Traditional vaccines are produced by using weakened or inactivated forms of disease-causing pathogens to produce the target antigen they are designed to protect against. Messenger RNA vaccines are a class of vaccines that employ a minute segment of genetic material, known as messenger RNA (mRNA), which contains directives for the cells in the body to generate a particular protein. This genetic material is synthesized in the laboratory and packaged into a lipid nanoparticle, which protects and helps it enter cells for further protein synthesis. During vaccination with mRNA vaccine, the lipid nanoparticles containing the mRNA are injected into the muscle of vaccinees. Once inside the cells, the mRNA instructs the cells to produce a protein which is then displayed on the surface of the cell, triggering an immune response. During this, the immune system recognizes the displayed protein as foreign and mounts a defense by producing antibodies and activating immune cells to target and eliminate the protein. Furthermore, these immune responses generate a memory cell, facilitating the immune system to promptly react in case of encountering the authentic pathogen as an infection in the future. The mRNA vaccines are flexible and the sequence can be easily synthesized in the lab based on the genetic information of the target pathogen. Additionally, mRNA vaccines can be developed for new strains or variants of the target disease easily. This was particularly evident during the COVID-19 pandemic, where mRNA vaccines like the Pfizer-BioNTech and Moderna vaccines were developed and authorized for emergency use within a year. But currently, available mRNA vaccines require extensive cold chain, antigen delivery, potential immune response variability optimization, and sophisticated manufacturing process. The efforts to explore next-generation mRNA vaccine development are aimed to further improve the effectiveness, stability, and delivery methods. One focus of research has been to enhance the stability of mRNA vaccines, particularly temperature sensitivity which makes storage and distribution easier, particularly in regions with limited access to cold chain infrastructure. Self-amplifying mRNA vaccines, on the other hand, are designed to generate multiple copies of the mRNA within cells which potentially leads to a higher production of the target protein, resulting in a stronger immune response. Additionally, studies are exploring new delivery systems to improve the target and efficiency of mRNA vaccines using specialized nanoparticles and liposomes to specifically deliver mRNA to certain cell types or immune cells. Another area of interest is the development of combination vaccines, where multiple mRNA sequences are included in a single vaccine protecting against multiple diseases targeting strains or variants of a particular pathogen simultaneously. While current mRNA vaccines are administered via intramuscular injection, studies are underway to deliver directly into the skin offering enhanced immune response and the ability to use smaller vaccine doses.

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with a high rate of mortality in kidney transplant recipients (KTRs). The current vaccine strategy for KTRs seems to be unable to provide effective protection against coronavirus disease 2019 (COVID-19) [2] and the occurrence of severe COVID-19 in some vaccinated KTRs suggested a lack of immunity. We analized here the antibody response in a group of 32 kidney transplant recipients (KTR) followed at the Nephrology and Dialysis unit of the Hospital Pio XI of Desio, Italy, compared with a group of 23 healthy workers classified as Late responders (HCW-LR) (10 males age 27-62) and 13 females (age 46-64). We observed that the patients need additional vaccine boosters due to their immunocompromised status and therapy to protect them from infections related to viral variants, in accordance with the literature.

The prediction of corticosteroid responses in coronavirus disease 2019 (COVID-19) patients is crucial in clinical practice, and exploring the role of artificial intelligence (AI)-assisted analysis of chest radiographs (CXR) is warranted. This retrospective case-control study involving hospitalized COVID-19 patients treated with corticosteroids was conducted from September 4th, 2021, to August 30th, 2022. The primary endpoint of the study was corticosteroid responsiveness, defined as the advancement of two or more of the eight-categories-ordinal scale. Serial abnormality scores for consolidation and pleural effusion on CXR were obtained using a commercial AI-based software based on days from onset of symptoms. Amongst the 258 participants included in the analysis, 147 (57%) were male. Multivariable logistic regression analysis revealed that high pleural effusion score at 6–9 days from onset of symptoms (adjusted odds ratio of [aOR]: 1.022, 95% confidence interval [CI]: 1.003-1.042, p=0.020) and consolidation scores up to 9 days from onset of symptoms (0-2 days: aOR: 1.025, 95% CI: 1.006-1.045, p=0.010; 3-5 days: aOR: 1.03 95% CI: 1.011-1.051, p=0.002; 6-9 days: aOR; 1.052, 95% CI: 1.015-1.089, p=0.005) were associated with an unfavorable corticosteroid response. AI-generated scores could help intervene in the use of corticosteroids in COVID-19 patients who would not benefit from them

Background: COVID-19 vaccines have been a game changer in the pandemic, their extensive use was favorable compared to the burden of COVID-19 complications. Despite the low incidence of complications, it was important to analyze them carefully to understand the underlying mechanisms and predisposing factors. For instance, myopericarditis especially from mRNA vaccines, and its relatively higher prevalence in young adults and adolescents has raised a public concern about the use of this vaccine in this group. We aimed through this review to compare the age likelihood of ADEM from COVID-19 vaccines, with that reported in myopericarditis cases; secondary outcome parameters included the gender and number of doses needed to induce COVID-19 vaccines related ADEM. Methodology: A literature search has been conducted on relevant databases to retrieve all case reports/series and systematic reviews describing ADEM with possible linkage to COVID-19. Exclusion criteria included any report not including the desired outcome parameters. Our results were then qualitatively compared with a similar systematic review reporting myopericarditis from COVID-19 vaccines. Results: In 38 cases with ADEM, mean age was 49±16 compared to 25±14 in myopericarditis, females were more likely to be affected, and while most of myopericarditis cases develop after the second dose, most of ADEM cases develop after the first dose (76%). Moreover, age>56 years was more predictive of negative outcome after ADEM in the form of death or permanent vegetative state. Conclusion: The discrepancy in age, gender and number of doses needed to induce complications between ADEM and myopericarditis, signify that the tissue affected is the major orchestrator of the age, gender, and dose characteristics, and not the type of vaccines. A leakier blood brain barrier with aging, might allow easier passage of autoantibodies and cytokines into the brain while lack of inhibitory immune checkpoints in the myocardium in young age might explain the higher prevalence of those cases in young adults and adolescents.

The occurrence of the COVID-19 pandemic has affected all aspects of our routine life. Here, we briefly reveal the less paid attention aspect, vocabulary. We extracted words from online news outlets during the first three months of the pandemic. The extracted words included many aspects, which we categorised into eight classes according to their functions and implications. We found out the top three dominant classes of vocabularies with the highest frequency compared to others, namely medical, economic and governance. The temporality in the pandemic timeline was vital in making sense of the predominant vocabulary. This paper is a rare preliminary report which provides a valuable insight into future articles with much more comprehensive data and analysis.

Vaccination has proven to be one of the most effective strategies against the COVID 19 pandemic. Several studies have evaluated and confirmed its effectiveness in different populations, particularly in reducing severe outcomes such as hospitalization and death. However, the potential of vaccination to protect against infection itself has been overlooked. The aim of this study was to determine the effectiveness of the booster dose in a sample of Colombian patients during the fourth wave of COVID-19 pandemic, which was associated with the emergence and predominance of the Omicron variant. A cross-sectional study was conducted on individuals who underwent RT-PCR testing for COVID-19 detection in a dedicated laboratory in Bogotá, Colombia, between December 30th 2021 and February 7th 2022. A total of 1,468 subjects were included in the study. The comparison between fully vaccinated individuals with a booster dose and those without the booster dose revealed a 28% reduction in the odds of infection (OR = 0.719 CI 0.531 - 0.971). Age (OR = 1,009 CI 1,001 - 1,018) and low economic status (OR= 1,812 CI 1,416- 2,319) were associated with an increased risk of infection.These findings suggest the need for booster vaccination in the general population to improve the prevention rates of SARS-CoV-2 infection and mitigate severe outcomes.

Background: The Covid-19 pandemic has globally impacted the lives of individuals, families, and children. In Italy, measures such as lockdowns and distance learning were implemented in schools, which affected the mental health of children and families. Methods: This article employs qualitative methodology to explore the experiences of children, parents, and teachers during the pandemic and lockdown, as well as the implementation of a death education project aimed at primary school children to help them process emotions and losses experienced during this period. Results: Distance learning posed challenges to the learning process and exacerbated social inequalities. Children suffered from limited social contact with friends and experienced negative emotions, including anger, fear, and concern for the health of their loved ones. The death education project provided a safe space for emotional expression and facilitated the acquisition of coping strategies. Open communication between adults and children about illness and death proved effective in mitigating the psychological impacts of loss and preventing traumatic bereavement. Conclusions: The findings highlight the utility of death education in enhancing children's ability to express their emotions and approach the topic of death morefrankly.

Background: The EFLM Task Force Preparation of Labs for Emergencies (TF-PLE) created a survey that has been distributed to its members for gathering information on the key hazards experienced by European medical laboratories during the COVID-19 pandemic. Methods: The survey was distributed to over 12,000 potential contacts (laboratory workers) via an EFLM newsletter, with responses collected between May 8 and June 8, 2023. Results: Two hundred replies were collected and examined from European laboratories. 69.7% and 78.1% of all responders said they were short on non-COVID and COVID reagents, respectively. Exactly half of respondents (50.0%) said that they could not complete all laboratory tests required for a specific period, but this figure climbed to 61.2% for COVID tests. Finally, 72.3% of respondents expressed exhaustion during the pandemic, and 61.2% reported increasing patient hostility. Conclusions: The COVID-19 pandemic had a significant impact on laboratory medicine in Europe. Cultural change, proactive planning, and even re-engineering in some parts of the laboratory industry may thus be necessary to prepare for future challenges.

Background: A growing number of studies have reported Coronavirus disease (COVID-19)-related to both respiratory and central nervous system dysfunctions. This study evaluates the neuromodulatory effects of spinal cord transcutaneous stimulation (scTS) on the respiratory functional state in healthy controls and patients with post-COVID-19 respiratory deficits as a step toward the development of a rehabilitation strategy for these patients.; Methods: In this before-after, interventional, case-controlled clinical study, ten individuals with post-acute COVID-19 respiratory deficits and eight healthy controls received a single twenty-minute-long session of modulated monophasic scTS delivered over the T5 and T10 spinal cord segments. Forced Vital Capacity (FVC), Peak Forced Inspiratory Flow (PIF), Peak Expiratory Flow (PEF), Time-To-Peak of Inspiratory Flow (tPIF), and Time-To-Peak of Expiratory Flow (tPEF) were assessed before and after the intervention; Results: In COVID-19 group, the scTS intervention led to significantly increased PIF (p= .040) and PEF (p= .049) in association with significantly decreased tPIF (p= .035) and tPEF (p= .013). In the Control Group, the exposure to scTS also resulted in significantly increased PIF (p= .010) and significantly decreased tPIF (p= .031). Unlike the results in COVID-19 group, there was significantly decreased PEF (p= .028) in association with significantly increased tPEF (p= .036). There were no changes for FVC after scTS in both groups (p= .67 and p= .503); Conclusions: In post-COVID-19 patients scTS facilitates excitation of both inspiratory and expiratory spinal neural networks leading to an immediate improvement of respiratory functional performance. This neuromodulation approach could be utilized in rehabilitation programs for patients with COVID-19 respiratory deficits.

Through the ACE2, a main enzyme of the renin-angiotensin system (RAS), the SARS-CoV2 gains access into the cell, resulting in different complications which may extend beyond the RAS and impact the Arachidonic Acid (ArA) pathway. The contribution of the RAS through ArA pathways metabolites in the pathogenesis of COVID-19 is unknown. We investigated whether RAS components and ArA metabolites can be considered biomarkers of COVID-19. We measured the plasma levels of RAS and ArA metabolites using an LC-MS/MS. Results indicate that Ang1-7 levels were significantly lower, whereas Ang II levels were higher in the COVID-19 patients than healthy control individuals. The ratio of Ang1-7/Ang II as an indicator of the RAS classical and protective arms balance was dramatically lower in COVID-19 patients. There was no significant increase in inflammatory 19-HETE and 20-HETE lev-els. The concentration of EETs was significantly increased in COVID-19 patients, whereas the DHETs concentration was repressed. Their plasma levels were correlated with Ang II concentration in COVID-19 patients. In conclusion, evaluating the RAS and ArA pathway biomarkers could provide helpful information for the early detection of high-risk groups, avoid delayed medical attention, facilitate resource allocation and improve patient clinical outcomes to prevent long COVID incidence.

The unprecedented COVID-19 pandemic posed major challenges to local, regional, and global economies and health systems, and fast clinical diagnostic workflows were urgently needed to contain the spread of SARS-CoV-2. Here, we describe the platform and workflow established at the Cornell COVID-19 Testing Laboratory (CCTL) for high-throughput testing of clinical samples from the university and the surrounding community. This workflow enabled efficient and rapid detection, and successful control of SARS-CoV-2 infection on campus and its surrounding communities. Our cost-effective and fully automated workflow enabled testing of over 8,000 pooled samples per day and provided results for over 2 million samples. Automation of time- and effort-intensive sample processing steps such as accessioning and pooling increased laboratory efficiency. Customized software applications were developed to track and store samples, deconvolute positive pools, track and report results and for workflow integration from sample receipt to result reporting. Additionally, quality control dashboards and turn-around time tracking applications were built to monitor assay and laboratory performance. As infectious disease outbreaks pose a constant threat to both human and animal health, the highly effective workflow implemented at CCTL could be modeled to establish regional high-capacity testing hubs for infectious disease preparedness and emergency response.

The challenge of accessing finance by entrepreneurs from traditional financial sources is pervasive. The COVID-19 pandemic further exacerbated the problem of limited access to finance from banks. Against this backdrop, the objective of the study was to determine the factors driving crowdfunding success during the COVID-19 pandemic in Africa. The ordinary least squares (OLS) and probit regression models were estimated to analyse 216 crowdfunding projects in Africa. The results of the study documented that targeted amount (TA), and COVID-19 pandemic were negative and significant drivers of crowdfunding success. Furthermore, comments (CMM) and duration (DRN) were negative and significantly affected crowdfunding success. Conversely, images (IM), videos (VD), backers (BCK), and updates (UPD) were positive and significantly affected crowdfunding success. The study contributes to the body knowledge by investigating the drivers of crowdfunding success during the COVID-19 pandemic period which hitherto had not been researched on extenisvely.

