In the aftermath of the COVID pandemic, post-COVID-19 syndrome (PCS) remains a challenge and may continue to represent a major health problem in the future. Moreover, the influence of type 2 diabetes and being overweight on PCS remains unclear. This study aimed to assess this influence. We performed an observational study from October 2020 to July 2022, which included 466 patients (269 males and 197 females) with a median age of 65. They were hospitalized due to COVID-19 pneumonia and had persistent symptoms after 1 month of COVID-19 infection. The patients were divided into four groups according to the study objectives: patients with type 2 diabetes, overweight patients, overweight patients with type 2 diabetes, and normal-weight patients without type 2 diabetes. The clinical and demographic data collected during hospitalization and regular visits at the Community Healthcare Center dr. Adolf Drolc Maribor were analyzed. Our results showed that type 2 diabetes patients had a more difficult course of treatment and longer hospitalization. Moreover, more type 2 diabetes patients underwent rehabilitation than the other study groups. The prevailing symptoms in our patients with PCS were dyspnea and fatigue, mostly in female patients with type 2 diabetes. Our study also showed that more women with type 2 diabetes and more overweight women with type 2 diabetes suffered from secondary infections. Further, more overweight patients were treated in the intensive care unit compared to the other groups. However, our study showed an interesting result that patients with type 2 diabetes had the shortest PCS durations. Type 2 diabetes and being overweight are risk factors for PCS onset and prolonged duration. Therefore, our data that revealed a shorter duration of PCS in type 2 diabetes patients compared to the other investigated groups was unexpected. We believe that answering this question regarding the results will enable us to improve PCS treatment in general.

The COVID-19 infections in Pakistan are spreading at an exponential rate and a point may soon be reached where rigorous prevention measures would need to be adopted. Mathematical models can help define the scale of an epidemic and the rate at which an infection can spread in a community. I used ARIMA Model, Diffusion Model, SIRD Model and Prophet Model to forecast the magnitude of the COVID-19 pandemic in Pakistan and compared the numbers with the reported cases on the national database. Results depicts that Pakistan could hit peak number of infectious cases between June 2020 and July, 2020.

Introduction: The rapid emergence of COVID-19 as a global crisis has led to the approval of many vaccinations, which were unfortunately associated with high complication rates due to a lack of sufficient safety studies. Objectives: The following manuscript focuses on discussing the demyelinating disorders that were noticed after COVID vaccine administration. Methods: We conducted a retrospective study using anonymous medical records from the US vaccine adverse events reporting system, complications retrieved included Acute disseminated encephalomyelitis (ADEM), Guillain Barre syndrome (GBS), and Multiple sclerosis (MS), outcome parameters were age, sex and the dose after which this complication was observed. Patients younger than 18 years-old were excluded as some of the vaccines, namely Janssen (JNJ-78436735) is not yet approved below this age. Results: Our analysis showed that demyelinating disorders were more likely to occur in patients over the age of 50 compared to other age groups, regardless of the type of vaccination, except for MS and ADEM occurrences after the Jansen vaccine. In addition, demyelinating complications were more likely to occur after the first dose of vaccination. Conclusion: Further research and observation of demyelinating diseases in different vaccinations, as well as additional in vitro studies, are recommended to further explain the pathogenesis of demyelinating disorder occurrence.

Currently available COVID-19 mRNA vaccines have demonstrated high efficacy in clinical trials.1-3 However, cancer patients, including those with hematological malignancies, were largely excluded from these trials. In this prospective, observational study we measured anti-S protein IgG titers as well as avidity in lymphoma patients (n=67) vaccinated with a COVID-19 mRNA vaccine. Serological response rates in lymphoma patients who were treatment naïve (100% in CLL, 88.9% in other, non-CLL non-Hodgkin lymphoma patients), or who were last treated more than 24 months prior to vaccination (100% in CLL, 90% in other-NHL), were similar to healthy controls (100%). Patients on active therapy, however, had a diminished response rate (40% in CLL, 21.0% in other-NHL). No patient who received anti-CD20 monoclonal antibodies (mAb) within six months of vaccination responded. Thus, the utility of testing anti-S titers should be explored in patients on active therapy or with recent anti-CD20 mAb exposure, to assess their response to vaccination. We also propose studying passive protection with S-protein mAbs as an alternative prophylactic strategy for patients who respond poorly to vaccination.

Background: In the current era of globalization, the Indonesian government's problem today is the weakening of nationalism and patriotism among the millennial generation. The large number of foreign cultures that have entered Indonesia has caused a sense of nationalism and patriotism. In addition, Indonesia is also facing the problem of spreading the Covid-19 virus. During the pandemic, various policies set by the government received protests from some circles because they felt their freedom was restricted. Therefore, the awareness of millennial generation nationalism is needed, especially during the Covid-19 pandemic like today. This research aims to make millennials aware of nationalism sense, which mainly to prevent the spread of Covid-19. This research is used to answer the questions of what the problems that arise due to the waning of the spirit of nationalism during the pandemic are? and what efforts should be made to maintain the spirit of nationalism? Methods: This research is a qualitative study using the literature review method. The articles used are research published in 2019 to 2021 in Google Scholar, with keywords that match the topic of millennial generation nationalism in the Covid-19 pandemic. Results and Discussion: The results of the study found that the spirit of Indonesian nationalism during the Covid-19 pandemic was decreasing. The decline in the sense of nationalism is due to several government policies that impact the psychology of society and the Indonesian economy. As a result, society, particularly the millennial generation, must play a role in breaking the chain of the Covid-19 virus's propagation by following the government's health standards. Conclusion: The government and society need to work together to understand nationalism in the millennial generation, especially in dealing with problems caused by the Covid-19 pandemic. Based on this, various efforts need to be made to foster the spirit of nationalism and overcome the Covid-19 pandemic. So that later, it can produce a generation that upholds the value of nationalism in everyday life.

BACKGROUND: From March to April 2020, Spain was the center of the SARS-CoV-2 pandemic, particularly Madrid with approximately 30% of the cases in Spain. The aim of this study is to report the suspected serious adverse drug reactions (SADRs) in COVID-19 patients versus non-COVID-19 patients detected by the prospective pharmacovigilance program based on automatic laboratory signals (ALSs) in the hospital (PPLSH) during that period. We also compared the results with the suspected SADRs detected during the same period for 2019. METHODS: All ALSs that reflected potential SADRs (including neutropenia, pancytopenia, thrombocytopenia, anemia, eosinophilia, leukocytes in cerebrospinal fluid, hepatitis, pancreatitis, acute kidney injury, rhabdomyolysis and hyponatremia were prospectively monitored in hospitalized patients during the study periods. We analyzed the incidence and the distribution of causative drugs for the COVID-19 patients. RESULTS: The incidence rate of SADRs detected in the COVID-19 patients was 760.63 (95% CI 707.89–816.01) per 10,000 patients, 4.75-fold higher than the SADR rate for non-COVID-19 patients (160.15 per 10,000 patients,95% CI 137.09–186.80), and 5.84-fold higher than the SADR rate detected for the same period in 2019 (130.19 per 10,000 patients, 95% CI 109.53–154.36). The most frequently related drugs were tocilizumab (59.84%), dexketoprofen (13.93%), azithromycin (8.43%), lopinavir-ritonavir (7.35%), dexamethasone (7.62%), and chloroquine/hydroxychloroquine (6.91%). CONCLUSIONS: The incidence rate of SADRs detected by the PPSLH in patients with COVID-19 was 4.75-fold higher than that of the non-COVID-19 patients. Caution is recommended when using medications for COVID-19 patients, especially drugs that are hepatotoxic, myotoxic, and those that induce thromboembolic events.

There is a current pandemic of a new type of coronavirus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The number of confirmed infected cases has been rapidly increasing. This paper analyzes the characteristics of SARS-CoV-2 in comparison with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and influenza. COVID-19 is similar to the diseases caused by SARS-CoV and MERS-CoV virologically and etiologically, but closer to influenza in epidemiology and virulence. The comparison provides a new perspective for the future of the disease control, and offers some ideas in the prevention and control management strategy. The large number of infectious people from the origin, and the highly infectious and occult nature have been two major problems, making the virus difficult to eradicate. We thus need to contemplate the possibility of long-term co-existence with COVID-19.

This work presents a compilation of data obtained by clinical psychologists during the Covid-19 pandemic in Brazil. Through searches on social media with #Covid19 and #MentalHealth and the exchange of information on networks of professionals, it was possible to compile and group the main psychological symptoms presented during isolation. Information was clustered according to the period it appeared, in order to guide future situations. Moreover, to prepare a group of clinical psychologists to provide online assistance.

Graph theory plays significant role in every field of science as well as technology. Every situation can be articulated in terms of suitable graphs by using various approaches of graph theory. Considering the recent pandemic in the world and the precautions taken for prevention of the COVID 19, it is the most appropriate way to exercise the graph models with theoretical as well as practical aspects to control this epidemic. This paper defines the variable set, variable graphs and their types with respect to variable vertex sets and variable edge sets. Depending upon the nature of the pandemic, there are four types of Virus graphs. Virus graph I and III are not so perilous for all living beings. Although, Virus graphs II and IV are extremely hazardous for the harmony of the world. In view of different aspects for expand of pandemic, growth types of virus graphs are divided in 1-1, 1-P and 1-all growth types. The COVID19 initially was in Virus graph-I type, but presently it is in Virus graph-II types. We present the table involving the number of infected people after n days with respect to different values of P and growth rates with I0 = 100. Moreover, the country wise starting dates of stages of the virus graph-I and II are specified. The concept of cut sets is applicable for prevention of COVID19 and the whole world is using the same analogy.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging infectious disease with currently a pandemic state. Cardiac function can be involved, affecting prognosis, in addition with lung feature severity, particularly in patients with comorbidities. Since the renin angiotensin aldosterone (RAA) system may interact with SARS-Cov-2, researches are still ongoing to assess the prognostic value of RAA blockers in cardiology.

With covid infection having a periodic occurrence and each wave affecting millions of people, there is an urgent need for healthcare providers to develop readily available biological markers to predict the severity and mortality of COVID-19 infection at an early stage of the disease to predict the most optimal management. The Neutrophil – lymphocyte Ratio (NLR) and Platelet-lymphocyte ratio (PLR), are novel inflammatory markers suggested to predict the severity of illness in COVID -19 patients. We evaluated a retrospective cohort of 224 patients with covid 19 illnesses from August 2020 to October 2020. We categorized the patients into 'mild' and 'moderate to severe as per the severity of their illnesses. The optimal cut-off values of the continuous NLR, PLR, and Age were calculated by applying the receiver operating characteristic (ROC) curve analysis. Sensitivity, specificity, and likelihood ratios were calculated from ROC analysis. The results showed that Age, Hb, and NLR are significant predictors of the severity of illness. So we quantified the predictive contribution of those variables by its Z- score and showed that NLR is the strongest predictor followed by Age.ROC curve analysis revealed NLR to be an excellent predictor of disease severity (sensitivity 88.30% and specificity 82.60%) at a cut-off of > 4.24. A cut-off of 165.63 was obtained for PLR, which showed good predictive value for the severity of illness. A NLR > 6 was used as a predictor for mortality due to covid illness with good sensitivity and specificity. Conclusion: NLR and PLR can be used as prognostic markers to identify the severity of covid illness and the probability of mortality in the future in low-resource settings. Given its low cost, easily available, accessible, and reproducible data, it can be used as a useful marker to assist the physician in early referral and treatment of covid 19 infected patients.

