scholarly journals A Mathematical Model for the COVID-19 Outbreak and Its Applications

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 990
Author(s):  
Roman Cherniha ◽  
Vasyl’ Davydovych
Keyword(s):  
Mathematical Model ◽  
Exact Solutions ◽  
Quantitative Description ◽  
Measured Data ◽  
Nonlinear Ordinary Differential Equations ◽  
The Novel ◽  
The Public ◽  
Public Data ◽  
Novel Coronavirus ◽  
Good Agreement

A mathematical model based on nonlinear ordinary differential equations is proposed for quantitative description of the outbreak of the novel coronavirus pandemic. The model possesses remarkable properties, such as as full integrability. The comparison with the public data shows that exact solutions of the model (with the correctly specified parameters) lead to the results, which are in good agreement with the measured data in China and Austria. Prediction of the total number of the COVID-19 cases is discussed and examples are presented using the measured data in Austria, France, and Poland. Some generalizations of the model are suggested as well.

scholarly journals Dynamics based on analysis of public data for spreading of disease

2021 ◽  
Author(s):  
Leonardo S. Lima
Keyword(s):  
Planck Equation ◽  
The Novel ◽  
Epidemic Spreading ◽  
Data Set ◽  
Public Health Agencies ◽  
The Public ◽  
Public Data ◽  
Health Agencies ◽  
Novel Coronavirus ◽  
Official Data

Abstract The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supported by the public health agencies in countries as Brazil, EUA and India is investigated. We perform the numerical analysis using the stochastic differential equation in Itô’s calculus (SDE) for the estimating of novel cases daily as well as analytical calculations solving the correspondent Fokker-Planck equation for the density probability distribution of novel cases, P(N(t); t). Our results display that the model based in the Itô diffusion fits well to the results due to uncertain in the official data and to the number of tests realized in the populations of each country.

scholarly journals Dynamics based on analysis of public data for spreading of disease

2021 ◽  
Author(s):  
Leonardo S. Lima
Keyword(s):  
Planck Equation ◽  
Probability Density Distribution ◽  
The Novel ◽  
Epidemic Spreading ◽  
Data Set ◽  
Public Health Agencies ◽  
The Public ◽  
Public Data ◽  
Health Agencies ◽  
Novel Coronavirus

Abstract The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supply by the public health agencies in countries as Brazil, United States and India is investigated. We perform a numerical analysis using the stochastic differential equation in Itô’s calculus for the estimating of novel cases daily, as well as analytical calculations solving the correspondent Fokker-Planck equation for the probability density distribution of novel cases, P(N(t); t). Our results display that the model based in the Itô’s diffusion fits well to the results due to uncertainty in the official data and to the number of testsrealized in populations of each country.

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 Dynamics based on analysis of public data for spreading of disease

2020 ◽  
Author(s):  
Leonardo S. Lima
Keyword(s):  
Public Health ◽  
The Novel ◽  
Epidemic Spreading ◽  
Data Set ◽  
Public Health Agencies ◽  
The Public ◽  
Public Data ◽  
Health Agencies ◽  
Novel Coronavirus ◽  
Official Data

Abstract The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supported by the public health agencies in countries as Brazil, EUA and India is investigated. We performed the numerical analysis using the stochastic differential equation for estimating of the novel cases diary as well as analytical calculations solving the correspondent partial equation for the distribution of novel cases P. Our results display that the model based in the Itô diffusion fits well to the results diary due to uncertain in the official data and to the number of tests realized in the populations of each country.

scholarly journals Dynamics based on analysis of public data for spreading of disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Leonardo S. Lima
Keyword(s):  
Planck Equation ◽  
Probability Density Distribution ◽  
The Novel ◽  
Epidemic Spreading ◽  
Data Set ◽  
Public Health Agencies ◽  
The Public ◽  
Public Data ◽  
Health Agencies ◽  
Novel Coronavirus

AbstractThe stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supply by the public health agencies in countries as Brazil, United States and India is investigated. We perform a numerical analysis using the stochastic differential equation in Itô’s calculus for the estimating of novel cases daily, as well as analytical calculations solving the correspondent Fokker–Planck equation for the probability density distribution of novel cases, P(N(t), t). Our results display that the model based in the Itô’s diffusion fits well to the results due to uncertainty in the official data and to the number of tests realized in populations of each country.