During the Covid 19 pandemic, we saw a huge impact on the lives of individuals in cities. The way people responded was controlled and limited. The lockdown restricted a lot of movements in the cities as well as contained the citizens in their houses. Through a semi-structured interview, the research aims to understand the change in behaviour and response of individuals across various cities. The paper aims to understand how people change their day-to-day life in cities during the pandemic and while the restrictions getting released post the first wave. The paper also understands how the pandemic impacted urban spaces and what value they hold for people. By interviewing individuals from different cities, the data were transcribed and analysed to understand this behavioural change and the attitude of people. The outcome of the research was derived as a concept map through the codes generated during the research.

The COVID-19 pandemic has affected millions of people globally, with respiratory organs being strongly affected in individuals with comorbidities. Medical imaging-based diagnosis and prognosis have become increasingly popular in clinical settings to detect COVID-19 lung infections. Among various medical imaging modalities, ultrasound stands out as low-cost, mobile, and radiation-safe imaging technology. In this comprehensive review, we focus on ultrasound-based AI studies for COVID-19 detection that use public or private lung ultrasound datasets. We surveyed articles that used publicly available lung ultrasound datasets for COVID-19 and reviewed publicly available datasets and organize ultrasound-based AI studies per dataset. We analyzed and tabulated studies in several dimensions, such as data preprocessing, AI models, cross-validation, and evaluation criteria. In total, we reviewed 42 articles, where 28 articles used public datasets, and the rest used private data. Our findings suggest that ultrasound-based AI studies for the detection of COVID-19 have great potential for clinical use, especially for children and pregnant women. Our review also provides a useful summary for future researchers and clinicians who may be interested in the field.

The years 2019 to 2022 are being marked by the pandemic resulting from a viral infection, COVID-19. The demand and use of PPE has never been so high and it is often discarded without considering the correct disposal route and the environmental impact that this type and volume of waste can generate. The aim of this study was to analyze the increased demand for PPE used during the pandemic and, consequently, the generation of these wastes. In addition to this analysis, it is extremely important to raise the discussion about the treatment of these residues and the possibilities of more ecological personal protection equipment, such as biodegradable or reusable ones. The extensive use of PPE, which is mostly plastics and is not easily degraded, mainly leads to its accumulation in landfills but, if disposed of incorrectly, it could reach marine environments, contributing to the formation of microplastics in the oceans. Therefore, this article also aims to relate these themes to the Sustainable Development Goals, as efficient management aligned with sustainable development goals is essential to mitigate these anticipated problems and ensure a more sustainable future.

Vaccine hesitancy remains a public health challenge. It has been argued that the sources of vaccine-related information may serve as important condiments to one’s decision to be vaccinated. However, little empirical attention is given to the subject. We contribute to this debate by assessing the level of COVID-19 vaccine hesitancy and the role of information explaining hesitancy, using the Nelson Mandela Bay Municipality of South Africa as a case study. Findings confirm high level of vaccine hesitancy, representing 78.8 percent of the respondents (which is above the national level of 41%). Furthermore, findings reveal that vaccination decisions are influenced by family, which is the most trusted among all institutions in the society, especially on sensitive matters and those shrouded by myths and misinformation. Additionally, the majority trusts health care workers and mass media as sources of health-related and general information; however, the use of popular personalities to convey health information is not supported. The findings reveal key socio-demographic and institutional drivers of COVD-9 vaccine hesitancy, such as age, inadequate information on the vaccine, trust issues, conspiracy beliefs, vaccine-related factors, and perceived side effects associated with the vaccine. Recommendations based on the findings are provided.

The phenomenon of vaccine hesitancy is a growing threat to public health with far-reaching implications. The widening gap between the vaccinated and the proportion needed for herd immunity raises two critical research questions that are of interest to practitioners, researchers, and policymakers: (1) What determines one’s decision to be vaccinated? and (2) What is the implication of COVID-19 vaccine hesitancy on economic recovery? In this study, we use empirical data in the context of South Africa to investigate factors affecting COVID-19 vaccine hesitancy and their implications for economic recovery. Findings reveal key socio-demographic and institutional drivers of COVD-9 vaccine hesitancy, which include age (the youth are more hesitant), inadequate information on the vaccine (those who perceive they have adequate information are vaccinated), trust issues in government institutions, conspiracy beliefs, vaccine-related factors, and perceived side effects associated with the vaccine. Additionally, an individual’s decision to remain hesitant about COVID-19 vaccination has implications for businesses and the economy by limiting movement and trade, increasing unemployment, and causing a resurgence of new variants. Based on the findings, action plans such as information dissemination, convenience vaccination centers, consistency communications, and targeted campaign strategies are recommended for improving vaccine intakes and a positive economic recovery.

Introduction. Covid-19 faced the world with serious health and socioeconomic issues. At the very beginning of the pandemics, the vaccine was considered by health authorities and the medical community the only way to curb the spread of the virus. One of the measures that have been proposed to increase vaccinations was the mandatory policy. The purpose of this study was to compare determinants of voluntary and mandatory vaccination among students of Albanian University. Methodology: This cross-sectional study by means of an online survey, was conducted among students enrolled in the private University “Albanian University”, Tirana, Albania during the last week of winter semester 7-14 Feb 2022. Results: 878 students participated in this study, among them 612 (69.7%) were females, 266 (30%) were males. 506 (57%) of the participants were enrolled in Medical Sciences (MS), 372(42.3%) were Non-Medical Science (Non-MS) group. 773 (88%) was vaccinated against Covid-19, 105 (11.8%) were not vaccinated. 466 (53%) reported voluntary vaccination, 412 (46.9%) reported mandatory vaccination. Among students that vaccinated voluntary 266 (57%) were from MS group, 200(42.9%) from Non-MS group. 237(57.5%) of students in mandatory vaccination group were from MS group, 175 (42.4%) from Non-MS. Conlusion. Vaccine safety and efficacy were hindering factors of vaccination. Also, based on the results of this study, the students felt encouraged to vaccinate by the academic staff. This clearly demonstrates that the staff does not lack the skills to enhance stu-dents' knowledge about the risk of infectious diseases and the importance of vaccination. Therefore, to influence as much as possible students’ attitude toward vaccination, comprehensive educational programs including modification of existing curricula should be considered.

Vaccination is the key infection control measure against Coronavirus Disease 2019 (COVID-19). Most municipalities in Japan have adopted an opt-in system for COVID-19 vaccination, but its background information is limited. We, therefore, aimed to examine the differences in vaccination coverages and their cancellation rates between opt-in and opt-out settings for COVID-19 vaccination in 10 cities in A prefecture, Japan. 10 cities in A Prefecture were surveyed by email as of 10 October 2021 on the vaccination coverage by age group (12 years and older) and the cancellation rate on the day of vaccination. We also checked on the complaints received in the opt-out group. Opt-out was adopted in one of the ten cities in which vaccination was designed for all household members aged 15-64, thus serving as the opt-out group. Vaccination coverage in the opt-out group was 88.2%-89.2% for the first dose and 84.9%-86.0% for the second dose at 95% confidence intervals in the comparable 20–64-year age group. In contrast, the overall opt-in group (nine cities, one of which did not have an identified vaccination rate) was 51.3%-83.6% for the first dose and 63.5%-74.8% for the second dose in the same age group. For the opt-out group, the cancellation rate on the day was 11.3% for the first dose and 3.7% for the second dose, which had a lower cancellation rate than that of the opt-out on influenza vaccines in previous studies, 71%. Meanwhile, the opt-in group did not monitor them. There were no complaints about default changes in the opt-out group. While there is room for further research, such as understanding the reasons for accepting the default change by residents in the opt-out group, it was suggested that making opt-out the default would promote COVID-19 vaccination.

The global COVID-19 pandemic has affected all spheres of human life, resulting in millions of deaths and overwhelming medical facilities. Moreover, the world has witnessed great financial hardship because of job losses resulting in economic havoc. Many sections of society have contributed in different ways to slow the spread of the virus and protect public health. For example, medical scientists are praised for their efforts to develop COVID-19 vaccines. Clinical trials have shown that the COVID-19 vaccines are highly effective in preventing symptomatic COVID-19 infections. However, many people around the world have been hesitant to get vaccinated. Vaccine misconceptions have emerged and increased due to a combination of factors, including the availability of information on the Internet and the influence of celebrities and opinion leaders. In this context, we have analyzed ChatGPT responses to relevant queries on vaccine misconceptions. The positive responses and supportive opinions provided by the AI chatbot could be instrumental in shaping people’s perceptions of vaccines and in encouraging users to get vaccinated and reduce misconceptions.

Background. The main impetus behind the worldwide Covid-19 vaccination campaign in 2021 was to reduce the mortality attributed to SARS-CoV-2 infection in the preceding year. Nevertheless, rigorous analyses of the mortality benefits conferred by this massive vaccination effort have been lacking. Methods Statistics offers us an essential methodological approach for measuring the impacts of Covid-19 vaccination on public health. The mathematical relation between vaccinated-alive groups can be repeated between vaccinated-dead groups with relatively high statistical reliability because of the large population numbers involved. This method also confers greater statistical usefulness because it eliminates the Simpson effect. Results Calculations were performed for each of the following five(5) four-week intervals: weeks 35-38 (2021), weeks 39-42 (2021), weeks 43-46 (2021), weeks 47-50 (2021), and weeks 50(2021)-1(2022). The results obtained confirm that the mortality of the vaccinated coronavirus-infected groups was 14.5% higher on average than the mortality of non-vaccinated coronavirus-infected groups. Conclusions Vaccinated infected groups appear to have higher average mortality than their non-vaccinated infected counterparts. The findings suggest the legitimacy of extending the statistics between vaccinated living and vaccinated dead individuals for different age groups. Calculating the impact of Covid-19 vaccination on the mortality rate is a necessary step towards satisfying the first principle of medicine: “Primum non nocere”, “Do no harm”.

Vaccination against SARS-CoV-2 has significantly contributed to the recent pandemic control. COVID-19 vaccines are available with different platforms and the primary clinical trials results presented acceptable safety profile of the approved vaccines. Nevertheless, the long-term assessment of the adverse events or rare conditions need to be investigated. The present systematic review, aimed at classification of Iranian case reports following COVID-19 immunization. To achieve this goal, the related published case reports were explored via PubMed, Web of Science and Google scholar according to PRISMA guideline and available up to 14th Dec, 2022. Out of 437 explored studies, the relevant data were fully investigated which totally led to 40 studies including 64 case reports with a new onset of a problem. The cases were then classified according to the various items such as the type of adverse event manifestations and COVID-19 vaccine. The reported COVID-19 vaccines in the studied cases included Sinopharm, AstraZeneca, and COVAXIN. The results showed that the adverse events presented in 8 different categories from which cutaneous problems accounted as the most prevalent manifestations (43.7%) in which rare diseases were also screened such as Steven-Johnson syndrome, Morphea and Toxic Epidermal Necrolysis. Notably, almost 60% of the cases had no comorbidities. Moreover, the obtained data revealed nearly half of the incidences occurred after the first dose of injection and the mean duration of improvement after the symptom onset was 18.72±24.69 days. 73% of all the cases were either significantly improved or fully recovered. Although the advantages of COVID-19 vaccination is undoubtedly significant, the high risk individuals including those with a history of serious disease or comorbidities immunodeficiency conditions should be vaccinated with the utmost caution.

The Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) first emerged in 2019 in China and has resulted in millions of human morbidities and mortalities across the globe. It has been shown that this novel virus originated in animals, mutated, and made the cross-species jump to humans. At the time of this communication, the Coronavirus disease (COVID-19) may be on way to an endemic form, however the threat of the virus is more for susceptible (older people and immunocompromised) people. The human body has more bacterial cells than its own, thus making us more bacterial than humans. As a consequence, the bacteriomes in the human body heavily influence human health and disease. The bacteriomes in the body and the immune system seem to be in constant association during bacterial and viral infections. In this review, we identify various bacterial spp. in major bacteriomes (oral, nasal, lung, and gut) of the body in healthy humans and compare them with dysbiotic bacteriomes of COVID-19 patients. We try to identify key bacterial spp. that have a positive effect on the functionality of the immune system and human health. These select bacterial spp. could be used as potential probiotics to counter or prevent COVID-19 infections. In addition, we try to identify key metabolites produced by probiotic bacterial spp. that could have potential anti-viral effects against SARS-CoV-2. These metabolites could be subject to future therapeutic trials to determine their anti-viral efficacy.

Cardiac complications of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been well-identified since the beginning of the current coronavirus disease 2019 (COVID-19) pandemic. Such conditions can occur of various etiologies, such as respiratory failure and hypoxemia, direct cardiac tissue damage due to viral replication, indirect myocarditis as systemic inflammation, and the interaction of different medications. Recently, with the start of the COVID-19 vaccination programs, COVID-19 vaccine-associated cardiac adverse events (AEs) have emerged and are increasingly being reported. Although these AEs are usually mild and self-limited, they can sometimes cause severe, catastrophic outcomes. This review compares the pathophysiology, diagnosis, and treatment of the de novo SARS-CoV-2 infection-related and COVID-19 vaccine-related myocarditis and pericarditis.