Coronavirus disease 2019 (COVID-19), the global pandemic caused by severe acute respiratory syndrome 2 virus (SARS-CoV-2) infection, has caused millions of infections and fatalities worldwide. Extensive SARS-CoV-2 research has been conducted to develop therapeutic drugs and prophylactic vaccines, and even though some drugs have been approved to treat SARS-CoV-2 infection, treatment efficacy remains limited. Therefore, preventive vaccination has been implemented on a global scale and represents the primary approach to combat the COVID-19 pandemic. Approved vaccines vary in composition, although vaccine design has been based on either the key viral structural (spike) protein or viral components carrying this protein. Therefore, mutations of the virus, particularly mutations in the S protein, severely compromise effectiveness of current vaccines and the ability to control COVID-19 infection. This review begins by describing the SARS-CoV-2 viral composition, mechanism of infection, role of angiotensin-converting enzyme 2, host defense responses against infection and the most common vaccine designs. Next, this review summarizes the common mutations of SARS-CoV-2 and how these mutations change viral properties, confer immune escape and influence vaccine efficacy. Finally, this review discusses global strategies that have been employed to mitigate the decreases in vaccine efficacy encountered against new variants.

COVID-19 disease, caused by the SARS-CoV2 virus, is a potentially fatal disease that represents a serious public health and economic problem worldwide. The SARS-CoV2 virus infects the lower respiratory tract and can cause pneumonia in humans. ARDS is the leading cause of death in COVID-19 disease. One of the main characteristics of ARDS is the cytokine storm, an uncontrolled systemic inflammatory response resulting from the release of pro-inflammatory cytokines and chemokines and growth factors, by immune cells. The other important aspect of the disease is represented by the involvement of the vascular organ that undergoes endothelitis. Hyperinflammation and endothelitis contribute in various ways to trigger coagulation disorders with diffuse micro thrombotic and thromboembolic phenomena. Lastly, multiple organ failure may occur (MOF). Since so far there is no approved treatment, there is an urgent need to reposition known treatments, considered safe, to be included in trials. Naturally produced interferons represent the body's first line of defense against viruses. Pharmacological forms, obtained by means of genetic recombination techniques, have long been approved and used to treat numerous pathologies. Interferons are divided into three families, within which some subfamilies are distinguishable. Only IFN-II comprises a single isoform which has completely different aspects and functions. The IFN I and III, however, each comprise different subfamilies (17 subfamilies the IFN-I and 4 subfamilies the IFN-III), share many aspects, representing the body's first antiviral response, but play different roles. The use of IFNs has been studied in two severe hCoV (Human Coronavirus) diseases, closely related to COVID-19 disease, such as SARS and MERS. Numerous in vitro and in vivo studies have been conducted, often in combination with other antivirals. The results have been controversial. The positive results in vitro and in experimental animals were often not replicable in humans. The possible positioning of these molecules in the right window of therapeutic opportunity requires that the complex dialogue between IFN, inflammasome, cytokines, pro-inflammatory chemokines, growth factors and barrier function be shed light.

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).

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.

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.

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.

The Corona Virus (COVID-19) pandemic situation has posed significant effect on tourism industry. Tourism destinations have embraced emergency health care measures and restrictions imposed on human movement around the world. Beaches and resorts are empty, peoples’ movements are stopped and travelling between territories is strictly controlled. The COVID-19 lockdown around the world has imposed negative impact on the livelihood of people and world economy as well. The present study attempts to find out the scopes for sustainable tourism development in near future from the consequences of social, economic, and environment in COVID-19 pandemic situation.

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.

Since the outbreak of SARS CoV-2 infection (Covid-19), healthcare professionals worldwide have been trying to find disease management and control alternatives to encourage immunotherapies. Immunotherapy is an efficient therapeutic option used against comparable viral contaminations such as MERS-CoV and SARS-CoV. The aim of the current study is to assess the existing knowledge associated with SARS-CoV-2 immunotherapy. Information available in published articles and their quality highlights the importance of following strict scientific rules for clinical outcomes. Thus, these studies have shown enough data to confirm that immunomodulation is the main topic investigated in research about Covid-19 therapy. Therefore, it is possible saying that immunotherapy is certainly the appropriate option against this virus.

The current outbreak of the novel coronavirus also known as COVID-19 was declared as a public health emergency by the WHO where over a million people have been affected by the disease with over 50000 deaths till date. Social distancing is a method to minimize crowd interactions and prevent the spread of disease within groups of people. This is a common practice which has been carried out over generations to minimize the spread of virus by limiting its reproduction rate (R0) among communities. The article focuses on how social distancing has been used to deal previous pandemics globally and the issues that needs to be addressed to tackle the COVID-19 threat.

In this study, we surveyed over 600 participants to determine: a) major causes to mental stress during the pandemic and its future impacts, and b) diversity in public perception and acceptance (specifically for children) of Covid-19 vaccination. Statistical results and intelligent clustering outcomes indicate significant relationships between sociodemographic diversity, mental stress causes, vaccination perception, and Covid-19 infections. For instance, statistical results indicate significant dependence between mental stress due to Covid-19 and gender (p = 1.7e-05). Over 25% of males indicated work related stress comparing 35% in females however, females indicated more stressed (17%) due to relationships comparing to males (12%). Around 30% of Asian/Arabic participants don’t feel vaccination being safe as compared to 8% of white-British and 22% of white-European indicating significant dependence (p = 1.8e-08) with ethnicity. More specifically, vaccination acceptance for children is significantly dependent to ethnicity (p = 3.7e-05) where only 47% participants show willingness towards children’s vaccination. Primary dataset in this study along with experimental outcomes identifying sociodemographic information diversity with respect to public perception and acceptance of vaccination to children and potential stress factors might be useful for public and policy makers to be better prepared for future epidemics as well as working globally to combat mental health issues and running more effective vaccination campaigns.

Patients hospitalized with COVID-19 are at a higher risk of thrombotic events following discharge, however the role of extended thromboprophylaxis remains controversial. The purpose of this study is to evaluate current extended post-discharge thromboprophylaxis practice and its outcomes.This study was a single-center, retrospective chart review of patients within Hennepin Healthcare hospitalized with COVID-19 from April 1^st 2020 to December 31^st 2021 with increased risk of thrombotic event based on D-dimer. The primary outcome was to describe current prescribing practices based on the number of patients who were eligible and received anticoagulants on discharge. Secondary outcomes included comparing the patient’s risk for thromboembolism based on a modified International Medical Prevention Registry on Venous Thromboembolism (IMPROVE-VTE) score to the current internal prescribing practice guideline, evaluating efficacy outcomes based on new thromboembolic events, and assessing safety of extended-thromboprophylaxis using the International Society of Thrombosis and Hemostasis criteria for major bleeding within 30 days of hospitalization discharge.Of 1984 patients who were hospitalized with COVID-19 infection, 961 patients were eligible to receive thromboprophylaxis at discharge, with a total of 191 patients who received anticoagulation according to the Hennepin Healthcare practice guideline. However, using the IMPROVE-VTE score, only 206 patients qualified for post-discharge thromboprophylaxis, and 63 total patients received anticoagulation. A new thromboembolic event occurred in 20 patients (5.8%) and 14 patients (4.1%) experienced major bleeding.The Hennepin Healthcare guideline for extended thromboprophylaxis at discharge encompassed more patients compared to the IMPROVE-VTE score. The incidence of a new thromboembolic event and major bleeding were low in both groups, although venous thrombotic events occurred more in thromboprophylaxis group than in patients who did not receive anticoagulation at discharge, more clinical data are needed for a conclusion.

The COVID-19 pandemic has resulted in an unprecedented acceleration in scientific production across multiple disciplines. The vast number of publications available makes it challenging for healthcare professionals and researchers to keep up with the current state of knowledge regarding COVID-19. This article presents covid19-help.org, a free expert-curated database designed to increase the availability of relevant original data related to COVID-19 treatment and prevention via immunization. To accelerate the process of identifying relevant original scientific publications and to simplify annotation of their content, the database uses our artificial intelligence in medical literature (AIM.lit) tool. The article provides an overview of the covid19-help.org database design, the criteria used to select publications, and the use of the AIM.lit tool. The database allows users to easily search and filter records, provides concise information on individual substances and their mechanisms of action, lists relevant original scientific publications with annotations, and offers links to external resources. The AIM.lit tool increases the speed of publication selection and extraction of basic relevant information, without compromising the validity of the data. The technology and experience gained from creating the covid19-help.org database and its tools could also be useful in other areas where scientific information organization is a challenge.

There is an urgent need to advance safe and affordable COVID-19 vaccines for low- and middle-income countries of Asia, Africa and Latin America. Such vaccines rely on proven technologies such as recombinant protein-based vaccines to facilitate its transfer for emerging market vaccine manufacturers. Our group is developing a two-pronged approach to advance recombinant protein-based vaccines to prevent COVID-19 caused by SARS CoV2 and other coronavirus infections. One vaccine is based on a yeast-derived (Pichia pastoris) recombinant protein comprised of the receptor binding domain (RBD) of the SARS-CoV formulated on alum and referred to as the CoV RBD219-N1 Vaccine. Potentially this vaccine could be used as a heterologous vaccine against COVID-19. A second vaccine specific for COVID-19 is also being advanced using the corresponding RBD of SARS-CoV-2. The first antigen has already undergone cGMP manufacture and is therefore “shovel ready” for advancing into clinical trials, following vialing and required GLP toxicology testing. Evidence for its potential efficacy to cross-protect against SARS-CoV-2 includes cross-neutralization and binding studies using polyclonal and monoclonal antibodies. Evidence in support of its safety profile include our internal assessments in a mouse challenge model using a lethal mouse adapted SARS strain, which show that SARS-CoV RBD 291N1 (when adsorbed to Alhydrogel®) does not elicit eosinophilic lung pathology. Together these findings suggest that recombinant protein-based vaccines based on the RBD warrant further development to prevent SARS, COVID-19 or other coronaviruses of pandemic potential.

