Digital skills are essential in today’s digital age, which means that students must gain technology-enhanced skills from higher education for their future careers. Studies in Art & Design (A&D) programs in this university surveyed three faculties’ perspectives and nineteen students’ experiences. During the COVID-19 pandemic, this university changed its teaching and learning strategies by offering courses online during autumn 2020 and spring 2021 during mandatory quarantine. However, the A&D program was not entirely based online. As a result, it is important to take a closer look at the A&D programs offered in order to assess the faculties’ perspectives and students’ experiences during the two online semesters. The study included online surveys from instructors’ perspectives and with regard to students’ experiences about the quality of studio learning, traditional studio learning opportunities, and online studio learning opportunities via either live (on-campus) or online studios. Using relationship-based research design, posttest data surveys were collected to ascertain the differences in the mean scores, standard deviations, and percentages of some forms of agreement between the faculties’ perspectives and students’ experiences of the quality of studio learning, traditional studio learning opportunities, and online studio learning opportunities in these Art & Design (A&D) programs. This quantitative research aimed to develop formative assessments and suggestions while establishing whether it would be possible to hold all A&D courses online in a higher education setting.

A fundamental aspect in the evolution of Time-to-Digital Converters (TDCs) implemented within Field-Programmable Gate Arrays (FPGAs), given the increasing demand for detection channels, is the optimization of resource utilization. This study reviews the principal methodologies employed for implementing low-resource TDCs in FPGAs. It outlines the foundational architectures and interpolation techniques utilized to bolster TDC performances without unduly burdening resource consumption. Low-resource Tapped Delay Line, Vernier Ring Oscillator, and Multi-Phase Shift Counter TDCs, including the use of SerDes, are reviewed. Additionally, novel low-resource architectures are scrutinized, including Counter Gray Oscillator TDCs and interpolation expansions using Voltage-Temperature-Consumption stable IODELAYS. Furthermore, the advantages and limitations of each approach are critically assessed, with particular emphasis on resolution, precision, non-linearities, and, especially, resource utilization. A comprehensive summary table encapsulating existing works on low-resource TDCs is provided, offering a comprehensive overview of the advancements in the field.

The automotive industry is continuously developing to meet the needs of users in terms of efficiency and convenience. The Thailand government has set a policy for Thailand to be a hub for the production of electric vehicles and key components in the region, with a target to produce electric and zero-emission vehicles by 2030. This article is an example of communication in an electric vehicle system. The CAN Bus system is a communication system in electric vehicles that can receive and send communication data via CAN-Hight/Low lines designed for vehicles. CAN Bus is a standard communication system supported by global organizations and used in modern automotive systems. The design of the communication system in electric vehicles uses MRS Developers Studio software to help write programs to receive and send data and prioritize the importance of the received data. The system consists of communication examples studied, such as pressing the start button, turning on/off the headlights, turning on/off the turn signal, turning on/off the brake light, turning on/off the emergency light, sending the horn signal, sending the signal to shift forward/backward, and tuning the motor gear system. From the communication examples mentioned, the communication will be a prototype transport set for small electric vehicles under the scope of the lithium battery energy storage system, NMC type, size 72 V 25 Ah, to test the use, efficiency, and stability in CAN Bus communication up to 1000 times.

Background: The monocyte-phagocyte system (MPS), including monocytes/macrophages and dendritic cells (DCs), plays a key role in anti-viral immunity. We aimed to analyze the prognostic value of the MPS components on in-hospital mortality in a cohort of 58 patients (M/F ; mean ageSD years) with COVID-19 pneumonia and 22 age- and sex-matched healthy controls. Methods: We measured frequencies and absolute numbers of peripheral blood CD169+ monocytes, conventional CD1c+ and CD141+ (namely cDC2 and cDC1), and plasmacytoid CD303+ DCs by means of multi-parametric flow cytometry. A gene profile analysis of 770 immune-inflammatory related human genes and 20 SARS-CoV-2 genes was also performed. Results: Median frequencies and absolute counts of CD169-expressing monocytes were significantly higher in COVID-19 patients than in controls (p 0.04 and p 0.01, respectively). Conversely, percentages and absolute numbers of all DC subsets were markedly depleted in patients (p

This paper reports on the optimization of thin-film coating assisted self-sustainable off-grid hybrid power generation systems for cattle farming in rural areas of Bangladesh. Bangladesh is a lower middle-income country with declining rates of poverty among its 160 million people due to persistent economic growth in conjunction with balanced agricultural improvements. Most of the rural households adopt a mixed farming system by cultivating crops and simultaneously rearing livestock. Among the animals raised, cattle are considered as the most valuable asset for the small/medium-scale farmers in terms of their meat and milk production. Currently, along with the major health issue, the COVID-19 pandemic is hindering the world’s economic growth and has thrust millions into unemployment; Bangladesh is also in this loop. However, natural disasters such as COVID-19 pandemic and floods, largely constrain rural smallholder cattle farmers from climbing out of their poverty. In particular, small and medium-scale cattle farmers face many issues that obstruct them from taking advantage of market opportunities and imposing a greater burden on their families and incomes. An appropriate measure can give a way to make those cattle farmers’ businesses both profitable and sustainable. Optimization of thin-film coating assisted self-sustainable off-grid hybrid power generation system for cattle farming is a new and forward-looking approach for sustainable development of the livestock sector. In this study, we design and optimize a thin-film coating assisted hybrid (photovoltaic-battery-generator) power system by using the Hybrid Optimization of Multiple Energy Resources (HOMER, Version 3.14.0) simulation tool. An analysis of the results has suggested that the off-grid hybrid system is more feasible for small and medium-scale cattle farming systems with long-term sustainability to overcome the significant challenges faced by smallholder cattle farmers in Bangladesh.

Three patients with severe life-threatening COVID-19 who failed to achieve substantial improvement on tocilizumab, received pulse therapy with corticosteroids (methylprednisolone, 1000 mg/day IV for three consecutive days) and intravenous immunoglobulin (20 g/day IV). This was associated with a prompt resolution of respiratory failure, elimination of cytokine release syndrome, and reversal of pulmonary CT changes. The treatment was generally safe and well tolerated. There was no evidence of protracted persistence of the virus in the patients who received pulse therapy. Randomized controlled trials are necessary to specify the efficacy and safety of high-dose methylprednisolone and intravenous immunoglobulin in the treatment of severe life-threatening COVID-19 separately or in combination.

A new coronavirus (SARS-CoV-2) have determined a pneumonia outbreak in China (Wuhan and Hubei) on December 2019. While pharmaceutical and non-pharmaceutical intervention strategies are strengthened worldwide, the scientific community has been studying the risk factors associated with SARS-Cov-2, to enrich epidemiological information. For a long time, before the industrialized era, air pollution has been a real and big health concern and it is today a very serious environmental risk for many diseases and anticipated deaths in the world. It has long been known that air pollutants increasing the invasiveness of pathogens for humans by acting as a carrier and making people more sensitive to pathogens through a negative influence on the immune system. Based on scientific evidences, the hypothesis that air pollution, resulting from a combination of factors such as meteorological data, level of industrialization as well as regional topography, can acts both as an infection carrier as a harmful factor of the health outcomes of COVID-19 disease has been raised recently. This hypothesis is turning in scientific evidence, thanks to the numerous studies that have been launched all over the world. With this review, we want to provide a first unique view of all the first epidemiological studies relating the association between air pollution and SARS-CoV-2. Major findings are consistent, highlighting the important contribution of air pollution on the COVID-19 spread and with a less extent also PM₁₀.

Coronavirus Disease 2019 (COVID-19), caused by a novel coronavirus named Severe Acute Respiratory Syndrome - Coronavirus-2 (SARS-CoV-2), emerged in early December 2019 in China and attained a pandemic situation worldwide by its rapid spread to nearly 167 countries with 287.239 confirmed cases and 11.921 human deaths with a case fatality rate (CFR) of around 4 per cent. Bats were considered as the reservoir host, and the search of a probable intermediate host is still going on. Animals have anticipated culprit of SARS-CoV-2 as of now. The disease is mainly manifested by pneumonia and related respiratory signs and symptoms, but the involvement of the gastrointestinal system and nervous system is also suggested. The severe form of the disease associated with death is mainly reported in older and immune-compromised patients with pre-existing disease history. Death in severe cases is attributed to respiratory failure associated with hyperinflammation. Cytokine storm syndrome associated with rampant inflammation in response to SARS-CoV-2 infection is considered as the leading killer of COVID-19 patients. COVID-19 patients were reported with higher levels of many pro-inflammatory cytokines and chemokines like IFN-g, IL-1b, IP-10, and MCP-1. Furthermore, severe cases of COVID-19 revealed higher levels of TNF-α, G-CSF, and MIP-1A. Blood profile of the COVID-19 patients exhibits lymphopenia, leucopenia, thrombocytopenia and RNAaemia along with increased levels of aspartate aminotransferase. SARS-CoV-2 infection in pregnant women does not lead to fetus mortalities unlike other zoonotic coronaviruses like SARS-CoV and MERS-CoV, with no evidence of intrauterine transmission to neonates. Rapid and confirmatory diagnostics have been developed, and high efforts are being made to develop effective vaccines and therapeutics. In the absence of any virus-specific therapeutic, internationally health care authorities are recommending adoption of effective prevention and control measures to counter and contain this pandemic virus. This paper is an overview of this virus and the disease with a particular focus on SARS-COV-2 / COVID-19 clinical pathology, pathogenesis and immunopathology along with a few recent research developments.

We revisit a 2023 JAMA-published analysis of data from patients admitted for either COVID-19 or influenza to U.S. Veterans Administration (VA) hospitals in the fall/winter of 2022-2023. We note that baseline characteristics between the cohorts were similar, and the difference in vaccination rates was minimal, even after propensity score weighting. Had the vaccines been even minimally effective, significant differences in vaccination percentages would be expected. These findings call into question any efficacy claims associated with either the COVID-19 or influenza vaccines. Furthermore, the lack of efficacy of the influenza vaccines in reducing hospitalization is consistent with an earlier detailed study that found the same lack of efficacy, further validating the current result. This suggests that comparing vaccination rates between those hospitalized for different vaccine-preventable diseases can serve as a practical method for validating the vaccine efficacy claims of different vaccines.

This study offers an in-depth analysis of the COVID-19 pandemic’s trajectory in several member countries of the European Union (EU) to assess similarities in their crisis experiences. We also examine data from the United States to facilitate a larger comparison across continents. We introduce our new approach, which uses a spatio-temporal algorithm to identify five distinct and recurring phases that each country undergoes at different times during the pandemic. These stages include a Comfort Period characterized by minimal COVID-19 activity and limited impacts. The Preventive Situation demonstrates the implementation of proactive measures, with relatively low numbers of cases, deaths, and Intensive Care Unit (ICU) admissions. The Worrying Situation is defined by high levels of concern and preparation as deaths and cases begin to rise and reach substantial levels. The Panic Situation is marked by a high number of deaths relative to the number of cases and a rise in ICU admissions, denoting a critical and alarming period of the pandemic. Finally, the Epidemic Control Situation distinguishes itself by limiting COVID-19 deaths despite a high number of new cases. By examining these phases, we identify the various waves of the pandemic, indicating periods where the health crisis has a significant impact. This comparative analysis highlights the time lags between countries as they transition through these different critical stages and navigate the waves of COVID-19.

The COVID-19 pandemic and tuberculosis have epidemiological similarities, being transmitted airborne, favored by direct contact, crowded environments and vulnerable biological status. We performed a retrospective study of 45 cases of pulmonary tuberculosis associated with COVID-19 (TB+COV+) compared to 45 cases with tuberculous monoinfection (TB+COV-), hospitalized during 2021-2022. The demographic characteristics were similar in the two groups, predominating men, a median age of 51 years, living in rural areas, medium level of education and smoking. Common symptoms of the two groups were cough, weight loss, profuse sweating, loss of appetite and hemoptysis, while fever, headache, myo-arthralgias and digestive symptoms characterized the TB+COV+ forms. The scores of radiological lesions in the TB+COV+ compared to TB+COV- group were significantly higher and persistent, revealing more frequent bilateral extensive lung lesions. There were no significant differences in the biological parameters between the two groups. Mortality was 2.2%, regardless of the association of COVID-19. The frequency of infections with Clostridioides difficile was higher in TB+COV+ cases. In conclusion, the co-infection of COVID-19 had an impact on the clinical and biological expression of tuberculosis diagnosed in a pandemic context.

