scholarly journals Novel Dynamic Structures of 2019-nCoV with Nonlocal Operator via Powerful Computational Technique

Biology ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 107 ◽  
Author(s):  
Wei Gao ◽  
P. Veeresha ◽  
D. G. Prakasha ◽  
Haci Mehmet Baskonus
Keyword(s):  
Mathematical Model ◽  
Nonlocal Operator ◽  
Computational Technique ◽  
The Novel ◽  
Adomian Decomposition ◽  
Dynamic Structures ◽  
Novel Coronavirus ◽  
The Mathematical Model ◽  
Natural Decomposition ◽  
The City

In this study, we investigate the infection system of the novel coronavirus (2019-nCoV) with a nonlocal operator defined in the Caputo sense. With the help of the fractional natural decomposition method (FNDM), which is based on the Adomian decomposition and natural transform methods, numerical results were obtained to better understand the dynamical structures of the physical behavior of 2019-nCoV. Such behaviors observe the general properties of the mathematical model of 2019-nCoV. This mathematical model is composed of data reported from the city of Wuhan, China.

scholarly journals A Note on COVID-19 Diagnosis Number Prediction Model in China

2021 ◽  
Author(s):  
Yi Li ◽  
Xianhong Yin ◽  
Meng Liang ◽  
Xiaoyu Liu ◽  
Meng Hao ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Future Trend ◽  
Disease Prediction ◽  
The Novel ◽  
Limited Impact ◽  
Infected People ◽  
Health Authorities ◽  
Novel Coronavirus ◽  
New Diagnosis ◽  
The Mathematical Model

Abstract Objective: In December 2019, pneumonia infected with the novel coronavirus burst in Wuhan, China. We aimed to use a mathematical model to predict number of diagnosed patients in future to ease anxiety on the emergent situation. Methods: According to all diagnosis number from WHO website and combining with the transmission mode of infectious diseases, the mathematical model was fitted to predict future trend of outbreak. Our model was based on the epidemic situation in China, which could provide referential significance for disease prediction in other countries, and provide clues for prevention and intervention of relevant health authorities. In this retrospective, all diagnosis number from Jan 21 to Feb 10, 2020 reported from China was included and downloaded from WHO website. We develop a simple but accurate formula to predict the next day diagnosis number: ，where N i is the total diagnosed patient till the i th day, and was estimated as 0.904 at Feb 10. Results: Based on this model, it is predicted that the rate of disease infection will decrease exponentially. The total number of infected people is limited; thus, the disease will have limited impact. However, new diagnosis will last to end of March. Conclusions: Through the establishment of our model, we can better predict the trend of the epidemic in China.

scholarly journals DESIGN OF A NONLINEAR SITR FRACTAL MODEL BASED ON THE DYNAMICS OF A NOVEL CORONAVIRUS (COVID-19)

Fractals ◽  
2020 ◽  
Vol 28 (08) ◽  
pp. 2040026 ◽  
Author(s):  
YOLANDA GUERRERO SÁNCHEZ ◽  
ZULQURNAIN SABIR ◽  
JUAN L. G. GUIRAO
Keyword(s):  
Mathematical Model ◽  
Fractal Model ◽  
Contact Rate ◽  
The Novel ◽  
Nonlinear Mathematical Model ◽  
Huge Number ◽  
Social Distancing ◽  
Natural Stabilization ◽  
Novel Coronavirus ◽  
The Mathematical Model

The aim of the present paper is to state a simplified nonlinear mathematical model to describe the dynamics of the novel coronavirus (COVID-19). The design of the mathematical model is described in terms of four categories susceptible ([Formula: see text], infected ([Formula: see text], treatment ([Formula: see text] and recovered ([Formula: see text], i.e. SITR model with fractals parameters. These days there are big controversy on if is needed to apply confinement measure to the population of the word or if the infection must develop a natural stabilization sharing with it our normal life (like USA or Brazil administrations claim). The aim of our study is to present different scenarios where we draw the evolution of the model in four different cases depending on the contact rate between people. We show that if no confinement rules are applied the stabilization of the infection arrives around 300 days affecting a huge number of population. On the contrary with a contact rate small, due to confinement and social distancing rules, the stabilization of the infection is reached earlier.

