Coronavirus 2019-nCoV Research Articles

Correlation between Leukocyte Count and Blood Sedimentation Rate with C-Reactive Protein in Covid-19 Confirmed Patients at Gresik Regional General Hospital

Coronavirus Disease 2019 (Covid-19) is a new type of disease caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SAR-CoV-2) virus which was previously called Novel Coronavirus (2019-nCov). The spread of Covid-19 is very fast and can cause death. The increase in the number of leukocytes is directly proportional to the clinical severity of Covid-19 patients, which begins with viral invasion of the respiratory tract, then the virus will attack target cells, causing an increase in interleukin-6 which is a polypeptide cytokine and c-reactive protein that will code for leukocyte proliferation. Inflammation is a mechanism to protect from various microorganisms, in the inflammatory process cells will release various pro-inflammatory cytokines including c-reactive protein and fibrinogen. This increase in fibrinogen causes high levels of the erythrocyte sedimentation rate. This study aims to determine the relationship between the number of leukocytes and the erythrocyte sedimentation rate on the value of c-reactive protein in confirmed Covid-19 patients. This type of research uses a cross sectional design with purposive random sampling technique using secondary data. Data collection in this study was carried out in June 2022 at the RSUD Ibnu Sina Gresik Laboratory. Statistical test using Spearman correlation test. This study shows that there is a very strong relationship between the number of leukocytes and c-reactive protein (p = 0.000, r = 0.873) then there is a strong relationship between the erythrocyte sedimentation rate and c-reactive protein (p = 0.000, r = 0.659) in patients Covid-19.

Content and Sentiment Analysis of The New York Times Coronavirus (2019-nCOV) Articles with Natural Language Processing (NLP) and Leximancer

The purpose of this study was to prove the use of content and sentiment analysis to understand public discourse on Nytimes.com around the coronavirus (2019-nCOV) pandemic. We examined the pandemic discourses in the article contents, news, expert opinions, and statements of official institutions with natural language processing methods. We analyzed how the mainstream media (Nytimes.com) sets the community agenda. As a method, the textual data for the research were collected with the Orange3 software text-mining tool via the Nytimes.com API, and content analysis was conducted with Leximancer software. The research data were divided into three categories (first, mid, and last) based on the date ranges determined during the pandemic. Using Leximancer concept maps tools, we explained concepts and their relationships by visualizing them to show pandemic discourse. We used VADER sentiment analysis to analyze the pandemic discourse. The results gave us the distance and proximity positions of themes related to Nytimes.com pandemic discourse, revealed according to their conceptual definitions. Additionally, we compared the performance of six machine learning algorithms on the task of text classification. Considering the findings, it is possible to conclude that in Nytimes.com (2019-nCOV) discourse, some concepts have changed on a regular basis while others have remained constant. The pandemic discourse focused on specific concepts that were seen to guide human behavior and presented content that may cause anxiety to readers of Nytimes.com. The results of the sentiment analysis supported these findings. Another result was that the findings showed us that the contents of the coronavirus (2019-nCOV) articles supported official policies. It can be concluded that regarding the coronavirus (2019-nCOV), which has caused profound societal changes and has results such as death, restrictions, and mask use, the discourse did not go beyond a total of 15 main themes and about 100 concepts. The content analysis of Nytimes.com reveals that it has behavioral effects, such as causing fear and anxiety in people. Considering the media dependency of society, this result is important. It can be said that the agenda-setting of society does not go beyond the traditional discourse due to the tendency of individuals to use newspapers and news websites to obtain information.