Background Research in the subject of the influence of SARS-CoV-2 mechanisms on human’s homeostasis remains actual problem. Particular interest is the study of pathomorphological changes in the appendix in children with COVID-19. Objectives Aim of the study: morphological and molecular biological evaluation of the appendix in children of different age groups with COVID-19. Methods Groups were formed on the basis of anamnestic, clinical and morphological data: I (n = 42; aged 2 to 18 years, average - 10.8 years) – with an established clinical diagnosis: coronavirus infection (COVID-19; PCR+); II (n = 55; aged 2 to 18 years, average - 9.7 years) – with a confirmed clinical diagnosis of acute appendicitis; collected before the onset of the COVID-19 pandemic in 2017-2019; III (n = 38; aged 2 to 18 years, average - 10.3 years) - control group. Histological and immunohistochemical studies were conducted using primary antibodies to CD3, CD4, CD68, CD163, CD20, CD138 and to pro-inflammatory (IL-1, IL-6) and anti-inflammatory (IL-4, IL-10) cytokines. Results In most samples of appendix in children with COVID-19 were discovered signs of destructive phlegmonous-ulcerative and gangrenous appendicitis. An increase in CD3+, CD4+, CD68+, CD163+, CD20+ CD138+ immunocompetent cells was found in the appendix of children with COVID-19. As well, there is an increase in pro-inflammatory (IL-1, IL-6) and anti-inflammatory (IL-4, IL-10) cytokines. Conclusions The aforementioned pathological and immunohistochemical changes were more pronounced in the group of children aged 6-12 years (childhood).

COVID-19 has become a pandemic which resulted in measures being taken for health and safety of people. The spreading of the disease was particularly evident in indoor spaces, where people tend to get overcrowded. One such place is the airport where a plethora of passengers flow to common places, such as coffee shops, duty free shops as well as toilets and gates. Guiding the passengers to less overcrowded places within the airport may be a solution to less spreading. In this paper we suggest a passenger routing algorithm whereby the passengers are guided to less crowded places by using a weighting factor, which is minimised to accomplish the desired goal. We modeled a number of shops in an airport using the AnyLogic software and we tested the algorithm showing that the exposure time is less with routing and that the people get appropriately spread to the common spaces, thus, preventing overcrowding.

Surface Plasmon Resonance (SPR) technology has been known as a powerful tool for studying biomolecular interactions because it offers real-time and label-free multiparameter analysis with high sensitivity. This article summarizes the results that have been obtained from the use of SPR technology in studying the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutations. This paper will begin by introducing the working principle of SPR and the kinetic parameters of the sensorgram which include the association rate constant (ka), dissociation rate constant (kd), equilibrium association constant (KA), and equilibrium dissociation constant (KD). At the end of the section, we will summarize kinetic data on the interaction of SARS-CoV-2 with different variants with various ligands which were obtained from the results of SPR signal analysis. These affinity-related kinetic data are very useful both in drug discovery for therapeutic purposes and in the detection of SARS-CoV-2.

In the field of modeling social systems, the use of agent-based models (AM) has become a powerful tool for understanding processes occurring in society, in particular, for studying the spread of infections among the population. The agent model is based on a synthetic population consisting of agents, their interactions and sometimes the territory in which the interaction occurs. The choice of an appropriate method for creating such artificial populations and the selection of parameters becomes a key issue affecting the realism of the model and its ability to reflect real-world scenarios. This article delves into the interplay between agent-based modeling, synthetic population construction, and parameter selection, offering our insight into the complex process of modeling infectious disease dynamics. The review concludes with an exploration of extending the Covasim model [1] to experiments in computational epidemiology. Covasim, a dynamic transmission modeling tool, is known for its ability to adapt to different scenarios and offers predictive information critical for managing epidemiological situations. The Covasim model could include improvements to better simulate real-world epidemic conditions, including a revised transmission strategy to account for accumulation through daily contacts. In addition, we propose to add a module for intercity travel and a visualization package that will significantly expand the functionality of Covasim. These improvements make Covasim a more versatile and efficient tool for modeling and analyzing epidemic processes.

Although COVID-19 primarily affects the respiratory system, it can have various effects on other organs, including the cardiovascular system. COVID-19 can lead to a prothrombotic status, promoting bloodclotting, which can potentially affect native vessels and implanted de-vices. The exact mechanisms by which it leads to increased clotting are not yet fully understood but may involve inflammation, endothelial dysfunction, and a hyperactive immune response. In the present report, we describe a case of an acute aortic stent-graft thrombosis four days after resolution of Sars-Cov2 infection. The patient required emergent explantation of the stent-graft, after the failure of endovascular bailout procedures.

AI-based approaches are increasingly being used to revolutionize vaccine development for COVID-19. Small molecules, peptides, and epitopes are being collected for therapy discovery, which could also direct AI-based models, screening, or generation [1]. AI-based models are being used for drug discovery and vaccine development, and pre-existing data is being leveraged through machine learning approaches for COVID-19 drug discovery and vaccine development [1]. The best candidate targets for future treatment development are being identified and evaluated using AI-based models [1]. AI-based approaches can be used to overcome challenges in manufacturing, storage, logistics, and safety and efficacy issues related to different vaccine candidates for COVID-19 [2]. AI algorithms can help identify the best vaccine candidates for COVID-19 while considering the efficiency of antigenic peptides for immune response generation [2]. The presentation of antigenic peptides by major histocompatibility complex (MHC) class II molecules is the first step after COVID-19 vaccine administration for any vaccine-induced immune response [2]. Thus, AI-based models are being used to identify the best vaccine candidates for COVID-19 and to ensure that the vaccine-induced immune response is efficient and safe. The utilization of AI-based methods to address logistical, manufacturing, storage, safety, and efficacy issues regarding several COVID-19 vaccine candidates will be examined in this study. Additionally, while considering the effectiveness of antigenic peptides for the induction of an immune response, we will determine the best potential targets for the next treatment development and assess how AI-based models can help discover the best vaccine candidates for COVID-19. This research ultimately intends to offer insights into how AI-based techniques can transform COVID-19 vaccine development and how they can be applied to address vaccine development issues. In this paper, we focus on recent advances in using artificial intelligence to develop COVID-19 drugs and vaccines, as well as the potential of intelligent training in discovering COVID-19 therapeutics, highlighting potential challenges and solutions.

Body mass index has been studied as one of the factors that negatively influences COVID-19. In this work we intend to analyze this influence. A representative sample of the population of Beira Interior was used (around 2%), to which immunity research and a socio-demographic survey were carried out. It was found that obesity influences the vaccination rate, and all other variables analyzed were not influenced by the body mass index.

The coronavirus disease (COVID-19) is a respiratory tract infection caused by the new virus SARS-CoV-2. In March 2020, the World Health Organization (WHO) declared a worldwide COVID-19 pandemic. Since then, there has been a rush to find preventative or curative treatment. This arrived with the appearance of the COVID-19 vaccine, months after the declaration of the pandemic. In the setting of global COVID-19 immunization, there have been reports of rare skin immune-mediated diseases (IMD) after COVID-19 vaccination, particularly systemic sclerosis. Systemic sclerosis (SSc) is the most reported new onset IMD following messenger RNA (mRNA) COVID-19 vaccination. The pathogenesis of SSc is not fully understood, and the diagnosis is based on clinical symptoms. We report a 54-year-old male, with no prior history of autoimmune disorder, with rapid and progressive skin thickening (Modified Rodnan skin score 30/51), weeks after his mRNA COVID-19 vaccination. Antinuclear antibodies (ANA) showed a strongly positive nuclear fine-speckled pattern, but no SSc autoantibodies were found. The patient was diagnosed with SSc based on the persistence of autoantibodies and the clinical criteria according to the 2013 American College of Rheumatology/European League Against Rheumatism classification. Due to the proximity of the two events, we hypothesized a cross-reaction between COVID-19 vaccination and, in genetically predisposed patients, an emergence of systemic sclerosis. Our case suggests a potential relationship between the mRNA COVID-19 vaccine and new-onset autoimmune diseases. Physicians should be aware of this possible association.

(1) Background: Older people hospitalized with Covid-19 can reduced the capacity to walk. However, the prevalence of impairment of ambulation capacity still need to be established. Objective: To estimate the prevalence and identify the risk factors associated with the impairment of ambulation capacity at hospital discharge of older people with Covid-19. (2) Methods: A retrospective cohort study. Included age > 60 years, both sexes, hospitalized due to Covid-19. Clinical data was collected from the medical records. Ambulation capacity prior to Covid-19 infection was assessed through the patient report from his relatives. Multiple logistic regressions were performed to identify the risk factors associated with the impairment of ambulation at hospital discharge. (3) Results: Data from 429 older people were randomly. Among the 56.4% who were discharged, 57.9% had reduced ambulation capacity. Factors associated with reduced ambulation capacity at discharge were hospital stay higher than 20 days (OR: 3.5) and dependent ambulation capacity prior to Covid-19 (OR: 11.3). (4) Conclusion: More than half of the older people who survived hospitalized due to Covid-19 had reduced ambulation capacity at hospital discharge. Impaired ambulation prior to the infection, and a longer hospital stay were risks factors for reduced ambulation capacity.

Background: The global pandemic of coronavirus disease 2019 (COVID-19) resulted to many deaths from fulminant respiratory failure. Chronic obstructive pulmonary disease (COPD) is the leading cause of morbidity and mortality worldwide. There has been great concern regarding the impact of COPD on COVID-19 illness. Methods: Data from the Philippine CORONA Study were analyzed to determine the association of COPD and COVID-19 in terms of mortality, disease severity, respiratory failure, mechanical ventilation, and lengths of stay in the intensive care unit (ICU) and hospital. The influence of smoking on COVID-19 disease severity and mortality were also reviewed. Results: A total of 10,881 patients were included in the study and 156 (1.4%) patients had been diagnosed with COPD. Majority of COVID-19 patients with COPD had other existing comorbidities: hypertension, diabetes mellitus, chronic cardiac disease, and chronic kidney disease. COPD patients more commonly present with severe or critical COVID-19. COPD patients with COVID-19 were at higher risk to experience in-hospital mortality, respiratory failure, and to be admitted in the ICU. Smokers were more likely to present with higher COVID-19 severity and experience in-hospital mortality. Conclusion: Our study supports that the growing evidence that COPD among COVID-19 patients is a risk for higher mortality, more severe form of COVID-19, higher ICU admission, and higher respiratory failure needing ventilatory support. Smoking increases risk for developing severe COVID-19 and mortality.

Introduction: Real-world safety studies can provide important evidence on the thromboembolic risk associated with COVID-19 vaccines, considering that millions of people have been already vaccinated against COVID-19. In this study, we aimed to estimate the incidence of thromboembolic events after COVID-19 vaccination and to compare the Oxford–AstraZeneca vaccine with other COVID-19 vaccines. Methods: We conducted a retrospective real-world safety study using data from two different data sources: the Italian Pharmacovigilance database (Rete Nazionale di Farmacovigilanza, RNF) and the Campania Region Health system (Sistema INFOrmativo saNità CampanIA, SINFONIA). From the start date of the COVID-19 vaccination campaign (December 27th, 2021) to September 27th, 2022, information on COVID-19 vaccinations and thromboembolic evets were extracted from the two databases. The reporting rate (RR) and its 95% confidence interval (95%CI) of thromboembolic events for 10,000 doses was calculated for each COVID-19 vaccine. Moreover, the odds of being vaccinated with the Oxford–AstraZeneca vaccine vs. the other COVID-19 vaccines in cases with thromboembolic events vs. controls without thromboembolic events were computed. Results: A total of 12,692,852 vaccine doses were administered in Campania Region, of which 6,509,475 (51.28%) were in female and mostly related to the Pfizer-BioNtech vaccine (65.05%), followed by Moderna (24.31%), Oxford–AstraZeneca (9.71%), Janssen (0.91%), and Novavax (0.02%) vaccines. A total of 641 ICSRs with a COVID-19 vaccines and a vascular events were retrieved from the RNF for the Campania Region, of which 453 (70.67%) were in female. Most ICSRs reported the Pfizer-BioNtech vaccine (65.05%), followed by Oxford–AstraZeneca (9.71%), Moderna (24.31%), and Janssen (0.91%). A total of 2,451 events were reported in the ICSRs (3.8 events for ICSRs) of which 292 were thromboembolic events. The highe RRs of thromboembolic events were found with the Oxford–AstraZeneca vaccine (RR: 4.62, 95%CI: 3.50-5.99) and Janssen vaccine (RR: 3.45, 95%CI: 0.94-8.82). Thromboembolic events were associated with a higher likelihood of exposure to the Oxford–AstraZeneca vaccine compared to Pfizer-BioNtech (OR: 6.06; 95%CI: 4.22-8.68) and Moderna vaccines (OR: 6.46; 95%CI: 4.00-10.80). Conclusion: We observed a higher reporting of thromboembolic events with viral-vector based vaccines (Oxford–AstraZeneca and Janssen) and an increased likelihood of being exposed to the Oxford–AstraZeneca vaccine compared to the mRNA vaccines (Pfizer-BioNtech and Moderna) among thromboembolic cases.

During the pandemic, assisted reproductive treatments suffered from major disruptions in their terms due to the restrictions imposed. The objective of this study is to evaluate the level of anxiety of women whose treatments were either suspended or delayed. Methods: Descriptive cross-sectional study conducted between April and May 2020. The State-Trait Anxiety Inventory was applied in a Spanish adapted version. The research also included social, personal, and work aspects which may be involved in the challenging situation. Results: A total of 115 patients participated in the study (73.7%). Women showed a mean in trait anxiety of 17.79 (SD = 8.80) and a mean in state anxiety of 19.95 (SD = 9.08). Neither the type of treatment nor the time of infertility are predictors of trait anxiety or state anxiety. More age pressure and more worry were associated with more trait and state anxiety (p<0.001). The most common emotional reactions to discontinuation of fertility treatments were sadness and anxiety. Conclusions: Discontinuation of fertility treatments due to confinement restrictions had a negative impact on the mental health of women who were following a process of assisted reproduction treatment, increasing their levels of emotional distress and anxiety.