SMEs constitute the backbone of the Syrian economy which have suffered manifold challenges due to the continuous Syrian war. Covid-19 added further pressures on Syrian SMEs and force them to take certain adaptation strategies to survive. This paper aims to investigate the main challenges that face Syrian SMEs during the pandemic and illustrate how they respond to adversities emerged from governmental intervention to control the spread of the virus. It also discusses the measures initiated by the government to support SMEs during the pandemic. Through interviewing persons from the Syrian SMEs ecosystem, we find that high interest rates on SMEs loans, decline on demand as well as high inflation represent the main challenges. SMEs respond to these challenges by marketing products online, stock procurement, and strengthen connections with stakeholders. We recommend the Syrian authorities reduce lending rates and increase loan size available to SMEs to help them overcome the pandemic adversities. Moreover, SMEs will immensely benefit from training on digital tools to enhance their expansion and survival opportunities. Furthermore, bazars should be organized around the year to give SMEs the opportunity to gain continuous access to markets. In addition, incubation services should be revised, particularly, to SMEs with great potential to grow to create the suitable environment for them to scale and flourish.

While vaccines are a well-established method of controlling the spread of infectious diseases, vaccine hesitancy jeopardizes curbing the spread of COVID-19. Through the Vaccine Information Network (VIN), this study explored barriers and motivators to COVID-19 vaccine uptake. We conducted 18 focus group discussions with male and female community members, stratified by country, age group, and—for Zimbabwe only—by HIV status. Participants’ median age across both countries was 40 years (interquartile range of 22–40) and most (65.9%) were female. We conceptualized the key themes within the World Health Organization’s Strategic Advisory Group of Experts on Immunization (SAGE) 3Cs (convenience, confidence, complacency) vaccine hesitancy model. Barriers to vaccine uptake—lack of convenience, low confidence, and high complacency—included inaccessibility of vaccines and vaccination sites, vaccine safety and development concerns, and disbelief in COVID-19’s existence. Motivators to vaccine uptake—convenience, confidence and low complacency—included accessibility of vaccination sites, user-friendly registration processes, trust in governments and vaccines, fear of dying from COVID-19 and knowing someone who had died or become infected with COVID-19. Overall, vaccine hesitancy in South Africa and Zimbabwe was influenced by inconvenience, a lack of confidence, and high complacency around COVID-19 vaccines.

The outbreak of Coronavirus, as well as its emerging potential consequences, has become a global challenge worldwide, demanding effective and controlled therapeutic strategies. Potential drug candidates could achieve that with minimal toxicity. The current investigation selected 2-Deoxy-D-glucose prescribed by Defense Research and Development Organization (DRDO), India. The derivative and modified form was tested through in silico analysis against COVID-19 main protease complex with N3 inhibitor. The derived form of 2-Deoxy-D-glucose was generated by replacing the hydroxy group with a hydrogen atom, and Cypate 2-Deoxy-D-glucose was chosen as a derivative against the COVID-19 main protease complex. A molecular docking approach was adopted to identify the stable and competent form among the modified and derivative forms of 2-Deoxy-D-glucose based on binding energy. By further promoting the stabilized complex, these compounds' toxicity was also scrutinized through ADMET analysis to predict the potential candidate. The current investigation suggested that the modified version of 2-Deoxy-D-glucose was more stable with minimal toxicity against COVID-19 main protease.

Mint and to a lesser extent menthol have been used since antiquity for medicinal purposes. Key components of mint and menthol use such as composition and intake, safety and traditional uses are discussed prior to a review of clinical and human performance outcomes in the areas of digestive and respiratory health; antibacterial and anti-fungal properties, nocioception, migraine and headache and emerging evidence regarding COVID 19. Evidence suggests benefit for patients with irritable bowel syndrome and related digestive issues, with analgesic and respiratory effects also noted. Perceptual characteristics relating to thermal comfort and sensation, taste sensitivity and alertness are also considered; these effects are predominantly driven by stimulation of transient receptor potential melastatin 8 (TRPM8) activity resulting in sensations of cooling and freshness, with lesser influence on thirst. Finally, sport performance is considered as a domain that may further elucidate some of the aforementioned underpinning outcomes due to its systemic and dynamic nature, especially when performed in hot environmental conditions.

Given that population COVID-19 vaccination does not appreciably reduce SARS-CoV-2 transmission, instead, the potential to reduce hospitalization has been used to justify coercive vaccine passports. We aim to use a recently published research study as an example in order to demonstrate how data can be misinterpreted and result in deriving misleading ethical and policy implications. Bagshaw et al wrote that unvaccinated patients with COVID-19 in Alberta, Canada “had substantially greater rates of ICU admissions, ICU bed days, and ICU related costs than vaccinated patients did. This increased resource use would have been potentially avoidable had these unvaccinated patients been vaccinated.” The authors in Bagshaw et al then concluded that their findings “have important implications for discourse on the relative balance of increasingly stringent public health protection (restrictions), including mandatory vaccination policies, and the sustainability and function of health system infrastructure and capacity during the ongoing COVID-19 pandemic.” Here we show the following. First, the effect of vaccination on intensive care admissions were grossly over-estimated due to several limitations of this and almost all other vaccine studies. Second, an effect of vaccination on access to acute care and on all-cause excess deaths was grossly over-stated due to several more likely causes being omitted from discussion and from the common narrative. Third, policy implications were overstated and at best unclear due to missing consideration of more relevant aspects required to inform policy. Overall, the data cannot support what Bagshaw et al called “increasingly stringent public health protection (restrictions), including mandatory vaccination policies”.

Background Several vaccines have been approved for prevention of the coronavirus disease discovered on 31st December in Wuhan, China. Pakistan procured vaccines from various countries. However, the lack of knowledge and reluctance of the general population to embrace the use of the vaccines are considered to be the major determinants of the slow vaccination rate. Hence, it is necessary to evaluate the willingness of the general population about their perception of the COVID-19 vaccination. Methods A cross sectional survey based on a self-structured questionnaire comprising 18 questions was conducted (from April 21-June 21) on 400 Pakistani participants to evaluate their knowledge, attitude and perception towards the COVID-19 vaccination. Chi-square independent t-test and one-way Anova including a multiple step wise linear regression were used to draw conclusions about the results. P< 0.05 was considered significant. Results A total of 400 participants responded in the KAP survey of which 46.5% were female and 53.5% were male. The mean age of participants was 36.08 years. This survey showed a poor knowledge (50.5%), a fair attitude (75.1%) and a poor perception (58.1%) towards the COVID-19 vaccination. Higher mean knowledge and attitude scores was reported in the age group 21-40, females and unmarried urban citizens. Regression analysis showed that age, education, residence and employment status influenced the knowledge and perception score to a considerable extent. Conclusions The findings reflect an inadequate knowledge and perception on the one hand but a better attitude towards the COVID-19 vaccination. This KAP survey will help in better understanding the opinion of the general population towards vaccination and will be useful for policy makers and health care authorities aiming to increase the vaccination rate.

A large body of research has examined people’s attitudes toward mandatory vaccination to cope with the COVID-19 pandemic. However, studies have yet to explore how Chinese people view the COVID-19 vaccine mandates, let alone placing such views in the country’s highly politicized context. On the other hand, facing the high pressure of loosening its zero-COVID policies amidst the worldwide practices of co-existing with the COVID-19 virus, the country has to improve its vaccination coverage quickly. In this situation, it is more than necessary to systematically investigate the Chinese public’s attitude to mandatory vaccination against the virus and the underlying determinants. The current study utilizes data from a national survey adopting quota sampling to analyze the Chinese public’s medical and non-medical considerations when judging compulsory COVID-19 vaccination. The study reveals that thanks to China’s successful lockdown policies, personal risk, and benefit perceptions did not dominate their views regarding vaccination mandates. Instead, conspiracy beliefs regarding the pandemic outbreaks, conspiratorial thinking, and nationalism more strongly predicted their willingness to accept mandatory vaccination. Given the potentially massive impacts of the COVID-19 infection, if China opens its door and loosens its strict quarantine restrictions, the Chinese public needs to be educated with more medically valuable and relevant information to improve their vaccination protection against COVID-19.

Recycling and waste management have garnered immense popularity in recent years, but few studies have been carried out regarding these systems. Therefore, an in-depth literature review was done in order to highlight the different sectors of the recycling system that need to be reformed. Hence this study examined recycling and waste management systems within three categories–medical, municipal, and plastic–that were carried out pre and post COVID by reviewing previous studies, technical reports, and annual reports. This was done by visiting numerous academic search engines alongside online resources that were utilized to assemble literature related to waste and recycling systems. Continuing a recurring idea was that no matter the type of waste, further research regarding all waste should be carried out. Additionally, since recycling and waste management are a vital part of our society, and seeing how unpredictable events such as the pandemic may be, it is paramount that that research is done not only on how the pandemic has affected systems now, but also how we can learn from current issues to utilize them for future “waste shocks”.

Objectives: To analyze cumulative incidence and mortality by COVID-19 in the different types of nursing homes, in the first and second wave.Methods: Data source: Transparency portal of the Generalitat de Catalunya, official COVID-19 register of all Catalan nursing homes (from March to December 10, 2020). Variables: Affectation of disease and mortality by COVID-19 in geriatric centers in Catalonia, stratified by size of center and type of management. Univariate, bivariate and multivariate linear regression analysis, IBM^TMSPSS^® v.20.Results:N = 1,057 residences (63,682 beds, average = 60.48). 52% have <50 beds, 42.8% between 50-150 beds, and 5%> 150 beds. COVID-19: Cumulative incidence: 21,370 (confirmed + suspicious); mortality: 5,010 (confirmed + suspicious).233 residences did not register COVID-19 patients (22%) and 636 did not register COVID-19 deaths (60.2%).According to the type of supplier, the lowest incidence of COVID-19 was in non-accredited (36.2% without cases), then concerted / collaborators (19.3%) and own of the Generalitat de Catalunya (7.9 %, p = 0.000). The centers with the fewest deaths were the non-accredited (78% without deaths), followed by contracted / collaborators (56.8%) and those of the Generalitat de Catalunya (41.3%, p = 0.000).Depending on the size, no COVID-19 patients were registered: 168 centers <50 beds (30.5%); 64 of the 50-150 beds (14.2%); and 1 of the> 150 beds (1.9%) (p = 0.000). 395 of the <50 beds did not register deaths due to COVID-19 (71.8%), 232 of the 50-150 beds (51.3%), and 9 of the> 150 beds (17%) (p = 0.000).Discussion:Of the 1,057 centers analyzed, 22% did not register cases and in 60% there were no deaths from COVID-19.Residences without concert / collaboration with the Generalitat and with fewer beds showed a lower cumulative incidence and mortality due to COVID-19 during the first wave.

Abstract Introduction There is a clear link between self-medication practice and ongoing pandemic diseases like COVID-19, According to studies conducted globally and the general Ethiopian population turned to self-medication and symptomatic treatment as a result of inadequate COVID-19 treatment and also about 80% of the population amassed drugs for pandemic use. Objective: The objective of this study was to assess self-medication practice for treatment of Covid-19 and reason to use self- medication among residents in Bedelle city and its surrounding, Southwest Oromia, Ethiopia. Methodology: A cross sectional study design was employed and the standardized questionnaire was developed by reviewing relevant literatures then the data was collected using face to face interview. Final data was analyzed by using SPSS version 23. Result: The final study contained 415 respondents in total, with a response rate of 98.5%. The majority of responses were females and between the ages of 18 - 25 Category. In this study population, the use of self-medication since the onset of the Covid-19 epidemic was reported by participants were around 50.6%. Analgesics (42.4%) and cold medicines (29.5%) were the most frequently used medications for treatment of COVID-19. Also the reported uses of these drugs included treatment of Covid-19 symptoms like the Headache (22.2%), Fever (13.2%), respiratory infective (14.3%), and cold (21.4%) were the most frequently reported symptoms for self-medication. Self-medication methods were used more frequently by women than Men. Conclusion: According to this study, analgesics and cold medications are commonly self- medicated drugs used for Covid-19 therapy. It is a serious health concern, particularly when COVID-19 symptoms are present, and high consumption of self-medication has been linked to COVID-19 prevention or treatment. Key words: Covid-19, Medicine, Practice, Bedelle city, Self-Medication

Background: Medical comorbidities increase the risk of severe COVID-19 infection. In some studies, obstructive sleep apnea (OSA) has been identified as a comorbid condition that is associated with an increased prevalence of COVID-19 infection and hospitalization, but few have investigated this association in a general population. Research Question: In a general population, is OSA associated with increased odds of COVID-19 infection and hospitalization and are these altered with COVID-19 vaccination? Study Design: Cross-sectional survey of a diverse sample of 15,057 U.S. adults Results: COVID-19 infection and hospitalization rates were 38.9% and 2.9% respectively. OSA or OSA symptoms were reported in 19.4%. In logistic regression models adjusted for demographic, socio-economic and comorbid medical conditions, OSA was positively associated with COVID-19 infection (aOR: 1.58, 95%CI: 1.39-1.79) and COVID-19 hospitalization (aOR: 1.55, 95% CI: 1.17-2.05). In fully adjusted models, boosted vaccination status was protective against both infection and hospitalization. Boosted vaccination status attenuated the association between OSA and COVID-19 related hospitalization, but not infection. Participants with untreated or symptomatic OSA were at greater risk for COVID-19 infection; those with untreated, but not symptomatic OSA were more likely to be hospitalized. Interpretation: In a general population sample, OSA is associated with a greater likelihood of having had a COVID-19 infection and a COVID-19 hospitalization with the greatest impact observed among persons experiencing OSA symptoms or who were untreated for their OSA. Boosted vaccination status attenuated the association between OSA and COVID-19 related hospitalization.

Pineapple is a highly demanded fruit in international markets, thanks to its unique appearance and flavor, high fiber content, vitamins, folic acid, and minerals. It makes the pineapple production and processing market a significant source of income for producing countries, such as Costa Rica. Nowadays, its processing produces a large amount of waste with negative consequences for the environment. However, pineapple waste is an essential source of cellulose, hemicellulose, lignin, and other high-value products like enzymes (bromelain). These by-products can be obtained by pineapple waste biorefinery, generating an additional source of export goods and foreign currency, framing pineapple processing in the concept of the circular economy. This review discusses how incorporating biorefinery in the pineapple production processes can contribute to the post-COVID 19 economy in Costa Rica. Pineapple production in Costa Rica is explored, and the contamination of generated residues is delineated. Furthermore, the primary processes for by-product extraction via biorefinery, their general characteristics and applications in the medical field, and their contribution to the circular economy are presented.