Coronavirus: Towards controlling of the pandemic - Indian scenario

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 462-468
Author(s):  
Latika kothari ◽  
Sanskruti Wadatkar ◽  
Roshni Taori ◽  
Pavan Bajaj ◽  
Diksha Agrawal
Keyword(s):  
Control Measures ◽  
The Novel ◽  
Medical Treatments ◽  
Health Crisis ◽  
The Public ◽  
Infection Control Measures ◽  
The Social ◽  
Asking Questions ◽  
The Government ◽  
Novel Coronavirus

Coronavirus disease 2019 (COVID-19) is a communicable infection caused by the novel coronavirus resulting in severe acute respiratory syndrome coronavirus 2 (SARS-CoV). It was recognized to be a health crisis for the general population of international concern on 30th January 2020 and conceded as a pandemic on 11th March 2020. India is taking various measures to fight this invisible enemy by adopting different strategies and policies. To stop the COVID-19 from spreading, the Home Affairs Ministry and the health ministry, of India, has issued the nCoV 19 guidelines on travel. Screening for COVID-19 by asking questions about any symptoms, recent travel history, and exposure. India has been trying to get testing kits available. The government of India has enforced various laws like the social distancing, Janata curfew, strict lockdowns, screening door to door to control the spread of novel coronavirus. In this pandemic, innovative medical treatments are being explored, and a proper vaccine is being hunted to deal with the situation. Infection control measures are necessary to prevent the virus from further spreading and to help control the current situation. Thus, this review illustrates and explains the criteria provided by the government of India to the awareness of the public to prevent the spread of COVID-19.

High cytokine levels and cytokine storm in the novel coronavirus infection

2021 ◽  
pp. 38-47
Author(s):  
Maksim Leonidovich Maksimov ◽  
Albina Ayratovna Zvegintseva ◽  
Lyudmila Yurievna Kulagina ◽  
Albina Zainutdinovna Nigmedzyanova ◽  
Elvina Ramisovna Kadyseva
Keyword(s):  
Peripheral Blood ◽  
High Frequency ◽  
The Novel ◽  
Cytokine Storm ◽  
The Public ◽  
Systemic Inflammatory Reaction ◽  
Scientific World ◽  
Cytokine Levels ◽  
Coronavirus Infection ◽  
Novel Coronavirus

A review article is based on current foreign sources. The level of cytokines in the peripheral blood can be increased in many diseases, but in some cases there may be an excess of their normal concentration in tens, hundreds or more times with the development of a peculiar clinical picture, which is based on a systemic inflammatory reaction. In the literature this condition has received the figurative name «cytokine storm», which highlights an extremely violent reaction of the immune system with an unknown (often unfavorable) outcome. Close attention of the scientific world and the public to the problem of extremely high levels of cytokines in the peripheral blood (hypercytokinemia) was drawn due to the high frequency of the cytokine storm in the novel coronavirus infection.

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.

scholarly journals The Impact of Armed Conflict on the Epidemiological Situation of COVID-19 in Libya, Syria and Yemen

2021 ◽  
Vol 9 ◽  
Author(s):  
Mohamed A. Daw
Keyword(s):  
Armed Conflict ◽  
Early Stage ◽  
Armed Conflicts ◽  
Cumulative Number ◽  
The Novel ◽  
Global Pandemic ◽  
Large Numbers ◽  
Public Data ◽  
Novel Coronavirus ◽  
The Impact

Background: Since the Arab uprising in 2011, Libya, Syria and Yemen have gone through major internal armed conflicts. This resulted in large numbers of deaths, injuries, and population displacements, with collapse of the healthcare systems. Furthermore, the situation was complicated by the emergence of COVID-19 as a global pandemic, which made the populations of these countries struggle under unusual conditions to deal with both the pandemic and the ongoing wars. This study aimed to determine the impact of the armed conflicts on the epidemiology of the novel coronavirus (SARS-CoV-2) within these war-torn countries and highlight the strategies needed to combat the spread of the pandemic and its consequences.Methods: Official and public data concerning the dynamics of the armed conflicts and the spread of SARS-COV-2 in Libya, Syria and Yemen were collected from all available sources, starting from the emergence of COVID-19 in each country until the end of December 2020. Datasets were analyzed by a set of statistical techniques and the weekly resolved data were used to probe the link between the intensity levels of the conflict and the prevalence of COVID-19.Results: The data indicated that there was an increase in the intensity of the violence at an early stage from March to August 2020, when it approximately doubled in the three countries, particularly in Libya. During that period, few cases of COVID-19 were reported, ranging from 5 to 53 cases/day. From September to December 2020, a significant decline in the intensity of the armed conflicts was accompanied by steep upsurges in the rate of COVID-19 cases, which reached up to 500 cases/day. The accumulative cases vary from one country to another during the armed conflict. The highest cumulative number of cases were reported in Libya, Syria and Yemen.Conclusions: Our analysis demonstrates that the armed conflict provided an opportunity for SARS-CoV-2 to spread. The early weeks of the pandemic coincided with the most intense period of the armed conflicts, and few cases were officially reported. This indicates undercounting and hidden spread during the early stage of the pandemic. The pandemic then spread dramatically as the armed conflict declined, reaching its greatest spread by December 2020. Full-blown transmission of the COVID-19 pandemic in these countries is expected. Therefore, urgent national and international strategies should be implemented to combat the pandemic and its consequences.

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