scholarly journals A numerical solution by alternative Legendre polynomials on a model for novel coronavirus (COVID-19)

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Elham Hashemizadeh ◽  
Mohammad Ali Ebadi
Keyword(s):  
Mathematical Model ◽  
Numerical Solution ◽  
Legendre Polynomials ◽  
Algebraic System ◽  
The Novel ◽  
Kutta Method ◽  
System Of Differential Equations ◽  
Runge Kutta Method ◽  
Novel Coronavirus ◽  
The Mathematical Model

Abstract Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. This paper provides a numerical solution for the mathematical model of the novel coronavirus by the application of alternative Legendre polynomials to find the transmissibility of COVID-19. The mathematical model of the present problem is a system of differential equations. The goal is to convert this system to an algebraic system by use of the useful property of alternative Legendre polynomials and collocation method that can be solved easily. We compare the results of this method with those of the Runge–Kutta method to show the efficiency of the proposed method.

scholarly journals A Note on COVID-19 Diagnosis Number Prediction Model in China

2020 ◽  
Author(s):  
Yi Li ◽  
Xianhong Yin ◽  
Meng Liang ◽  
Xiaoyu Liu ◽  
Meng Hao ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Scientific Information ◽  
Future Trend ◽  
The Novel ◽  
Infected People ◽  
The Public ◽  
Health Authorities ◽  
Novel Coronavirus ◽  
New Diagnosis ◽  
The Mathematical Model

AbstractImportanceTo predict the diagnosed COVID-19 patients and the trend of the epidemic in China. It may give the public some scientific information to ease the fear of the epidemic.ObjectiveIn December 2019, pneumonia infected with the novel coronavirus burst in Wuhan, China. We aimed to use a mathematical model to predict number of diagnosed patients in future to ease anxiety on the emergent situation.DesignAccording to all diagnosis number from WHO website and combining with the transmission mode of infectious diseases, the mathematical model was fitted to predict future trend of outbreak.SettingOur model was based on the epidemic situation in China, which could provide referential significance for disease prediction in other countries, and provide clues for prevention and intervention of relevant health authorities.ParticipantsIn this retrospective, all diagnosis number from Jan 21 to Feb 10, 2020 reported from China was included and downloaded from WHO website.Main Outcome(s) and Measure(s)We develop a simple but accurate formula to predict the next day diagnosis number:,where Ni is the total diagnosed patient till the ith day, and α was estimated as 0.904 at Feb 10.ResultsBased on this model, it is predicted that the rate of disease infection will decrease exponentially. The total number of infected people is limited; thus, the disease will have limited impact. However, new diagnosis will last to March.Conclusions and RelevanceThrough the establishment of our model, we can better predict the trend of the epidemic in China.

scholarly journals Mobility-Guided Modeling of the COVID-19 Pandemic in Metro Manila

2020 ◽  
Author(s):  
Bernhard Egwolf ◽  
O.P. Nicanor Austriaco
Keyword(s):  
The Philippines ◽  
The Novel ◽  
National Capital Region ◽  
Viral Spread ◽  
Mobility Data ◽  
National Capital ◽  
Metro Manila ◽  
The Government ◽  
Novel Coronavirus ◽  
The City

ABSTRACTCOVID-19 is a novel respiratory disease first identified in Wuhan, China, that is caused by the novel coronavirus, SARS-CoV-2. To better understand the dynamics of the COVID-19 pandemic in the Philippines, we have used real-time mobility data to modify the DELPHI Epidemiological Model recently developed at M.I.T., and to simulate the pandemic in Metro Manila. We have chosen to focus on the National Capital Region, not only because it is the nation’s demographic heart where over a tenth of the country’s population live, but also because it has been the epidemiological epicenter of the Philippine pandemic. Our UST CoV-2 model suggests that the government-imposed enhanced community quarantine (ECQ) has successfully limited the spread of the pandemic. It is clear that the initial wave of the pandemic is flattening, though suppression of viral spread has been delayed by the local pandemics in the City of Manila and Quezon City. Our data also reveals that replacing the ECQ with a General Community Quarantine (GCQ) will increase the forecasted number of deaths in the nation’s capital unless rigorous tracing and testing can be implemented to prevent a second wave of the pandemic.