The repurposing of licenced drugs for use against COVID-19 is one of the most rapid ways to develop new and alternative therapeutic options to manage the ongoing pandemic. Given the approximately 8,000 licenced compounds available from Compounds Australia that can be screened, this paper demonstrates the utility of commercially-available ex vivo/3D airway and alveolar tissue models. These models are a closer representation of in vivo studies compared to in vitro models, but retain the benefits of rapid in vitro screening for drug efficacy. We demonstrate that several existing drugs appear to show anti-SARS-CoV-2 activity against both Delta and Omicron Variants of Concern in the airway model. In particular, fluvoxamine, as well as aprepitant, everolimus, and sirolimus have virus reduction efficacy comparable to the current standard of care (remdesivir, molnupiravir, nirmatrelvir). Whilst these results are encouraging, further testing and efficacy studies are required before clinical use can be considered.

Background: Covid-19 patients with any pre-existing cardio-vascular disease (CVD) are at highest risk for viral infection and for developing of severe disease. Pathophysiological mechanism is characterized by the viral link to Angioten-sin-Converting Enzyme 2 (ACE2) and the involvement of the endothelial system with the release of cytokines and direct damage on myocardium, micro throm-bosis, and alterations of oxygen diffusion. Aim of the study is to analyze clinical course, treatment and outcome in patients (gender stratified) with pre-existing CVD. Methods: Out of the 1299 (700 M/599 F) patients admitted to Internal Medicine COVID Unit of “Castelli Hospital”, Lazio, Italy, from 01/01/2021 to 31/12/2021, 278 patients (167 M/111 F), mean age 76 (76 M/ 75 F) had previous CVD. Demographic characteristics, length of the stay (LOS) and oxygen therapy were evaluated. Results: Most common CVD pathologies were Hearth Failure (HF): 131 (72 M/59 F), Atrial Fibrillation (AF): 45 (25 M/20 F), Myocardial Infarction (MI): 26 (19 M/7 F) and associations among them. 100% of CVD COVID patients under-went Non-Invasive Ventilation (NIV) and were treated with more than 5 drugs. HF was linked with increased LOS (23 days) compared to AF (21 days), MI (18 days) and no CVD (16 days). Overall mean LOS was 16,5 days. 21,4% of total pa-tients had CVD. Conclusions: Timely identification and evaluation of patients with pre-existing CVD are fundamental for adequate treatment based on gender, severity and state of illness and for risk reduction. Keywords: polypharmacy, gender medicine; COVID 19; Sars CoV 2; cardiovas-cular disease.

Background: This study describes the attitudes and practices of Brazilian adults regarding the mandatory vaccination for COVID-19 and the hesitancy to children´s vaccination. Methods: The participants answered an online questionnaire disseminated on social networks. An adaptation of the SAGE-WG questionnaire was used to measure the children's vaccination hesitancy. Results: Among 1,007 participants, 677 (67.4%) believed that vaccination for COVID-19 among adults should be mandatory. Just over half of the participants (51.5%) believe that parents and guardians should be free to decide whether their children should be vaccinated against COVID-19, and 9.1% were unsure about this. Younger, non-religious people who have higher self-perceptions of risk for COVID-19, and who evaluate the federal government's performance in combating the disease as bad or very bad, have a higher agreement with mandatory vaccination, a lower agreement that parents and guardians should be free to vaccinate their children, and lower child vaccination hesitancy scores. Conclusion: In Brazil, mandatory COVID-19 vaccination for adults is far from a consensus, and an expressive part of the population believes that parents and guardians should be free to choose whether or not to vaccinate their children. These perceptions and vaccine hesitancy for children are associated with religious and political inclinations.

(1) Background: When the Omicron variant of SARS-CoV-2 first emerged in Germany in January 2022, data on related disease severity among children and adolescents was not yet available. Given Omicron’s high transmissibility, the ability to assess its impact on admission and hospitalization rates in children’s hospitals is critical for the purpose of understanding the scope of its burden on the German health care system. (2) Methods: From January 24, 2022 to July 31, 2022, SARS-CoV-2 cases admitted to German pediatric hospitals were monitored via a national, clinician-led reporting system (CLRS) established by the German Society for Pediatric Infectious Diseases (DGPI). Cases treated on general wards and intensive care units, as well as patient age and need for respiratory support were recorded. (3) Results: From January to July 2022, a median of 1.7 cases (range 0.4–3) per reporting pediatric hospital per day were hospitalized on general wards, whereas a median of 0.1 cases (range 0–0.4 cases) were on intensive care units. Of all hospitalized patients, 4.2% received respiratory support. (4) Conclusions: Despite the high incidence rates documented in connection with the Omicron variant in early 2022, the number of pediatric hospital admissions, and especially the number of cases with need for intensive care treatment and respiratory support due to a symptomatic SARS-CoV-2 infection, remained relatively low. Higher Omicron incidence rates had only a modest impact on SARS-CoV-2-related admissions and hospitalization in German children’s hospitals.

Purpose: The study aimed to investigate if there were any links between liver function biomarkers and immunoglobulins levels in serum, and Toll-like receptors (TLRs) and neuropilin-1 (NRP1) in COVID-19 patients. The study also aimed to assess the accuracy—sensitivity, specificity, and area under the curve (AUC) by the receiver operator curve (ROC) analysis for immunoglobulins levels and TLRs expressions. Patients and Methods: This study included 150 patients (100 patients with confirmed COVID-19 and 50 healthy volunteers as a control group). Patients with COVID-19 were subdivided into two groups according to the severity of symptoms (moderate and severe, with 50 patients each). Serum C-reactive protein (CRP), alanine aminotransaminase (ALT), aspartate aminotransaminase (AST), albumin, lactate dehydrogenase (LDH), immunoglobulin (Ig) G, and IgM levels were estimated. TLRs (TLR2 and TLR4) and NRP1 gene expression in blood samples were investigated using quantitative real-time polymerase chain reaction (qRT-PCR). ROC analysis was also applied to determine the accuracy of various detected parameters in predicting the possibility of COVID-19 infection. Results: In COVID-19 patients, serum parameters related to liver function, except serum albumin, CRP, IgG, IgM, and TLR2, TLR4, and NRP1 mRNA expression levels, significantly elevated compared to controls. Severe COVID-19 patients exhibited significantly higher liver enzymes (ALT, AST and LDH), CRP, and TLR2 mRNA expression levels and lower albumin levels than the moderate group. In the moderate and severe groups, ALT, CRP, TLR2, and TLR4 had a significant positive correlation with IgM levels. ALT, AST, LDH, CRP, TLR2, and TLR4 showed a significant positive correlation with IgG levels in both groups. In both the moderate and severe groups, NRP1 expression was found to be significantly correlated with CRP, IgG, IgM, TLR2, and TLR4. In contrast, serum albumin levels exhibited a significant negative correlation with IgG and IgM levels only in the severe group, but they showed a significant negative correlation with TLR2, TLR4, and NRP1 expression in both moderate and severe groups. Serum ALT and AST activities were positively correlated with NRP1 expression in the moderate group but not in the severe group and as well as TLR2 and TLR4 expression in both the moderate and severe groups. ROC analysis indicated that AUC was higher than 0.800 for serum IgM level and TLR4 gene expression in moderate COVID-19 group. Conclusions: The increased liver function biomarkers in serum and NRP1 expression are closely correlated with sustained activations in humoral and innate immune responses during COVID-19 infection. As a result, TLR2, TLR4, and NRP1 could be targets for limiting COVID-19 infection and impairment effects on liver function. Moreover, detection of IgM level in serum and TLR4 expression in blood have a good accuracy in predicting the possibility of infection with COVID-19 in moderate cases.

Background: Coronavirus disease 2019 (COVID-19) remains a mystery in many respects. The importance of less common life-threatening diseases is still unclear. Therefore, in this study, it was attempted to determine the frequency of nontraumatic hemothorax, chylothorax, pleural, and pericardial effusion (PCE) in patients who underwent thoracic computed tomography during the pre-pandemic and pandemic period. Materials and Methods: This retrospective study included 147 patients over the age of 18 who were admitted to the emergency department between January 1st, 2019, and December 31st, 2020. The year 2019 was taken as the pre-pandemic period and the year 2020 was the pandemic period. Comorbidity, survival, and laboratory parameters of the patients were evaluated. Results: The mean age of the 147 patients included in the study was 66.41 ± 12.81 years, 54 (36.7%) were female, and the age range was 22–88 years. The mean plasma lactate dehydrogenase (LDH) level of the patients was 373.97 ± 115.77 U/L, plasma protein was 5.45 ± 1.00 gr/dL, fluid LDH was 229.37 ± 125.73 U/L, fluid/plasma LDH was 0.60 ± 0.23, fluid/plasma protein was 0.55 ± 0.29, and the amount of fluid discharged was 562.11 ± 243.01 mL. Bilateral lung involvement was present in 72 (49%) patients, and coagulation use was present in 59 (40.1%) patients. Pleural effusion (PE) was found in 43 (76.8%) of the hospitalized patients, hemothorax in 11 (19.6%) patients, and chylothorax in 4 (7.1%) patients. However, PCE was more common in the 16 (42.1%) patients admitted to the intensive care unit (ICU) (P < 0.001). While 38 (25.9%) of the patients were admitted to the ICU, mortality was observed in 30 (20.4%) patients. Conclusion: Although PE, nontraumatic hemothorax, chylothorax, and PCE are rare in COVID-19 patients, they can cause severe inflammation and poor prognosis.

We determined the levels of neutralizing antibodies against the SARS-CoV-2 ancestral strain, Delta and Omicron variants of concern (VOCs) in 125 healthcare workers, who received Coro-naVac as their primary vaccination and later received either a single ChAdOx1 or a combination of two consecutive boosters using either two ChAdOx1 doses or a ChAdOx1 or BNT162b2 as the primary and second boosters, respectively, or 2 doses of BNT162b2. The titers 12 weeks after primary vaccination were inadequate to neutralize the all strains. After a single ChAdOx1 boost-er, the levels of neutralization at Day 30 varied significantly, only a small proportion of partici-pants developing neutralizing titers against Omicron at Day 7 and 30. The two doses of ChA-dOx1 as the booster induced lowest activity. A combination ChAdOx1 and BNT162b2 induced greater neutralization than by two doses of ChAdOx1. Two doses of BNT162b2 as the booster had the maximal activity against Omicron VOC.

The COVID-19 is an exponentially growing disease that has intentioned nations to use technologies to detect the coronavirus infection. Several nations are working greatly to fight against COVID-19. Many nations have been using a range of devices to combat the pandemic, seeking information about growth, monitoring as well as the leaking the confidential information of the residents. This research aims to assist infected people online using the Internet of Things (IoT) and Blockchain technologies through smart devices. IoT-based healthcare devices gather useful information, provide additional insight through symptoms and behaviors, allow remote monitoring, and simply give people better self - determination and healthcare. Blockchain allows the secure transfer of patient health information, regulates the medical distribution network. A four-layer architecture is proposed using IoT and Blockchain to detect and prevent individuals to be COVID 19. This research provides a framework for patients with COVID-19 infectious disease and recognizes health issues and diagnoses online. Smart devices such as smartphones can install any mobile apps such as Aarogya Setu, Tawakkalna, and so on. These applications can track COVID-19 patients properly. The installation of mobile apps on smart devices focuses to reduce the time and cost and increase the performance of the infectious patient's condition. A four-layer architecture is proposed using IoT and Blockchain technologies. Many research works focus on investigating, analyzing, and highlighting the affected individuals through guiding the COVID-19 infection. Eventually, various mobile apps are recognized and addressed in this paper.

The COVID-19 pandemic has highlighted the vitalness of telehealth in our medical world, where considering a restructuring of healthcare services has become paramount. In fact, telemedicine has recently earned a valuable place in many specialties; and its implications in cardiology and cardiovascular medicine were among the leading interests. In this letter, we gathered previous evidence supporting the merit of telemedicine in the fields of cardiology and cardiovascular medicine—medical branches in which patients require meticulous care and continuous monitoring—as well as protrusions of concerns about the uncertainty regarding the efficacy of telemedicine’s future implications and technologies. In sum, in the context of this still on-going pandemic, medical institutions must strive to improve telehealth technologies and implement solid future research directions in this growing field—to be able to persevere in meeting the needs of the patients. As long as no conclusive evidence exists regarding the fields where telemedicine is most worthwhile, healthcare systems will always keep the dread of wasting resources on developing ineffective programs. We conclude that telemedicine has been attributed a considerable attention in managing cardiac and cardiovascular conditions; nevertheless, further studies with solid designs are still needed to confirm its validity and utility in those specialties.

The new SARS-CoV-2 coronavirus has brought with it an increase in the use of digital platforms and an exponential increase in the number of scientific papers worldwide. The purpose of this study is to show a global overview of the digital transformation from 1975 to the present (2021). The main collection of the Web of Science database was used to retrieve global scientific production on digital transformation. Bibliometric indicators of production, visibility, impact, and collaboration were analyzed to assess research progress on the topic. The results show that digital transformation is a construct of recent development, increasingly relevant and transdisciplinary, with a clear growth after the declaration of the global COVID-19 pandemic.

