stock returns; (iii) the impact of the early stage of the COVID-19 pandemic on the stock market trend gradually weakens as the intermediate time interval increases. In addition, over time, the duration of the negative impact of the COVID-19 pandemic on the stock returns became shorter, and the recovery rate of the impact became faster; (iv) under the managed floating exchange rate regime, the stock returns changed synchronously with the pressures of exchange rate appreciation and depreciation, and under the free-floating exchange rate regime, the effect of the exchange rate on stock returns was almost zero, while the impact of exchange rate channels in eurozone countries was related to the characteristics of national economies. Thus, governments should make greater efforts to improve the compulsion and effectiveness of epidemic prevention policies and strengthen their control over exchange rate fluctuations to alleviate the negative impact of the COVID-19 pandemic on the stock markets.

COVID-19-Related Vaccine Hesitancy among Community Hospitals’ Healthcare Workers in Singapore

COVID-19 has culminated in widespread infections and increased deaths over the last 3 years. In addition, it has also resulted in collateral economic and geopolitical tensions. Vaccination remains one of the cornerstones in the fight against COVID-19. Vaccine hesitancy must be critically evaluated in individual countries to promote vaccine uptake. We describe a survey conducted in three Singapore community hospitals looking at healthcare workers’ vaccine hesitancy and the barriers for its uptake. The online anonymous survey was conducted from March to July 2021 on all staff across three community hospital sites in SingHealth Singapore. The questionnaire was developed following a scoping review and was pilot tested and finalized into a 58-item instrument capturing data on demographics, contextual features, knowledge, attitudes, perceptions, and other vaccine-related factors in the vaccine hesitancy matrix. Logistic regression analysis was employed for all co-variates that are significant in univariate analysis. The response rate was 23.9%, and the vaccine hesitancy prevalence was 48.5% in the initial phase of the pandemic. On logistic regression analysis, only being female, a younger age, not having had a loved one or friend infected with COVID-19 and obtaining information from newspapers were associated with vaccine hesitancy in healthcare workers in Singapore community hospitals.

Citrullination in the pathology of inflammatory and autoimmune disorders: recent advances and future perspectives

Numerous post-translational modifications (PTMs) govern the collective metabolism of a cell through altering the structure and functions of proteins. The action of the most prevalent PTMs, encompassing phosphorylation, methylation, acylations, ubiquitination and glycosylation is well documented. A less explored protein PTM, conversion of peptidylarginine to citrulline, is the subject of this review. The process of citrullination is catalysed by peptidylarginine deiminases (PADs), a family of conserved enzymes expressed in a variety of human tissues. Accumulating evidence suggest that citrullination plays a significant role in regulating cellular metabolism and gene expression by affecting a multitude of pathways and modulating the chromatin status. Here, we will discuss the biochemical nature of arginine citrullination, the enzymatic machinery behind it and also provide information on the pathological consequences of citrullination in the development of inflammatory diseases (rheumatoid arthritis, multiple sclerosis, psoriasis, systemic lupus erythematosus, periodontitis and COVID-19), cancer and thromboembolism. Finally, developments on inhibitors against protein citrullination and recent clinical trials providing a promising therapeutic approach to inflammatory disease by targeting citrullination are discussed.

Economic vulnerability assessment of EU countries to the impact of COVID-19 pandemic with the revised CEV index

The COVID-19 pandemic had a wide range of detrimental consequences for the global and national economies. It is vital to identify particularly susceptible areas to adopt effective strategies to alleviate the adverse effects of a pandemic. The objective of the paper is to assess the economic vulnerability of EU countries to the COVID-19 pandemic impact using the revised CEV Index. In the study, methods of multivariate statistics were used to analyse the effects of the pandemic. The revised CEVI replaces the 20-dimensional set of features with one aggregate measure, estimated for 27 EU Member States. According to the study, the economic vulnerability of EU countries to the COVID-19 pandemic varies significantly. The most vulnerable countries are in southern Europe, where the tourism sector plays a significant role in GDP composition. Highly susceptible are also Baltic countries: Latvia and Lithuania. The pandemic's harmful impact was the least seen in Germany and Scandinavian countries. The results of this study can be used as a tool for the formulation of policies aimed at overcoming the adverse consequences of economic vulnerability. The CEVI indicates certain areas in the country's economy that make it more fragile. Thus, it can play a significant role in the decision-making process. In the event of a pandemic shock, the CEVI, in combination with other tools, can be an effective instrument for improving the economy's resilience and helping it recover faster.