Impact of parent’s knowledge and attitude about pediatric dental treatment during the Covid-19 pandemic in Bhairahawa City, Nepal

A new type of coronavirus that causes pneumonia was first detected in December 2019, in Wuhan. It was first denoted as the 2019 novel coronavirus (2019-nCoV). The International Committee on Taxonomy of Viruses, Wuhan in December 2019, referred to a new coronavirus capable of infecting humans as SARS-CoV-2. At the same time, the World Health Organization declared the official name of the disease caused by this virus as COVID-19.In this cross-sectional questionnaire survey, 180 participants out of 190 participants were included to evaluate the knowledge and attitude about the pediatric dental treatment during covid-19 pandemic among parents, who visited the department of Pedodontics and Preventive Dentistry, of Universal College of Medical Sciences, during covid-19 pandemic for three months (February 2021 to April 2021), in Bhairahawa, Nepal.In this study out of 180 participants, 105(58.33%) were male and 75(41.66%) were female. All parents were concerned and aware of COVID-19. Every child was explained about covid-19 viruses by their parents.Even though the parents were aware of the Covid-19 pandemic and had discussed it with their children, still they do not prefer any kind of dental treatment even in severe pain. As they thought that other places are less infectious than a pediatric dental clinic.Thus, the aim of this study was to evaluate the knowledge and attitude of pediatric dental patients’ parents’ towards COVID-1 9 in Bhairahawa, Nepal.

Insilico Screening for Identification of Hits against SARS-Cov-2 Variant of Concern B.1.617 and NSP12 Mutants by Molecular Docking and Simulation Studies

Abstract Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV), also known as SARS-CoV-2, have caused global epidemics with high morbidity and mortality. Active research on finding effective drugs against 2019-nCoV/SARS-CoV-2 is going on. In silico screening represents the best approach for hits identification and could shorten the time and reduce cost compared to de novo drug discovery. Recently, CoV2 mutations have been a big concern in India, particularly on non-structural proteins (NSPs) and Spike Protein (B.1.617) which are the key targets that play a pivotal role in mediating viral replication and transcription. Herein, this study analyzed the NSPs and spike’s structural aspects of mutant strains of SARS-CoV-2. The three-dimensional structures of NSPs and S Spike proteins were retrieved from the protein data bank or modeled. And a dataset of an antiviral compound library containing 490,000 drug-like ligands and structurally diverse biologically active scaffolds was used for our studies. Initially, the molecular alignment was performed for library compounds with the reference drug molecule to find targets that match the field points. Antiviral compounds having a similarity score >0.6; were selected for further docking studies with wild and mutant NSPs and S Spike protein of SARS-CoV-2 variant B.1.617. The docking studies identified a potent analog MA-11, which exhibited the highest binding affinity towards wild and mutant proteins. Further, molecular dynamics simulation studies of selected compounds confirmed their perfect fitting into NSP12 and spike active sites and offer direction for further lead optimization and rational drug design.

STUDENT PERCEPTIONS ABOUT THE NEWS OF THE DETERMINATION OF CORONAVIRUS (2019-nCoV) PANDEMIC INVASION AND THE NEW LIFESTYLE ORDER ON SOCIAL MEDIA INSTAGRAM

It’s been being public consumption globally the news about new disease that came from Wuhan, China. This also caused a lot of anxiety to the several levels of society. Because, the transmission of this disease is very fast. Its called severe acute respiratory syndrom (SARS) that has been appeared in mid-December 2019. This time it appear with a new form called SARS-CoV-2 as the caused of the Corona Virus Disease 2019 (Covid-19) pandemic which causes respiratory system disorder, acute pneumonia, until death.
 With the information that determines the percentage of virus transmission above make Indonesian people in particular experience excessive anxiety to the death will cause emotional dysfunction such neuroticism, depression, and psycosomatic disorder.
 With a massive news development of this Covid-19 everyday as the news headline, the government try to enforce the new normal policies that will no border to the public activity of course with the awarness of the health protocol.
 The perception that formed in to college student about the news of confirmation pandemic invasion of Novel Coronavirus (2019-nCoV) and new normal life on social media instagram between one to another was not the same because affected by several factors and caused some perception effect to the communicant. Such as cognitive effect, affection effect, and behavioral effect that surely affect to the their daily activity.