During the COVID-19 pandemic, WIC increased the Cash Value Benefit (CVB) for fruits and vegetables by roughly $25/month/person. We sought to understand WIC participant perceptions of this change and barriers and facilitators to using the CVB. We conducted 10 virtual focus groups (5 rural, 5 urban/suburban) with WIC participants (n=55) in North Carolina in March 2022. Focus groups were recorded and transcribed. We open coded the content and used thematic analysis to uncover consistencies within and between sampled groups. Participants expressed favorable perceptions of the CVB increase and stated the pre-pandemic CVB amount was insufficient. Barriers to using the increased CVB were identifying WIC approved fruits and vegetables in stores and insufficient supply of fruits and vegetables. Barriers were more pronounced in rural groups. CVB use facilitators were existing household preferences for fruits and vegetables and the variety of products that can be purchased with the CVB relative to other components of the WIC food package. Participants felt the CVB increase allowed their families to eat a wider variety of fruits and vegetables. The CVB increase may improve fruit and vegetable intake, particularly if made permanent, but barriers to CVB and WIC benefit use may be limiting the potential impact.

The development of inexpensive, fast and reliable screening tests for COVID-19 is, as yet, an unmet need. The present study was aimed at evaluating the usefulness of serum arylesterase activity of paraoxonase-1 (PON1) measurement as a screening test in patients with different severity levels of COVID-19 infection. We included 615 COVID-19 positive patients who were classified as asymptomatic, mildly symptomatic, severely symptomatic, or fatally symptomatic. Results were compared with 50 healthy volunteers, 330 patients with cancer and 343 with morbid obesity. Results showed PON1 activity greatly decreased in COVID-19 compared to healthy vol-unteers; receiver operating characteristics plot showed a high diagnostic accuracy. The degree of COVID-19 severity did not influence PON1 levels. Our results indicated that PON1 determination was efficient for disease diagnosis but not for prognosis. Further, patients with obesity or cancer presented alterations similar to those of COVID-19 patients. As such, elevated levels of PON1 in-dicate the absence of COVID-19, but low levels may be present in various other chronic diseases. The assay is fast and inexpensive. We suggest that PON1 measurement could be used as an initial, high cut-off point screening method, while lower values should be confirmed with the more ex-pensive nucleic acid amplification test.

Cardiovascular diseases (CVD´s) continue as the primary cause of death worldwide. During the past couple of years, and with the surge of the COVID-19 pandemic, deaths linked to CVD´s were -slightly overshadowed by those deaths related to COVID-19, albeit during the highest peaks of the pandemic. The present study derived form understanding the correlation between both diseases, from the standpoint of patients already diagnosed with CVD´s (n = 41883) and what comorbidities had the highest influence on overall patient death (n = 3637). Obesity, hypertension, and diabetes are all linked to worsening the outcome of COVID-19 positive patients, hence they were considered when looking at the overview of all CVD positive patients. Our finding showed that 1697 deaths were related to diabetes (p < 0.001), 987 deaths were related to obesity (p < 0.001), and lastly 2499 deaths were attributed to hypertension (p < 0.001) individually. Using logistic regression modeling, we found diabetes (OR: 1.744, p < 0.001) and hypertension (OR: 2.179, p < 0.001) had a high impact on patient deaths. Hence, having a CVD diagnosis, with hypertension and/or diabetes seems to increase the likely-hood of complication leading to death in COVID-19 positive patients.

COVID-19 outbreak started in the Chinese city of Wuhan and spread around the globe in months due to its high contagious level. Hence, this disease posed a great challenge to researchers and mathematicians. Numerous mathematical models have been suggested to visualize the spreading speed and trends of this pandemic. In this paper, a comparison of a widely established and accepted method, the Susceptible-Exposed-Infected-Quarantined-Recovered-Death-Insusceptible (SEIQRDP) model with a newly-proposed fractional-order SEIQRDP is studied. Densely populated Countries of Asia (Pakistan, India, and Bangladesh) have been chosen as data sets and both algorithms have been applied to their data. The same comparison technique has also been used on the data of two polar countries, New Zealand and Russia, that validated our findings. Error comparison of both algorithms has been recorded in a tabulated form which shows multi-fold erroneous trends over WHO data of selected countries.

The Covid-19 pandemic and the initial focus on handwashing measures have again highlighted the importance of water access as an essential service in protecting human health. Yet, especially in southern cities, uneven geographies of water access – often mediated by fragmented and unequal infrastructure systems – may hamper the fight against infectious diseases. The spread of SARS-CoV-2 presented a dilemma for water providers as well as residents in water-deprived urban areas as they had to adhere to new hygiene standards and requirements, despite limited access to basic water infrastructure. Therefore, a deeper understanding of pandemic urban waterscapes – the infrastructure and governance systems as well as everyday practices and technologies – is necessary for ongoing debates on (post-) pandemic or zoonotic cities. In our paper, we focus on changes in urban (water) governance and government water projects in Nairobi since early 2020. We show that Covid-19 has contributed to changes in Nairobi’s waterscape but only in conjunction with recent changes in the city’s overall governance structure. However, if these waterscape changes lead to greater equity in water access, and if they have helped to curb the spread of SARS-CoV-2, is more than questionable.

The COVID-19 pandemic has put a lot of pressure on health systems worldwide. Mass vaccination against SARS-CoV-2 has reduced morbidity and mortality worldwide. Despite their safety profiles, vaccines like any other medical product can cause adverse events. Yet, in countries with poor epidemiological surveillance and monitoring systems, reporting vaccine-related adverse events is scarce. The objective of this study was to describe self-reported vaccine adverse events after receiving one of the available COVID-19 vaccine schemes in Ecuador. A cross-sectional analysis based on an online self-reporting 32-questionnaire was conducted in Ecuador from April 1st to July 15th, 2021. Participants were invited by social media, radio, and TV to voluntarily participate in our study. A total of 6,654 participants were included in this study. A 38.2% of the participants reported having at least one comorbidity. Patients received AstraZeneca, Pfizer, and Sinovac vaccines, and these were distributed 38.4%, 31.1%, and 30.5%, respectively. Pain, inflammation at the injection site (20,01%), and headache (16,91%) were the most reported adverse events. Women addressed ESAVIs (64%), more often than men (36%). After receiving the first dose of any available COVID-19 vaccine, a total of 19,481 self-reported ESAVIs were informed (86.9% were mild, 11.6% moderate and 1.5% severe). In terms of vaccine type and brand, the most reactogenic vaccine was AstraZeneca with 57.8%, followed by Pfizer (24.9%) and Sinovac (17, 3 %). After the second dose, 6,757 self-reported ESAVIs were reported (87.0% mild, 10.9% moderate, and 2.1% severe). AstraZeneca vaccine users reported a higher proportion of ESAVIs (72.2%) in comparison to Pfizer/BioNTech (15.9%) and Sinovac Vaccine (11.9%). Swelling at the injection site, headache, muscle pain, and fatigue were the most common ESAVIs for the first as well as second dose. In conclusion, most ESAVIs were mild. AstraZeneca users were more likely to report adverse events. Participants without a history of COVID-19 infection, as well as those who receive the first dose, were more prone to report ESAVIs.

This study aims to comparatively analyse the importance and performance of the health of Korean and Japanese adolescents during the prolonged coronavirus disease 2019 (COVID-19) pandemic. Data were collected from 1,341 sampled Korean and Japanese adolescents in September 2021 through online and offline surveys. The collected data were analysed with frequency analysis, reliability testing, t-test, and importance-performance analysis (IPA). The following results were obtained. First, adolescents in the two countries perceive various factors about health as important during the COVID-19 pandemic, but their performance is weak compared to their perceived importance. Second, Korean adolescents had greater perceived importance for all factors of health perception compared to their Japanese counterparts. Third, the difference in performance between Korean and Japanese adolescents was especially evident for ‘hygiene management’, and there were significant differences in performance in ‘disease management’ and ‘physical activity’. Fourth, in quadrant 4 of the IPA matrix, there were similarities and differences in a particular factor of health perception between Korean and Japanese adolescents. Based on these results, we proposed measures to emphasise the importance of health and enhance performance among Korean and Japanese adolescents.

The urgency of the COVID19 pandemic caused a surge in related scientific literature. This surge made the manual exploration of scientific articles time-consuming and inefficient. Therefore, a range of exploratory search applications have been created to facilitate access to the available literature. In this survey, we give a short description of certain efforts in this direction and explore the different approaches that they used.

Nowadays, the presence of pathogen-specific antibodies in the blood is widely controlled by a serodiagnostic technique based on the lateral flow immunoassay (LFIA). However, its common one-stage format with an antigen immobilized in the binding zone of a test strip and a nanodis-persed label conjugated with immunoglobulin-binding proteins is associated with risks of very low analytical signals. It is caused by the presence of non-specific immunoglobulins in very large excess to the target antibodies in the tested samples thus decreasing their binding with the detected labels. In this study, the first stage of the immunochromatographic serodiagnosis was carried out in its traditional format using a conjugate of gold nanoparticles with staphylococcal immunoglobulin-binding protein A and an antigen immobilized on a working membrane. At the second stage, a labeled immunoglobulin-binding protein was added, which enhanced the coloration of the bound immune complexes. The use of two separated steps, binding of specific antibodies, and further coloration of the formed complexes allowed a significant reducing the influence of non-specific immunoglobulins on the assay results. The proposed approach was ap-plied for the serodiagnosis using a recombinant RBD protein of SARS-CoV-2. As a result, an in-crease in the intensity of test zone coloration by more than two orders of magnitude was demonstrated, which enabled to significantly reduce false-negative results. When testing a panel of 16 positive and 8 negative serum samples, the diagnostic sensitivity of the LFIA was 62.5% for the common format and 100% for the enhanced format; the diagnostic specificity of both variants was 100%.

Pineapple is a highly demanded fruit in international markets, thanks to its unique appearance and flavor, high fiber content, vitamins, folic acid, and minerals. It makes the pineapple production and processing market a significant source of income for producing countries, such as Costa Rica. Nowadays, its processing produces a large amount of waste with negative consequences for the environment. However, pineapple waste is an essential source of cellulose, hemicellulose, lignin, and other high-value products like enzymes (bromelain). These by-products can be obtained by pineapple waste biorefinery, generating an additional source of export goods and foreign currency, framing pineapple processing in the concept of the circular economy. This review discusses how incorporating biorefinery in the pineapple production processes can contribute to the post-COVID 19 economy in Costa Rica. Pineapple production in Costa Rica is explored, and the contamination of generated residues is delineated. Furthermore, the primary processes for by-product extraction via biorefinery, their general characteristics and applications in the medical field, and their contribution to the circular economy are presented.

Background: In the span of just two years, tracking the COVID-19 pandemic through wastewater surveillance has advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field. Objectives: We examine the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition of early monitoring efforts to more formalized programs within the public health system. Discussion: Wastewater surveillance has rapidly developed as a public health tool Clinical testing programs are ramping down and home testing is on the rise, making wastewater monitoring important for future surveillance of COVID-19. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and organizational challenges and draw useful lessons. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should continue and should promote knowledge co-development. While wastewater surveillance has demonstrated utility for tracking COVID-19, there remain technical challenges and open scientific questions that researchers are equipped to address, which will contribute to building robust surveillance programs that provide public health practitioners with new insights into population health.

The purpose of this study was to explore the role of moral distress on physician burnout during COVID-19. Physicians in the US were interviewed between February and March 2021; 479 responded to our survey. Results indicated that moral distress was a key mediator in explaining the relationship between perceived organizational support, medical specialization, emotional labor, and coping on burnout. There was no support for increased burnout among female physicians, and contracting COVID-19 likewise did not play a role in burnout. Our findings suggest that physician burnout can be mitigated by increasing perceived organizational support; likewise, physicians who engaged in deep emotional labor and problem-focused coping tended to fare better when it came to feelings of moral distress and subsequent burnout.

The COVID-19 pandemic has highlighted the adverse consequences created by an infodemic specifically on compliance with public health guidance and vaccine uptake. COVID-19 vaccine hesitancy is a complex construct that is related to health beliefs, misinformation exposure, and perceptions of governmental institutions. This study draws on theoretical models and current data on the COVID-19 infodemic to explore the association between perceived risk of COVID-19, levels of misinformation endorsement, and opinions about the government response on vaccine uptake. We surveyed a sample of 2,697 respondents from the US, Canada, and Italy using a mobile platform between 21-28 May, 2021. Using multivariate regression, we found that country of residence, risk perception of contracting and spreading COVID-19, perception of government response and transparency, and misinformation endorsement was associated with the odds of vaccine hesitancy. Higher perceived risk was associated with lower odds of hesitancy, while lower perceptions of government response, and higher misinformation endorsement were associated with higher hesitancy.

The COVID-19 pandemic is the biggest public health threat facing the globe today. Multiple vaccines have been approved, however the emergence of viral variants such as the recent Omicron, raises the possibility of booster doses to achieve adequate protection. In Brazil, the CoronaVac (Sinovac) vaccine was used, however it’s important to assess the immune response to this vaccine over time. This study aimed to monitor the anti-SARS-CoV-2 antibody responses in those immunized with CoronaVac and SARS-CoV-2 infected individuals. Samples were collected between August 2020 and August 2021. Within the vaccinated cohort, some individuals had history of infection by SARS-CoV-2 prior to immunization and others not. We analyzed RBD-specific and neutralizing- antibodies. Anti-RBD antibodies were detected in both cohorts, with a peak between 45-90 days post infection or vaccination, followed by a steady decline over time. In those with previous history of COVID-19, a higher, longer, more persistent response was observed. This trend was mirrored in the neutralization assays, where infection followed by immunization resulted in higher, longer lasting responses which were conditioned on the presence of levels of RBD antibodies right before the vaccination. This supports the necessity of booster doses of CoronaVac in due course to prevent serious disease.