scholarly journals Web Application for Statistical Tracking and Predicting the Evolution of Active Cases with the Novel Coronavirus (SARS-CoV-2)

2021 ◽  
pp. 70-74
Author(s):  
Iulia Clitan ◽  
◽  
Adela Puscasiu ◽  
Vlad Muresan ◽  
Mihaela Ligia Unguresan ◽  
...  
Keyword(s):  
Neural Network ◽  
Mathematical Model ◽  
Web Application ◽  
Point Of View ◽  
The Novel ◽  
End User ◽  
First Case ◽  
Novel Coronavirus ◽  
Second Wave ◽  
Over Time

Since February 2020, when the first case of infection with SARS COV-2 virus appeared in Romania, the evolution of COVID-19 pandemic continues to have an ascending allure, reaching in September 2020 a second wave of infections as expected. In order to understand the evolution and spread of this disease over time and space, more and more research is focused on obtaining mathematical models that are able to predict the evolution of active cases based on different scenarios and taking into account the numerous inputs that influence the spread of this infection. This paper presents a web responsive application that allows the end user to analyze the evolution of the pandemic in Romania, graphically, and that incorporates, unlike other COVID-19 statistical applications, a prediction of active cases evolution. The prediction is based on a neural network mathematical model, described from the architectural point of view.

The Novel Coronavirus: A Major Global Health Concern

2020 ◽  
Vol 8 (1) ◽  
Keyword(s):  
Care Staff ◽  
Health Concern ◽  
Health Care Staff ◽  
The Novel ◽  
Risk Of Infection ◽  
Inhibitory Effects ◽  
Runny Nose ◽  
Novel Coronavirus ◽  
Nucleoprotein N ◽  
The City

Today, Coronavirus (Cov) is one of the most dangerous diseases worldwide, and many people suffer from it. Coronavirus as a deadly virus was first recognized and spread in the City of Wuhan, Province of Hubei, China. This virion contains nucleocapsid, which is consists of phosphorylated nucleoprotein (N) and genomic RNA. The RNA of coronaviruses is enveloped, not fragmented, and is a positively sensitive single-stranded RNA that is known to be the largest viral genome in various sizes from 26 to 32 kV. Cov usually tends to provoke mild to severe respiratory disease. The symptoms of Cov may comprise headache, cough, fever, sore throat, runny nose, and a discomfort sensation. People with chronic diseases and health care staff are at greater risk of infection. Some compounds, such as mycophenolic acid and cyclosporine A, RNAi, and monoclonal antibodies have shown inhibitory effects against Cov. This article briefly discusses the nature, symptoms, transmission, treatment, prevention, and protection of this deadly virus.

scholarly journals A Review of Updates on Vaccines and Treatment Options for Covid-19

2021 ◽  
Vol VI (I) ◽  
pp. 1-9
Author(s):  
Naiha Tahir ◽  
Ayema Rehman ◽  
Muhammad Zain ◽  
Mubashir Rehman
Keyword(s):  
Focal Point ◽  
Treatment Options ◽  
The Novel ◽  
Wholesale Market ◽  
Current Management ◽  
Enveloped Virus ◽  
Global Pandemic ◽  
Novel Coronavirus ◽  
In The Beginning ◽  
The City