Advances in research on sleep disorders promoting the deterioration of novel coronaviruses

Novel coronavirus pneumonia (Corona Virus Disease 2019, COVID-19) is a disease with fever, dry cough and progressive dyspnea as the main manifestations. 2019 novel coronavirus (2019-nCOV) is transmitted by contact transmission. Sleep disorders are linked to novel coronavirus, it not only reduces the life motivation of patients with COVID-19, but increases the burden on the family members who care for patients. Sleep disorder is related to the aggravation of COVID-19 to some extent. Sleep disorders are a significant factor in advance of COVID-19 into the severe disease, and the pathophysiological changes in COVID-19 also contribute to the problem of it. Sleep disorders exacerbate the body's psychological stress promoting decreased immune function, while interfering with the normal exercise of physiological functions of reactive T cells, which have specific defenses against 2019-nCOV can prevent 2019-nCOV from entering the body, so people with sleep disorders infected with 2019-nCOV will have more severe symptoms than those who do not suffer from sleep disorders. Because the link between COVID-19 and sleep disorders is poorly understood by clinicians, this article describes recent research advances on sleep disorders that exacerbate COVID-19 disease, patient sleep status, and treatment options.

Impact of 2019 Novel Coronavirus (2019-nCov) Pandemic and Lockdown on Parents and Caregivers in Ontario, Canada.

The COVID-19 pandemic has impacted parents' and children's well-being. This study aimed to evaluate the impact of the COVID-19 pandemic and its preventive measures on children's well-being and their parents' anxiety level. Parents/caregivers were invited to respond to a self-administered survey. The primary outcome was to assess the rate and severity of parental anxiety during the pandemic/lockdown. Four hundred and thirty parents completed the survey. Ninety-two (21%) and 10 (2%) parents reported that their children gained or lost weight during the pandemic, respectively. Eighty-one (19%) parents reported a regression in their children's developmental milestones, particularly in toileting, speech, and social interaction. The GAD-7 mean scores increased by 2.9 points (95% CI [2.5, 3.25]; P < .001) in comparison with prepandemic scores. Adjusted multivariable analysis showed that having children with psychological conditions and a maternal education level less than a university degree were significantly associated with higher parental anxiety.

The Possible Therapeutic Application of CO on COVID-19

An outbreak of pneumonia caused by a novel Coronavirus (2019-nCoV) is ongoing in China [1]. The disease caused by 2019-nCoV was recently named as COVID-19 by WHO. Although the case-fatality rate of COVID-19 (about 2.3% up to now) is lower than SARS, they share many similarities [2,3]. Early studies have shown that increased pro-inflammatory cytokines were associated with pulmonary inflammation and extensive lung damage in SARS patients [4], while the latest report on COVID-19 showed that 2019-nCoV infection lead to high amounts of both Th1 and Th2 cytokines [5]. Moreover, ICU patients had higher levels of GCSF, IP10, TNFα, MCP1, IL2, IL7, IL10, MIP1A, suggesting the cytokine storm was associated with disease severity [5]. Corticosteroid therapy was frequently gave as a combined regimen for possible benefit by reducing inflammatory-induced lung injury. However, the drug is immunosuppressive and may delay viral clearance if given before viral replication is controlled [6], side-effects of corticosteroid also occurred in other cases [7]. Therefore, novel anti-inflammatory molecules could be considered in the treatment of COVID-19.

Impact of COVID-19 on Fintech with Reference to Youngster

In Wuhan, China, in December 2019, the Novel Coronavirus (2019-nCoV) was discovered for the first time. Covid-19, the virus-caused disease, had been reported in 205 countries by the end of March 2020. There had been about 700,000 cases of infection and 33,000 fatalities worldwide.” Kerala, India, reported the first case of 2019-nCoV in the final week of January 2020. Since that time, 27 States and Union Territories have reported about 1353 cases. More than 300 cases have been reported by the State of Tamil Nadu, and at the time of writing, 110 samples were being investigated. Around 290 people in Kerala are infected, and 120,000 more are being monitored. Children, families, and entire communities could be at risk from the 2019 n-CoV. In addition to the risk of secondary morbidity and mortality, the virus infection itself has direct health effects. It also has a negative impact on the economy and way of life of marginalised people. Basic services like health, education, and social protection programmes will inevitably be disrupted. Children and parents experienced fear, panic, anxiety, and stress as a result of the 21-day total lockdown that the Indian government had announced. Correct information must be given, myths, misconceptions, and false information must be dispelled, social isolation should be encouraged, hand and personal hygiene should be promoted, and flu-like symptoms should be treated as soon as possible.