After the first weeks of vaccination against the SARS-CoV-2, several cases of acute thrombosis were reported. These news reports began to be shared frequently across social media platforms. The aim of this study was to conduct an analysis of Twitter data related to the overall discussion. Data was retrieved from 14th March to 14th April using the keyword ‘blood clots’. A dataset with n=266,677 tweets was retrieved, and a systematic random sample of 5% of tweets (n=13,334) were entered into NodeXL for further analysis. Social network analysis was used to analyse the data by drawing upon the Clauset-Newman-Moore algorithm. Influential users were identified by drawing upon the betweenness centrality metric. Text analysis was applied to identify the key hashtags and websites used at this time. More than half of the network was comprised of retweets and the largest groups within the network were broadcast clusters where a number of key users were retweeted. The most popular narratives were around highlighting the low risk of obtaining a blood clot from a vaccine and highlighting higher blood clot risks in medicines commonly consumed. A wide-variety of actors drove the discussion on Twitter ranging from writers, physicians, the general public academics, celebrities, and journalists. Twitter was used to highlight the low potential of obtaining a blood clot from a vaccine and encouraged vaccinations among the public.

COVID-19 has a severe risk of spreading rapidly, the quick identification of which is essential. In this regard, chest radiology images have proven to be a practical screening approach for COVID-19 affected patients. This study proposes a deep learning-based approach using Densenet-121 to detect COVID-19 patients effectively. We have trained and tested our model on the COVIDx dataset and performed both 2-class and 3-class classification, achieving 96.49% and 93.71% accuracy, respectively. By successfully utilizing transfer learning, we achieve comparable performance to the state-of-the-art method while using 15x fewer model parameters. Moreover, we performed an interpretability analysis using Grad-CAM to highlight the most significant image regions at test time. Finally, we developed a website that takes chest radiology images as input and detects the presence of COVID-19 or pneumonia and a heatmap highlighting the infected regions. Source code for reproducing results and model weights are available.

Covid-19 has caused infections and deaths worldwide. While research in the field of Data Science has contributed good predictions of positive Covid-19 case numbers, this study's review of literature shows there is little research in the use of variants of the virus in predictions. We set out to define and evaluate novel variant features. We find that features relating to variant trends, thresholds and amino acid substitutions are especially powerful in two tasks. In the first task, predicting Covid-19 case numbers, accuracy improved from 71.53% without variant features to 82.12% with variant features. In the second task, predicting transmission severity of variants between two classes, we created a method to build some variable ensembles through selecting appropriate models that are generated with variant features. The test results showed that our ensembles are more accurate and reliable. One particular ensemble of 14 models correctly classified 90.91% of variants, outperforming other models including the popular Random Forest ensemble. In addition, as the variant features have represented more underlying information about Covid-19 pathophysiology, our ensemble methods use only a few data samples to achieve an accurate prediction. The ensemble of 14 models uses only 50 cases of each variant, an ability that could be exploited for early detection of highly infectious variants. These research findings may benefit public health professionals, policy makers, and the research community in the collective efforts to overcome this disease.

The Physics Informed Neural Networks framework is applied to the understanding of the dynamics of Coronavirus of 2019. To provide the governing system of equations used by the framework, the Susceptible-Infected-Recovered-Death mathematical model is used. The study focused on finding the patterns of the dynamics of the disease which involves predicting the infection rate, recovery rate and death rate; thus predicting the active infections, total recovered, susceptible and deceased at any required time. The study used data that was collected on the dynamics of COVID-19 from the Kingdom of Eswatini between March 2020 and September 2021. The obtained results showed less errors thus making highly accurate predictions.

In response to the COVID-19 pandemic, social distancing measures were put into place to flatten the pandemic curve. It was projected older adults were at increased risk for poor psychological and health outcomes resulting from increased social isolation and loneliness. However, little re-search has supported this projection among community-dwelling older adults. While growing body of research has examined the impact of the COVID-19 pandemic on older adults, there is a paucity of qualitative research that captures the lived experience of community-dwelling older adults. The current study aimed to better understand the lived experience of community-dwelling older adults during the first six months of the pandemic. Semi-structured one on one interviews were conducting with independent living older adults aged 65 years and older. After achieving saturation, 22 interview were analyzed using inductive thematic analysis. Following a recursive process, two overarching themes emerged from the data: perceived threat and challenges of the pandemic and coping with the pandemic. Specifically, participants reflected on the threat of contracting the virus and challenges associated with living arrangement, social isolation, and financial insecurity. Participants shared their coping strategies to maintain health and wellbeing, including behavioral strategies, emotion-focused strategies, and social support. Overall, this re-search highlights resilience among older adults during the first six months of the pandemic.

Pre-COVID-19, doodling was identified as a measure of burnout in researchers attending a weekly, in-person health narratives research group manifesting team mindfulness. Under the group’s supportive conditions, variations in doodling served to measure change in participants’ reported depression and anxiety—internal states directly associated with burnout, adversely affecting healthcare researchers, their employment, and their research. COVID-19 demanded social distancing during the group’s 2020/21 academic meetings. Conducted online, the group’s participants who chose to doodle did so alone during the pandemic. Whether the sequestering of group participants during COVID-19 altered the ability of doodling to act as a measure of depression and anxiety was investigated. Participants considered doodling during the group’s online meetings increased their enjoyment and attention level—some expressed it helped them to relax. However, unlike face-to-face meetings during previous non-COVID-19 years, solitary doodling during online meetings was unable to reflect researchers’ depression or anxiety. COVID-19 limitations necessitating doodling alone maintained the benefits group members saw in doodling but hampered the ability of doodling to act as a measure of burnout in contrast to previous in-person doodling. This result is seen to correspond to one aspect of the group’s change in team mindfulness resulting from COVID-19 constraints.

The Dark Web is known as a place triggering a variety of criminal activities. Anonymization techniques enable illegal operations, leading to the loss of confidential information and its further use as bait, a trade product or even a crime tool. Despite technical progress, there is still not enough awareness of the Dark Web and its secret activity. In this study, we introduced the Dark Web Enhanced Analysis (DWEA), in order to analyze and gather information about the content accessed on the Dark Net based on data characteristics. The research was performed to identify how the Dark Web has been influenced by recent global events, such as the COVID-19 epidemic. The research included the usage of a crawler, which scans the network and collects data for further analysis with machine learning. The result of this work determines the influence of the COVID-19 epidemic on the Dark Net.

COVID-19 has been extremely difficult to control. The lack of understanding of key aspects of pandemics has affected virus transmission. On the other hand, there is a demand to incorporate Computational Thinking (CT) in the curricula with applications in STEM. However, there are still no exemplars in the curriculum that apply CT to real-world problems such as controlling a pandemic or other similar global crises. In this paper, we fill this gap by proposing exemplars of CT for modeling the pandemic. We designed exemplars following the three pillars of the APEC InMside framework for CT: algorithmic thinking, computational modeling, and machine learning. For each pillar, we designed a progressive sequence of activities that covers from elementary to high school. In an experimental study with elementary and middle school students from 2 schools of high vulnerability, we found that the computational modeling exemplar can be implemented by teachers and correctly understood by students. We conclude that it is feasible to introduce the exemplars at all grade levels, and that this is a powerful example of STEM integration that helps reflect and tackle real-world and challenging public health problems of great impact for students and their families.

Several recent surges in COVID-19 cases due to newly emerging variant strains of SARS-CoV-2 with greater transmissibility have highlighted the virus’s capability to directly modulate spike-ACE2 interactions and promote immune evasion by sterically masking the immunogenic epitopes. Recently, there have also been reports of the bidirectional transfer of coronavirus between different animal species and humans. The ability of coronavirus to infect and adapt to a wide range of hosts can be attributed to new variants that modify the molecular recognition profile of the spike protein (S protein). The receptor-binding domain of the spike protein specifically interacts with key host receptor molecules present on the host cell membranes to gain entry into the host and begin the infection cycle. In this review, we discuss the molecular, structural, and functional diversity associated with the coronavirus receptors across their different phylogenetic lineages and its relevance to various symptomatology in the rapid human-to-human infection in COVID-19 patients, tropism, and zoonosis. Despite this seeming diversity of host receptors, there may be some common underlying mechanisms that influence the host range, virus transmissibility, and pathogenicity. Understanding these mechanisms may be crucial in not only controlling the ongoing pandemic but also help in stopping the resurgence of such virus threats in the future.

Based on hospital capacities, facts from past experience with the coronavirus disease 2019 (COVID-19) virus and the number of dark infections during the second wave (DII = 2D2), a reasonable limiting value of 140/D2 for the 7-day incidence per 100,000 persons (MSDIHT) and a second wave herd immunization threshold fraction value of 0.26 in Germany were calculated. If the MSDIHT is held below this limiting value, the German hospital system can cope with the number of new seriously infected persons without any triage decisions. On the basis of the SIRV epidemics model, the classical threshold values for herd immunization were calculated for 18 countries. For these countries, the dates regarding when herd immunization against the second COVID-19 wave will be reached were estimated

The COVID-19 pandemic has severely affected the food supply chain, including producers, retailers, wholesalers, and customers. To minimize the impacts caused by pandemics and epidemics on food supply chains, it is fundamental to implement effective policies that ensure continuity in the provision, affordability, and distribution of basic food items. This research aims to identify the main impacts of pandemics and epidemics on food supply chains and policies that can minimize these impacts. Based on a systematic literature review (SLR), 174 documents are analysed to propose a taxonomy of impacts on four supply chain links: demand-side, supply-side, logistics and infrastructure, and management and operation. The taxonomy presents the main impacts, as well as the respective mitigation policies simultaneously. In addition, the literature review leads to the development of a comprehensive causal loop diagram (CLD) with the identification of main variables and their relationship with food supply chains. Finally, a specific research agenda is proposed by identifying main research gaps. These findings provide a structured method for evaluating policies that ensure the functioning of food supply chains, particularly in disruptions such epidemics and pandemics.

Background. A previous study demonstrated the performance of the Salivette® (SARSTEDT, Numbrecht, Germany) as a homogeneous saliva collection system to diagnose COVID-19 by RT-qPCR, notably for symptomatic and asymptomatic patients. However, for convalescent patients, the corroboration of molecular detection of SARS-CoV-2 in paired nasopharyngeal swabs (NPS) and saliva samples was unsatisfactory. Objectives. The aim of the present work was to assess the concordance level of SARS-CoV-2 detection between paired sampling of NPSs and saliva collected with Salivette® at two time points, with ten days of interval. Results. A total of 319 paired samples from 145 outpatients (OP) and 51 healthcare workers (HW) were collected. Due to significant waiting rate at hospital, most of the patients ate and/or drank in waiting their turn. Consequently, a mouth washing was systematically proposed prior saliva collection. None of the HW were diagnosed SARS-CoV-2 positive using NPS or saliva specimens at both time points (n=95) by RT-qPCR. The virus was detected in 56.3% (n=126/224) of the NPS samples from OP, but solely 26.8% (n=60/224) of the paired saliva specimens. The detection of the internal cellular control, the human RNase P, in more than 98% of the saliva samples, underlined that the low sensitivity of saliva specimens (45.2%) for SARS-CoV-2 detection was not attributed to an improper saliva sample storing or RNA extraction. Conclusions. Then, the mouth washing decreased viral load of buccal cavity conducting to impairment of SARS-CoV-2 detection. Viral loads in saliva neo-produced appeared insufficient for molecular detection of SARS-CoV-2. At the time that saliva tests could be a rapid, simple and noninvasive strategy to assess on large scale schooled children in France, the determination of the performance of saliva collection become imperative to standardize procedures.

After the arrival of a new airborne virus to the world, science is aiming to develop solutions to withstand the spread and contagion of the SARS-CoV-2 coronavirus. The most severe among the adopted measures is to remain in home isolation for a significant number of hours per day, in order to avoid the spreading of the infection in an uncontrolled way through public spaces. Recent literature showed that the major route of transmission is via aerosols produced especially in poorly ventilated inner spaces. With regard to contagion rates, accumulated incidence or number of hospitalizations due to COVID-19, Spain has reached very high levels, therefore this article develops a quantitative and qualitative analysis of the requirements established in Spain with respect to the European framework in reference to ventilation parameters indoors. For this, a case study has been analyzed, representing a common residence in current Spanish residential developments. Results show that the criteria established in the applicable regulations are not sufficient to ensure health as well as to avoid contagion by aerosols indoors.

India is ranked 5th in world in terms of Covid-19 publications accounting for 6.7% of the total. About 60% of the Covid-19 publications in the year 2020 are from United States, China, UK, Italy, and India. We present a bibliometrics analysis of the publi-cation trends and citation structure along with identification of major research clusters. By performing network analysis of authors, citations, institutions, key-words, and countries, we explore semantic associations by applying visualization techniques. Our study shows lead taken by United States, China, UK, Italy, India in Covid-19 research may be attributed to the high prevalence of Covid-19 cases in those countries witnessing the first outbreak and also due to access to Covid-19 data, access to labs for experimental trials, immediate funding, and overall support from the govt. agencies. Large number of publications and citations from India are due to co-authored publications with countries like United States, UK, China, and Saudi Arabia. Findings show health sciences with highest the number of publications and citations, while physical sciences and social sciences and humanities counts were low. A large proportion of publications fall into the open access category. With India as focus, by comparing three major pandemics SARS, MERS, Covid-19 from biblio-metrics perspective, we observe much broader involvement of authors from multiple countries for Covid-19 studies as compared to SARS and MERS. Finally, by applying bibliometric indicators, we see an increasing number of sustainable develop-ment-related studies from the Covid-19 domain, particularly concerning the topic of good health and well-being. This study allows for a deeper understanding on how the scholarly community from a populous country like India pursued research in the midst of a major pandemic which resulted in closure of scientific institutions.