The world is currently experiencing COVID-19, one of the worst pandemics that have happened in this century, affecting 10.7 million people worldwide. It has caused massive growth in the number of employees working from home. However, employees have minimal cybersecurity resources unlike organizations with security teams protecting them against attacks. Hence, cybersecurity plays an important role as users can be easily targeted by cybercriminals. This paper examines how cyberattacks have increased during this pandemic and shows how greatly they have affected health organizations, individuals and social networking applications. Results of the attacks include data breaches, false announcements and operations being disrupted. Attacks occurring during this pandemic and how they were handled are also critically discussed. The existing contributions do touch on related attacks but do not provide in-depth solutions regarding the issues. Even though there are many works and findings that were done previously, technology is ever evolving. Therefore, we need to be well versed with current and future issues and provide the latest mechanisms to prevent cybersecurity threats from occurring. On our share, we intend to present our findings on the challenges being faced by the population and its increasing threats as well as presenting unique solutions that can help organizations or related persons understand or spread awareness on the importance of cybersecurity. Through the research performed in this paper, it is found that there are many ways these issues can be alleviated. However, the issue is that there is significant lack of action and investment in terms of actual implementation and application of the available solutions.

The outbreak of Corona Virus effected negatively on the world’s economy which has already touched the maximum sectors. Readymade garments sector has the large contribution in Bangladesh’s economy. For increasing the locked down period, it is hitting badly by stopping production and cancellation of orders with some issues. This paper will represent the brief scenario and impacts of garments sector in recent days and the economy status of Bangladesh for the pandemic. The study is based on secondary data, collected from different authentic journals and web portals etc. Bangladesh’s garments earnings mostly depended on export but on these days, the buyers are cancelling their orders and the factories are being failed to give payments to the worker, some are being shut down also. As the duration of locked down is increasing, there is a huge chance to get unemployed and Bangladesh can be faced an undisciplined condition in near future. BGMEA and BKMEA are taking necessary steps to support the worker. Ensuring health security, the authorities are trying to reopen the factories limitedly to meet up the immediate needs. The government has taken the situation on most priority and introduce some improvement packages to run the economy smoothly and reduce the losses of the country for the pandemic.

Globally, an approximate of 380,000 patients succumbed to death due to the pandemic COVID-19 which also infected more than six million people since December 2019. Not sparing anyone, COVID-19 infections are widely reported among healthcare professionals, sanitation workers and researchers too while global leaders and various governments are providing their best in defending their citizens against this airborne and contact spread virus. In order to contain the virus and protect millions of lives from this deadly coronavirus, there is a need to have a combination of advanced engineering technology and medical facilities. Application of applied science, engineering and technology diffuse almost every aspect of contemporary living. Grasping the fundamentals to determine humanity's most imperative and forthcoming challenges is essential. Artificial Intelligence, the technology that learns, adapts and reciprocates the actions according to the situations, finds optimum position in the fight against corona virus and acts as a powerful tool against this pandemic. In this research article, the authors discusses how Artificial Intelligence (AI) can be leveraged to fight the deadly virus. The research paper further discusses the efficient utilization of AI across the globe to help in testing, treating and serving the population in these hard times. This manuscript focuses on the potential impact of the process in which AI can be implemented to prevent, test and treat.

Globally, there is massive uptake and explosion of data and challenge is to address issues like scale, pace, velocity, variety, volume and complexity of this big data. Considering the recent epidemic in China, modeling of COVID-19 epidemic for cumulative number of infected cases using data available in early phase was big challenge. Being COVID-19 pandemic during very short time span, it is very important to analyze the trend of these spread and infected cases. This chapter presents medical perspective of COVID-19 towards epidemiological triad and the study of state-of-the-art. The main aim this chapter is to present different predictive analytics techniques available for trend analysis, different models and algorithms and their comparison. Finally, this chapter concludes with the prediction of COVID-19 using Prophet algorithm indicating more faster spread in short term. These predictions will be useful to government and healthcare communities to initiate appropriate measures to control this outbreak in time.

On 11 March 2020, the coronavirus disease (COVID-19) was defined by the World Health Organization as a pandemic. Severe acute respiratory syndrome-2 (SARS-CoV-2) is the newly evolving human coronavirus infection, causing (COVID-19), first appeared in Wuhan, China in December 2019 and spread rapidly all over the world. COVID-19 is being increasingly investigated in virology, epidemiology, and clinical management strategies. There is currently no established consensus on the standard of care in the pharmacological treatment of COVID-19 patients. However, certain medications suggested for other diseases tend to be potentially effective for treating this infection, although, so far, without clear evidence. Therapies include new agents which are currently tested in several clinical trials, in addition to other medications that have been repurposed as antiviral and immune-modulating therapies. Previous high-morbidity human coronavirus epidemics such as the 2003 SARS-CoV and the 2012 Middle East respiratory syndrome coronavirus (MERS-CoV) prompted the identification of compounds that could theoretically be active against the emerging coronavirus SARS-CoV-2. Moreover, the advances in molecular biology techniques and computational analysis allowed better recognition of the virus structure and quicker screening of chemical libraries to suggest potential therapies. This review aims to summarize rationalized pharmacotherapy considerations in COVID-19 patients, to serve as a tool for health care professionals at the forefront of clinical care during this pandemic. All the therapies reviewed require either additional drug development or randomized large-scale clinical trials to be justified for clinical use.

This paper aims to analyze the effects of Covid-19 on financial markets from the perspective of Complexity. The Covid-19 pandemic has caused turmoil in financial markets and is already one of the most important financial crises in history, causing a fall in several stock markets as well as great volatility. Unlike past crises, which in most cases were caused either by problems of fiscal deficits or in the financial system, this crisis has its origin in an epidemic disease, which occurred in Wuhan, China, and quickly spread across the globe affecting transport networks, commerce and finance, and will affect the public debt of many countries. This is a systemic situation in which there is a need to consider several interconnected systems, financial instability and high financial risk, something that econophysics and some complexity theorists already do. Therefore, this paper intends to show, theoretically, the systemic and complex character of the recent financial crisis caused by Covid-19.

Severe COVID-19 disease is characterised by an exaggerated inflammatory response, called cytokine storm, accompanied by a condition of immune depression. Even sepsis is characterised by an exaggerated inflammatory response, called SIRS (Systemic Inflammatory Response Syndrome), accompanied by a condition of immune depression called CARS (compensatory anti-inflammatory response syndrome). Clinical studies reveal that most sepsis patients who did not die during the hyper inflammatory response (SIRS) subsequently succumbed to the condition of immune depression (CARS). Severe acute pancreatitis begins with local inflammation that induces systemic inflammatory response syndrome (SIRS), accompanied and followed by a compensatory anti-inflammatory response (CARS). In COVID-19 disease, the male response to SARS CoV-2 virus is typically characterised by a robust inflammatory response. Instead, a cell-mediated immune response is dominant in women. This means that the male sex tends to have a more robust hyper inflammatory response than the female one. Furthermore, in women the condition of immune depression is less represented, therefore they are more protected. Sepsis, severe acute pancreatitis and COVID-19 disease evolve between two fundamental aspects: hyper inflammation and immunodepression. The experience gained over years of studies of sepsis and severe acute pancreatitis suggests that therapies should be differentiated according to the evolutionary stage of the disease. The goal is to save the lives of most patients with COVID-19 disease. The identification of critical points, suitable for designing the windows of therapeutic opportunity, may allow the use of therapeutic interventions, in the COVID-19 disease, which are effective (there are no approved drugs yet), safe (without significant side effects), targeted (based on the evolutionary phase of the disease) personalized, (based on sex, co-morbidities, age, etc.) and timely (based on signs, symptoms, laboratory parameters and instrumental investigations).

To elucidate the cellular immune response to coronavirus disease (COVID-19) among children, we assessed cellular immunity in 8 children post-vaccination for COVID-19 and 11 children after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, using the T-SPOT®.COVID assay for both the spike (S) and nucleocapsid (N) proteins. In the vaccinated group, the T-SPOT®.COVID assay for the S protein yielded positive results in all eight children. In contrast, in the post-infection group, the assay for the N protein was positive in 5 of 11 children, with 3 of these 5 children requiring hospital admission, including 2 who needed mechanical ventilation. Therefore, the T-SPOT®.COVID assay is valuable for assessing cellular immunity against COVID-19, and most children infected with COVID-19 may not develop such immunity unless the disease severity is significant.

Background There is a considerable overlap between clinical presentation of post-COVID-19 condition (PCC) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) . Many of their common symptoms can be linked to dysregulation of the autonomic nervous system (dysautonomia). This study aimed to objectively assess autonomic function in patients with PCC and in patients with ME/CFS whose disease was not related to COVID-19. Methods Synchronous recordings of an electrocardiogram, continuous dynamics of blood pressure in the digital artery using the Penaz method and ultrasound pneumotachography with the spirography function were obtained with spiroarteriocardiorhythmography method in 34 patients diagnosed with ME/CFS, in whom the onset of the disease was not associated with COVID-19, 29 patients meeting PCC definition and 32 healthy controls. Heart rate variability (HRV), systolic and diastolic blood pressure variability (RV), respiration variability were assessed at rest and in tests with fixed respiratory rates. At rest, indicators of baroreflex regulation were additionally determined (baroreflex effectiveness index and baroreflex sensitivity). Results The total power, power of very low frequency, low-frequency and high-frequency of RR interval variability at rest as well as baroreflex effectiveness index in up-ramps of arterial blood pressure and baroreflex sensitivity were significantly lower both in PCC and ME/CFS patients compared to HC. Several diagnostic prediction models for ME/CFS were developed based on HRV parameters. During slow breathing HRV parameters return to normal in PCC, but not in ME/CFS. Correlation analysis revealed a close relationship of HRV, RV parameters and baroreflex sensitivity with fatigue, but not with HADS depressive/anxiety symptoms in ME/CFS and PCC. Conclusion A similar pattern of HRV and baroreflex failure with signs of a pathological acceleration of age-dependant dysautonomia was identified in ME/CFS and PCC. The clinical, diagnostic and therapeutic implications of these findings are discussed, in light of previously described relationship between inflammation, vascular pathology, atherosclerotic cardiovascular disease and autonomic dysfunction.