The anti-Covid19 vaccination campaign has been fortified on the positive effects that immunization is bringing the nations, since infection rates, hospitalizations, and deaths have been falling according to the data in constant disclosure by official government organs and the channels of communication. In Brazil, the effective and free National Vaccination Program haven’t prioritized patients with rare diseases, who have extreme comorbidities, and who had to follow the calendar prepared by the government. The problematic question is why these “rare people” weren´t considered priorities. The understanding of the reasons and the resumption of the debate about the rights of patients with rare diseases justify this study, which sought to be based on regular descriptors issued by official government agencies and by critics of rare disease issues in debates made in scientific articles. We sought to respond to the following objectives: analyze dispensed care of rare disease patients in the vaccination campaign anti-Covid-19; identify the procedures implemented by the National Vaccination Plan for the Brazilian population over 18 years of age; describe the panorama of the pandemic disease since its discovery to the mutations already disseminated; and evaluate the effectiveness of the plan implemented from the perspective of “rare person”.

In this article, ‎we examine an allocation issue faced by European Health Union (EHU)‎. ‎Given this situation, ‎we introduce the issue of vaccine selection. ‎The model proposed in this paper helps to implement vaccination optimally using matching theory. ‎By adopting the mechanism presented in this article, ‎this is done more easily and more quickly, ‎so that mortality in society is lower and public satisfaction is increased. ‎This is similar to the issues analyzed in the literature on the design mechanism of non-perishable goods.

ATC is a rare cancer with a slightly growing incidence and a poor prognosis determined by the delay of treatment, usually revealed by an enlarging goiter with compressive symptoms and, more rarely, by inflammatory and thyrotoxic symptoms, a clinic entity called malignant pseudothyroiditis (MPT) mimicking subacute thyroiditis (SAT). With the advent of COVID-19 pandemic, many cases of COVID-19 related SAT were described with the usual clinical presentation enriched by the COVID-19 symptoms, leading to the emergence of atypic clinical pictures. We present the case of a 60-year-old patient who developed, one month after a COVID 19 acute infection, a clinical presentation of SAT with atypical ultrasound features leading to the diagnosis of MPT; histological atypia was misleading, finally making precise diagnosis was difficult. To our best knowledge, this is the first ever reported case of MPT mimicking COVID-19 SAT. We reviewed thirty five cases published to date and discuss the mechanisms underlying MPT physiopathogenesis and the ultrasound and histological features. We point out the similarities between MPT and SAT and the role of ultrasound at clinical presentation workup. Finally there are two key points to remind: First, to perform neck ultrasound in any painful goiter and, in case of atypia, perform a US guided core-needle biopsy, a complementary CT-scan and quickly refer the patient to an expert center. Second, always think that COVID-19 infection is a recent entity and be aware that it can influence the clinical presentation of any disease.

The COVID-19 pandemic has expanded globally and caused serious consequence in both health system and the economy. MPV is one of two oral antivirals for COVID-19 with mild-to-moderate symptoms that have received FDA approval so far. This study aims to evaluate the cost-utility of using MPV in COVID-19 treatment. To compare the utility costs of MPV and non-MPV treatments for COVID-19 patients, we used a decision tree model. Data on clinical efficacy, cost, and quality of life were gathered from previous studies. The incremental effective cost ratio (ICER) calculated based on costs incurred and quality-adjusted life years (QALY), was considered as primary out-come. The total cost of MPV treatment and not using MPV was 15,362,516 VND (618 USD) and 15,771,262 VND (634 USD), respectively. The estimated QALY with using-MPV was 28.33, while without MPV was 19.72. The ICER was dominant, resulting in savings of 47,453 VND/QALY (1.9 USD). MPV is a cost-effective medication used to treat COVID-19. In mild-to-moderate COVID-19 patients, MPV considerably lowers costs and improves quality of life. However, several clinical factors of the drug still need to be taken into account.

Rationale: The possible effect of Particulate Matter (PM10 and PM2.5 of diameter 10 and 2.5 µm respectively) levels on Covid-19 mortality is now well established. However, time-evolution of Covid-19 mortality according to PM2.5 levels has been scarcely investigated. Aim: To understand this relationship at the European level for the period 2020 (beginning) - 2022 (end). Methods: 16 representative locations in Europe (81 million people) with heterogeneous levels of PM2.5 (µg.m-3), from low to high. PM2.5 levels were assessed by various methods, and Covid-19 mortality was reported by Johns Hopkins University. Results: The trend of Covid-19 mortality vs. PM2.5 levels varied among locations. Overall, the estimated mean value was of a 40±20% mortality increase per 1 µg.m-3 PM2.5 increase. The stronger the positive gradient of the PM peak, the stronger the positive gradient of the Covid-19 mortality. Exposure to several PM peaks during about a 2-month period was the main contributor to Covid-19 mortality increases. Conclusion: Our data confirm a temporal relation between PM2.5 exposure and Covid-19 mortality, considering a 2-month integration-time for pollution events. Number-concentrations of PM should be used in the future rather than the PM2.5 mass-concentrations (µg.m-3) with the consideration of PM composition to better explain this finding.

The SARS coronavirus 2 (SARS-CoV-2) is the causative agent of the 2019 coronavirus disease (COVID-19) pandemic that has executed 6.9 million people and infected over 765 million. It’s become a major worldwide health alarm and is also known to cause abnormalities in various systems, including the hematologic system. COVID-19 infection primarily affects the lower res-piratory tract and can lead to a cascade of events, including a cytokine storm, intravascular thrombosis, and subsequent complications such as arterial and venous thromboses. COVID-19 can cause thrombocytopenia, lymphopenia, and neutrophilia, which are associated with worse out-comes. Prophylactic anticoagulation is essential to prevent complication and death rate associated with the virus's effect on the coagulation system. It is crucial to recognize these complications early and promptly start therapeutic anticoagulation to improve patient outcomes. While rare, COVID-19-induced disseminated intravascular coagulation exhibits some similarities to DIC induced by sepsis. LDH, D-dimer, ferritin, and CRP biomarker are often increase in serious COVID-19 cases and poor prognosis. Understanding the pathophysiology of the disease and identifying risk factors for adverse outcomes is critical for effective management of COVID-19.

Patients diagnosed with cancer are less frequently covered by preventive measures for cardiovascular diseases. The frequent co-occurrence of these diseases makes it necessary to apply parallel diagnostics and cardiological treatment with anti-cancer therapy. Case report: We present a case of a 73-year-old former smoker with hyperlipidemia, type 2 diabetes, and arterial hypertension, after a partial right nephrectomy in 2005 due to kidney cancer, diagnosed with SARS-COV-2 infection in April 2022. Follow-up chest imaging showed a 20 mm focal lesion in the left lung further classified as a small cell neuroendocrine carcinoma. Unexpectedly the patient was hospitalized for ST-segment elevation inferior left ventricular (LV) myocardial infarction treated successfully with coronary angioplasty, however heart failure (HF) with reduced left ventricle ejection fraction was diagnosed. One month later patient required another hospitalization due to the HF decompensation and cardiological treatment was optimized with flozin addition to the standard HF therapy. After cardiological approval chemotherapy was initiated with the cisplatinum-etoposide regimen and continued for 6 months without HF decompensation and significant deterioration of renal function. After that, the patient underwent radical radiotherapy. Follow-up chest computed tomography scans showed regression of the neoplastic lesion. Conclusions: Coincidence of newly recognized cancer and infection might contribute and provoke serious cardiological events . To reduce the risk of cardiovascular complications, early periodic cardiological surveillance and optimal pharmacotherapy are required.

The outbreak of COVID-19 in 2020 caused significant disruptions to global shipping and the world economy. This paper aims to investigate the impact of the pandemic on global shipping by analyzing the Baltic Dry Index (BDI). The BDI is a metric that reflects the worldwide shipping costs and directs related to supply and demand conditions, making it an indicator of economic production. The study utilizes data from 2019 to 2021, before and after the outbreak of COVID-19, and considers 13 independent variables, including raw materials, energy, stock market indexes, global port calls, and confirmed COVID-19 cases to investigate how to influent the BDI. The study employs stepwise regression to select variables and build models before and after the pandemic. The findings reveal that the key factors affecting the freight index BDI before the outbreak are: international scrap steel prices, iron ore prices, and the Commodity Research Bureau Index. However, after the COVID-19 outbreak, the factors affecting the BDI changed to the Shanghai Index, global port calls, and the number of confirmed COVID-19 cases.

The coronavirus disease–2019 pandemic created major obstacles for effective smoking cessation programs by significantly limiting access to healthcare. This retrospective study aimed to assess the effectiveness of a self-developed smoking cessation program during the pandemic. The program was based on remote lectures, educational interventions, and hybrid services provided by an outpatient clinic. We enrolled 513 participants between January 2019 and February 2022. Data on demographic characteristics, medical history, and smoking status at baseline and after at least 1-year follow-up were collected from medical records and a standardized self-developed questionnaire. Participants were classified into two groups according to their current smoking status. The smoking cessation rate at 1 year was 37%. Major predictors of smoking cessation were the place of residence, ability to refrain from smoking during severe illness, and the number of cigarettes smoked per day. The proportion of participants with high levels of nicotine dependence at baseline was 40.8% vs 29.1% at 1 year (p=0.003). In the group that did not quit smoking, there were more participants who smoked within 5 minutes after waking up, as compared with participants who quitted smoking (40.4% vs 25.4%; p=0.0004). Effective smoking cessation interventions can be performed using remote counseling and education.

Preventive behavior is one of the main strategies to contain the spread of the coronavirus, understand the factors that influence adherence or hesitation to protective measures and the way the population behaves during a health crisis is of great importance. Aim: To analyze the factors associated with adherence to protection measures against Covid-19 in Brazil. Method: cross-sectional study, survey type online, between the period of August 2020 and February 2021. The population included in the study were Brazilians, aged 18 years or older. Non-probabilistic sampling was used to obtain the sample. The data was stored on the "Redcap" platform and analyzed in a descriptive and inferential approach. Results: The sample consisted of 1,516 people, women adopted 10% more protective measures than men, people with higher education level and higher income, within the age group between 40-59 years, were those who most adhered to the measures imposed by health agencies. Carrier of Asthma, Diabetes Mellitus, Systemic Arterial Hypertension, Obesity and smoking were factors that increased the adherence of protective measures in the fight against COVID-19. Conclusion: Being female, aged between 40 and 59 years, higher education, smoking, not having a religion, having health insurance, and being a carrier of chronic diseases were associated with greater adherence to protective measures against COVID-19.

The COVID-19 pandemic has posed an unprecedented challenge to healthcare and the available solutions are unsatisfactory. Classical homeopathy may have a role to play in alleviating this burden. Covid cases treated with homeopathy was curated with the intention to provide basic information for further studies. The results are promising although far from being definitive. 367 patients considered were for statistical analysis, the mean age of the participants was 42.75 years, and males and females were 166 and 201 respectively. The mean follow-up period was 6.5 (SD 5.3) days, with a median of 1 homeopathic remedy used per case. 192 patients were diagnosed by RT–PCR, 111 by the WHO clinical criteria and 64 via retrospective antibodies. According to the WHO criteria, 255 were confirmed cases, 61 were probable cases, and 51 were suspected cases. It was seen that 73.8% of covid patients improved under homeopathic treatment, even those among severe disease 78.6%. Correlational analyses showed that presence of fever was associated with more likelihood of improvement and increasing age and a greater number of homeopathic remedies required in a case were associated negatively with improvement. However, it was seen that severe cases were more likely to improve under homeopathic treatment.

COVID-19 infection in the pediatric population usually leads to a mild illness, however, a rare but serious complication of MIS-C has been seen in children. MIS-C usually presents 2-4 weeks after COVID-19 infection or exposure, and rare reports have been documented in neonates. Vaccinations for COVID-19 have been approved for children 6 months and above in the United States, and recent reports suggest significantly low prevalence and risk of complications of MIS-C in vaccinated children compared to unvaccinated children. Vaccinations for COVID-19 are safe and recommended during pregnancy and prevent severe maternal morbidity and adverse birth outcomes. Evidence from other vaccine-preventable diseases suggests that through passive transplacental antibody transfer, maternal vaccinations are protective against infections in infants during the first 6 months of life. Various studies have demonstrated that maternal COVID-19 vaccination is associated with the presence of anti-spike protein antibodies in infants, persisting even at 6 months of age. Further, completion of a 2-dose primary mRNA COVID-19 vaccination series during pregnancy is associated with reduced risk for COVID-19–associated hospitalization among infants aged 6 months or less. Therefore, it can be hypothesized that maternal COVID-19 vaccination can reduce the risk of and severity of MIS-C in infants. In this article, we review the literature to support this hypothesis.