The novel coronavirus disease (COVID-19) has created immense threats to public health on various levels around the globe. The unpredictable outbreak of this disease and the pandemic situation are causing severe depression, anxiety and other mental as physical health related problems among the human beings. To combat against this disease, vaccination is essential as it will boost the immune system of human beings while being in the contact with the infected people. The vaccination process is thus necessary to confront the outbreak of COVID-19. This deadly disease has put social, economic condition of the entire world into an enormous challenge. The worldwide vaccination progress should be tracked to identify how fast the entire economic as well as social life will be stabilized. The monitor ofthe vaccination progress, a machine learning based Regressor model is approached in this study. This tracking process has been applied on the data starting from 14^th December, 2020 to 24^th April, 2021. A couple of ensemble based machine learning Regressor models such as Random Forest, Extra Trees, Gradient Boosting, AdaBoost and Extreme Gradient Boosting are implemented and their predictive performance are compared. The comparative study reveals that the AdaBoostRegressor outperforms with minimized mean absolute error (MAE) of 9.968 and root mean squared error (RMSE) of 11.133.

In this modern era, continuous change is the first step in forming a new structure between theory and practice. The idea of ​​a juggernaut is very relevant to the theory of structuration with current conditions in the 21st century, where technology becomes a reference that can crush anyone who is not responsive to its power. This technology takes one path and takes many roles from various fields: economic, social, political, legal, and educational. This 21st century is marked by great momentum for changes in human behavior and civilization, namely the industrial revolution 4.0 and the arrival of Covid-19, which have changed many social structures and human activities. This makes history a means of connecting the problems in the 21st century with past events. By using a descriptive qualitative method, this paper will reveal how technological developments are very influential on educational and political developments and what are the challenges faced based on historical perspective?. In this case, the study aims to discuss the history and challenges of Indonesia's education system and government system in the 21st century and give a solution. The data used are from 2 books, 14 journal articles, and 4 websites with a span of 2019-2021. The research results are expected to be used as a further study in the face of the development of the modern era in the fields of education and government. This study also has limitations, namely only on the face of the development of the modern era in the fields of education and government.

Plant species with anti-inflammatory properties might play an essential role in combatting COVID-19 via reducing cytokine storms. We aimed to review the extant evidence of the potential therapeutic efficacy of natural products against cytokine storms by inhibiting interleukin-6 (IL-6) as a major pathological mediator. Data were collected following an electronic search in major databases (Pubmed, Scopus, Web of Science, Google Scholar) and also preprint articles on preprint and medRxiv servers by using a combination of relevant keywords. Seventeen active compounds and medicinal plants were found and reviewed in the present review. Results of both in-vivo and in-vitro experiments conducted on these compounds showed that Phillyrin, SMFM, Qiangzhi decoction, curcumin, Shen-Fu, Forsythia, and Alpha-Mangostin inhibit the production of IL-6. Andrographolide and Liu Shen Wan have an inhibitory effect on releasing this agent, while Ilex Asprella and Deoxy-11,12-didehydroandrographolide and naringin reduce the expression of IL-6. Theaflavin and Cholorogenic acid inhibit the secretion of IL-6, Xuebijing, and Chai-Hu-Gui-Zi-Gan-Jiang-Tang and Lipanpaidu prescription can reduce the serum level of IL-6. These agents also effectively improve infected lungs, increase survival rates, and minimize tissue damage. Medicinal plants and their phytochemical ingredients with down-regulatory effects on the expression of IL-6 have a potential influence on the inhibition of cytokine storms during viral infection caused by COVID-19. Therefore, phytochemicals could be regarded as promising candidates for managing cytokine storm inflammatory responses due to COVID-19 infection.

Clubhouse is an auditory app that allows users to host various rooms surrounding a diverse range of topics from Artificial Intelligence to Philosophy. Along with its educational and serene approach, it is known for its popularity amongst celebrities, including Elon Musk, Mark Zuckerburg, CEO of Shopify, and its elusive invite and ios-only pass into gaining access into Clubhouse. Waiting lists are available in the case of not achieving an invite, but to further speed the process, various sellers on eBay, Reddit, Twitter, etc., charging invites from $10-$200. This research paper covers the phenomenon of Clubhouse and the emergence of audio-only rooms, along with a hypothesis of why Clubhouse and other apps of a similar kind are experiencing a harsh downfall despite its seemingly successful business model.

Abstract: COVID-19 in 2020 brought challenges to the Brazilian public health system with an emerging virus with respiratory contagion called SARS-CoV-2. There are few studies in Brazil and in some countries, on the increased incidence of certain viral respiratory infections, includ-ing H1N1 and coronavirus and their association with low levels of vitamin D, zinc and iron. The aim of this study was to demonstrate that the deficit of vitamin D, zinc and iron has an impact on the infectious process of patients with COVID-19 and to establish new forms of prevention for the worsening of COVID-19 in the human body. Data were collected from medical records and test results from patients being followed up during the treatment period for COVID-19. Patients with low blood levels of vitamin D, zinc and iron during the treatment period of COVID-19 had a higher percentage of worsening and complications requiring hospitalization in intensive care beds. The ingestion of vitamin D, zinc and iron in the treatment period of patients with COVID-19 in addition to being an immunological protector against SARS-CoV-2 and alleviating the process of worsening the disease can also act as a biomarker in cases of this disease.

Objective: To investigate social, economic, and environmental contributors to quit or continue smoking and vaping during the COVID-19 pandemic. Methods: A qualitative study design was adopted to identify smokers’ beliefs in a LMIC, using a small community sample. Results: 276 participants were primarily surveyed. Motivation to continue smoking included temporary pleasurable effects, working remotely, stress or anxiety, whereas a motivator to quit smoking was the overlap with COVID-19 symptomatology. There was a rise in social awareness regarding the potential harm of smoking and vaping during the pandemic yet those participants who were younger felt they were immune from its morbid complications. Conclusions: With paradoxical associations of COVID-19 with cigarette and vape usage, it is important to pay attention to biases in data in favor of educating its users of the increased risk of severe disease.

This paper aims to contribute to the advancement of scientific knowledge about the impact of the COVID-19 pandemic on social workers and the social work profession in Romania. Research has shown that social work is a profession at high risk for developing the burnout syndrome, which has many detrimental effects on both social workers and the clients that they serve. Two conceptual models are used to frame the discussion: the theoretical framework of VUCA (volatility, uncer-tainty, complexity, and ambiguity) to discuss the challenges of the unprecedented context the COVID-19 pandemic has created for social workers; stress and burnout to explain the negative impact of this period of time. Based on convergent mixt methods, the study sample consisted of 83 social workers employed in statutory and private social services in Romania, from different fields of intervention. Results show that 25,3% of respondents suffer from a high level of burnout and 44.6% scored in a range that indicate a medium level of burnout. A group of 31.1% have managed to handle stress factors in a healthy manner. Main stressors found are especially personal (fear of contamination, personal and family) and work-related factors (workload, new legislative rules and decisions, inconsistency, instability, ambiguity of managerial decisions, or even their absence or non-assumption, lack of clarity of working procedures, limited managerial and supervisory support, limited financial resources), less than client related factors (lack of direct contact, risk of contami-nation in two ways, managing beneficiaries fears, difficulties related to technology and digital skills). Study results point to the importance of organizational support and developing a self-care plan that help protect against occupational stress and burnout. Recommendations are made putting forward the voice of fieldworkers and managers fostering initiatives and applications of sustainability-based measures and activities designed to deal with the challenges of the VUCA environment.

Bangladesh has achieved tremendous progress in the fisheries sector that is making evidential contribution to food security, nutrition and livelihoods. Based on secondary data collected from the Department of Fisheries, Bangladesh and related un-published grey literature, this paper highlights the performance and challenges of the fisheries with emphasis on COVID-19 impact as well as the significance of this sector for achieving the Sustainable Development Goals (SDGs). The total fish production is increased more than six times over the last three decades (7.54 to 43.84 lakh MT) due to the dissemination of improved culture techniques and extension services. Inland closed water contributions have been increasing to 16.24%, while inland open water have declined 10.23% and marine fisheries have dropped 6.27% over the past 18 financial years (2000-2001 to 2018-2019). COVID-19, a major health crisis has also affects various issues associated with aquatic resources and communities. Transportation obstacles and complexity in the food supply, abstraction to start production, labour crisis, sudden illness, poor consumer demand, commodity price hike, creditor's pressure and reduced income were identified as affecting COVID-19 drivers. The combined effect of these drivers poses a significant threat to people’s income (SDG1- eliminate poverty), nutrition (SDG2- erase hunger), food security (SDG3- good health and wellbeing, and SDG12- responsible consumption and production) that demands comprehensive actions. Several recommendations have been elicited, which are important to implement for the achievement of SDGs as well management and imprvement of the aquatic sector (SDG14- life below and SDG16- life above water) .

Background: A comprehensive response to the unprecedented SARS-CoV-2 (COVID-19) chal-lenges for public health and its impact on radiation oncology patients and personnel for resilience and adaptability is presented. Methods: The general recommendations included working remote-ly when feasible, implementation of screening/safety and personal protective equipment (PPE) guidelines, social distancing, regular cleaning of treatment environment, and testing for high-risk patients/procedures. All teaching conferences, tumor boards, and weekly chart rounds were con-ducted using a virtual platform. Additionally, specific recommendations were given to each sec-tion to ensure proper patient treatments. The impact of these measures, especially adaptability and resilience, were evaluated through specific questionnaire surveys. Results: These comprehen-sive COVID-19 related measures resulted in most staff expressing a consistent level of satisfaction in regards to personal safety, maintaining a safe work environment, continuing quality patient care and continuing educational activities during the pandemic. There was a significant reduction in patient treatments and on-site patient visits with an appeciable increase in the number of tele-medicine e-visits. Conclusions: Survey results demonstrated substantial adaptability and resili-ence, including in the rapid recovery of departmental activities during the reactivation phase. In the event of a future public health emergency, the measures implemented may be adopted with good outcomes by radiation oncology departments across the globe.

In Mexico, it is estimated that due to the economic system the overexploitation of natural resources, environmental impacts and health have been generated, with high rates of overweight and obesity. This review analyzes the impacts on food safety, environmental health, and the economy in Mexico before and during the COVID-19 contingency. Derived from the analysis, among the lessons learned we can include: the health contingency due to COVID-19 had negative repercussions on food security, environmental health and the economy, which require the promotion of public policies (health, environment and economy) and migrate to a health prevention system and an agroecological model, which includes multidisciplinary and intersectoral interventions (government, academia, researchers, civil society organizations, business groups and citizens themselves) to reform and enforce the right to enjoy adequate food and a healthy environment. The contingency due to COVID19 has shown us that this must go from an ideology to being a reality and the lessons learned will have to focus on promoting an innovative and ethical culture of generating an economy, with a gender balance, resilience to climate change, management transparent technology and a priority in health and this will lead to progress in the food security of the population.

The emergence of the COVID-19 outbreak has caused a pandemic situation in over 210 countries. Controlling the spread of this disease has proven difficult despite several resources employed. Millions of hospitalization and deaths have been observed, and thousands of cases daily with many measures in place. Due to the complex nature of COVID-19, we proposed a system of time-fractional equations to understand the transmission of the disease better. Nonlocality involved in the model has made fractional differential equations appropriate for modeling the behavior. However, solving these types of models is computationally demanding. Our proposed generalized compartmental COVID-19 model incorporates effective contact rate, transition rate (from exposed quarantine and recovered to susceptible and infected quarantined individuals), quarantine rate, disease-induced death rate, natural death rate, natural recovery rate, recovery rate of quarantine infected for a holistic study of the coronavirus disease. A detailed analysis of the proposed model is carried out, including the existence and uniqueness of solutions, local and global stability analysis of the disease-free equilibrium analysis, and sensitivity analysis. Furthermore, numerical solutions of the proposed model are obtained with the generalized Adam-Bashforth-Moulton method developed for the fractional order model. Our analysis and solutions profile show that each of these incorporated parameters is very important in controlling the spread of COVID-19, especially quarantining exposed and infected individuals and the effective contact rate. Based on the results with different fractional order, we observe that there seems to be a third or even fourth wave of the spike in cases of COVID-19, which is what is happening right now in many countries.

The Covid-19 pandemic caused very serious problems almost to the whole world, so every opportunity must be considered to improve the situation. Decontamination carried out from the air can also be considered for surface clearance of larger areas, so the possibility of this application should also be investigated regarding pandemic. There are many examples of the use of drones for disinfection to improve the epidemic situation, but good practices, as well as factors influencing the effectiveness, have not yet been identified. In the case of using drone for disinfections during a pandemic, based on the reports, we can clearly discover the adapted use of agricultural drones. In this paper, the authors perform calculations with different values of flight speed (10 to 50 km/h), flight altitude (1 to 5 m), and flow rate (1 to 5 l / min) to determine the possible amount of disinfectant fluid per unit area. The results show that by changing the parameters, the amount of disinfectant per unit area can be given within quite wide limits (30 - 0.24 g/m2). Although the results raise many new questions it can help to identify adequate flight parameters depending on different disinfectant liquids.

This study aimed to focus on how to design a low-cost greenhouse for the cultivation of crops, to propose the cost-effectiveness analysis of small agribusiness, and to promote sustainable agricultural production during and after the COVID-19 crisis for helping grassroots and anyone who lost their job. This article is qualitative engineering research, studying of literature reviews of greenhouse farming concept and Micro, Small and Medium Enterprises, then, designing low-cost greenhouse model which was preliminarily adapted for hot climate countries. Three plants that were selected as representative plants of this model include sunflower, water spinach, and wheat. The greenhouse model, measuring 5 x 7 x 4 m (W x L x H), was designed for this mission. The total cost of one building is approximately 97,994 THB. For the worthiness of the investment, farmers should build at least three greenhouse buildings, which will return total income to farmers approximately 34,666.09 THB per month. The suggestion includes further knowledge and financial supports from the government sectors among farmers, then, boost them up using high-level technology and also planting high-price agribusiness production to promote the local economy to be strong and sustainable.