The novel coronavirus disease 19 (COVID-19) has resulted in an estimated 20 million excess deaths and the recent resurgence of COVID-19 in China is predicted to result in up to 1 million deaths over the next few months. With vaccines unable to halt transmission it is important to continue our quest for safe, effective, affordable drugs that will be available to all countries. Drug repurposing is one of the strategies being explored in this context. Recently, out of 7,817 approved drugs, 214 candidates were systematically down-selected using a combination of 11 filters including approval status, assay data against SARS-CoV-2, pharmacokinetic, pharmacodynamic and toxicity profiles. These drugs were subjected in this study to virtual screening against various targets of SARS-CoV-2 followed by molecular dynamic studies of the best scoring ligands against each target. The chosen molecular targets were Spike receptor binding domain, Nucleocapsid protein RNA binding domain, and key non-structural proteins 3, 5, 12, 13 and 14. Four drugs approved for other indications — alendronate, cromolyn, natamycin and treprostinil — look sufficiently promising from our in silicostudies to warrant further in vitro and in vivo investigations as appropriate to ascertain their extent of anti-viral activities.

The global spread of coronavirus disease (COVID -19) worldwide has had a significant effect on social and economic growth. The contamination keeps on advancing quickly and eccentrically, representing a significant test to its recognition and conclusion. Coronaviruses are commonly recognized by seclusion from tests, regardless of whether natural or clinical, utilizing some atomic science procedures, which can take a few days. In this work an analytical review of virus transmission, methods of diagnosing COVID -19 using artificial intelligence techniques to classify images and types of biosensors. At long last, the deformities and points of interest of each kind of sensor are recognized and examined. This exploration gives an explanatory audit of the utilization of crown infection COVID-19 in 2019. Related examinations were led utilizing five dependable databases, for example, Science Direct, IEEE Xplore, Scopus, Web of Science, and PubMed. An acceptable investigation is remembered for this audit, which can be depended upon as a logical database to put resources into another technique for recognizing COIVD-19.

Persistence of symptoms beyond three months after COVID-19 infection, often referred to as post-COVID-19 condition (PCC), is commonly experienced. It is hypothesized that PCC results from autonomic dysfunction with decreased vagal nerve activity, which can be indexed by low heart rate variability (HRV). The aim of this study was to assess the association of HRV upon admission with pulmonary function impairment and number of reported symptoms beyond three months after initial hospitalization for COVID-19 between February and December 2020. Follow-up took place three to five months after discharge and included pulmonary function tests and the assessment of persistent symptoms. HRV analysis was performed on one 10s electrocardiogram obtained upon admission. Analyses were performed using multivariable and multinomial logistic regression models. Among 171 patients who received follow-up, and with an electrocardiogram at admission, decreased diffusion capacity of the lung for carbon monoxide (DLCO) (41%) was most frequently found. After a median of 119 days (IQR 101-141), 81% of the participants reported at least one symptom. HRV was not associated with pulmonary function impairment or persistent symptoms three to five months after hospitalization for COVID-19.

This study is a cross-sectional survey involving physicians around Indonesia aimed to explore physician hesitancy to treat COVID-19 patients after experiencing COVID-19 infection coupled with associated occupational risk factors. The questionnaire was distributed via contact information from the Indonesian Physician Association database. Out of 383 participants, 25.6% suffered from moderate symptoms of COVID-19 and 2.9% were admitted for critical care. Hesitancy to treat suspected, probable, or confirmed COVID-19 patients was found in 20.3% of physicians. A higher hesitancy rate was found in older physicians and those with less experience in treating COVID-19 patients. Specialist trainees and those who work in public hospitals were physicians with the lowest hesitancy in treating COVID-19 patients. There is a significant hesitancy in treating COVID-19 patients among physicians who have suffered from COVID-19 which calls for further action by management and policy makers.

For over two years, the global COVID-19 pandemic has persisted, and its continuation is anticipated. The emergence and rapid spread of numerous new virus variations across continents have been observed. These variants, differing from previously known strains, manifest a spectrum of behaviors and clinical presentations, ranging from asymptomatic cases to severe illnesses and fatalities. Despite substantial research efforts in recent years, significant uncertainties persist in understanding the disease, encompassing variations in clinical outcomes, comorbidities, and challenges faced by individuals infected with COVID-19. Beyond the acute phase of infection, the prevalence of post-COVID-19 symptoms, often denoted as "long COVID," is notable, particularly in individuals recovering from the disease. Nevertheless, a research gap persists concerning the pathophysiological mechanisms underlying newly emerging viral variant infections, post-COVID-19 conditions, and the corresponding therapeutic strategies. This review is presented to analyze recent advancements in comprehending the pathophysiology and therapy of COVID-19.

Background : Our objectives were to investigate the incidence of elevated methemoglobin level among COVID-19 patients at intensive care unit. The correlation of methaemoglobinemia with mortality and some haematological parameters was also tested. Methods: The diagosis of coronavirus -19 infection was confirmed by RT-PCR. The quantitative method for determination of methemoglobin was it’s cyanide derivative by spectrophotometry. The reference range was less than 2 percent. Results: There were altogether 46 patients (11 male, 35 female) included. Their median age value was 70 y. ( 29 – 89). The methemoglobin median value was 4,3%. 15 of 46 patients died. The methemoglobin median value of departed patients was 8 % , and 2,5% was among survivors. ( P= 0,001) 19 patients were blood transfused. Their methemoglobin median was 11 % , otherwise the non transfused patients presented 2,7 % methemoglobin median. ( p= 0,001). We performed two binary logistic regression calculation, in order to judge the elevated methemoglobin level as an independent risk factor for the mortality. The predictor of methaemoglobin was 0,062 the constant -1,266 the odds ratio 1,06. The other binary logistic regression tested the fact of transfusion for the mortality. Predictor of transfusion 1,1474, constant -1,2527 odds ratio 3,15 There was no significant correlation between methemoglobin and CRP level. Discussion: The methemoglobin is not able to transport oxygen. It’s association with mortality is discussed by some papers.There are several hypothesis in the literature to explain it’s occurrence in COVID-19. The role of coronavirus proteins as oxydative agents was mentioned. The importance of enzyme defect is emphasized. The impact of reactive oxygen free radicals in inflammation is also probable. Some papers mentioned applying local anesthetics and azythromycin as a risk. The role of transfusion is obscure, because the methemoglobin can be elevated in blood conserves during storage. Conclusion: Testing the methemoglobin seems to be important, but the pathomechanism needs further research.. The traceability and standardization of different measurement methods at intensive care units is the key for defining it’s pathogenetic role.

The novel coronavirus has affected the mental state of the general public, more so among healthcare workers. During the pandemic when the infectivity had become intense, dental professionals were at stake as their work demanded more proximity with oral and nasal secretions. Many dentists had to close their clinics for fear of infection. This had a significant impact on their financial, social and emotional wellbeing. Stress is what arises when something we care about is at stake. Dentistry which is already a stressful discipline, the pandemic has multiplied the already existing pressures of isolation, the focus on perfectionism, compromise on treatment, and time pressures. Our study has attempted to assess the perceived stress among dentists and the various correlates impacting the same. Resilience is the capacity to bounce back productively during stressful situations. Resilience acts like a buffer to wither stress. Resilience is neither permanent nor global. In our study, we have attempted to assess resilience among dentists using a standard validated scale and various sociodemographic factors impacting resilience. Further, we have tried to assess the correlation between stress and resilience. We found that senior dentists with more years of experience had more resilience and their perceived stress was less. Though we found increased perceived stress among women dentists, resilience did not have any gender difference. It is essential to be pandemic prepared with the implementation of resilience-building strategies at various levels.

Abstract: Background: COVID-19 is a respiratory disease that eventually became pandemic with 300 million people infected around the world. Alongside the improvement in COVID-19 management and vaccine development, identifying biomarkers for COVID-19 has recently reported to help in early prediction and managing severe cases which might improve outcome. The Aim of our study was to find out if there is any correlation between clinical severity and elevated hematological and biochemical markers in Covid-19 patients and its effect on the outcome Methods: We have collected data retrospectively of socio-demographic, medical history, biomarkers, and diseases outcome from five hospitals and health institutions in the Kingdom of Saudi Arabia. Results: Pneumonia was the most common presentation of COVID 19 in our cohort. All biomarkers (D-Dimer, CRP, troponin, LDH and ferritin) except for the mean lowest white blood cells were found to have significant correlation (p<0.05) with worse COVID-19 disease outcomes. There was a sig-nificant association between the inflammatory biomarkers and the disease severity of COVID 19 patients (p<0.001). Patients with evidence of severe respiratory disease particularly who required mechanical ventilation (MV) had higher biomarkers, when compared to those with stable respiratory condition (p<0.001). Conclusion: Identifying biomarkers predicts outcome for COVID-19 patients and may significantly help in the management.

The situation in the world of pandemics is rapidly changing, and the second wave of COVID-19 has put a lot of pressure on the government and private sector, which are primarily responsible for controlling the situation. COVID-19 positive cases have increased in recent months relative to last year, and the number of patients admitted to hospitals has also increased, despite the fact that few of them were denied admission due to shortage of beds. Normal people who experience any symptoms immediately isolate themselves and begin taking the COVID medications prescribed by medical personnel and their team. During these times, all domestic people tossed the wrappers and boxes of medicines into the regular trash can, and the waste was handed over to the waste collector, who treated it like any other domestic waste and disposed of it using open dumping or other methods. The goal of this perspective is to suggest the collections of these types of waste from domestics, and protect the natural resources like water, soil, and even living beings like animals from pollution (from the effect of SARS-CoV-2). The main challenge for environmental waste management agencies is determining who has COVID positive and which houses generate these types of waste; thus, proposed strategy may be beneficial to the long-term sustainability of natural resources and animals.

In the advent of COVID-19 pandemic, testing is highly essential to be able to isolate, treat infected persons, and finally curb transmission of this infectious respiratory disease. Group testing has been used previously for various infectious diseases and recently reported for large-scale population testing of COVID-19. However, possible sample dilution as a result of large pool sizes has been reported, limiting testing methods’ detection sensitivity. Moreover, the need to sample all individuals prior to pooling overburden the limited resources such as test kits. An alternative proposed strategy where test is performed on pooled samples from individuals representing different households is presented here. This strategy intends to improve group testing method through the reduction in the number of samples collected and pooled during large-scale population testing. Moreover, it introduces database system which enables continuous monitoring of the population’s virus exposure for better decision making.

Aim: This study was designed to understand the changes in dietary and lifestyle behaviours that are major determinants of health during the COVID-19 outbreak. Methods: A cross-sectional study was conducted through an online questionnaire using a convenience sample of 415 adults living in Kuwait (age range 18-73 years). Results: The overall prevalence of being overweight and obesity among participants was 37.2% and 33.1% respectively. The study identified significant changes in the dietary habits and lifestyle behaviours of participants during COVID-19. In general, there was an increase in the percentage of participants that consumed four or more meals a day, skipped breakfast, and engaged in frequent late night snacking. Moreover, there was a drastic decrease in the frequency of fast food consumption and an increase in the percentage of participants who had their main meal freshly made. Furthermore, there was a great reduction in physical activity and an increase in the amount of screen time and sedentary behaviours. A notable increase was detected in day-time sleep and a decrease in night-time sleep among participants. Conclusion: This study indicates that due to the increased prevalence of habits conducive to increased rates of being overweight and obesity during the COVID-19 outbreak, there is a high likelihood that the pandemic will further exacerbate the already widespread problem of obesity and being overweight in Kuwait.