Severe Acute Respiratory Syndrome Coronavirus 2 commonly known as SARS-CoV-2 is the utmost challenging pandemic that attracted scientific community to discover therapeutics as well as vaccination solutions to control SARS-CoV-2. Different diagnostic and detection methods have been improved and re-introduced from the previous observations of SERS and MERS. Due to the high mortality rate and fast spread, researchers all around the globe gathered to develop an effective vaccine. The review article summarizes various types of vaccines, mutants of virus, strategies in tackling virus, vaccine development and its global distribution with the focus on the use of mix and match of vaccines to fight the virus. The reported studies depict the design and production of successful COVID-19 vaccines with good efficacy as the selected vaccine population embrace high-risk personages i.e. above the age of 60, frontline workers and other essential service workers. We have targeted at delivering an outline of the determinations devoted to an effectual vaccine for novel Covid-19 that has restricted the domain by means of human health, economy, as well as life.

Cryptocurrencies are now the most popular investment instruments among millenials. Crypto offers great returns in a short period of time. Prior to COVID-19, Crypto experienced significant price fluctuations accompanied by an increase in the number of high transaction volumes. This situation was disrupted by the presence of the COVID-19 which made the world economy devastated, marked by the decline of stock prices in the world, especially in Indonesia. A paired test was conducted in this study to compare the state of Crypto before and during COVID-19 with the variables of Risk, Transaction Volume, Return, and Sharpe Performance. The results showed that there was a significant difference in the variables of Transaction Volume and Return. However, there was no significant difference in the Risk and Sharpe performance before and during COVID-19. This study shows that despite the COVID-19 pandemic, the enthusiasm of investors who transact crypto assets is not affected and they still get returns in accordance with the investments made. The high risk will be followed by a high standard deviation, so that the Sharpe Performance is small. Cryptocurrencies still have many gaps to research, such as regulation, so that many countries have not legalized Crypto transactions. If there is no regulation for Crypto, it is certain that an increase in cybercrime harms crypto investors and threatens global financial stability. Nevertheles, with or without COVID-19, investment transactions gain and lose based on confidence in the limited market. Therefore, the success of confidence fluctuations in crypto encourages the emergence of alternative coins created by investors to conduct an Initial Coin Offering (ICO).

Objective: Several authors have analyzed the impact of the pandemic on the incidence rates of different conditions. Our aim was to analyze the impact of the COVID-19 pandemic on primary care new diagnoses of respiratory diseases. Methods: This was an observational retrospective study performed to describe the impact of COVID-19 pandemic on primary care new diagnosis of respiratory diseases other than lung cancer. Incidence rate ratio between pre-pandemic and pandemic period was calculated. Results: We found an decrease in the incidence of respiratory conditions (IRR 0.65) during the pandemic period. When we compared the different groups of diseases according to ICD-10, we found a significant decrease in the number of new cases during the pandemic period, except in the case of pulmonary tuberculosis, abscesses or necrosis of the lungs and other respiratory complications. Instead, we found increases in new diagnoses of flu and pneumonia (IRR 2.17) and respiratory interstitial diseases (IRR 1.41). Conclusion: There has been a decrease in new diagnosis of most respiratory diseases during the COVID-19 pandemic. The real clinical impact of this situation is still unknown. Large-scale real-life studies will make it possible to evaluate the long-term true impact of COVID-19 pandemic on the respiratory diseases management.

It is no news that the COVID–19 pandemic has affected many persons in different ways. As the number of reported cases rises across the globe, efforts are geared towards production and administration of effective vaccines for the disease. However, many developing countries are faced with the dilemma of how to slow the spread and flatten the curves of the disease as the available vaccines are not enough. Interestingly, the dynamics of the disease can be analysed to get useful insights to enhance the making of suitable preventive policies that will slow the spread, ultimately flatten the curves of the disease and also help in managing any future occurrence. In this work, the aim is to analyse the dynamics, and estimate the basic reproduction number of the second wave of the pandemic in Nigeria using a Susceptible-Infected-Recovered-Deceased (SIRD) compartmental–based model. The dynamics of the disease is described by a system of nonlinear ordinary differential equations. The model takes into consideration the current control policies in place - social distancing, mask usage, personal hygiene and quarantine. Available data provided by Nigeria Centre for Disease Control (NCDC), World Health Organization (WHO) and Wolfram Data Repository were used for the computations. The Quasi–Newton algorithm was implemented in fitting the proposed model to the available data and a sensitivity analysis was presented. Major parameters - effective contact rate, average recovery time, average mortality rate, and overall effectiveness of the control policies - influencing the dynamics of the disease, and the basic reproduction numbers were estimated. The turning points of the disease during the second wave were also obtained. The proposed model gave estimated values for the parameters influencing the spread of the disease. Also, the measure of the overall effectiveness of the current control policies gave insight into how effective the measures are.

COVID-19 national spikes had been reported at varying temporal scales as a result of differences in the driving factors. Factors affecting case load and mortality rates have varied between countries and regions. We investigated the association between various socio-economic, demographic and health variables with the spread on COVID-19 cases in Eswatini using the maximum likelihood estimation method for count data. A generalized Poisson regression (GPR) model was fitted with the data comprising of fifteen covariates to predict COVID-19 risk in Eswatini. The results showed that variables that were key determinants in the spread of the disease were those that included the proportion of elderly above 55 years at 98% (95% CI: 97%-99%) and the proportion of youth below 35 years at 0.08% (95% CI: 0.017%-38%) with a pseudo R-square of 0.72. However, in the early phase of the virus when cases were fewer, results from the Poisson regression showed that household size, household density and poverty index were associated with COVID-19. We produced a risk map of predicted COVID-19 in Eswatini using the variables that were selected at 5% significance level. The map could be used by the country to plan and prioritize health interventions against COVID-19. The identified areas of high risk may be further investigated in order to find out the risk amplifiers and assess what could be done to prevent them.

This study explored the living situations, financial conditions, religious obligations, and social distancing of Muslims during the covid 19 pandemic. In total, 20 Muslim community members living in the Kanto region were recruited, 15 of them were included in the in-depth qualitative and five in the focus group interviews. The Snowball method was used, and the questionnaires were designed into four themes. The audio/video interviews were conducted via Zoom and NAVIO was used to analyse the data thematically. The major Muslim events were cancelled, and the recommended physical distancing was maintained during the prayers at home and in the mosques. The Japanese government's financial support to each person was a beneficial step towards social protection, which was highlighted and praised by every single participant. Regardless of religious obligations, the closer of all major mosques in Tokyo demonstrates to the Japanese community how serious they are about adhering to the public health guidelines during the pandemic. This study highlighted that the pandemic has affected the religious patterns and behaviour of Muslims from inclusive to exclusive in a community and narrated the significance of religious commitments.

Majority of published articles have talked about the challenges faced by students in learning online however, little has been talked about what the teachers have gone through especially during these times of the pandemic. This paper discusses the factors university teachers face when teaching online. These factors include accessibility to the internet, level of interaction between teachers and students, costs incurred, availability of training and academic policies kept in place to enhance effectiveness of teaching online. These are further divided into personal, social and economic factors where the teachers’ age, gender, remuneration, availability of resources, location and the economic status of the country is discussed in relation to the effectiveness of online learning. Upon carrying out a literature review on articles written on the effectiveness of online learning with the main focus being teachers, it was noted that the main factors affecting the effectiveness of online learning was the availability of internet connection and training provided to teachers. In Kenya, majority of the rural areas lack access to the internet and devices to learn online which makes it difficult for a teacher to teach effectively given the pandemic constraints. This study sheds light on the need for institutions and governments to take input from their teachers and train them on how to make online learning more effective. It also shows the status of universities in Kenya which had to shift to learning online due to the pandemic. Majority of them took time to adapt to this new change due to the discussed factors. Therefore it is recommended that the Government should train teachers and address the issue of lack of internet and electricity in Kenya.

The newly discovered coronavirus (COVID-19) has disrupted traditional methods of conducting research, particularly qualitative research. However, there remains a number of methods by which qualitative data can still be collected. These include the use of digital voice, video, and text-based tools, online surveys, and content analysis. Text-based sources can help to overcome the limitations of time and space, and also can be cost-effective. This chapter draws from data collected from 12 participants across Zimbabwe and demonstrates how these tools can be used to generate data or to sample data that is already available to satisfy research questions and meet research objectives. It recommends researchers to experiment with new ways of collecting qualitative data while also observing safety protocols and ethical considerations.

While the long-term effects of COVID-19 are yet to be determined, its immediate impact on crowdfunding is nonetheless significant. This study takes a computational approach to more deeply comprehend this change. Using a unique data set of all the campaigns published over the past two years on GoFundMe, we explore the factors that have led to the successful funding of a crowdfunding project. In particular, we study a corpus of crowdfunded projects, analyzing cover images and other variables commonly present on crowdfunding sites. Furthermore, we construct a classifier and a regression model to assess the significance of features based on XGBoost. In addition, we employ counterfactual analysis to investigate the causality between features and the success of crowdfunding. More importantly, sentiment analysis and the paired sample t-test are performed to examine the differences in crowdfunding campaigns before and after the COVID-19 outbreak that started in March 2020. First, we note that there is significant racial disparity in crowdfunding success. Second, we find that sad emotion expressed through the campaign's description became significant after the COVID-19 outbreak. Considering all these factors, our findings shed light on the impact of COVID-19 on crowdfunding campaigns.

Many inflammatory mechanisms are involved in the pathophysiology of COVID-19 infection. COVID-19 inhibits IFN antiviral responses, so we should expect an out-of-control viral replication. “Cytokine storms” occur due to the over-production of pro-inflammatory cytokines after an influx of neutrophils and monocytes/macrophages and may be responsible for the immunopathology of the lung involvement. Several cascades have been reported in the activation process of NF-κB. In this paper, to find new therapeutic options for COVID-19 infection, we reviewed some natural products that could potentially inhibit the NF-κB pathway. We found that sevoflurane, quercetin, resveratrol, curcumin, KIOM-C, bergenin, garcinia kola, shenfu, piperlongumine, wogonin, oroxylin, plantamajoside, naringin, ginseng, kaempferol, allium sativum L, illicium henryi, isoliquiritigenin, lianhua qingwen, magnoflorine, and ma Huang Tang might be effective in inhibiting the NF-KB pathway. These natural products could be helpful in the control of COVID-19 infections. However, larger clinical trials are needed to ascertain the efficacy of these products fully.

Pneumonia is a leading cause of death worldwide, and one of the most significant approaches to diagnose pneumonia is Chest X-ray (CXR) since it was used in clinical scenes. Convolutional neural networks (CNNs) have been widely used in computer vision community. Along with the development of CNNs, we want to make use of CNNs to recognize CXR of people who get pneumonia and make classification. It is important, especially during epidemic period. In this paper, we present a new type of residual learning framework, PEPX-Resnet, which makes use of a type of lightweight residual, and apply this network to CXR dataset. The result shows that PEPX-Resnet is easier to optimize and can have better results, especially for COVID-19 cases. PEPX-Resnet could reach higher accuracy, f1 score and some other evaluations for CXR dataset.

The great lockdown of the current COVID-19 pandemic has significant consequences on the global Higher Education Studies (HES).To find the relevance of eLearning in the HES, our study calculates the economic costs of higher education during Covid-19 in Bangladesh, which includes both stu-dents’ cost and institutional cost. The study used a purposive random sample survey conducted on 105 students enrolled in higher education in different categories of institutions to identify the stu-dents’ cost during this pandemic. The institutional cost of higher education is analyzed by breaking down the budget allocated in the education sector in Bangladesh and reviewing the literature. The result indicates that the HES of Bangladesh experiences a huge economic cost due to this pandemic and the study found eLearning can reduce the economic impact of HES. In the post-COVID-19 world, higher education will never be the similar because many institutions that already had experi-ence a huge advantage from online education. The findings of the study might be helpful for the policymakers to frame effective education policies during any bizarre situation that creates huge cost in higher education sector.

Background: The aim of our study was to analyze the effect of socioeconomic inequalities, both at the individual and area of residence levels, on the probability of COVID-19 confirmed infection, and its variations across three pandemic waves. Methods: Retrospective cohort study. We included data from all individuals tested by COVID-19 during the three waves of the pandemic, from March to December 2020 (357,989 individuals). We studied the effect of inequalities on the risk of having a COVID-19 confirmed diagnosis after being tested using multilevel analyses with two levels of aggregation: individuals and basic healthcare area (BHA) of residence (deprivation level and type of zone). Results: Patient profile changed through the pandemic, with a predominance of low-paid employees living in deprived BHA. Workers with low salaries, unemployed and people on minimum integration income or who no longer receive the unemployment allowance, had a higher probability of COVID-19 infection than workers with salaries ≥€18,000 per year. Inequalities were higher in women and in the second wave. The deprivation level of BHA of residence influenced the risk of COVID-19 infection, especially in the second wave. Conclusions: There are inequalities in the risk of COVID-19 confirmed infection, both at individual and area level. It is necessary to develop individual and area coordinated measures in the control, diagnosis and treatment of the epidemic, in order to avoid an increase in the already existing inequalities.