Responses against infectious disease pandemics: a narrative review on COVID-19

Currently, the world is facing the coronavirus disease 2019 (COVID-19) pandemic. With this, an emerging infectious disease pandemic in the absence of effective antiviral agents and vaccines for a novel virus is no different from the 1918 influenza pandemic, which became a great disaster for humankind. We also experienced a global lockdown with a stringent implementation of social distancing, which is a first for mankind living in the present day, and has led to enormous economic damage and restrictions on individual freedom. The microorganism that will cause the next pandemic may be a highly fatal avian influenza virus, another coronavirus, or a completely different microorganism. This COVID-19 pandemic is an enormous lesson for humankind and is tantamount to a vaccine in preparation for the next pandemic. Important and urgent undertakings were given to each country in terms of complementing laws and regulations for a stronger and more resilient healthcare system, such as investment in research and development for new rapid diagnostic technologies, vaccines, new therapeutic agents, among others.

Cryptocurrency as Epidemiologically Safe Means of Transactions: Diminishing Risk of SARS-CoV-2 Spread

In comparison with other respiratory viruses, the current COVID-19 pandemic’s rapid seizing the world can be attributed to indirect (contact) way of transmission of SARS-CoV-2 virus in addition to the regular airborne way. A significant part of indirect transmission is made through cash bank notes. SARS-CoV-2 remains on cash paper money for period around four times larger than influenza A virus and is absorbed by cash notes two and a half times more effectively than influenza A (our model). During the pandemic, cryptocurrencies have gained attractiveness as an “epidemiologically safe” means of transactions. On the basis of the authors’ gallop polls performed online with social networks users in 44 countries in 2020–2021 (the total number of clear responses after the set repair 32,115), around 14.7% of surveyed participants engaged in cryptocurrency-based transactions during the pandemic. This may be one of the reasons of significant rise of cryptocurrencies rates since mid-March 2020 till the end of 2021. The paper discusses the reasons for cryptocurrency attractiveness during the COVID-19 pandemic. Among them, there are fear of SARS-CoV-2 spread via cash contacts and the ability of the general population to mine cryptocurrencies. The article also provides a breakdown of the polled audience profile to determine the nationalities that have maximal level of trust to saving and transacting money as cryptocurrencies.

Stochastic actor-oriented modelling of the impact of COVID-19 on financial network evolution

The coronavirus disease 2019 (COVID-19) pandemic has led to tremendous loss of human life and has severe social and economic impacts worldwide. The spread of the disease has also caused dramatic uncertainty in financial markets, especially in the early stages of the pandemic. In this paper, we adopt the stochastic actor-oriented model (SAOM) to model dynamic/longitudinal financial networks with the covariates constructed from the network statistics of COVID-19 dynamic pandemic networks. Our findings provide evidence that the transmission risk of the COVID-19, measured in the transformed pandemic risk scores, is a main explanatory factor of financial network connectedness from March to May 2020. The pandemic statistics and transformed pandemic risk scores can give early signs of the intense connectedness of the financial markets in mid-March 2020. We can make use of the SAOM approach to predict possible financial contagion using pandemic network statistics and transformed pandemic risk scores of the COVID-19 and other pandemics.

The Misattributed and Silent Causes of Poor COVID-19 Outcomes Among Pregnant Women

Abundant evidence strongly suggests that the condition of pregnancy makes women and their fetuses highly vulnerable to severe Corona-virus 2019 (COVID-19) complications. Here, two novel hypoxia-related conditions are proposed to play a pivotal role in better understanding the relationship between COVID-19, pregnancy and poor health outcomes. The first condition, "misattributed dyspnea (shortness of breath)" refers to respiratory symptoms common to both advanced pregnancy and COVID-19, which are mistakenly perceived as related to the former rather than to the latter; as a result, pregnant women with this condition receive no medical attention until the disease is in an advanced stage. The second condition, "silent hypoxia", refers to abnormally low blood oxygen saturation levels in COVID-19 patients, which occur in the absence of typical respiratory distress symptoms, such as dyspnea, thereby also leading to delayed diagnosis and treatment. The delay in diagnosis and referral to treatment, due to either "misattributed dypsnea" or "silent hypoxia", may lead to rapid deterioration and poor health outcome to both the mothers and their fetuses. This is particularly valid among women during advanced stages of pregnancy as the altered respiratory features make the consequences of the disease more challenging to cope with. Studies have demonstrated the importance of monitoring blood oxygen saturation by pulse oximetry as a reliable predictor of disease severity and outcome among COVID-19 patients. We propose the use of home pulse oximetry during pregnancy as a diagnostic measure that, together with proper medical guidance, may allow early diagnosis of hypoxia and better health outcomes.