The COVID-19 has caused gigantic negative effects on populace wellbeing, society, education, and the economy in Bangladesh. The aim is to deliver a comprehensive overview of the observed and the possible impacts that could appear in the coming days. The study is based on secondary information. During the early period, due to a lack of accurate facts about the case affected and death tension up-and-down among the nations. The total number of confirmed cases is increasing following geometric patterns in Bangladesh. Dairy farmers, vegetable producers, pharmaceuticals, poultry farmers are in deep crisis due to lower prices. Also, the pandemic has seriously affected educational systems, banking, FDI, ready-made garments, remittances, etc Finally, it is not possible to mitigate the effects of pandemic individually but the integrated effort from the state authority as well as concern people of all sectors need to come forward.

In the ongoing Covid-19 pandemic, if a preventive restriction (PR), intended to arrest the transmission of the virus, is effective we expect a decrease in the rate of transmission. If an effective PR is lifted or relaxed, the rate may show some increase. We test this expectation in the history of PR imposition and relaxation in all countries based on available public database. We found marginal or no negative correlation between standing stringency index of PR and change in slope of the local curve. A change in stringency index was significantly negatively correlated with change in slope, but change in stringency of PRs could explain only 6.1 percent of the variance in rates of transmission. The distribution of slope changes after imposing versus after relaxing PRs was highly overlapping with only a tail consisting of 4.5 % PR impositions being clearly non-overlapping with PR relaxation. Non-parametrically, only 9.4% of PR impositions were associated with a reduction in the slope above the expectation of a null hypothesis. In brief, globally, preventive restrictions have played a very small role in the pandemic process over the one year period. This feedback needs to be considered in making policy for disease prevention in the further course of the pandemic as well as in any future threats of respiratory disease epidemics.

COVID-19, previously known as “2019 novel coronavirus”, is a newly discovered virus which causes severe acute respiratory syndrome, similar to corona virus 2 (SARS-CoV-2), which has spread widely through human to human contact and was declared a pandemic by the WHO in March 2020. To cope with this pandemic many countries have adopted nationwide lockdowns which restrict nonessential activities and encourage their populations to avoid public transport, work from hone wherever possible, and to maintain social distancing at all times. While the severity of these shutdowns has varied with country, large geographic regions of the world (including China, India, Iran, Italy, Spain, and the USA) have all been severely affected, not just in the loss of human life, but also in terms of the financial impacts the lockdowns will have on their countries future prosperityIt was previously reported that a number of environmental factors, including humidity and temperature, played an important role in development and spread of the SARS-Corona Virus infection with the virus retaining viability for over 5 days at temperatures between 22–25^oC and relative humidity (RH) of 40–50%. Whereas, elevated temperatures and higher RH (38^oC, and >95% RH) decreased virus viability (Kroumpouzos et al., 2020). The spread of COVID-19 started in low temperature areas of China, with major outbreaks subsequently occurring in Iran, Japan, Northern Italy and South Korea. These new virus epicenters all had similar temperature and latitude, along the 30-50^◦N” zone. Subsequently, the virus was spread to regions of elevated temperature, such as India, the Middle East and Thailand, due to international travel (Kroumpouzos et al., 2020).The aim of this study was to consider the environmental impact of COVID-19, including water pollution. The paper is divided into four sections. In the first section the current literature related to COVID-19 is reviewed. In the second section a recent update on COVID-19 globally is presented, followed by a descriptive impact on the environment in the third section and finally in the fourth section the COVID-19 related worldwide environmental impact is discussed. Since COVID-19 is a currently an active pandemic with no end in sight, while constructive conclusions can only be made on the limited data currently, which may be prone to high errors. However, these conclusions may provide some preliminary suggestions for assisting in assessing spreading patterns of COVID-19 across the globe, and may be of long-term significances with respect to assessing the environmental impact of lockdown policies due to COVID-19 worldwide.

Socio-demographic factors are responsible of health inequalities also in vaccination. The aim of this study was to evaluate their role at population level through a population-based study performed on the whole population entitled to receive COVID-19 vaccines in Umbria Region, Italy, and registered to the Regional Healthcare Service as of February 28th, 2021. Socio-demographic characteristics and vaccination status in terms of uptake at least one dose of any available vaccine, completion of the primary vaccination cycle and uptake of the booster doses as of February 28th, 2022 were col-lected from the Umbria regional database. The percentage of eligible population who did not initiate the COVID-19 vaccination, complete the full vaccination cycle and get the booster dose was 11.8%, 1.2% and 21.5% respectively. A younger age, being a not-Italian citizen, and not holding an ex-emption for chronic disease/disability and a GP/FP were associated to all the endpoints. Females, as compared to males, were more likely to not initiate the vaccination but less likely to not receive the booster dose. On the contrary, results on the deprivation index were not conclusive. The findings, beyond confirming current knowledge at population level, provide new inputs for better tailoring vaccination campaigns.

Currently, there is no specific treatment for COVID-19 proven by clinical trials. WHO and CDC guidelines therefore endorse supportive care only. However, frontline clinicians have been applying several virus-based and host-based therapeutics in order to combat SARS-CoV-2. Medications from COVID-19 case reports, observational studies and the COVID-19 Treatment Guideline issued by the China's National Health Commission (7^th edition published March 3^rd, 2020. Edited translation attached) are evaluated in this review. Key evidence from relevant in vitro researches, animal models and clinical studies in SARS-CoV-2, SARS-CoV and MERS-CoV are examined. Antiviral therapies remdesivir, lopinavir/ritonavir and umifenovir, if considered, could be initiated before the peak of viral replication for optimal outcomes. Ribavirin may be beneficial as an add-on therapy and is ineffective as a monotherapy. Corticosteroids use should be limited without indicating comorbidities. IVIG is not recommended due to lack of data in COVID-19. Xuebijing may benefit patients with complications of bacterial pneumonia or sepsis. The efficacy of interferon is unclear due to conflicting outcomes in SARS and MERS studies. Chloroquine and hydroxychloroquine have shown in vitro inhibition of SARS-CoV-2 and may be beneficial as both prophylactic and treatment therapy. For patients who developed cytokine release syndrome, interleukin-6 inhibitors may be beneficial. Given the rapid disease spread and increasing mortality, active treatment with readily available medications may be considered timely prior to disease progression.

Almost four years after COVID-19 was declared a global health emergency, equitable distribution of the vaccine remains a challenge, especially among homeless people, the fastest growing population in Brazil. Therefore, we sought to identify the factors associated with completion of the COVID-19 vaccination schedule among homeless people in Brazil. Materials and Methods: We carried out a cross-sectional study in the capital cities of Brazil's Federative Units, considering people living on the streets as the target population. We used a sequential inclusion approach, with individual interviews conducted by trained professionals, using a validated questionnaire. We used descriptive statistics to analyze the data and a binary logistic regression model to identify factors associated with homeless individuals who completed the COVID-19 vaccination schedule. Results: It was identified that the highest density of homeless people and indicators related to COVID-19 is located in the Northeast, Southeast and South regions of Brazil. The primary data sample consisted of 1,392 participants, predominantly male (n: 961; 69.0%), with an average age of 38.3±15.2 years, belonging to the black/brown race/color (n: 1,097; 78.8%), with an elementary school education (n: 1,060; 76.1%). The factors associated with completing the vaccination schedule were: receiving government aid (OR: 1.58; 95%CI: 1.09 - 2.30), visits from Health Agents from the Street Clinic (OR: 3.19; 95%CI: 1.95 - 5.36), history of COVID-19 (OR: 5.77; 95%CI: 3.17 - 11.15), support for mandatory vaccination against COVID-19 (OR: 3.76; 95%CI: 2.48 - 5.76), trust in the efficacy of vaccines (OR: 3.92; 95%CI: 2.63 - 5.89), seeking information from NGOs, street clinics, community leaders (OR: 1.91; 95%CI: 1.01 - 3.88) and trust in the Federal Government's statements on vaccines (OR: 1.57; 95%CI: 1.06 - 2.31).Conclusion: The study advances knowledge by highlighting the completeness of the COVID-19 vaccination schedule among the homeless population. The source of information proved to be one of the determinants of completeness, and the Unified Health System played a leading role in raising awareness among homeless people, notably through its strategy of street clinics, when available. The evidence points to the importance of affirmative and inclusive actions that guarantee access to the vaccine for homeless people.

The harrowing second wave of COVID-19 in India has led to much discussion over the quality and timeliness of reporting of deaths attributed to the pandemic. In this brief report, we aim to present the existing evidence, as well as the broader complexities surrounding the mortality burden of COVID-19 in India. This article sheds light on the following epidemiological issues: (1) general and India-specific challenges to COVID-19 death reporting, (2) latest COVID-19 mortality estimates in India as of May 16, 2021, (3) the apparent scale of uncaptured COVID-19 deaths, and (4) the role of disaggregated historic mortality trends in quantification of excess deaths attributed to COVID-19. We conclude with a set of high-level policy recommendations for improving the vital surveillance system and tracking of causes of death in India. We encourage direct efforts to integrate health data and indirect strategies for cross-validation of registered deaths. Such system-wide advances would drastically aid epidemiological research efforts and strengthen India’s position to overcome future public health crises.

The article revisits previous viruses such as Ebola to extrapolate the socio-economic implications of the COVID-19. Using secondary sources and the Sustainable Livelihoods Framework (SLF) to guide understanding, the article argues that unless measures are put in place to safeguard smallholder activities in Zimbabwe, COVID-19 has the potential to reproduce the same catastrophic implications created by Ebola in West African countries where peasant food systems where shattered and livelihoods strategies maimed. With a perceptible withdrawal of the government from small-scale farming towards large-scale capital intensive operations, smallholders could now be even more vulnerable. The article concludes that social assistance should now be intensified to protect its vulnerable population from the ravages of COVID-19.

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.

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&lt;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&lt;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.

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.

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.

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.

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.

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.