Covid-19 has become a non-natural national disaster that affects the national resilience of the Indonesian state. In maintaining national resilience, the implementation of state defense is needed. This research aims to describe the awareness of defending the state of millennials during the current situation of the Covid-19 pandemic in Indonesia by using a quantitative approach with descriptive analysis methods with survey techniques. The results of this study indicate that most millennials are aware of the obligation to defend the state amid the current Covid-19 pandemic, namely by implementing health protocols such as preparing cleaning equipment, conducting social distancing, and working from home. However, there are still millennials who cannot run it for some reason. Based on the results of this study, it concluded that most millennials are aware of the obligation to defend the state during a pandemic by complying with health protocols as a form of state defense character.

The trace element copper (Cu) is part of our nutrition and essentially needed for several cuproenzymes that control redox status and support the immune system. In blood, the ferroxidase ceruloplasmin (CP) accounts for the majority of circulating Cu and serves as transport protein. Both Cu and CP behave as positive, whereas serum selenium (Se) and its transporter selenoprotein P (SELENOP) behave as negative acute phase reactants. In view that coronavirus disease (COVID-19) causes systemic inflammation, we hypothesized that biomarkers of Cu and Se status are regulated inversely, in relation to disease severity and mortality risk. Serum samples from COVID-19 patients were analysed for Cu by total reflection X-ray fluorescence and CP was quantified by a validated sandwich ELISA. The two Cu biomarkers correlated positively in serum from patients with COVID-19 (R=0.42, p<0.001). Surviving patients showed higher mean serum Cu and CP concentrations in comparison to non-survivors ([mean+/-SEM], Cu; 1475.9+/-22.7 vs. 1317.9+/-43.9 µg/L; p<0.001, CP; 547.2.5 +/- 19.5 vs. 438.8+/-32.9 mg/L, p=0.086). In contrast to expectations, total serum Cu and Se concentrations displayed a positive linear correlation in the patient samples analysed (R=0.23, p=0.003). Serum CP and SELENOP levels were not interrelated. Applying receiver operating characteristics (ROC) curve analysis, the combination of Cu and SELENOP with age outperformed other combinations of parameters for predicting risk of death, yielding an AUC of 95.0%. We conclude that the alterations in serum biomarkers of Cu and Se status in COVID-19 are not compatible with a simple acute phase response, and that serum Cu and SELENOP levels contribute to a good prediction of survival. Adjuvant supplementation in patients with diagnostically proven deficits in Cu or Se may positively influence disease course, as both increase in survivors and are of crucial importance for the immune response and antioxidative defence systems.

Along with the increasing number of Covid-19 cases, the development of false news or misinformation about Covid-19 -19 is getting bigger. This article aims to analyze public opinion about the various hoaxes that were widely spread in Indonesia during the pandemic. The method used is a mixture, namely literature review, in the form of searching for related journals regarding the distribution of hoaxes during the pandemic and conducting online surveys via a google form. The research conducted indicates that during the pandemic there were rapid spreads of fake news, it is proven with more than 45% of the participants who were often heard hoax news about Covid-19 on online media. From this evidence, it also can be discovered that hoax news can affect a person's belief in the Covid-19 virus.

Electronic Health Record (EHR) is being used in most healthcare institutions to preserve and share health records instead of a paper-based method. Data records must be exchanged amongst various parties and users' privileges to manage access to their records should also be provided. In addition to the basic standards of secrecy, confidentiality and integrity of information, these facts further demonstrate the need for interoperability and consumer control to access their personal data. Electronic Health Record (EHR) system faces issues of protection of data, trust and management issues. In recent Covid-19 pandemic, various applications, tools and websites were launched that stores records. Also, many personal records related to health need to be shared among different parties for early detection, contact tracing, monitoring and the future prediction that requires accurate and reliable data. Simultaneously, the citizens will be hesitant in providing their personal details due to privacy concerns and social stigma. Blockchain technology has arisen as a powerful technology that can offer the immutability, confidentiality and user access properties of stored information and provided distributed storage. This paper analyses the blockchain suitability in EHR and its further applications in efficient Covid-19 pandemic management.

After a long waited span, the whole world could see the ray of covid-19 vaccine to resist the planet to watch the death procession. But some country people especially the people of Bangladesh keep them aside to take the vaccination. This study aims to understand the perception towards the COVID-19 vaccination program in Bangladesh and the targeted subject is the university student as they are suffering highly depression nowadays. Higher education has been affected globally as a result of the COVID-19 pandemic in 223 countries. Moreover, for this pandemic situation, the university students can not complete their graduation which binds them to enter their professional career. Alike all of the developed countries, as well as developing countries, Bangladesh, also considered vaccination as an effective measure to protect the peoples from the Covid-19 virus. This study targeted three psychological factors of the university students and surveyed 322 students from the different universities in Bangladesh to understand their perception regarding vaccines. Moreover, it is seen that most of the students doubt the effectiveness of the vaccine which interrupts them from taking the vaccine willingly.

With the COVID-19 pandemic continuing and the resulting economic burden increasingly apparent, the Indonesian government began to prepare a "new normal" phase and make peace with COVID-19. From this new decision arises the question of the readiness of businesses and the industrial sector to resume operations amid COVID-19. This article aims to provide concise and precise information about the preparations that can be made by businesses to operate safely amid COVID-19 based on existing scientific studies and literatures. From the literature visits it can be concluded that transmission and danger of a COVID-19 pandemic can be prevented through: creation of infectious disease prevention and response plan, implementing basic infection prevention measures, policies and procedures for proper identification and isolation of sick people, applying flexibilities in policies, and protections in the workplace.

Rapid online surveys are an important tool in tracking the public’s knowledge and perceptions during infectious disease outbreaks. In June 2020, during the early phases of COVID-19 vaccines development, a survey had been conducted, aimed at assessing attitudes and opinions about vaccination of 885 Italian adults, in addition to their vaccine literacy levels (i.e. skills of finding, understanding and using information about vaccines). In January 2021, the same questionnaire has been administered to a similar population (n=160). Interactive vaccine literacy was significantly higher than in June 2020 (mean score 3.38 vs 3.27 respectively, P=.0021). The percentage of participants willing to be vaccinated against COVID-19 was assessed by the means of either-or questions, and was equally high in both surveys (>90%), which is quite reassuring, despite metrics based on categorical scales cannot identify hesitant subjects.

Objective: To investigate the association between deprivation and COVID-19 outcomes in Italy during pre-lockdown, lockdown and post-lockdown periods.Design: Retrospective cohort study.Setting: All municipalities in Italy with less than 50,000 population.Participants: 38,534,169 citizens and 222,875 COVID-19 cases reported to the Italian epidemiological surveillance were assigned to quintiles based on the deprivation index of their municipality of residence.Interventions: The COVID-19 pandemic during pre-lockdown, lockdown and post-lockdown from the 20th of February to the 15th of October of 2020.Main outcome measures: Multilevel negative binomial regression models, adjusting for age, sex, population-density and region of residence were conducted to evaluate the association between deprivation and COVID-19 incidence, case-hospitalisation rate and case-fatality. The association measure was the rate ratio.Results: During pre-lockdown, lockdown and post-lockdown, the incidence rate ratios (IRR) with 95% confidence interval (CI) in the most deprived quintile with respect to the least deprived quintile were 1.17 (95% CI 0.98 to 1.41), 1.14 (1.03 to 1.27) and 1.47 (1.32 to 1.63), respectively. In those three periods, the case-hospitalization IRR were 0.68 (0.51 to 0.92), 0.89 (0.72 to 1.11) and 0.99 (0.81 to 1.22) and the case-fatality IRR were 0.92 (0.75 to 1.13), 0.95 (0.85 to 1.07) and 1.02 (0.73 to 1.41), respectively.Conclusions: During lockdown and post-lockdown, but not during pre-lockdown, a higher incidence of cases was observed in the most deprived municipalities compared with the least deprived ones. No differences in case-hospitalisation and case-fatality according to deprivation were observed in any period under study.

The earlier analytical analysis (part A) of the Susceptible-Infectious-Recovered (SIR) epidemics model for a constant ratio k of infection to recovery rates is extended here to the semi-time case which is particularly appropriate for modeling the temporal evolution of later (than the first) pandemic waves when a greater population fraction from the first wave has been infected. In the semi-time case the SIR model does not describe the quantities in the past; instead they only hold for times later than the initial time t=0 of the newly occurring wave. Simple exact and approximative expressions are derived for the final and maximum values of the infected, susceptible and revovered/removed population fractions as well the daily rate and cumulative number of new infections. It is demonstrated that two types of temporal evolution of the daily rate of new infections j(tau) occur depending on the values of k and the initial value of the infected fraction I(0)=eta: in the decay case for k > 1-2 eta the daily rate monotonically decreases at all positive times from its initial maximum value j(0)=eta (1-eta). Alternatively, in the peak case for k<1-2 eta the daily rate attains a maximum at a finite positive time. By comparing the approximated analytical solutions for j(tau) and J(tau) with the exact ones obtained by numerical integration, it is shown that the analytical approximations are accurate within at most only 2.5 percent. It is found that the initial fraction of infected persons sensitively influences the late time dependence of the epidemics, the maximum daily rate and its peak time. Such dependencies do not exist in the earlier investigated all-time case.

The COVID-19 pandemic has caused ~ 2 million fatalities. Significant progress has been made in advancing our understanding of the disease process, one of the unanswered questions, however, is the anomaly in the case/mortality ratio with Mexico as a clear example. Herein, this anomaly is explored by spatial analysis and whether mortality varies locally according to local factors. To address this, hexagonal cartogram maps (hexbin) used to spatially map COVID-19 mortality and visualise association with patient-level data on demographics and pre-existing health conditions. This was further interrogated at local Mexico City level by choropleth mapping. Our data show that the use of hexagonal cartograms is a better approach for spatial mapping of COVID-19 data in Mexico as it addresses bias in area size and population. We report sex/age-related spatial relationship with mortality amongst the Mexican states and a trend between health conditions and mortality at the state level. Within Mexico City, there is a clear south, north divide with higher mortality in the northern municipalities. Deceased patients in these northern municipalities have the highest pre-existing health conditions. Taken together, this study provides an improved presentation of COVID-19 mapping in Mexico and demonstrates spatial divergence of the mortality in Mexico.

In January 2020, the World Health Organization declared a public health emergency and announced a new coronavirus disease (COVID-19), which would later go on to be declared as a pandemic, changing the global sphere and placing the economies of almost all countries under heavy stress. The airline industry, that had just begun recovering after facing crises one after another in the last two decades, from early 2000 due to 9/11, to the global financial crisis later, is now oce again facing an enormous challenge of closed borders and greater lockdowns due to the pandemic. Borders are closed, with very few planes are in the air, while the rest are grounded. The purpose of this paper is to give a conceptual understanding of the current pandemic situation and its consequences on the airline industry. The paper takes a unique perspective of human resource management (HRM) that is rarely used in the airline industry.

Background. The novel coronavirus (SARS-COV-2) and related syndrome (COVID-19) has required a worldwide measure of quarantine with severe consequences for millions of people. Methods. Since psychopathological consequences related to social restrictions have been reported, a systematic review according to Cochrane Collaboration guidelines and the PRISMA Statement was performed to quantify the effects of quarantine on mental health of adults. Major databases - Pubmed, Scopus, Embase, PsycInfo, and Web of Science- were researched for observational studies with data on mental health indexes related to quarantine or isolation for epidemic infections. Results. Twenty-one independent studies were included for 82,312 subjects. Conclusions. The results showed that at least 20% of people exposed to these conditions reported a psychological distress, with a prevalence of PTSD, depression and, less often, generalized anxiety. Important methodological bias weakens the conclusion of most studies, opening to the need of further research on mental health after quarantine and related risk/buffering factors.

The science around the use of masks by the general public to impede COVID-19 transmission is advancing rapidly. Policymakers need guidance on how masks should be used by the general population to combat the COVID-19 pandemic. In this narrative review, we develop an analytical framework to examine mask usage, considering and synthesizing the relevant literature to inform multiple areas: population impact; transmission characteristics; source control; PPE; sociological considerations; and implementation considerations. A primary route of transmission of COVID-19 is via respiratory droplets, and is known to be transmissible from presymptomatic and asymptomatic individuals. Reducing disease spread requires two things: first, limit contacts of infected individuals via physical distancing and other measures, and second, reduce the transmission probability per contact. The preponderance of evidence indicates that mask wearing reduces the transmissibility per contact by reducing transmission of infected droplets in both laboratory and clinical contexts. Public mask wearing is most effective at reducing spread of the virus when compliance is high. The decreased transmissibility could substantially reduce the death toll and economic impact while the cost of the intervention is low. Given the current shortages of medical masks we recommend the adoption of public cloth mask wearing, as an effective form of source control, in conjunction with existing hygiene, distancing, and contact tracing strategies. Because many respiratory droplets become smaller due to evaporation, we recommend increasing focus on a previously overlooked aspect of mask usage: mask-wearing by infectious people ("source control") with benefits at the population-level, rather than mask-wearing by susceptible people, such as health-care workers, with focus on individual outcomes. We recommend that public officials and governments strongly encourage the use of widespread face masks in public, including the use of appropriate regulation.