The novel Coronavirus knew as Covid 19 or SARS-CoV-2, is a newly discovered virus responsible for the huge global pandemic infecting the human race at a deadly pace. This is an RNA enveloped virus that targets the human respiratory system severely while damaging other major systems. Covid 19 pandemic is similar to the severe acute respiratory syndrome related coronavirus (SARS-CoV) endemic and the Middle East Respiratory Syndrome Coronavirus (MERS-CoV), but this one is spreading at a fire-speed. The outbreak was known as pneumonia in the beginning; however, it became a threat later on, owing to its high contagion rate. The origin of this virus was sought to be from the seafood wholesale market, very popular in the city of Wuhan. This review has been put together to overview the disease, its etiology, clinical features and treatment methods. The focal point of this review is to highlight the current management of this disease.

scholarly journals Epidemiological Features of the Incidence of COVID-19 in Moscow in the Period from March 1 to August 31, 2020

2021 ◽  
pp. 57-62
Author(s):  
AV Ivanenko ◽  
DV Soloviev ◽  
NA Volkova ◽  
VM Glinenko ◽  
OA Smirnova ◽  
...  
Keyword(s):  
Statistical Significance ◽  
High Rate ◽  
The Novel ◽  
Upper Respiratory Tract ◽  
Epidemiological Features ◽  
Student’S T ◽  
Novel Coronavirus ◽  
Tract Infections ◽  
The City ◽  
Spearman’S Correlation

Introduction: Coronavirus (SARS-CoV-2) infection is a global healthcare and social problem due to a rapid ubiquitous spread of the virus, a high rate of complications and deaths. The disease is often asymptomatic, which can contribute to its spread, while the most common complication is the development of pneumonia with or without acute respiratory failure and respiratory distress syndrome, which are often fatal. These characteristics of the disease, along with the almost complete lack of immunity in the population around the world (before the mass spread), allowed SARS-CoV-2 to spread freely among the population of all countries. Our objective was to assess the epidemiological features of the incidence of the novel coronavirus disease (COVID-19) in the population of the city of Moscow. Materials and methods: We conducted a retrospective analysis of all confirmed COVID-19 cases, the total number of diagnostic tests for COVID-19, and the incidence of upper respiratory tract infections registered in Moscow from March 1 to August 31, 2020. The correlation analysis was performed by calculating the Spearman’s correlation coefficient and subsequent statistical significance of differences in the compared relative values (p) from the Student’s t-test. Confidence intervals were determined with the calculation of average errors of the compared variables – m(σ). Conclusion: The revealed features of the COVID-19 incidence in Moscow help establish the factors influencing the development of the epidemic process in the city and give an accurate prediction of the COVID-19 situation for the future.

scholarly journals Antiviral potential of phytoligands against chymotrypsin-like protease of COVID‐19 virus using molecular docking studies: An optimistic approach

2020 ◽  
Author(s):  
Ratish Chandra Mishra ◽  
Rosy Kumari ◽  
Shivani Yadav ◽  
Jaya Parkash Yadav
Keyword(s):  
Molecular Docking ◽  
Binding Energy ◽  
Drug Repositioning ◽  
Docking Studies ◽  
The Novel ◽  
Lead Compounds ◽  
Recent Outbreak ◽  
Novel Coronavirus ◽  
The City ◽  
Ucsf Chimera

Abstract A recent outbreak of the novel coronavirus, COVID‐19, in the city of Wuhan, Hubei province, China and its ensuing worldwide spread have resulted in lakhs of infections and thousands of deaths. As of now, there are no registered therapies for treating the contagious COVID‐19 infections, henceforth drug repositioning may provide a fast way out. In the present study, a total of thirty-five compounds including commonly used anti-viral drugs were screened against chymotrypsin-like protease (3CLpro) using SwissDock. Interaction between amino acid of targeted protein and ligands was visualized by UCSF Chimera. Docking studies revealed that the phytochemicals such as cordifolin, anisofolin A, apigenin 7-glucoside, luteolin, laballenic acid, quercetin, luteolin-4-glucoside exhibited significant binding energy with the enzyme viz. - 8.77, -8.72, -8.36, -8.35, -8.13, -8.04 and -7.87 Kcal/Mol respectively. Therefore, new lead compounds can be used for drug development against SARS‐CoV‐2 infections.

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