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 detection of coronavirus (COVID-19) is now a critical task for the medical practitioner. The coronavirus spread so quickly between people and approaches 100,000 people worldwide. In this consequence, it is very much essential to identify the infected people so that prevention of spread can be taken. In this paper, the deep feature plus support vector machine (SVM) based methodology is suggested for detection of coronavirus infected patient using X-ray images. For classification, SVM is used instead of deep learning based classifier, as the later one need a large dataset for training and validation. The deep features from the fully connected layer of CNN model are extracted and fed to SVM for classification purpose. The SVM classifies the corona affected X-ray images from others. The methodology consists of three categories of Xray images, i.e., COVID-19, pneumonia and normal. The method is beneficial for the medical practitioner to classify among the COVID-19 patient, pneumonia patient and healthy people. SVM is evaluated for detection of COVID-19 using the deep features of different 13 number of CNN models. The SVM produced the best results using the deep feature of ResNet50. The classification model, i.e. ResNet50 plus SVM achieved accuracy, sensitivity, FPR and F1 score of 95.33%,95.33%,2.33% and 95.34% respectively for detection of COVID-19 (ignoring SARS, MERS and ARDS). Again, the highest accuracy achieved by ResNet50 plus SVM is 98.66%. The result is based on the Xray images available in the repository of GitHub and Kaggle. As the data set is in hundreds, the classification based on SVM is more robust compared to the transfer learning approach. Also, a comparison analysis of other traditional classification method is carried out. The traditional methods are local binary patterns (LBP) plus SVM, histogram of oriented gradients (HOG) plus SVM and Gray Level Co-occurrence Matrix (GLCM) plus SVM. In traditional image classification method, LBP plus SVM achieved 93.4% of accuracy.

Background: This study aimed to examine the course of Depression and anxiety in COVID-19 survivors with a psychiatric history compared with those without a psychiatric history. Methods: A web-based cross-sectional survey for COVID-19 survivors was conducted from July to September 2021. 6016 COVID-19 survivors, the accuracy of whose responses was determined to be assured, were included in analyses. Exposures included psychiatric history and time since COVID-19 infection, and the main outcomes and measures included severity of depression and anxiety, as assessed using the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7), respectively. Results: Mean severity of PHQ-9 and GAD-7 were significantly higher in participants with a psychiatric history than in those without a psychiatric history. Two-way analysis of covariance for PHQ-9 showed a significant main effect of the presence of psychiatric history and a significant interaction effect of psychiatric history × time since infection. Two-way analysis of covariance for the GAD-7 score revealed a significant main effect of the presence of psychiatric history and time since COVID-19 infection and the interaction effect of these factors. Conclusions: The course of depression and anxiety was more severe in COVID-19 survivors with a psychiatric history than in those without a psychiatric history.

The aim of the article is to determine the predictors of mental health among Polish society. Research was conducted after the first wave of the pandemic. Due to such an approach, it was possible to determine whether secondary effects of the pandemic have impact on mental health, apart from socio-demographic and psychological factors. In order to gather the research material, the CAWI on-line survey method was applied and carried out within the framework of the Ariadna Research Panel on the sample of 1079 Poles aged 15 and over. The FCV-19S scale, which is used to measure the fear of COVID-19 was applied in the measurement. It is a verified diagnostic instrument used to measure mental health in a lot of countries. The results of a hierarchical regression analysis have shown that the factors which increase the level of fear of COVID-19 are demographic, social and psychological features as well as attitudes towards the pandemic. The results of research indicate the significance of social context in the analysis and explanation of the effects of disasters and cataclysms.

The emergence of novel coronavirus (SARS-CoV-2) in marked as the highest pathogenic coronavirus that has crossed from the hosts to the human population in the twenty-first century. The spreading of COVID-19 in different chinese cities and around the world is travel-related viral spread with the unprecedented nosocomial outbreaks. It has also shown with high case-fatality rates, indeed to urgent prophylactic and therapeutic settings. Scientific advancements of the SARS-CoV-2 pandemic allowed for rapid progress to understand the epidemiology and pathogenesis of SARS-CoV-2. This review highlights the the genomic structure of SARS-CoV-2 with the proposed roles of genotype and phenotype of SARS-CoV-2 in pathogenesis and discuss recent results supporting treatment strategies of COVID-19 with a special focus on how these new insights may facilitate rational development of SARS-CoV-2 for targeted therapies in the future.

A striking aspect of COVID-19 is the difference in the outcome of the infection between different countries, and different ethnic groups within one country. We surveyed the literature on SARS-CoV-2 complemented with comparative publications on SARS-CoV and other coronaviruses to capture the current understanding of virus – host interactions including virus subtypes, transmission, zoonotic aspects, and potential host determinants.

In the context of the COVID-19 pandemic, thousands of healthcare workers (HCWs) infected with COVID-19 have lost their lives worldwide. At the early stage of the epidemic, when COVID-19 was still not considered as a pandemic, a large number of Chinese HCWs were infected. Officials reported that more than 3,000 HCWs in Hubei contracted the virus at the early stage of the outbreak due to limited knowledge of the virus. Following reports of overloaded local hospitals, more than 42,000 medical staff, including those from the military, were dispatched to Hubei from across the country. At the peak of the fight, one in 10 intensive care medics in China were working in Wuhan. During fighting against COVID-19 in China, although a large number of HCWs were infected by SARS-CoV-2 in the early stages of the epidemic, the timely adoption of measures indicated that, a faster rate of diagnosis could be achieved, patients were isolated in-time, HCWs’ safety was prioritized, training on basic protective knowledge and unified management of HCWs was strengthened, and effective protective measures were implemented. This resulted in the accomplishment of zero SARS-CoV-2 infection among the 42,632 members of the national medical teams sent to Hubei, and the number of COVID-19 cases among HCWs in local hospitals also significantly decreased, thereby indicating that hospital-acquired infections of SARS-CoV-2 among HCWs are fully preventable.

With the rapid evolution of SARS-CoV-2, the emergence of new strains is an intriguing question. This paper presents an evolutionary theory to analyze the mutations of the virus and identify the conditions that lead to the generation of new strains. We represent the virus variants using a 4-letter sequence based on amino acid mutations on the spike protein and employ an n-distance algorithm to derive a variant phylogenetic tree. We show that the theoretically-derived tree aligns with experimental data on virus evolution. Additionally, we propose an A-X model, utilizing the set of existing mutation sites (A) and a set of randomly generated sites (X), to calculate the emergence of new strains. Our findings demonstrate that a sufficient number of random iterations can predict the generation of new macro-lineages when the number of sites in X is large enough. These results provide a crucial theoretical basis for understanding the evolution of SARS-CoV-2.

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

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

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

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

COVID-19 is a potentially fatal viral infection. This study investigates geography, demography, socioeconomics, health conditions, hospital characteristics, and politics as potential explanatory variables for death rates at the state and county levels. Data from the Centers for Disease Control and Prevention, the Census Bureau, Centers for Medicare and Medicaid, Definitive Healthcare, and USAfacts.org were used to evaluate regression models. Yearly pneumonia and flu death rates (state level, 2014-2018) were evaluated as a function of the governors’ political party using repeated measures analysis. At the state and county level, spatial regression models were evaluated. At the county level, we discovered a statistically significant model that included geography, population density, racial and ethnic status, three health status variables along with a political factor. State level analysis identified health status, minority status, and the interaction between governors’ parties and health status as important variables. The political factor, however, did not appear in a subsequent analysis of 2014-2018 pneumonia and flu death rates. The pathogenesis of COVID-19 has greater and disproportionate effect within racial and ethnic minority groups, and the political influence on the reporting of COVID-19 mortality was statistically relevant at the county level and as an interaction term only at the state level.

Seroprevalence studies suggest that the number of PCR-confirmed COVID-19 cases is significantly smaller than the true number of infections. I study logintidual seroprevalence data from 7 sites across the US, from early April 2020 to June 27. I show that not only COVID-19 seroprevalence does not seem to increase over time, there is no clear association between the number of cases reported during a period and the change in seroprevalence during the same time. I conclude that as they are, seroprevalence studies can only be used in the qualitative sense and distinguish between populations with no COVID-19 exposure, to those populations where the virus had already started spreading.

Currently, the COVID‐19 has directly affected the millions of humans lives. The symptoms of the disease involving fever, malaise, chest infection, and breathing difficulties, were identified, and its existence is continuously becoming restructured. The World Health Organization (WHO) had mentioned the wide diagnostics test besides COVID-19 that would also assist medical facilities to recognize infectious diseases as well as currently focusing efficiently on preventing and afterward defeating this viral disease. The infection is usually transmitted among human beings in direct contact, greatest through the liquid bubbles generated through cough, sneeze, or speaking. This paper reviews the COVID 19 pandemic, its history, current updates, contact tracing applications, and use of emerging technologies like the Internet of Things (IoT) and Blockchain for stopping the spreading and provide service online to the patient from a distance.

Some COVID-19 patients develop interstitial pneumonia that can evolve into Acute Respiratory Distress Syndrome (ARDS). This is accompanied by an inflammatory cytokine storm. SarS-CoV has proteins capable of promoting cytokine storm, especially in patients with comorbidities, including obesity. Since there is currently no resolutive therapy for ARDS and given the scientific literature regarding the use of adenosine, its application has been hypothesized. Adenosine through its receptors is able to inhibit the acute inflammatory process, increase the protection capacity of the epithelial barrier and reduce the damage due to an overactivation of the immune system, such as in cytokine storms. These features are known in ischemia / reperfusion models and could also be exploited in acute lung injury, with hypoxia. In light of these hypotheses, for compassionate use, a COVID-19 patient, with unresponsive respiratory failure, was treated with adenosine. The results showed a rapid and clear improvement in clinical conditions, with the negative effect of detection of SarS-CoV2.

Bangladesh has adopted some special steps to control the quick spread of the COVID-19 pandemic situation. However, the local residents’ knowledge, attitudes, and practices towards the disease have a direct impact on the success of the controlling measures taken by the state. This article explores knowledge (K) about preventions, attitude (A) to the disease, and practices (P) of preventing COVID-19 situation of the young age groups residing in Bangladesh. Quantitative data were collected online using a KAP questionnaire from 932 participants. Results show the population is generally aware of the symptoms, keeping social distance by staying home and are concerned about re-spreading after the lock-down period. However, they are quite unsure about the possible medicines frequently talked about in the media and the necessity of avoiding animal protein. One of the major limitations is, these findings should not be generalized due to the low number of participants compared to the total population in Bangladesh.

The outburst of the CoVid-19 pandemic has raised several questions leading to a complex system in terms of modeling. Indeed, the modeling of the epidemic, at the level of a country, needs considering each of the different sources of contamination as well as the public health authorities' strategy, in a specific way. With this in mind, in the present paper, we develop a mathematical model of the CoVid-19 epidemic in Senegal. In the model, the population is subdivided into five compartments: susceptible, infected but asymptomatic, symptomatic, quarantined, and recovered immune people. In addition, due to its important impact on the propagation of the disease, we add one more variable: the number of infected objects. %\vspace{1mm} Therefore, the model corresponds to a system of six non-linear ordinary differential equations we submit to an analytical study to prove the relevancy of the model, simulate the evolution of the epidemic, and retrieve epidemiological parameters, namely the infection rate and the basic reproduction number, ${\cal R}_0$. Based on the senegalese territory CoVid-19 data, we simulate various scenarios as for the evolution of the epidemic in the country, in order to predict the peak and its magnitude with regard to the application of barrier measures. We also explore the option of collective immunity with special protection for vulnerable people. In doing so, non-available parameters are identified using some mathematical identification technics.

The recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread so rapidly and severely affected the people of almost every country in the world. The highly contagious nature of this virus makes it difficult to take control of the present pandemic situation. With no specific treatment available, the coronavirus disease 2019 (COVID-19) presents a threat to people of all ages including the elderly people and people with other medical complications as a vulnerable group to this disease. Better understanding of viral pathogenesis, appropriate preventive measures, early diagnosis and supportive treatments of the infected patients are now the general solutions to fight against this viral transmission. But, as an emerging disease, most about it remains still poorly understood. This article holds an overview on the origin and structure, pathogenesis, diagnosis and possible therapeutic options for the causative agent, SARS-CoV-2 and disease, COVID-19. However, few therapeutic options, laboratory experiments and other strategies proposed here need to be further clinically tested.

The spread of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions, affecting over 150 countries in a matter of months. Even though containment measures in China have reduced new cases by more than 90%, this reduction is not the case elsewhere, as the US, Spain and Italy have come off worse-off by the spread of the virus, and there is serious concern regarding the national health systems' capacity around the world and Africa, in particular, to effectively respond to the needs of infected patients who require intensive care for the COVID-19 illness. As a result, authorities around the world have resorted to the lockdown strategy to curb the spread of the virus. Therefore, the study aimed at investigating the effect of the lockdown strategy in curbing the spread of the COVID-19 virus in Nigeria. Consequently, the study found daily relative risk increase in cases, and daily relative risk increase in mortality. Also observed is the growth in cases in areas where active measures were not taken. Further, halt in business activities has rendered many penniless and unable to provide for themselves basic amenities. The study recommends that there is need to implement community-level measures of social distancing which may include closing schools, need for individuals with COVID-19 case or respiratory symptoms be properly taken care of, trace and quarantine those who must have come in contact with affected persons and introducing stay at home palliatives for the general public.

An outbreak of a pandemic COVID-19 disease caused by a novel coronavirus SARS-CoV-2 has posed a serious threat to human health and the economy of the whole world. Bangladesh is one of the most densely populated countries in the world, which has also come under the attack of this viral disease. This perspective report aimed to describe the responses of Bangladesh to tackle the COVID-19, particularly on how Bangladesh is dealing with this novel viral disease with limited resources. The first case of a COVID-19 patient was detected in Bangladesh on March 8, 2020. Since then, a total of 2,144 peoples are officially reported as COVID-19 infected with 84 deaths. To combat the COVID-19, the government has taken various steps to tackle the epidemic outbreak of it such as diagnosis of the suspected cases, quarantine of doubted people and isolation of infected patients, local or regional lockdown, grant general leave from all offices for staying home of people, increase public awareness and enforce social distancing and so on. In addition, to address the socio-economic situations, the government announced several financial stimulus packages of about USD 11.17 billion. However, very limited diagnostic facilities, health workers, resources such as hospital beds, personal protective equipment, intensive care unit, and ventilators in the hospitals along with limited public unawareness are the major challenges for Bangladesh to tackle the situation effectively. This report described the responses of Bangladesh to tackle the COVID-19 and discusses prevailing challenges to mitigate this highly contagious disease with limited resources.

Nurses have experienced several psychological and work-related issues during the COVID-19 pandemic including pandemic burnout and job burnout. The aim of the study was to examine the impact of social support and resilience on COVID-19 pandemic burnout and job burnout among nurses. We conducted a cross-sectional study in Greece. Study population included 963 nurses. We measured social support, resilience, COVID-19 pandemic burnout, and job burnout with the Multidimensional Scale of Perceived Social Support, Brief Resilience Scale, COVID-19 burnout scale, and single item burnout measure respectively. Nurses received high levels of social support, while their resilience was moderate. Additionally, nurses experienced moderate levels of COVID-19 burnout and job burnout. Increased social support (adjusted beta = -0.075, 95% CI = -0.125 to -0.024) and increased resilience (adjusted beta = -0.399, 95% CI = -0.491 to -0.308) were associated with reduced COVID-19 pandemic burnout. We found a negative relationship between social support and job burnout (adjusted beta = -0.263, 95% CI = -0.405 to -0.121). A similar negative relationship was found between resilience and job burnout (adjusted beta = -0.529, 95% CI = -0.785 to -0.272). Social support and resilience can act as protective factors against COVID-19 pandemic burnout and job burnout among nurses. Policy makers should develop and implement appropriate strategies to improve nurses’ social support and resilience since they are the backbone of healthcare systems worldwide.

Background: COVID-19 pandemic has pulled us all a few steps back, were we never shake hands or hug each other when we meet our friends and family after a gap, but instead we greet them by saying Namaste and joining our hands together. As we all know, COVID-19 spreads through air and the only way to shield ourselves is by maintaining a safe distance from one another. Methodology: In order to conduct a meta-analysis on the number of COVID-19 cases in Kerala and India, the data was retrieved from various sites hosted by the government bodies. The data for analysis was collected from May 2020 to July 2020. The average number of days required to reach every 5000 fresh cases were also calculated using this data. COVID-19 has affected all the economy holistically regardless of financial, behavioral, or societal aspects. Conclusion: Lifting of the lockdown in a step by step process keeping in mind the necessities for the nation was a thoughtful act, but the people who mistook this opportunity and did not remain in quarantine after coming from abroad was recognized as the reasons behind the sudden and uncontrolled rise in the number of COVID-19 cases in Kerala, India. The government authorities had no other option but to lift the restrictions to reduce the economic burdens that had already affected the daily wage worker and farmers prompting them to give up their lives.

Despite the availability of effective vaccines that lower mortality and morbidity associated with COVID-19, many countries including Italy adopted strict vaccination policies and mandates to increase the uptake of the COVID-19 vaccine. Such mandates have sparked debates on the freedom to choose whether or not to get vaccinated. In this study, we examined the people’s belief in vaccine choice as a predictor of willingness to get vaccinated among a sample of unvaccinated individuals in Italy. An online cross-sectional survey was conducted in Italy in May 2021. The survey collected data on respondents’ demographics and region of residence, socioeconomic factors, belief in the freedom to choose to be vaccinated or not, risk perception of contracting and transmitting the disease, previous vaccine refusal, opinion on adequacy of government measures to address the pandemic, experience in requesting and being denied government aid during the pandemic, and intent to accept COVID-19 vaccination. The analysis employed binary logistic regression models using a hierarchical model building approach to assess the association between intent to accept vaccination and belief in the freedom to choose to vaccinate, while adjusting for other variables of interest. 984 unvaccinated individuals were included in the study. Respondents who agreed that people should be free to decide whether or not to vaccinate with no restrictions on their personal life had 85% lower odds of vaccine acceptance (OR=0.15 ;95% CI,0.09,0.23) after adjusting for demographic and socioeconomic factors and their risk perception of contracting and transmitting COVID-19. Belief in the freedom to choose whether or not to accept vaccinations was a major predictor of COVID-19 vaccine acceptance among a sample of unvaccinated individuals in Italy in May 2021. This understanding of how individuals prioritize personal freedoms and the perceived benefits and risks of vaccines, when making health care decisions can inform the development of public health outreach, educational programs and messaging.

Poverty is one of the indexes that can see how a country succeeds in development. In Indonesia, the poverty rate is high as the impact of the Covid-19 pandemic increases over time. Therefore, a solution is embraced in the form of government policies in tackling poverty in Indonesia. The purpose of this study is to analyze the poverty caused by the Covid-19 pandemic.What is the current state of poverty caused by the Covid-19 pandemic in Indonesia? and what are the previous government policies that have succeeded in reducing poverty in Indonesia? The method used in this study is the literature review method based on the results of critical analysis of journal articles that are relevant to the topic of discussion. The results showed that three government policies have succeeded in lowering the poverty level in Indonesia, namely the PKH program policy, the zakat policy as an indicator of poverty reduction, and the Bank Wakaf Mikro policy. Therefore, this study focuses on the policy as a study for government policy in lowering poverty levels due to the Covid-19 Pandemic.

Background: The ongoing outbreak of Coronavirus Disease 2019 (COVID-19) represents a major threat to human health, which impairs the functionality of several organs. One of the hardest challenges in the fight against COVID-19 is the development of wide-scale, effective, and rapid laboratory tests to control disease severity, progression, and possible sudden worsening. Monitoring patients in real-time is indeed highly demanded in this pandemic era when physicians need reliable and quantitative tools to prioritize patients’ access to intensive care departments. In this regard, salivary biomarkers are extremely promising, as they allow for a fast and non-invasive specimens’ collection, which can be repeated multiple times. Methods: We compare salivary levels of immunoglobulin A subclasses (IgA1 and IgA2) and free-light chains (FLC k and λ) in a cohort of 29 SARS-CoV-2 patients and 21 healthy subjects. Results: We found that each biomarkers differs significantly between the two groups, with p-values ranging from 10-8 to 10-4. The performance ranking of these markers, shows that λFLC level (p=1.4e-8) is the best-suited candidate to discriminate the two groups, with an accuracy of 0.94 (0.87-1.00 95% CI), a precision of 0.91 (0.81-1.00 95% CI), a sensitivity of 1.00 (0.96-1.00 95% CI) and a specificity of 0.86 (0.70-1.00 95% CI). Conclusion: These results suggest λFLC as an ideal indicator of patient conditions. This is more strengthened in consideration that λFLC half-life (approximately 6 hours) is significantly shorter than the IgA one (21 days): thus λFLC appears displaying the potential to effectively monitor patients fluctuation in real-time.

As medical schools cope with the consequences of the COVID-19 pandemic, a new cohort of students will be admitted in the fall. Administrators are again challenged to make unprecedented enrollment decisions without standardized exams. This challenge provides unique opportunities to support holistic admissions but also abruptly bypasses a process that has been employed since 1928. This article highlights key factors that are being considered during current medical school admission cycles, including limited opportunities to take standardized exams, heightened student anxiety, and potential exam alternatives. These factors are framed and discussed within the context of the medical college admission test (MCAT) exam.

The current Covid-19 pandemic has hugely disrupted the delivery of routine and established medical care. Patients can develop a wide range of clinical signs and symptoms from a cough and fever to severe respiratory failure. There is an ongoing argument on a concise investigative pathway to ensure the safety of all healthcare workers. The stethoscope can help with any clinical respiratory assessment but the risk of cross infection is high. Computer tomography should not be routinely performed. There is a potential place for lung ultrasound but outcomes are not yet determined.