The age-related mortality and morbidity risk of COVID-19 has been considered speculative without enough scientific evidence. This study aimed to collect more evidence on the association between patient age and risk of severe disease state and/or mortality from SARS-CoV-2 infection. Genomic dataset along with metadata (3608 samples) retrieved from GISAID from different geographical regions were grouped into 10 age groups (0-10, 11-20, 21-30, 31-40, 41-50, 51-60, 61-70, 71-80, 81-90, 91-100 years) as well as high-risk or low-risk according to patient clinical status. Genomic sequences were aligned and analyzed using MAFFT and FASTTREE to build a phylogenetic tree in order to identify age-risk associations based on phylogenetic clustering. Case fatality rates (CFR), as well as the Odds ratio (OR) for high-risk outcomes, were calculated for different age groups. Results revealed that individuals aged between 25-50 years have the best immune response to the infection. On the other hand, disease fatality was higher in patients aging above 50 years. We created an application to calculate the OR of being at high risk given a certain age threshold from GISAID datasets. OR values increased between ages 1-10 years (1.271) and 11-20 years (1.313) but reduced at age range 21-30 years (1.290) and increased again for 61-70 years (2.465). CFR calculated for each of the age groups had peak values at 90-100 years (26.8%) and the lowest at 0-10 years (0%). The CFR for ages above 50 years was about twice greater (11.6%-26.8%) than that for ages below (0-6.6%). The phylogenetic analysis revealed that the majority of samples obtained from India showed low-risk among different age groups and were defined as clade GH. Another cluster from Singapore visualization showed unfavorable patient outcome across several age groups and were classified under clade O. To conclude, this study analyses showed a variety of age-risk associations. As scientists from different countries upload more genomes to globally shared databases, more evidence will reinforce mortality risk associations in COVID-19 patients.

Many universities and colleges worldwide suspended classroom teaching due to the novel coronavirus pandemic and switched to online teaching. The current cross-sectional study was carried out to analyze the impact of lockdown due to coronavirus disease 2019 (COVID-19) pandemic on the academic performance of veterinary medical students and researchers. Veterinary medical students and researchers were invited to answer an online google form questionnaire. A total of 1398 participants were from 92 different countries answered the questionnaire with response rate of 94.52%. The data showed that COVID-19 pandemic lockdown affected the academic performance of most participants (96.7%) with varying degrees. The mean evaluation scores for the online education in general was 5.06 ± 2.43 while that for the practical parts was 3.62± 2.56. Although online education provides an opportunity for self-study. The main challenge online education faces in veterinary medical science is how to give practical lessons. Since most of the subjects are practical; therefore, it is not easy to learn it online. Students think that it is difficult to fulfill the veterinary competencies only with online education system. Online education can be improved by making it more interactive, showing medical procedures in real situations, giving concise information, and providing 3D virtual tools to mimic the real situation.

From the moment the World Health Organization (WHO) declared COVID-19 to be a pandemic disease, COVID-19 began to affect the lives of many healthcare providers worldwide. In response to this pandemic, urology departments and training residency programs implemented urgent measures to reduce outpatient clinics, adopted the use of telemedicine, regulated emergency and outpatient urological procedures, promoted the use of operating theatres, and developed the use of sustainable e-learning alternatives to traditional urology resident/staff educational activities. Here, we review the response of urologists in Saudi Arabia to the COVID-19 pandemic and how they applied both for the patients and for the healthcare of urologist personnel.

South America has become the new epicenter of the coronavirus, especially in Brazil where the disease continues to spread exponentially across the country. This text aims to analyze the psychosocial factors of Covid-19 on back to school strategies in Brazil from a bioecological perspective. At the microsystem level, the population is experiencing different levels of stress and fear; at the mesosystem level, changes in routines, separation from family and friends, and closure of schools; and at the macrosystem level, national guidelines to control the pandemic, institutional standards on a national and international scale. Therefore, the main focus for the success of school return must be in the prevention of contagion and with physical and psychological health, and should not only consider the demands of curricula, financial or administrative management. For this reason, it is paramount that greater female representativeness is increased in decision-making levels of the meso and macrosystem, regarding the resumption of school and academic activities in the pandemic period, since the number of female leaders in decision-making, is still insufficient.

Introduction Most cases of COVID-19 coronavirus infection occurred in the Chinese city of Wuhan at the end of December 2019 in the form of acute pneumonia. COVID-19 virus infects people of all ages. The most affected elderly people with underlying medical conditions. This may cause various symptoms such as fever, difficulty breathing, lung infection, coughing and sneezing. Aim The aim of the present study to highlight the COVID-19 pandemic in Saudi Arabia. Method A search was conducted using the relevant keywords to retrieve the studies conducted in Saudi Arabia regarding COVID-19. The search was by Google Scholar, Pub MED, and Twitter. Conclusion The COVID-19 pandemic carries multiple-risk, and public health groups, such as the United States' Centres for Disease Control and Prevention (CDC) and the World Health Organisation (WHO), are monitoring the pandemic and posting updates on their website. These groups have also made recommendations on disease prevention and treatment, and according to the Saudi Centres for Disease Control, they have also included the necessary public health measures for mandatory reporting by calling a certain number and through the e-health monitoring network.

In only a few months after initial discovery in Wuhan, China, SARS-CoV-2 and the associated COVID-19 disease has become a global pandemic causing significant mortality and morbidity. In the absence of vaccines and effective therapeutics, reliable serological testing can be a key element of public health policy to control further spread of the disease and gradually ease quarantine measures. However, prior to launch of large-scale seroprevalence studies to assess herd immunity, it is critical to understand the limits and potential of current SARS-CoV-2 serological tests on the market. In this study, we provide an overview of serological testing and conduct a systematic review of independent evaluations of SARS-CoV-2 serological tests performance. Our findings show significant variability in the accuracy of marketed tests and highlight several lab-based and point-of-care rapid diagnostic tests with high performance level in detecting SRAS-CoV-2 specific antibodies. The findings of this review highlight the need for ongoing independent evaluations of commercialized COVID-19 diagnostic tests.

Most popular statistical models in epidemic evolution focus on the dynamics of average relevant quantities and overlooks the role of small fluctuations on the model parameters. Models for Covid-19 are no exception. In this paper we show that the role of time-correlated fluctuations, far from being negligible, can in fact determine the spreading of an epidemic and, most importantly, the resurgence of the exponential diffusion in the presence of time-limited episodes in promiscuity behaviours.

Introduction: The exponential growth of the SARS-CoV-2 virus transmission during the first months of 2020 has placed substantial pressure on health systems worldwide. The complications derived from the novel coronavirus disease (COVID-19) vary in due to comorbidities, sex and age, with more than 50% of the patients who require some level of intensive care developing acute respiratory distress syndrome (ARDS). Areas covered: Various complications caused by SARS-CoV-2 infection have been identified, the most lethal being the acute respiratory distress syndrome, caused most likely by the presence of severe immune cell response and the concomitant alveolus inflammation. The authors carried out an extensive and comprehensive literature review on SARS-CoV-2 infection, the clinical, pathological and radiological presentation as well as the current treatment strategies. Expert Opinion Elevation of inflammatory biomarkers is a common trend among seriously ill patients. The information available strongly suggests that in COVID-19 patients, their altered immune response, including a massive cytokine storm, is responsible for the further damage evidenced among ARDS patients. The increasingly high number of scientific articles and evidence available can only suggest that the individualization of each case is the norm, not all patients with acute respiratory failure due to COVID-19 meet the Berlin definition and therefore ARDS should be considered as a heterogeneous disease, with a wide range in the expression of its severity and clinical manifestations.

Coronavirus Disease 2019 (COVID-19) is a respiratory illness caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). It is considered to be first reported from Wuhan, Hubei Province, China in December 2019. As of present, there are over 3.7 million identified cases worldwide and more than 259,000 deaths have been reported. This disease, its incubation period, course, complications, and the basis of spread remains a potential question due to variation in the pattern of spread around the globe and relatively fewer number of large-scale studies at present. This literature review aims to study the available data on its spread and incubation period. A literature search using PubMed with regular keywords ‘coronavirus’ and ‘COVID-19’, and Medical Subject Headings (MeSH) search for their etiology and pathogenicity was done with the search builder. The literature search revealed 26,689 studies among which 14 studies were selected for review. Studies were selected after the application of inclusion criteria and exclusion criteria with the removal of duplicates, and careful review for the outcome of interest ‘incubation period’. Among the 14 studies selected for review, there were eight review articles, five case reports, and one comparative study. The current literature review concludes that the mean incubation period for most of the literature falls between five days to 12 days with minimum reported time from known exposure to the onset of a symptom being one day and the maximum reported time from exposure to the onset of a symptom being 18 days.

We live in extraordinary times, where COVID-19 pandemic has brought the whole world to a screeching halt. Tensions and contradictions that surround the pandemic ridden world include the availability, and the lack thereof, various facial protection measures to mitigate the viral spread. Here, we comprehensively explore the different type of facial protection measures, including masks, needed both for the pubic and the health care workers (HCW). We discuss the anatomy, the critical issues of disinfection and reusability of masks, the alternative equipment available for the protection of the facial region from airborne diseases, such as face shields and powered air purifying respirators (PAPR), and the skin-health impact of prolonged wearing of facial protection by HCW. Clearly, facial protection, either in the form of masks or alternates, appears to have mitigated the pandemic as seen from the minimal COVID-19 spread in countries where public mask wearing is strictly enforced. On the contrary, the healthcare systems, that appear to have been unprepared for emergencies of this nature, should be appropriately geared to handle the imbalance of supply and demand of personal protective equipment including face masks. These are two crucial lessons we can learn from this tragic experience.

This paper presents a new interactive visualization system to represent and compare rate of spread of COVID 19 pandemic across different countries over time. We surveyed existing visualization techniques used in various websites and media outlets and introduced use of a knee detection algorithm that divides the exponential spread in multiple linear components. A set of use cases demonstrates the utility of the system in comparing the spread across different countries for both analysis and prediction.

The COVID-19 pandemic has presented the world with increased challenges. The response to this pandemic has led to a sudden disruption of routine medical and elective surgical care. Most hospitals across the globe have had to change the way outpatient clinics are carried out and postpone non-urgent elective surgical procedures. NHS England ceased all elective general surgeries to train and re-deploy their staff to support the increased pressures from COVID-19 in an intensive care setting. However, with a decline of reported cases and deaths, the return to undertaking non-urgent elective services is imminent. In May 2020, Radha and Afzal published the first evidence-based guidelines for the resumption of elective orthopaedic services titled “Evidence based suggestions for the return to elective orthopaedic surgery following the COVID-19 Pandemic”. The pathway presented is adapted from the “Evidence based suggestions for the return to elective orthopaedic surgery following the COVID-19 Pandemic” and could potentially be used as a model for other surgical specialities. We present a three-phased return back to urological services. Safe resumption of elective care is possible but needs to be carefully planned.

Introduction: Clinicians have been struggling with the optimal diagnostic approach of patients with suspected COVID-19. We evaluated the added value of chest CT over RT-PCR alone. Methods: Consecutive adult patients with suspected COVID-19 presenting to the emergency department (Academic Medical Center, Amsterdam University Medical Centers, the Netherlands) from March 16^th to April 16^th were retrospectively included if they required hospital admission and underwent chest CT and RT-PCR testing for SARS-CoV-2 infection. The CO-RADS classification was used to assess the radiological probability of COVID-19, where a score of 1-2 was considered as negative, 3 as indeterminate, and 4-5 as positive. CT results were stratified by initial RT-PCR results. For patients with a negative RT-PCR but a positive CT, serology or multidisciplinary discussion after clinical follow-up constituted the final diagnosis. Results: 258 patients with suspected COVID-19 were admitted, of which 239 were included because they had both CT and RT-PCR testing upon admission. Overall, 112 patients (46.9%) had a positive initial RT-PCR, and 14 (5.9%) had a positive repeat RT-PCR. Of 127 patients with a negative or indeterminate initial RT-PCR, 38 (29.9% [95%CI 21.3-39.3%]) had a positive CT. Of these, 13 had a positive RT-PCR upon repeat testing, and 5 had positive serology. The remaining 20 patients were assessed in a multidisciplinary consensus meeting, and for 13 it was concluded that COVID-19 was ‘very likely’. Of 112 patients with a positive initial RT-PCR result, CT was positive in 104 (92.9% [95%CI 89.3-97.5%]). Conclusion: In a high-prevalence emergency department setting, chest CT showed high probability of COVID-19 (CO-RADS 4-5) in 29.9% of patients with a negative or indeterminate initial RT-PCR result. As the majority of these patients had proven or ‘very likely’ COVID-19 after follow-up, we believe that CT helps in the identification of patients who should be admitted in isolation.