Impaired antibody responses were observed in patients with type 2 diabetes mellitus after receiving the inactivated COVID-19 vaccines

BackgroundPatients with type 2 diabetes mellitus (T2DM) have been reported to be more susceptible to 2019 novel coronavirus (2019-nCoV) and more likely to develop severe pneumonia. However, the safety and immunological responses of T2DM patients after receiving the inactivated vaccines are not quite definite. Therefore, we aimed to explore the safety, antibody responses, and B-cell immunity of T2DM patients who were vaccinated with inactivated coronavirus disease 2019 (COVID-19) vaccines.MethodsEighty-nine patients with T2DM and 100 healthy controls (HCs) were enrolled, all of whom had received two doses of full-course inactivated vaccines. At 21–105 days after full-course vaccines: first, the safety of the vaccines was assessed by questionnaires; second, the titers of anti-receptor binding domain IgG (anti-RBD-IgG) and neutralizing antibodies (NAbs) were measured; third, we detected the frequency of RBD-specific memory B cells (RBD-specific MBCs) to explore the cellular immunity of T2DM patients.ResultsThe overall incidence of adverse events was similar between T2DM patients and HCs, and no serious adverse events were recorded in either group. Compared with HCs, significantly lower titers of anti-RBD-IgG (p = 0.004) and NAbs (p = 0.013) were observed in T2DM patients. Moreover, the frequency of RBD-specific MBCs was lower in T2DM patients than in HCs (p = 0.027). Among the 89 T2DM patients, individuals with lower body mass index (BMI) had higher antibody titers (anti-RBD-IgG: p = 0.009; NAbs: p = 0.084). Furthermore, we found that sex, BMI, and days after vaccination were correlated with antibody titers.ConclusionsInactivated COVID-19 vaccines were safe in patients with T2DM, but the antibody responses and memory B-cell responses were significantly decreased compared to HCs.Trial registration number and dateNCT05043246. September 14, 2021. (Clinical Trials.gov)

COVID – 19 Infection: Origin, epidemiology, and clinical features of human coronavirus

Background: With the onset and spread of the 2019 novel coronavirus (2019-nCoV), a new public health disaster threatened the world. In December 2019, the virus was suggested to have originated from bats and had been transmitted to humans via unidentified intermediary species in Wuhan, Hubei Province, China. There have been about 469, 212, 705 confirmed cases across the globe with about 6, 077, 255 reported deaths as of 03/18/2022. Infection is contracted by inhaling droplets or touching infected surfaces and introducing pick-up viruses to the nose, mouth, and eyes. The coronavirus incubation time is currently believed to be between two and fourteen days after exposure, and the infection can cause the severity of illness, including the death of the patient. Methods: The study employed a narrative review method to investigate literature and establish the current status of coronavirus and the most effective measures in curbing its infection rate and management of infected persons. Results: The study revealed that Vitamin C, hydroxychloroquine, antibiotics, and antivirals such as remdesivir and sotrovimab are treatment remedies used in proven instances. At home, adequate ventilation and sunlight are suggested to facilitate the reduction in exposure to SARS-CoV-2. Other prevention strategies include rooms, surfaces, and equipment with regular decontamination preferably with sodium hypochlorite, Individuals are encouraged to take the COVID-19 vaccine. Conclusion: Various measures outlined in this study have proven to decrease the spread of SARS-CoV-2 in Ghana, with the global consequences of this new disease still being explored.

Assessment of the Prevalence and Incidence of COVID-19 in Saudi Arabia.