Covid-19 Economic Vulnerability Index: EU Evidence

The COVID-19 pandemic outbreak caused many negative effects on both the global and national economies. To implement effective policies to mitigate the negative impact of a pandemic, it is necessary to identify particularly vulnerable areas. The objective of this paper is to rank the EU countries in terms of the level of vulnerability of their economies to the impact of the pandemic. For this purpose, the COVID-19 Economic Vulnerability Index (CEVI) was constructed. It replaces the 15-dimensional set of characteristics of the countries with one aggregate, synthetic indicator estimated for 27 EU member states. In the study multivariate statistical methods, including agglomerative clustering and multi-attribute methods of object assessment were used to analyse the effects of the pandemic. The research shows that EU countries have different levels of economic vulnerability to the impact of the COVID-19 pandemic. The southern European countries (Spain, Croatia, Greece and Italy), where the tourism sector plays an important role in GDP composition, are the most fragile. Germany and the Scandinavian countries proved to be the least sensitive to the negative impact of the pandemic. The CEVI can be an important part of the decision support system. It enables the identification of countries that show greater vulnerability to the economic impact of the COVID-19 pandemic and may help support countries that need help the most. The proposed index also indicates certain areas in the country's economy that make it more vulnerable. The CEVI in combination with other instruments can be a very useful tool to improve the economy's resilience and help it recover faster in the event of a pandemic shock.

Influence of Mass Media on Italian Web Users During the COVID-19 Pandemic: Infodemiological Analysis

BACKGROUND

Concurrently with the COVID-19 pandemic, the world has been facing a growing infodemic, which has caused severe damage to economic and health systems and has often compromised the effectiveness of infection containment regulations. Although this infodemic has spread mainly through social media, there are numerous occasions on which mass media outlets have shared dangerous information, giving resonance to statements without a scientific basis. For these reasons, infoveillance and infodemiology methods are increasingly exploited to monitor information traffic on the web and make epidemiological predictions.

OBJECTIVE

The purpose of this paper is to estimate the impact of Italian mass media on users' web searches to understand the role of press and television channels in both the infodemic and the interest of Italian netizens in COVID-19.

METHODS

We collected the headlines published from January 2020 to March 2021 containing specific COVID-19-related keywords published on PubMed, Google, the Italian Ministry of Health website, and the most-read newspapers in Italy. We evaluated the percentages of infodemic terms on these platforms. Through Google Trends, we searched for cross-correlations between newspaper headlines and COVID-19-related web searches. Finally, we analyzed the web interest in infodemic content posted on YouTube.

RESULTS

During the first wave of COVID-19, the Italian press preferred to draw on infodemic terms (rate of adoption: 1.6%-6.3%) and moderately infodemic terms (rate of adoption: 88%-94%), while scientific sources favored the correct names (rate of adoption: 65%-88%). The correlational analysis showed that the press heavily influenced users in adopting terms to identify the novel coronavirus (cross-correlations of ≥0.74 to ≤0.89, P value <.001; maximum lag=1 day). The use of scientific denominations by the press reached acceptable values only during the third wave (approximately 80%, except for the television services Rai and Mediaset). Web queries about COVID-19 symptoms also appeared to be influenced by the press (best average correlation=0.92, P<.007). Furthermore, web users showed pronounced interest in YouTube videos of an infodemic nature. Finally, the press gave resonance to serious "fake news" on COVID-19, which caused pronounced spikes of interest from web users.

CONCLUSIONS

Our results suggest that the Italian mass media have played a decisive role in spreading the COVID-19 infodemic and addressing netizens' web interest, thus favoring the adoption of terms that are unsuitable for identifying COVID-19. Therefore, the directors of news channels and newspapers should be more cautious, and government dissemination agencies should exert more control over such news stories.

Influence of Mass Media on Italian Web Users During the COVID-19 Pandemic: Infodemiological Analysis

BACKGROUND

Concurrently with the COVID-19 pandemic, the world has been facing a growing infodemic, which has caused severe damage to economic and health systems and has often compromised the effectiveness of infection containment regulations. Although this infodemic has spread mainly through social media, there are numerous occasions on which mass media outlets have shared dangerous information, giving resonance to statements without a scientific basis. For these reasons, infoveillance and infodemiology methods are increasingly exploited to monitor information traffic on the web and make epidemiological predictions.