In India the first case of coronavirus disease 2019 (COVID-19) reported on 30 January 2020, and thereafter cases were increasing daily after the last week of Feb. 2020. COVID-19 identified as family member of coronaviridae where previously Middle East Respiratory Syndrome MERS and Severe Acute Respiratory Syndrome SARS belongs to same family. The COVID-19 attacks on respiratory system signing fever, cough and breath shortness, in severe cases may cause pneumonia, SARS or some time death. The aim of this study work is to develop model which predicts the epidemic peak for COVID-19 in India by using the real-time data from 30 Jan to 10 May 2020. There are uncertainties while identifying the population information due to the incomplete and inaccurate data, we initiate the most popular model for epidemic prediction i.e Susceptible, Exposed, Infectious, & Recovered SEIR initially the compartmental model for the prediction. Based on the solution of the state estimation problem for polynomial system with Poisson noise, we estimate that the epidemic peak may reach the early-middle July 2020, initializing recovered R0 to 0 and Infected I0 to 1. The outcomes of the model will help epidemiologist to isolate the source of the disease geospatially and analyze the death. Also government authorities will be able to target their interventions for rapidly checking the spread of the epidemic.

Background: Although no specific treatment for COVID 19 has been proven effective yet, some drugs with in vitro potential against SARS-CoV-2 virus have been proposed for clinical use. Hydroxychloroquine has in vitro anti-viral and immunomodulatory activity, but there is no current clinical evidence of its effectiveness on the outcome of the disease. Methods: We enrolled all 18-85 years old inpatients from Central Defense Hospital, Madrid, Spain, who were hospitalised due to COVID-19 and had a definitive outcome (either dead or discharged). We used a statistical survival analysis. Results: We analysed 220 medical records. 166 patients met the inclusion criteria. 48,8 % of patients not treated with HCQ died, versus 22% in the group of hydroxychloroquine (p=0,002). According to clinical picture at admission, hydroxychloroquine increased the mean cumulative survival in all groups from 1,4 to 1,8 times. This difference was statistically significant in the mild group. Conclusions: in a cohort of 166 patients between 18 to 85 years hospitalised with COVID-19, hydroxychloroquine treatment with an initial loading dose of 800mg improved patient survival when admitted in early stages of the disease. There was a non-statistically significant trend towards survival in all groups, which will need to be clarified in subsequent studies.

The COVID-19 pandemic is one of the largest challenges in medicine and health care worldwide in recent decades, and it is infecting and killing increasing numbers of people every day. In this paper, we discuss the possible relationships among lysosomotropism, increasing lysosomal pH, and the SARS-CoV-2 infection and disease process, and we deduce a possible approach for treatment and prophylaxis. Lysosomotropism is a biological characteristic of small molecules, such as (hydroxyl)chloroquine, amitriptyline, NB 06, or sertraline, which is present in addition to intrinsic receptor-mediated or enzymatic pharmacological effects. Lysosomotropic compounds affect prominent inflammatory messengers, such as IL1B, CCL4, CCL20, and IL6, as well as cathepsin L dependent viral entry (fusion) into host cells. Therefore, this heterogeneous group of compounds is a promising candidate for the prevention and treatment of SARS-CoV-2 infections, as well as influenza A infections and cytokine release syndrome (CRS) triggered by bacterial or viral infections. Patients who have already taken medications with lysosomotropic compounds for other pre-existing conditions may benefit from this treatment in the COVID-19 pandemic. Increased lysosomal pH levels play an important role in the disease process in common skin disorders, such as psoriasis and atopic dermatitis, thus suggesting that affected individuals might benefit from their particular conditions in the COVID-19 pandemic. We suggest data analysis of patients with these diseases, and who are treated with lysosomotropic compounds, and, if the results are promising, subsequent clinical testing of off-label therapy with clinically approved lysosomotropic compounds in the current COVID-19 pandemic and future influenza A pandemics.

Registry and survey data gave an opportunity to compare possible roles of social attitudes and social values in control and limit the COVID-19 pandemic. We analysed social values and time series of daily R0 (reproduction rate) estimates for 27 European countries. Embedded and affective autonomy are significantly negatively associated (p-Value<0.05) with controlled R0. It could mean that well interconnected societies with high attention to maximize utilities are more likely to couple with COVID-19. Hierarchy is significantly positively associated (p-Value<0.05) with controlled R0. Thus, hierarchical structures could inhibits control of COVID-19. The results emphasize the need to pay more attention to social values context in evaluating the effectiveness of mitigation strategies internationally.

With the pandemic of Corona Virus [Covid-19], another infectious disease such as dengue neglected In Indonesia. Since the majority of resources, both human and capital, are focusing more on Covid-19, it is still essential to also manage dengue as it is still becoming a threat to the community. This paper aims to predict the number of cases of dengue in Kupang, East Nusa Tenggara, which can help the government to plan for dengue program activities. The result shows the forecast that dengue will remain high for the whole year. With the stay at the home approach to preventing COVID19, chances to get dengue virus increased. Maintaining a clean environment, reduction of breeding sites, and other protective measurements against dengue transmission is very important to perform.

The World Health Organisation declared Covid-19 as a pandemic on 11th March 2020. The main approach to tackle Covid-19 worldwide is to screen and provide supportive care to patients. For screening purpose RT-qPCR based test are used as an initial detections assay. The test is expensive, time consuming and not suitable for mass scale screening/ confirmation requirement. A recent advancement is development of Immunoassay procedures (liquid Phase tests or bed side 10-20minute strip test). In order to help and accelerate bringing life to normal after lock down, Pakistan is in dire need to develop and adopt the immunoassay procedures for mass scale screening and confirmation of COVID-19 infection. It is cheap and easy to perform without a lab requirement.

In late February 2020, Coronavirus disease-2019 (COVID-19) has aggressively spread around many bordering provinces of the three most productive regions of northern Italy (Lombardy, Veneto and Emilia Romagna). The first outbreak exploded in the municipality of Codogno (Lombardy). The province of Ferrara (Emilia Romagna) has been indicated as an anomaly due to the lower number of confirmed cases (1·065 cases per 1000 population). We argue that the spread of the virus throughout Emilia Romagna has a possible explanation in the geographical location of most of its provinces along the Via Emilia, an ancient Roman road that runs throughout the region, which we consider as a proxy for citizens’ movement, number of contacts, and social interactions. In order to test this hypothesis, we used a non-linear multiple regression analysis on aggregate province data to investigate the association between the rates of confirmed cases and the distance from the Via Emilia. The results indicate that the infection rate decreases proportionally to the distance from Via Emilia (-14% every 10 km, p<0·001). Further studies are needed, but Ferrara’s “peculiarity” might have a geographical/behavioral explanation, due to its isolation from the regional main connection routes, which are still revolving around a road built by the ancient Romans 2,000 years ago.

The social distancing as a response to COVID 19 pandemic has led to the exceptional reductions of daily routine people activities and vehicle uses mainly in city. This same situation was also experienced by several busy, large, and populous cities in Southeast Asia (SA) countries. Correspondingly, this study aimed to test the hypothesis that the social distancing implementation period has increased the air quality in the term of carbon monoxide (CO) emission reduction as drawn from Jakarta city as an example of the one of populated cities in SA region. The CO was measured in parts per billions (ppb) and monitored on the daily basis employing remote sensor platform. The monitor periods were started from January, February, March, and April 2020 with 10 measurement days for each month. The social distancing was implemented from mid of March to the recent April. The CO measurement data were statistically tested to justify the significant effects of social distancing on the CO levels. Based on the CO data analysis, the order of CO mean by months is February > January > March > April. The CO levels for January, February, March, and April were 87.46 ppb (95%CI: 83.54-91.37), 88.20 ppb (95%CI: 81.65-94.74), 86.38 (95%CI: 81.06-91.69), and 78.68 (95%CI: 74.03-83.32) respectively. This study also find significant difference (p<0.05) of CO levels especially in April when social distancing has been implemented. Hence, these findings illustrate the potential air pollutant reduction gained from implementing social distancing as can be seen in April.

This pandemic of COVID-19 is tedious to control. The only lockdown is the way to stop the spread of this infection. Conventional health care is facing a real challenge to operate. Primarily the challenge is to provide health care support for COVID-19 patients with limited resources and continue the health care services like earlier.Perhaps, this challenge is the same but magnitude is different from different geographical locations around the globe. In this article, we presented a Bayesian algorithm with the Code to predict cancer death due to COVID-19. This code is possible to run at different time points and different geographical locations around the world. This code will help us to get the best strategy and shift the treatment option for cancer treatment. The model would provide physicians with an objective tool for counseling and decision making at different hotspots and small areas to implement.

The recent worldwide outbreak of the novel corona-virus (COVID-19) opened up new challenges to the research community. Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic. Such predictions can be helpful to control and prevent the spread of such diseases. The main challenges of applying AI is the small volume of data and the uncertain nature. Here, we propose a shallow Long short-term memory (LSTM) based neural network to predict the risk category of a country. We have used a Bayesian optimization framework to optimized and automatically design country-specific networks. We have combined the trend data and weather data together for the prediction. The results show that the proposed pipeline outperforms against state-of-the-art methods for 170 countries data and can be a useful tool for such risk categorization. The tool can be used to predict long-duration outbreak of such an epidemic such that we can take preventive steps earlier.

Covid-19 is often related to hyperinflammation that drives lung or multi-organ injury. The immunopathological mechanisms that cause excessive inflammation following SARS-Cov-2 infection are under investigation while different approaches to limit hyperinflammation in affected patients are being proposed. Here, a computational protein-protein interaction network approach was used on recently available data to identify possible Covid-19 inflammatory mechanisms and bioactive genes. First, network analysis of putative SARS-Cov-2 cellular receptors and their directly associated proteins, led to the mining of a robust neutrophil response signature and multiple relevant inflammatory genes. Second, analysis of RNA-seq datasets of lung epithelial cells infected with SARS-Cov-2 revealed that infected cells specifically expressed neutrophil-attracting chemokines, further supporting the likely role of neutrophils in Covid-19 inflammation. Third, analysis of RNA-seq datasets of bronchoalveolar lavage fluid from Covid-19 patients, identified neutrophil-specific genes and chemokines. Different immunoregulatory and neutrophil-relevant molecules mined here such as, TNFR, IL8, CXCR1, CXCR2, ADAM10, GPR84, MME-neprilysin, ANPEP and LAP3 are druggable and might be therapeutic targets in efforts to limit SARS-Cov-2 inflammation in severe clinical cases. The role of neutrophils in Covid-19 needs to be studied further.

Introduction: The Pandemic of COVID-19, an infectious disease caused by SARS-CoV-2 motivated the scientific community to work together in order to gather, organize, process and distribute data on the novel biomedical hazard. Here, we analyzed how the scientific community responded to this challenge by quantifying distribution and availability patterns of the academic information related to COVID-19. The aim of our study was to assess the quality of the information flow and scientific collaboration, two factors we believe to be critical for finding new solutions for the ongoing pandemic. Materials and methods: The RISmed R package, and a custom Python script were used to fetch metadata on articles indexed in PubMed and published on Rxiv preprint server. Scopus was manually searched and the metadata was exported in BibTex file. Publication rate and publication status, affiliation and author count per article, and submission-to-publication time were analysed in R. Biblioshiny application was used to create a world collaboration map. Results: Our preliminary data suggest that COVID-19 pandemic resulted in generation of a large amount of scientific data, and demonstrates potential problems regarding the information velocity, availability, and scientific collaboration in the early stages of the pandemic. More specifically, our results indicate precarious overload of the standard publication systems, significant problems with data availability and apparent deficient collaboration. Conclusion: In conclusion, we believe the scientific community could have used the data more efficiently in order to create proper foundations for finding new solutions for the COVID-19 pandemic. Moreover, we believe we can learn from this on the go and adopt open science principles and a more mindful approach to COVID-19-related data to accelerate the discovery of more efficient solutions. We take this opportunity to invite our colleagues to contribute to this global scientific collaboration by publishing their findings with maximal transparency.

Covid-19 has given a halt to all the activities in the world. Europe was most affected, followed by the United States of America. It has taken more than 350000 lives until now. In this study, we have assessed the severity of Covid-19 by analyzing the mortality rate of Covid-19 and other chronic diseases. The Covid-19 data and “death rate” data caused by other diseases were downloaded from the world health organization (WHO) website. A normalized method was used to see the mortality rate of Covid-19 in comparison to other diseases. The deaths caused by Covid-19 in April 2020 have overtaken the average number of deaths caused by Cancer, Cardiovascular diseases, and other diseases in Belgium, the United Kingdom (UK), Spain, France, and Ireland. Covid-19 was found to be strongly correlated with non-communicable respiratory diseases and Cancer with correlation coefficients 0.73 and 0.67 respectively. The severity of Covid-19 in the United States of America (USA) was moderate. The severity of Covid-19 in Asian countries was found to be low. Europe showed the highest diversity in the mortality rate of Covid-19. On average, except for a few European countries, Cardiovascular diseases, cancer, and non-communicable respiratory diseases were still more lethal and caused more deaths than Covid-19.

The recently emerged coronavirus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS- CoV-2) is the newest threat to human health. It has already infected more than half a million people worldwide, leading to a lot of deaths. Although it causes mild flu-like disease in most patients, lethality may increase to more than 20% in elderly subjects, especially those with comorbidities, like hypertension, diabetes or lung and cardiac disease, and the mechanisms are still elusive. Common symptoms at the onset of illness are fever, cough, myalgia or fatigue, headache, and diarrhea or constipation. Interestingly, respiratory viruses have also placed themselves as relevant agents for CNS pathologies. Here we discuss several CNS related features, referred by several patients, especially at the beginning of the disease. Thus, we also discuss the possibility by which SARS-CoV-2 may affect the olfactive system of patients, either directly or indirectly.