Considering the challenges of sustainable education in emergency remote teaching (ERT) during the coronavirus (COVID-19) pandemic, this study provides basic principles for future ERT implementation based on the experience of higher education in Indonesia. Seven local expert distance educators reviewed the ERT principles, participating in the early stages to check the relevance, content validity, and readability of the five principles proposed in the context of Indonesian education. After an extensive expert review, the ERT principles were evaluated using quantitative data through an online survey (82 students and 45 faculty members). In addition, open-ended questionnaire responses, experiences, and challenges encountered by 21 respondents (College Dean, Associate Dean of Academics, and faculty quality assurance of seven universities/colleges in three provinces in Indonesia) in ERT were used and analyzed. This study suggests that ERT should be designed based on the principles of simplicity, accessibility, affordability, flexibility, and empathy in all learning activities in unfavorable situations. This study complements previous work and can thus be used for generalized principles for teaching activities in similar emergencies, especially in developing countries.

Alcoholism is a condition associated with psychiatric and psychiatric problems, where the respiratory system is damaged through the mucociliary ladder mechanism and alveolar macrophage dysfunction. In the time COVID-19 has been observed a dramatic increase in alcohol consumption mediated by levels of anxiety and situations of confinement. In this work we analyze the relationship between alcoholism and SARS, especially with SARS-CoV-2, explained by a degradation of the host defenses of the respiratory epithelium by changing the barrier function, the discharge of cytokines and the functions of the cilia. All of them involved in the defense mechanism. of the lungs. This leads to a worse prognosis for patients precisely because of alcohol consumption. Based on this approach, alcoholism will exacerbate the consequences of COVID-19.

We report the first detection of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus from a dog in Connecticut during February 2021. Complete genome sequencing and phylo-genetic analysis of the hCoV-19/USA/CT-CVMDL-Dog-1/2021 (CT_Dog/2021) virus were con-ducted to identify the origin and lineage of the virus. The CT_Dog/2021 virus belonged to the GH/B1.2. genetic lineage and was genetically close to SARS-CoV-2 identified from humans in the U.S. during the winter of 2020-2021. However, it was not related to other SARS-CoV-2 identified from companion animals in the U.S. It contained both D614G in spike and P323L in nsp12 substitutions which have become the dominant mutations in the United States. The continued sporadic detections of SARS-CoV-2 in companion animals warrant public health concerns about their potential to become a new reservoir species of SARS-CoV-2.

Background: The COVID-19 pandemic has hit the Spanish economy hard. The result is an unprecedented economic and social crisis due to uncertainty about the remedy, and due to the socio-economic effects on people’s lives. Methods: We performed a retrospective analysis of the macro-economic impact of COVID-19 in 2020, using the principal indicators of the Spanish economic and productive model. National statistics were examined in the search for impacts or anomalies occurring since the beginning of the pandemic. To estimate the strength of the impact on each of the indicators analysed, we used Bayesian structural time series. Results: In 2020, the cumulative impact on the Gross Domestic Product was of -11.41% [95% credible interval: -13.46; -9.29]. The indicator for Business Turnover fell by -9.37% [-12.71; -6.07]. The reduction in business activity was related to the sharp fall in demand. The Spanish employment market was strongly affected; our estimates showed a cumulative increase of 11.9% [4.27; 19.45] in the rate of unemployment during 2020. The autonomous communities which are economically the most heavily dependent on the services sector were those which recorded the worst indicators. Conclusions: Our estimates portray a dramatic situation in our country, and show all too clearly the fragility of a productive system which has to make the behavioural changes that are necessary to confront the COVID-19 pandemic.

Since December 2019, the world is fighting against coronavirus disease (COVID-19). This disease is caused by a novel coronavirus termed as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This work focuses on the applications of machine learning algorithms in the context of COVID-19. Firstly, regression analysis is performed to model the number of confirmed cases and death cases. Our experiments show that autoregressive integrated moving average (ARIMA) can reliably model the increase in the number of confirmed cases and can predict future cases. Secondly, a number of classifiers are used to predict whether a COVID-19 patient needs to be admitted to an intensive care unit (ICU) or semi-ICU. For this, classification algorithms are applied to a dataset having 5644 samples. Using this dataset, the most significant attributes are selected using features selection by ExtraTrees classifier, and Proteina C reativa (mg/dL) is found to be the highest-ranked feature. In our experiments, random forest, logistic regression, support vector machine, XGBoost, stacking and voting classifiers are applied to the top 10 selected attributes of the dataset. Results show that random forest and hard voting classifiers achieve the highest classification accuracy values near 98%, and the highest recall value of 98% in predicting the need for admission into ICU/semi ICU units.

As the world is striving to recover from the shockwaves triggered by the Covid-19 crisis, all hands are needed on deck to transition towards a green recovery and make peace with nature as prerequisites of a global sustainable development pathway. In this paper, we examine the blockchain hype and the gaps in data and tools to build promising use cases for blockchain technology to accelerate global efforts in the decade of action towards achieving the SDGs. We attempted to break the hype-cycle portraying blockchain’s superiority by navigating a rational blockchain use case development approach. By prototyping an SDG Acceleration Scorecard to use blockchain-enabled solutions as SDG accelerators, we aim to provide useful insights towards developing an integrated approach that is fit-for-purpose to guide organizations and practitioners in their quest to make informed decisions to design and implement blockchain-backed solutions as SDG accelerators. Acknowledging the limitations in prototyping such tools, we believe these are minimally viable products and should be considered as living tools that can further evolve as the blockchain technology is getting mature, its pace of adoption increasing, and its lessons learned, good practices and standards widely shared and internalized by teams and organizations working on innovation for development.

Social isolation magnified by the restriction of movement order during the COVID-19 pandemic may lead to negative psychosocial health impact among community-dwelling older adults. We evaluated the feasibility of virtual research methods and virtual group exercises among individuals aged 60 years and over in Malaysia. Participants were recruited from the Promoting Independence in Seniors with Arthritis (PISA) pilot cohort through social media messages. A four-week course of virtual group exercise was offered. Anxiety and depression were assessed with the Hospital Anxiety and Depression Scale (HADS) during the last attended follow-up of the cohort study (pre-pandemic), pre-intervention, and post-intervention. Exercise adherence was recorded using diary with daily entries and attendance to the virtual group exercise sessions were captured daily. The outcomes of interest were changes of anxiety and depression scores from baseline to pre-intervention (pandemic-related) and post-intervention (virtual exercise related). Forty-three individuals were recruited. A significant increase in anxiety scores from baseline to pre-intervention was observed. Comparisons using repeated-measures analysis of variance between those who attendance ≥14 and &lt;14 group exercise sessions revealed no between-within subjects differences in depression scores. There was a 23% dropout rate in the post intervention survey and 60.5% of diaries were returned. This study demonstrated the feasibility of conducting research entirely virtually among older persons during the peak of global first wave of a pandemic. The pandemic has led to increased anxiety among community-dwelling older adults.

— Big Data analytics has come a long way since its inception. This field is growing day by day. With the advent of large handling capacity of computational analysis of modern computing systems as well as Internet of Things (IoT), this field has revolutionized the way we think about data. It has influenced the major domains such as healthcare, automobile, computing, climatology, and space communications. Of late, the health care sector has been largely influenced by this. This communication deals with the areas of healthcare where big data analytics has been largely influential. Encompassing the basics of Big Data Analytics (BDA) driven by IoT, the applications of it in healthcare sector are outlined, accompanied by future expectations. Additionally, it also presents a comprehensive analysis of recent application with special reference to Covid-19 in this sector.

Appropriate diagnostic testing to identify persons infected with SARS-COV-2 is a vital part of a health system’s ability to control the global pandemic of COVID-19 disease. The primary purpose of this review is to provide an overview of the mass testing strategy implemented throughout the UAE and the overall impact it has made on containing and controlling the spread of the disease. This study describes the mass testing strategy and capacity of the UAE during the pandemic of the new coronavirus SARS-COV-2. The UAE has conducted 15 million polymerase chain reaction (PCR) tests to SARS-COV-2, as of 15 November 2020. The number of tests per day varied from 10,000 by the end of March to 120,000 tests per day in November 2020. The mass testing initiative across the entire UAE forms an integral part of a bigger strategy focusing on testing, tracing contacts and isolating positive cases.

Sound signals from the respiratory system are largely the harbingers of human health. Early diagnosis of respiratory tract diseases is of great importance as it creates irreversible effects on human health when delayed. This diagnostic in the medical world has been made possible thanks to machine learning and signal processing analysis. The coronavirus epidemic, which is in question today and deeply shakes the whole world, has been revealed the importance of this issue even more. In terms of the coronavirus pandemic, it has become the focus of researchers to differentiate symptoms from similar diseases such as normal flu or influenza. Among these symptoms, the difference in cough sound has played a distinctive role in the proposed study. Several pioneering studies have proven that almost two-thirds of people who get corona have a dry cough. At this stage, the information of studies based on cough constitutes the main framework of our study. On the other hand, the basis of this study is based on machine learning algorithms. Clinical data collected under the supervision of doctors in a reliable environment was used as dataset. This dataset consists of 16 subjects suspected of the coronavirus with a specific patient demographic. In this study, using the polymerase chain reaction (PCR) test, suspected subjects were divided into two groups as negative and positive. The negative and positive labels represent the patient with non-COVID and with a COVID-19 cough respectively. Using the 3D plot or waterfall representation of the signal frequency spectrum, the salient features of the cough data are revealed. In this way, COVID-19 can be differentiated from other coughs by applying effective feature extraction and classification techniques. Power Spectral Density (PSD) based on Short Time Fourier Transform (STFT) and Mel Frequency Cepstral Coefficients (MFCC) were chosen as the efficient feature extraction method. Finally, among the classification techniques the Support Vector Machine (SVM) algorithm, was applied to the processed signals in order to identify and classify COVID-19 cough. In terms of results evaluation, the cough of subjects with COVID-19 has obtained with 95.86% classification accuracy thanks to the RBF kernel function of SVM and the MFCC method. In other words, the diagnosis of COVID-19 coughs was obtained with 98.6% and 91.7% sensitivity and specificity measures respectively.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system. The interferons (IFNs) were discovered in 1957, and recombinant IFN-β-1b was approved by the US Food and Drug Administration as the first disease-modifying therapy (DMT) for MS in 1993. Since that time, clinical trials and real-world observational studies have demonstrated the effectiveness of IFN therapies. The pivotal intramuscular IFN-β-1a phase 3 trial was the first to demonstrate that a DMT could reduce accumulation of sustained disability in MS. Patient adherence to treatment is higher with intramuscular IFN-β-1a, given once weekly, than with subcutaneous formulations requiring multiple injections per week. Moreover, subcutaneous IFN-β-1a is associated with an increased incidence of injection site reactions and neutralizing antibodies compared with intramuscular administration. In recent years, revisions to MS diagnostic criteria have improved clinicians’ ability to identify patients with MS and have promoted the use of magnetic resonance imaging (MRI) for diagnosis and monitoring. MRI studies show that treatment with IFN-β-1a, relative to placebo, reduces T2 and gadolinium-enhancing lesions and gray matter atrophy. Since the approval of intramuscular IFN-β-1a, several high-efficacy therapies have been approved for MS, though the benefit of these high-efficacy therapies should be balanced against the increased risk of serious adverse events. For some subpopulations of patients, including pregnant women, the safety profile of IFN-β formulations may provide a particular benefit. In addition, the antiviral properties of IFNs may indicate therapeutic opportunities for IFN-β in the treatment of viral infections such as COVID-19.

All RNA viruses deliver their genomes into target host cells through processes distinct from normal trafficking of cellular RNA transcripts. The delivery of viral RNA into most cells hence triggers innate antiviral defenses that recognize viral RNA as foreign. In turn, viruses have evolved mechanisms to subvert these defenses, allowing them to thrive in target cells. Therefore, drugs activating defense to exogenous RNA could serve as broad-spectrum antiviral drugs. Here we show that transcriptional signatures associated with cellular responses to the delivery of a non-viral exogenous RNA sequence into human cells predict small molecules with broad-spectrum antiviral activity. In particular, transcriptional responses to the delivery of Cas9 mRNA into human hematopoietic stem and progenitor cells (HSPCs) highly matches those triggered by small molecules with broad-spectrum antiviral activity such as emetine, homoharringtonine, pyrvinium pamoate and anisomycin, indicating that these drugs are potentially active against other RNA viruses. Furthermore, these drugs have been approved for other indications and could thereby be repurposed to novel viruses. We propose that the antiviral activity of these drugs to SARS-CoV-2 should therefore be determined as they have been shown as active against other coronaviruses including SARS-CoV-1 and MERS-CoV. Indeed, two of these drugs- emetine and homoharringtonine- were independently shown to inhibit SARS-CoV-2 as this article was in preparation. These drugs could also be explored as potential adjuvants to COVID-19 vaccines in development due to their potential effect on the innate antiviral defenses that could bolster adaptive immunity when delivered alongside vaccine antigens.

Introduction: We describe the clinical features and inpatient trajectories of older adults hospitalized with COVID-19, and explore relationships with frailty. Methods: This retrospective observational study included older adults admitted as an emergency to a University Hospital who were diagnosed with COVID-19. Patient characteristics and hospital outcomes, primarily inpatient death or death within 14 days of discharge, were described for the whole cohort and by frailty status. Associations with mortality were further evaluated using Cox Proportional Hazards Regression (Hazard Ratio [HR], 95% Confidence Interval). Results: 214 patients (94 women) were included of whom 142 (66.4%) were frail with a median Clinical Frailty Scale (CFS) score of 6. Frail compared to non-frail patients were more likely to present with atypical symptoms including new or worsening confusion (45.1% vs 20.8%, p<0.001) and were more likely to die (66% vs 16%, p=0.001). Older age, being male, presenting with high illness acuity and high frailty were independent predictors of death and a dose-response association between frailty and mortality was observed (CFS 1-4: reference; CFS 5-6: HR 1.78, 95% CI 0.90, 3.53; CFS 7-8: HR 2.57, 95% CI 1.26, 5.24). Conclusions: Clinicians should have a low threshold for testing for COVID-19 in older and frail patients during periods of community viral transmission and diagnosis should prompt early advanced care planning.