Background: COVID-19 is currently one of the most important medical challenges as it affects the entire population with children being infected as easily as adults. Objective: The study evaluated the mortality of under 17-year-olds and compare the frequency with that of adults in a cohort of 8986 COVID-19 positive patients hospitalized in a single care center. Design: retrospective clinical trial, all hospitalizations of COVID-19 positive patients as diagnosed by RT-qPCR were analyzed by revisiting their medical records. Setting: 8986 COVID-19 positive patients hospitalized in a Hospital de Base and the Infant and Maternal Hospital of São Jose do Rio Preto, SP, Brazil (HB/HCM) being these totals of 383 COVID-19 positive under 17-patients. Patients: patients COVID-19 positive under 17-year-olds were grouped by age and evaluated by analyzing their medical records. They were categorized as Group I, children, and adolescents under 19 years old and Group II, adults over 19 years. Results: Overall mortality in under 19-year-olds was 12 deaths, that is, 3.13% of the patients in this age group and 0.55% of the overall mortality from COVID-19. Mortality in the group of adults was 2197 equivalent to 24.45% of the hospitalized adults and 99.45% of overall deaths. Mortality was significantly higher for adults than for under 19-year olds (p-value < 0.0001). Regarding the different ages of children and adolescents, the number of deaths of under 1-year olds was 2/123 (1.62%), of 1-4 years it was 4/95 (2.11%), of 5-9 years it was 1/47 (2.13%), of 10-14 years it was 1/40 (2.5%) and of 15-19 years it was 4/78 (5.13%). There were no statistical differences between the different age groups ( p-value = 0.3). Conclusion: Mortality from COVID-19 in children and adolescents was lower than in adults and generally associated with other comorbidities with the main association being with heart disease.

The recent pandemic has greatly stressed supply chains, treatment modalities, and medical resources. Cold atmospheric plasma (CAP) has been used for a wide range of applications in biomedical engineering due to its many components including electrons, charged particles, reactive oxygen species (ROS), reactive nitrogen species (RNS), free radicals, ultraviolet (UV) photons, molecules, electromagnetic fields, physical forces, and electric fields. In this manuscript, we develop CAP devices for COVID-19. Our manuscript indicates the advantages of highlydeployable CAP devices for both sanitation and treatment, without the need for supply chains of special consumables such as hand sanitizers and the like. We hope that this timely research will help engage the broader community of engineers that wish to help the medical community with this pandemic and to prevent and treat future outbreaks.

Chikungunya, Dengue, and Zika viruses are endemic to Brazil, with a high annual incidence rate. It is a serious public health issue and is responsible for outbreaks and epidemics worldwide. As COVID-19 emerged as a pandemic, the diagnosis of arboviruses was underestimated. Hence, this study aimed to characterize the sociodemographic and clinical aspects of arboviruses in the con-text of the COVID-19 pandemic in the state of Maranhão, Brazil. Sociodemographic and clinical data were obtained by applying questionnaires to 179 patients treated at health units in São José de Ribamar, Paço do Lumiar, Raposa, Santa Inês, and Vargem Grande municipalities. Serologi-cal and polymerase chain reaction analyses were performed do detect Chikungunya, Zika, Den-gue, and COVID-19 infections. The Maranhão state registered 706 probable cases of Chikungunya from 2019 to 2020. In 2020, the cases were reduced by 74.8% compared to those reported in 2019. The test results were analyzed separately. Here, 46.3% of the Chikungunya virus test results were negative, and 36.8% were positive. For the Zika virus tests, most (79.9%) were positive, as well as the DENV1, DENV2, DENV3, and DENV4 tests (88.3%, 88.3%, 89.4%, and 65.9%, respectively). For the COVID-19 tests, of the 146 individuals tested, 52.7% were reactive when considering the anti-S test, and 17.8% were positive when considering the anti-N test. Fever and myalgia were the symptoms most frequently reported by patients. Our results emphasize the importance of contin-uous epidemiological surveillance of arboviruses in northeastern Brazil, and simultaneous test-ing for Chikungunya, Dengue, and Zika viruses among suspected patients.

The world has been highly impacted by the COVID-19 as the virus has spread to all continents – about 200 countries in total. The latest update claims about 4,000,000 confirmed cases and about 300,000 confirmed deaths owing to the COVID-19 pandemic. This probably makes the COVID-19 as the most dangerous contagious disease in the era 2000s. Apart from massive publications on this topic, there is no available qualitative analysis that describes the dynamic spreads of the COVID-19 and its impacts on healthcare and the economy. Through the system archetypes analysis, this paper explains that the dynamic spread of the COVID-19 consists of the limits to growth and the success to successful structures. The limits to growth elucidates that more symptomatic and asymptomatic patients owing to infected droplets may be bounded by self-healing and isolated treatments. The success to successful structure explains that once the COVID-19 affects the economy through the lockdown, there will be a limited fund to support the government aids and the aggregate demand. In overall, this paper gives readers simplified holistic insights into understanding the dynamic spread of the COVID-19.

At present, there are no hardware or biochemical systems allow to assess the severity of post-COVID syndrome in vivo. The hardware of the proposed biotechnical system is based on routine transthoracic electrical impedance rheography, which makes it possible to register the frequency characteristics of the patient's bioimpedance response to controlled stress stimulation, thereby simultaneously fixing the characteristics of his productive heart, the state of the hemomicrocirculatory bed, the efficiency of the gas transport function of his blood, and also reliably assess personal reactivity and adaptive potential. Subsequent mathematical approximation of the obtained biometric data by an original neural network makes it possible to rank the results obtained and automatically generate a program of medical rehabilitation for a particular patient, depending on the severity of his post-COVID syndrome. The study results proved two reliable physiological signs confirming the presence of latent post-COVID complications: a decrease in the base impedance value for light exercise and an increase in the length of the systolic arc of the rheocardiogram.

Abstract: This brief policy is written after experience treating COVID-19 positive radiation therapy patients to reduce risk to therapy staff and patients in radiation oncology department. It is important to prioritize the safety of staff and non-infected patients while ensuring the continuation of radiation oncology services. Radiation therapists have sustained contact with covid-19 patients in an enclosed vault. Protocols for correct disinfecting of equipment and room and therapists following methods for less transmission of virus is crucial. This policy covers prevention methods from COVID-19 transmission from patient to patient, patient to staff, staff to patient and staff to staff as follows A.Risk reduction by screening and preparing staff and rooms B.Radiation Therapist Policy for COVID-19 positive patient with CCC (Critical Cancer Care)

Abstract Kidney transplant recipients, because of a weak immune response due to the assumption of immunosuppressant are exposed to the risk of COVID-19 infection. This fact realize the problem on how to treat the severe infection without carrying the risk of acute rejection due to the reduction of the immunosuppressive drugs. The best are the prophylactic measures to be taken before transplantation as vaccination. If the patient is already transplanted, three measures may be undertaken: Vaccination, use of monoclonal antibodies, use of therapeutic antiviral small molecules. Concerning vaccination is still debated which one is the best and how many doses should be given. The surge of new virus variant is the major problem and invites to find new active vaccines. In addition, not all the transplanted patients develop antibodies. The other measure is the use of monoclonal antibodies. They may be used as prophylaxis or in the early stage of the disease. Finally, the antiviral small molecules may be used again as prophylaxis or treatment. Their major drawback are the interference with the immunosuppressive drugs and the fact that some of them cannot be administered to patients with low eGFR.

On 11th March 2020, the World Health Organization declared COVID-19 as a pandemic. Vaccination programs have advanced greatly in the global health period, despite widespread anti-vaccination attitudes and misinformation. Vaccine hesitancy of COVID-19 vaccine is currently a major issue in Saudi Arabia. This cross-sectional study was carried out from June 25, 2021 to October 2021 in order to investigate the knowledge levels of acceptance and hesitancy of COVID-19 vaccine among Saudi’s nationals. The data was collected through a close-ended structured questionnaire from a total of 565 respondents. Overall, 78.41% respondents were female, 62.48% having university level education and 61.06% were unemployed. Majority of the participants 82.30% (n=465) think that Pfizer vaccine has the highest efficiency against COVID-19. Our study concludes that majority of the participants have satisfactory knowledge about COVID-19 vaccination. Concerns over vaccine components, effectiveness of vaccine and possible side effects are among the key causes for vaccine hesitancy.

COVID-19 has affected 210 countries around the world, killed more than 240,000 and infected more than 3.4 million. Bangladesh, a South Asian low-middle-income economy, has experienced a demographic and epidemiological transition with rapid urbanization and a gradual increase in life expectancy. It is the seventh most populous country in the world and population of the country is expected to be nearly double by 2050. The increasing burden of noncommunicable diseases in Bangladesh can be attributable to rapid urbanization and nearly 50% of all slum dwellers of the country live in Dhaka division. In 2017, National Rapid Response Team of IEDCR investigated 26 incidents of disease outbreak. The joint survey of the Power and Participation Research Centre and BRAC Institute of Governance and Development reveals that per capita daily income of urban slum and rural poor drops by 80% due to present countrywide shutdown enforced by the government to halt the spread of Covid-19. 40%-50% of these population took loans to meet the daily expenses.

In the past decades, several new diseases have emerged in new geographical areas, with pathogens including Ebola, Zika, Nipah, and coronaviruses (CoVs). Recently, a new type of viral infection has emerged in Wuhan City, China, and initial genomic sequencing data of this virus does not match with previously sequenced CoVs, suggesting a novel CoV strain (2019-nCoV), which has now been termed as severe acute respiratory syndrome CoV-2 (SARS-CoV-2). Although Coronavirus disease 2019 (COVID-19) is suspected to originate from an animal host (zoonotic origin) followed by human-to-human transmission, the possibility of other routes such as food-borne transmission should not be ruled out. Compared to diseases caused by previously known human CoVs, COVID-19 shows less severe pathogenesis but higher transmission competence, as is evident from the continuously increasing number of confirmed cases globally. Compared to other emerging viruses such as Ebola virus, avian H7N9, SARS-CoV, or MERS-CoV, SARS-CoV-2 has shown relatively low pathogenicity and moderate transmissibility. Codon usage studies suggest that this novel virus may have been transferred from an animal source such as bats. Early diagnosis by real-time PCR and next-generation sequencing has facilitated the identification of the pathogen at an early stage. Since, no antiviral drug or vaccine exists to treat or prevent SARS-CoV-2, potential therapeutic strategies that are currently being evaluated predominantly stem from previous experience with treating SARS-CoV, MERS-CoV, and other emerging viral diseases. In this review, we address epidemiological, diagnostic, clinical, and therapeutic aspects, including perspectives of vaccines and preventive measures that have already been globally recommended.

Keywords: COVID-19, severity, influenza, serum antibodies, blood tests

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.