The global pandemic of coronavirus disease 2019 (COVID 19) is reported to have started in Wuhan City, Hebei Province, China. It has spread rapidly all over the world, including Saudi Arabia, having a severe health emergency. This new virus was named as the 2019 novel coronavirus (2019-nCoV), and now severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on previous practice and phylogenetic and taxonomic investigations. SARS-CoV-2 belongs to the family of Coronaviridae, Betacoronavirus, Sarbecovirus subgenus, genome β. Throughout the COVID 19 pandemic, several strains of SARS-CoV-2 have been recognized around the world. The SARS-CoV-2 variants have caused significant morbidity and mortality worldwide and in Saudi Arabia as well. The rate at which COVID-19 spread across borders and affected countries has highlighted the significance of health care systems to nations and global operations. This review focuses on the origin, epidemiology, pathophysiology, transmission, and the impact of this disease, while highlighting the knowledge about SARS-CoV-2 variants.

Procena novog molekularnog testa za detekciju SARS-CoV-2 nukleinske kiseline u uzorcima pljuvačke

Background: Molecular testing is considered the gold standard for the detection of SARS-CoV-2. This study aimed to compare the performance of the P742H SARS-CoV-2 Nucleic Acid Multiplex Detection Kit in salivary samples, with respect to the 732HF Novel Coronavirus (2019-nCoV) Nucleic Acid Detection Kit and the TaqPath COVID-19 CEIVD RT-PCR Kit, used at University-Hospital of Padova, Italy. Methods: One hundred twenty-four salivary samples selfcollected by healthcare workers (HCW) during the screening program at University-Hospital of Padova, Italy, from Oct to Nov 2022, were included in the study. RNA extraction was performed by Viral DNA and RNA Extraction Kit (Technogenetics, Lodi, Italy) and amplification by P742H and 732HF (Technogenetics, Lodi, Italy). RNA was extracted using MagNa Pure 96 DNA and Viral NA Small Volume Kit (Roche, Switzerland) for TaqPath analysis (Thermo Fisher Scientific, USA). Results: 94 samples were positive at P742H, while 30 were negative; for 732HF, 96 samples were positive, while 28 were negative, with an overall agreement of 97.5% (Cohen's = 0.930, p &lt; 0.001). TaqPath gave 95 positive samples, and 29 negative results, with an overall agreement of 100% (Cohen's = 1.0, p &lt; 0.001) with respect to P742H, and 97.5% (Cohen's = 0.931, p &lt; 0.001) with respect to 732HF. Comparing cycle threshold (Ct) between the P742H and 732HF, no statistically significant differences were found (p = n.s.). Conclusion: The P742H method proved better performances than 732HF for salivary samples, both presenting the same amplification time. In addition, P742H results were comparable to those obtained through the highthroughput method TaqPath.

Nurses’ Knowledge, Attitude, and Practice Regarding Personal Protective Equipment for the Prevention of COVID-19 in Public Hospitals Khartoum State Sudan 2022

Since December 2019, there had been a series of unexplained cases of pneumonia reported in Wuhan, China, and on 12 January 2020, the World Health Organization (WHO) named this new virus as the 2019 novel coronavirus (2019-nCoV). The Novel Coronavirus disease (COVID-19) is an emerging, rapidly changing global health challenge affecting all sectors, including the health sector. This study aimed to investigate nurses’ knowledge, attitudes, and practices regarding the prevention and control of COVID-19. Methods: This cross-sectional study was conducted among nurses in three public health hospitals in Khartoum state. A self-administered questionnaire was used. A total of 14 knowledge questions were adopted. There are 5 questions constructed for attitude. A total of 12 practice questions were used. Mean score of knowledge considers as follows when the mean more than 75% considers as good knowledge while this percent uses as good practice and poor practice respectively to analyze the mean score differences of knowledge, attitudes, and practices between the independent variables. Spearman correlation was used to assess the relationship between mean knowledge and attitude scores. Results: Of the 101 nurses approached, a total of 100 nurses responded (99.0% response rate). The mean age of the participants was 27.6 (SD 5.3) years, and the majority of the participants were male (293/434, 67.5%). The mean knowledge score was 1.01 (SD 0.100). The mean attitude score was 10.5 (SD 4.1), and 54.8% (238/434) of the participants had a good attitude toward COVID-19. The mean practice score was 1.4176 (SD 1.4176). There was a negative correlation between knowledge and attitude scores (P < -0.014) and between knowledge and practice scores (P < -0.081). Conclusions: The overall levels of knowledge and practice and attitude were good.