The rapid spread of the coronavirus disease 2019 (COVID-19) is a serious threat to public health systems globally and is subsequently, a cause of anxiety and panic within human society. Understanding the mechanisms and reducing the chances of having severe symptoms from COVID-19 will play an essential role in treating the disease, and become an urgent task to calm the panic. However, the COVID-19 test developed to identify virus carriers is unable to predict symptom development in individuals upon infection. Experiences from other plagues in human history and COVID-19 statistics suggest that genetic factors may determine the compliance with the virus, i.e., severe, mild, and asymptomatic. Here, a hypothesis is put forward based on the epidemiological characteristics and traits of COVID-19, and our gene expression analysis. It proposes that COVID-19 inactivation in the blood by blocking virus entry into other internal organs for reproduction through the blood circulation after lung cell invasion prevents severe symptoms. Additionally, we investigated a genetic connection between candidate genes and severe COVID-19 symptoms through the utilization of strategies combining hypothesis and data-driven approaches. A list of genes and important SNPs that require further investigation to aid the screening of individuals who may suffer severe illness if exposed to the virus is present. Those individuals should be intensively safeguarded and prioritised for treatment. Concurrently to further research on the COVID-19 pathogenesis, our results also offer a new research strategy for pandemic prevention and health maintenance.

Italy was the first country in Europe which imposed control measures of travel restrictions, quarantine and contact precautions to tackle the epidemic spread of the novel coronavirus (SARS-CoV-2) in all its regions. While such efforts are still ongoing, uncertainties regarding SARS-CoV-2 transmissibility and ascertainment of cases make it difficult to evaluate the effectiveness of restrictions. Here, we employed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model to assess SARS-CoV-2 transmission dynamics, working on the number of reported patients in intensive care unit (ICU) and deaths in Sicily (Italy), from 24 February to 13 April. Overall, we obtained a good fit between estimated and reported data, with a small fraction of unreported SARS-CoV-2 cases (19.5%; 95%CI=0%-34.7%) before 10 March lockdown. Interestingly, we estimated that the first set of restrictions reduced transmission rate in the community by 42% (95%CI=38%-46%), and that more stringent measures adopted on 23 March succeeded to drastically curb the transmission rate by 84% (95%CI=80%-88%). Thus, our estimates delineated the characteristics of SARS-CoV2 epidemic before restrictions taking into account unreported data. Further modeling after the adoption of control measures, moreover, indicated that restrictions reduced SARS-CoV2 transmission considerably.

Critically ill patients with COVID-19 may develop serious respiratory difficulties, causing a significant reduction in blood oxygen saturation pressure. Physical Ventilation of the lungs is one of the main methods to help critically ill patients through the acute phase of infection. During extreme situations when dysfunctional lungs are filled with sticky sputum in the alveolus or when there are simply not enough ventilators to match the need, the mortality rate can be dramatically increased. Here, we propose an intravenous injection method that may increase and maintain the blood oxygen pressure at normal levels. The intravenous (IV) infusion contains oxygen nanobubbles in physiological saline solution (ONPS), in which the dissolved oxygen content can be 2-6 times higher than the normal oxygen solubility in pure water. This makes it possible to oxygenate blood with a small limited volume of IV fluid without the risk of gaseous bubble formation in blood vessels.

The current Coronavirus Disease 19 (COVID-19) pandemic, caused by the SARS-CoV-2 virus, is unprecedented in recent history and threatens the lives and livelihoods of billions worldwide. The rapid spread and lack of modern parallels have left governments, health agencies, and the public racing to understand how to best mitigate and ultimately suppress the pandemic, but we are still working to understand the strengths and weaknesses of various interventions at our disposal. Few issues have been as contentious as the public use of face masks to control the pandemic’s spread. There is ongoing debate about their effectiveness, but an increasing body of evidence suggests that masks could be a useful in preventing the spread of coronavirus, leading several governments and health agencies to review and revise their policies. Here, we review the theory and evidence behind use of masks. The theory behind masks is that they prevent the spread of viral particles by infected persons, and inhalation of viral particles by uninfected persons. Even assuming masks are not 100% effective in preventing infection, they may reduce severity of infection by reducing viral dosing. Laboratory studies suggest masks may be effective in stopping both exhalation and inhalation of viral particles. However, real-world studies provided limited evidence for the use of masks in controlling influenza transmission and highlight potential problems associated with their misuse, such as poor compliance or improper use. Evidence for efficacy of face masks against the first SARS virus, SARS-CoV-1, implies that they may be effective against the current outbreak of SARS-Cov-2 virus. This is important as mathematical modeling suggests that even small reductions of in transmission rates can make a large difference over time, potentially slowing the pace of viral pandemics and limiting their spread. Perhaps the strongest argument for the use of masks is that countries with early adoption of masks have tended to see flatter pandemic curves, even without strict nationwide lockdowns. There is little evidence that respirators are more effective than surgical masks, but this may be due to misuse or poor compliance. Studies suggest some non-medical masks perform on par with medical masks. Improvised masks are less effective than medical masks, but may provide better protection than nothing at all. While many governments now encourage the use of improvised face coverings, more will need to be known about material, design, and who needs to wear masks, and when, to ensure effectiveness. Proper use of masks will also be important; if masks are used improperly or infrequently they may provide limited protection. It is important that public health policy makers consider the debate and the potential of masks as part of multi-faceted coronavirus control strategies.

In the midst of the novel coronavirus (SARS-CoV-2) epidemic, examining reported case data could lead to biased speculations and conclusions. Indeed, estimation of unreported infections is crucial for a better understanding of the current emergency in China and in other countries. In this study, we aimed to estimate the unreported number of infections in China prior to 23 March 2020 restrictions. To do that, we developed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model which estimated unreported cases and infections from the reported number of deaths. Our approach relied on the fact that observed deaths were less likely to be affected by reporting biases than reported infections. Interestingly, we estimated that R0 was 2.43 (95%CI= 2.42 – 2.44) at the beginning of the epidemic, and that 92.9% (95%CI= 92.5% - 93.1%) of total cases were not reported. Similarly, the proportion of unreported new infections by day ranged from 52.1% to 100%, with a total of 91.8% (95%CI= 91.6% - 92.1%) unreported infections. Agreement between our estimates and those from previous studies proved that our approach was reliable to estimate prevalence and incidence of undocumented SARS-CoV2 infections. Once tested on Chinese data, our model could be applied on other countries with different surveillance and testing policies.

We statistically investigate the Coronavirus Disease 19 (hereinafter Covid-19) epidemics, which is particularly invasive in Italy. We show that the high apparent mortality (or Case Fatality Ratio, CFR) observed in Italy, as compared with other countries, is likely biased by a strong underestimation of infected cases. To give a more realistic estimate of the mortality of Covid-19, we use the most recent estimates of the IFR (Infection Fatality Ratio) of epidemic, based on the minimum observed CFR, and furthermore analyse data obtained from the ship Diamond Princess, a good representation of a ‘laboratory’ case-study from an isolated system in which all the people have been tested. From such analyses we derive more realistic estimates of the real extension of the infection, as well as more accurate indicators of how fast the infection propagates. We then point out from the various explanations proposed, the dominant factors causing such an abnormal seriousness of the disease in Italy. Finally, we use the deceased data, the only ones estimated to be reliable enough, to predict the total number of infected people and the interval of time when the infection in Italy could stop.

Ligand and structure based virtual screening approaches were applied to clinical stage drugs as well as those approved for human use in an attempt to repurpose drugs for potential use against COVID-19. This approach involved ligand-based shape similarity searches, structure-based docking and pharmacophore searches with the help of pharmacophore queries derived from available ligands and receptor structures. Several compounds appeared as hits in pharmacophore and shape similarity searches and those docking to the SARS-CoV-2 viral 3CL protease were then ranked on the basis of docking scores.

The novel coronavirus, COVID-19 is now officially declared as a pandemic by the World Health Organization (WHO), and most parts of the world are taking drastic measures to restrict human movements to contain the infection. Like millions of others around the world, I am wondering, is there anything that could be done, other than keeping high personal hygiene, and be vigilant of symptoms, to reduce the chances of infection, or at least to reduce the burden of the disease. So far, the National and International health agencies, including the National Institutes of Health (NIH), the Centers for Disease Control and Prevention (CDC), and the WHO have provided clear guidelines for both preventive and treatment suggestions. In this opinion-based article, I want to discuss, why keeping the adequate micronutrient balance might enhance the host response and be protective of viral infections. A detailed in-depth discussion of various micronutrients is not the purpose of this article, I will mostly emphasize on the role of zinc in viral infection.

Background: COVID-19, a member of corona virus family is spreading its tentacles across the world due to lack of drugs at present. Associated with its infection are cough, fever and respiratory problems causes more than 15% mortality worldwide. It is caused by a positive, single stranded RNA virus from the enveloped coronaviruse family. However, the main viral proteinase (Mpro/3CLpro) has recently been regarded as a suitable target for drug design against SARS infection due to its vital role in polyproteins processing necessary for coronavirus reproduction.Objectives: The present in silico study was designed to evaluate the effect of Eucalyptol (1,8 cineole), a essential oil component from eucalyptus oil, on Mpro by docking study.Methods: In the present study, molecular docking studies were conducted by using 1-click dock and swiss dock tools. Protein interaction mode was calculated by Protein Interactions Calculator.Results: The calculated parameters such as RMSD, binding energy, and binding site similarity indicated effective binding of eucalyptol to COVID-19 proteinase. Active site prediction further validated the role of active site residues in ligand binding. PIC results indicated that, Mpro/eucalyptol complexes forms hydrophobic interactions, hydrogen bond interactions and strong ionic interactions.Conclusions: Therefore, eucalyptol may represent potential treatment potential to act as COVID-19 Mpro inhibitor. However, further research is necessary to investigate their potential medicinal use.

The pandemic of coronavirus disease (COVID-19), a disease caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV-2), is causing substantial morbidity and mortality. Older age and presence of diabetes mellitus, hypertension and obesity significantly increases the risk for hospitalization and death in COVID-19 patients. In this Perspective, informed by the studies on SARS-CoV-2, Middle East respiratory syndrome (MERS-CoV), and the current literature on SARS-CoV-2, we discuss potential mechanisms by which diabetes modulates the host-viral interactions and host-immune responses. We hope to highlight gaps in knowledge that require further studies pertinent to COVID-19 in patients with diabetes mellitus, hypertension and obesity.

Within the past several decades, the emergence of new viral diseases with severe health complications and mortality is evidence of an age-dependent, compromised bodily response to abrupt stress with concomitantly reduced immunity. The new severe acute respiratory syndrome coronavirus 2, SARS-CoV-2, causes coronavirus disease 2019 (COVID-19). It has increased morbidity and mortality in persons with underlying chronic diseases and those with a compromised immune system regardless of age and in older adults who are more likely to have these conditions. While SARS-CoV-2 is highly virulent, there is variability in the severity of the disease and its complications in humans. Severe pneumonia, acute respiratory distress syndrome, lung fibrosis, cardiovascular events, acute kidney injury, stroke, hospitalization, and mortality have been reported that result from pathogen–host interactions. Hallmarks of aging, interacting with one another, have been proposed to influence health span in older adults, possibly via mechanisms regulating the immune system. Here, we review the potential roles of the hallmarks of aging coupled with host–coronavirus interactions. Of these hallmarks, we focused on those that directly or indirectly interact with viral infections, including immunosenescence, inflammation and inflammasomes, adaptive immunosenescence, genomic instability, mitochondrial dysfunction, telomere attrition, epigenetic alterations, and impaired autophagy. These hallmarks likely contribute to the increased pathophysiological responses to SARS-CoV-2 among older adults and may play roles as an additive risk of accelerated biological aging even after recovery. We also briefly discuss the role of anti-aging drug candidates that require paramount attention in COVID-19 research.

As of 26 March 2020, Pakistan had 1179 cases of COVID-19, with most 421 cases from Sindh, 394 cases, 131 cases, 123 cases, 84 cases, 25 cases and 01 cases from Punjab, Balochistan, Khyber Pakhtunkhwa, Gilgit-Baltistan, Islamabad Capital Territory, and Azad Jammu and Kashmir respectively. Travel-related cases were the main source of SARS-CoV-2 infection during the early phase of the pandemic in Pakistan. Nevertheless, cases of local virus transmission are increasing day by day. As of 26 March 2020, nine deaths have been reported from COVID-19. The case fatality rate is 0.8%, which is less compare to China, Italy, USA, and Iran. The SIR (Susceptible-Infected-Recovered) model of epidemiological analysis predicts that almost 90 million population will be infected in the coming days with 5% critical cases that need health care facilities. However, the Pakistan health care system cannot provide services to this much population. Hence, we need to act timely to reduce this number by restricting local transmission of the disease. This can be done by mass testing, quarantine, isolation and social distancing of the active coronavirus cases in Pakistan. Moreover, better communication between the authorities is very much required to control disease transmission.