OBJECTIVE

The purpose of this paper is to estimate the impact of Italian mass media on users' web searches to understand the role of press and television channels in both the infodemic and the interest of Italian netizens in COVID-19.

METHODS

We collected the headlines published from January 2020 to March 2021 containing specific COVID-19-related keywords published on PubMed, Google, the Italian Ministry of Health website, and the most-read newspapers in Italy. We evaluated the percentages of infodemic terms on these platforms. Through Google Trends, we searched for cross-correlations between newspaper headlines and COVID-19-related web searches. Finally, we analyzed the web interest in infodemic content posted on YouTube.

RESULTS

During the first wave of COVID-19, the Italian press preferred to draw on infodemic terms (rate of adoption: 1.6%-6.3%) and moderately infodemic terms (rate of adoption: 88%-94%), while scientific sources favored the correct names (rate of adoption: 65%-88%). The correlational analysis showed that the press heavily influenced users in adopting terms to identify the novel coronavirus (cross-correlations of ≥0.74 to ≤0.89, P value <.001; maximum lag=1 day). The use of scientific denominations by the press reached acceptable values only during the third wave (approximately 80%, except for the television services Rai and Mediaset). Web queries about COVID-19 symptoms also appeared to be influenced by the press (best average correlation=0.92, P<.007). Furthermore, web users showed pronounced interest in YouTube videos of an infodemic nature. Finally, the press gave resonance to serious "fake news" on COVID-19, which caused pronounced spikes of interest from web users.

CONCLUSIONS

Our results suggest that the Italian mass media have played a decisive role in spreading the COVID-19 infodemic and addressing netizens' web interest, thus favoring the adoption of terms that are unsuitable for identifying COVID-19. Therefore, the directors of news channels and newspapers should be more cautious, and government dissemination agencies should exert more control over such news stories.

Identification of SARS-CoV-2 Main Protease Inhibitors Using Structure Based Virtual Screening and Molecular Dynamics Simulation of DrugBank Database

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is highly pathogenic to humans and has created an unprecedented global health care threat. Globally, intense efforts are going on to discover a vaccine or new drug molecules to control the COVID-19. However, till today, there is no effective therapeutics or treatment available for COVID-19. In this study, we aim to find out potential small molecule inhibitors for SARS-CoV-2 main protease (Mpro) from the known DrugBank database version 5.1.8. We applied structure-based virtual screening of the database containing 11875 numbers of drug candidates to identify potential hits for SARS-CoV-2 Mpro inhibitors. Seven potential inhibitors having admirable XP glide score ranging from -15.071 to -8.704 kcal/mol and good binding affinity with the active sites amino acids of Mpro were identified. The selected hits were further analyzed with 50 ns molecular dynamics (MD) simulation to examine the stability of protein-ligand complexes. The root mean square deviation and potential energy plot indicates the stability of the complexes during the 50 ns MD simulation. The MM-GBSA analysis also showed good binding energy of the selected hits (-83.2718 to -58.6618 kcal/mol). Further analysis revealed critical hydrogen bonds and hydrophobic interactions between compounds and the target protein. The compounds bind to biologically important regions of Mpro, indicating their potential to inhibit the functionality of this component.

The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators

The COVID-19 pandemic and induced economic and social constraints have significantly impacted the confidence of both consumers and businesses. Despite that, comprehensive studies of the impact of the COVID-19 pandemic on the consumer and business sentiment are still lacking. Thus, in our research we aim to identify consumer and business confidence indicators’ reaction to the spread of the COVID-19 pandemic in the Eurozone, the United States, and China. For this purpose, we used the method of correlation–regression analysis. We chose the consumer-confidence index, manufacturing purchasing manager’s index, and services purchasing manager’s index as dependent variables; and the number of confirmed cases of COVID-19, the number of deaths caused by COVID-19, and the mortality rate of COVID-19 infections as independent variables. The results showed a relatively rapid and robust effect of COVID-19 in the short period, but longer-term results depended on the region and were not so unambiguous: in the case of the Eurozone, the spread of COVID-19 pandemic did not affect the consumer-confidence index (CCI) or, in the cases of the United States and China, affected this index negatively; the purchasing managers’ index (PMI) in the services sector was significantly negatively affected by the mortality risk of COVID-19 infection; and the impact on the purchasing managers’ index (PMI) in the manufacturing industry appeared to be mixed.