Residual Attention Deep SVDD for COVID-19 Diagnosis Using CT Scans

COVID-19 is the common name of the disease caused by the novel coronavirus (2019-nCoV) that appeared in Wuhan, China in 2019. Discovering the infected people is the most important factor in the fight against the disease. The gold-standard test to diagnose COVID-19 is polymerase chain reaction (PCR), but it takes 5–6 h and, in the early stages of infection, may produce false-negative results. Examining Computed Tomography (CT) images to diagnose patients infected with COVID-19 has become an urgent necessity. In this study, we propose a residual attention deep support vector data description SVDD (RADSVDD) approach to diagnose COVID-19. It is a novel approach combining residual attention with deep support vector data description (DSVDD) to classify the CT images. To the best of our knowledge, we are the first to combine residual attention with DSVDD in general, and specifically in the diagnosis of COVID-19. Combining attention with DSVDD naively may cause model collapse. Attention in the proposed RADSVDD guides the network during training and enables quick learning, residual connectivity prevents vanishing gradients. Our approach consists of three models, each model is devoted to recognizing one certain disease and classifying other diseases as anomalies. These models learn in an end-to-end fashion. The proposed approach attained high performance in classifying CT images into intact, COVID-19, and non-COVID-19 pneumonia. To evaluate the proposed approach, we created a dataset from published datasets and had it assessed by an experienced radiologist. The proposed approach achieved high performance, with the normal model attained sensitivity (0.96–0.98), specificity (0.97–0.99), F1-score (0.97–0.98), and area under the receiver operator curve (AUC) 0.99; the COVID-19 model attained sensitivity (0.97–0.98), specificity (0.97–0.99), F1-score (0.97–0.99), and AUC 0.99; and the non-COVID pneumonia model attained sensitivity (0.97–1), specificity (0.98–0.99), F1-score (0.97–0.99), and AUC 0.99.

Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System

In early December 2019, a new virus named “2019 novel coronavirus (2019-nCoV)” appeared in Wuhan, China. The disease quickly spread worldwide, resulting in the COVID-19 pandemic. In the current work, we will propose a novel fuzzy soft modal (i.e., fuzzy-soft expert system) for early detection of COVID-19. The main construction of the fuzzy-soft expert system consists of five portions. The exploratory study includes sixty patients (i.e., forty males and twenty females) with symptoms similar to COVID-19 in (Nanjing Chest Hospital, Department of Respiratory, China). The proposed fuzzy-soft expert system depended on five symptoms of COVID-19 (i.e., shortness of breath, sore throat, cough, fever, and age). We will use the algorithm proposed by Kong et al. to detect these patients who may suffer from COVID-19. In this way, the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or not. Finally, we present the comparison between the present system and the fuzzy expert system.

Fuzzy-logic-based IoMT framework for COVID19 patient monitoring

Smart healthcare is an integral part of a smart city, which provides real time and intelligent remote monitoring and tracking services to patients and elderly persons. In the era of an extraordinary public health crisis due to the spread of the novel coronavirus (2019-nCoV), which caused the deaths of millions and affected a multitude of people worldwide in different ways, the role of smart healthcare has become indispensable. Any modern method that allows for speedy and efficient monitoring of COVID19-affected patients could be highly beneficial to medical staff. Several smart-healthcare systems based on the Internet of Medical Things (IoMT) have attracted worldwide interest in their growing technical assistance in health services, notably in predicting, identifying and preventing, and their remote surveillance of most infectious diseases. In this paper, a real time health monitoring system for COVID19 patients based on edge computing and fuzzy logic technique is proposed. The proposed model makes use of the IoMT architecture to collect real time biological data (or health information) from the patients to monitor and analyze the health conditions of the infected patients and generates alert messages that are transmitted to the concerned parties such as relatives, medical staff and doctors to provide appropriate treatment in a timely fashion. The health data are collected through sensors attached to the patients and transmitted to the edge devices and cloud storage for further processing. The collected data are analyzed through fuzzy logic in edge devices to efficiently identify the risk status (such as low risk, moderate risk and high risk) of the COVID19 patients in real time. The proposed system is also associated with a mobile app that enables the continuous monitoring of the health status of the patients. Moreover, once alerted by the system about the high risk status of a patient, a doctor can fetch all the health records of the patient for a specified period, which can be utilized for a detailed clinical diagnosis.

Experience in emergency response to 2019-nCoV positive cases in an international test competition

Objective: To analyze the performance of emergency response to 2019 novel coronavirus (2019-nCoV) positive cases in an international test competition in an Winter Olympic Game venue and provide evidences for the COVID-19 prevention and control in similar competitions. Methods: A retrospective analysis on the epidemiological investigation and nucleic acid test results of the cases, the implementation of prevention and control measures, including the communication with sport teams and others, was conducted. Results: The positive cases of 2019-nCoV among entering people were detected before entry, at airport, hotel and venue. Two positive cases were reported before entry, 2 positive cases infected previously and 3 asymptomatic cases were reported after the entry. The venue public health team and local CDC conducted epidemiological investigation and contact assessment jointly in a timely and efficient manner. No local secondary transmission occurred, but the nucleic acid test results of positive persons fluctuated, posing serious challenges to the implementation of prevention and control measures. Conclusion: In large scale international competition, there is high risk of imported COVID-19. It is necessary to fully consider the fluctuation of nucleic acid test results, the criteria for determination and cancellation of positive results and give warm care to positive cases in the emergency response.

Structure/Epitope-Based Immunoinformatics Analysis of Structural Proteins of 2019 Novel Coronavirus

The newly identified 2019 novel coronavirus (2019-nCoV) has caused more than ten million laboratory-confirmed human infections, including 20,000 deaths, posing a serious threat to human health. Currently, however, there is no specific antiviral treatment or vaccine. To identify immunodominant peptides for designing global peptide vaccine for combating the infections caused by 2019-nCoV, the structure and immunogenicity of 2019-nCoV structural protein were analyzed by bioinformatics tools. 33 B-cell epitopes and 39 T-cell epitopes were determined in four structural proteins via different immunoinformatic tools in which include spike protein (22 B-cell epitopes, 25 T-cell epitopes ), nucleocapsid protein (7 B-cell epitopes, 6 T-cell epitopes), membrane protein (2 B-cell epitopes, 7 T-cell epitopes), and envelope protein (2 B-cell epitopes, 1T-cell epitopes), respectively. The proportion of epitope residues in primary sequence was used to determine the antigenicity and immunogenicity of proteins. The envelope protein has the largest antigenicity in which residue coverage of B-cell epitopes is 24%. The membrane protein possesses the largest immunogenicity in which residue coverage of T-cell epitopes is 55.86%. The reason that immune storm was caused by 2019-nCoV maybe that the membrane and envelope protein expressed plentifully in cell infected. Further, studies involving experimental validation of these predicted epitopes is warranted to ensure the potential of B-cells and T-cells stimulation for their effective use as vaccine candidates. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.

New Coronavirus (2019-nCov) Mathematical Model Using Piecewise Hybrid Fractional Order Derivatives; Numerical Treatments

A new mathematical model of Coronavirus (2019-nCov) using piecewise hybrid fractional order derivatives is given in this paper. Moreover, in order to be consistent with the physical model problem, a new parameter μ is presented. The boundedness, existence, and positivity of the solutions for the proposed model are discussed. Two improved numerical methods are presented in this paper. The Caputo proportional constant nonstandard modified Euler–Maruyama method is introduced to study the fractional stochastic model, and the Grünwald–Letnikov nonstandard finite difference method is presented to study the hybrid fractional order deterministic model. Comparative studies with real data from Spain and Wuhan are presented.