scholarly journals Modeling of spreading of the novel coronavirus based in the stochastic dynamic

2020 ◽  
Author(s):  
Leonardo S. Lima
Keyword(s):  
Differential Equation ◽  
Mathematical Model ◽  
Stochastic Model ◽  
Planck Equation ◽  
Stochastic Dynamic ◽  
The Novel ◽  
Model Based ◽  
The Mean ◽  
Novel Coronavirus ◽  
Official Data

Abstract In this paper, one proposes a stochastic model based on Itô diffusion as mathematical model for time evolution of novel cases N(t) of the SARS-CoV-2 (COVID-19) in each day t. I propose a correspondent stochastic differential equation (SDE) analogous to classical differential equation for epidemic growing for some diseases as smallpox and typhoid fever. Furthermore, we made an analysis using the Fokker-Planck equation giving an estimating of the novel cases in the day t as the mean half-width of the distribution P(N,t) of novel cases. My results display that the model based on Itô diffusion fits well to the results supported by healthy Brazilian agencies due to large uncertainly in the official data generated by the low number of tests realized generating so a strong randomness in the official data.

scholarly journals Stochastic analysis using public data for forecasting of epidemic spreading of the novel coronavirus disease

2020 ◽  
Author(s):  
Leonardo dos Santos Lima
Keyword(s):  
Stochastic Model ◽  
Stochastic Analysis ◽  
Planck Equation ◽  
The Novel ◽  
Epidemic Spreading ◽  
Public Data ◽  
Health Agencies ◽  
The Mean ◽  
Novel Coronavirus ◽  
Official Data

Abstract We propose a stochastic model for epidemic spreading of the novel coronavirus based in data supported by the Brazilian health agencies. Furthermore, we performed an analysis using the Fokker-Planck equation estimating the novel cases in the day t as the mean half-width of the distribution of novel cases P(N,t). Our results display that the model based in the Itô diffusion adjusts well to the results supplied by health Brazilian agencies due to large uncertain in the official data and to the low number of tests realized in the population.

scholarly journals Modeling and forecasting of epidemic spreading of the SARS-CoV-2 based in the nonlinear stochastic dynamics

2020 ◽  
Author(s):  
Leonardo S. Lima
Keyword(s):  
Differential Equation ◽  
Mathematical Model ◽  
Stochastic Dynamics ◽  
Planck Equation ◽  
Epidemic Spreading ◽  
Model Based ◽  
Modeling And Forecasting ◽  
The Mean ◽  
Nonlinear Stochastic Dynamics ◽  
Official Data

Abstract In this paper, we propose a stochastic model based on Itô diffusion as mathematical model for time evolution of new cases N(t) of the SARS-CoV-2 (COVID-19) in each day t. We propose a correspondent stochastic differential equation (SDE) analogs to classical differential equations for epidemic growing for some diseases as smallpox and typhoid fever. Furthermore, we made an analysis using the Fokker-Planck equation giving an estimating of the new cases in each day t as the mean half-width of the distribution P(N,t) of new cases. Our results display that the model based on Itô diffusion fit well to the results supported by healthy Brazilian agencies due to large uncertain in the official results and to the low number of tests realized generating so a strong randomness in the official data.

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.

Curve Estimation Modeling for Predictions of the Novel Coronavirus (Covid-19) Epidemic in Nigeria

2020 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Christian Ebere Enyoh ◽  
Andrew Wirnkor Verla ◽  
Chidi Edbert Duru ◽  
Emmanuel Chinedu Enyoh ◽  
Budi Setiawan
Keyword(s):  
State Governments ◽  
The Novel ◽  
Curve Estimation ◽  
Exponential Models ◽  
Inverse Models ◽  
Forward Prediction ◽  
S Curve ◽  
Novel Coronavirus ◽  
Best Fit ◽  
Official Data

Based on the official Nigeria Centre for Disease Control (NCDC) data, the current research paper modeled the confirmed cases of the novel coronavirus disease 2019 (COVID-19) in Nigeria. Ten different curve regression models including linear, logarithmic, inverse, quadratic, cubic, compound, power, S-curve, growth, and exponential were used to fit the obtained official data. The cubic (R2 = 0.999) model gave the best fit for the entire country. However, the growth and exponential had the lowest standard error of estimate (0.958) and thus may best be used. The equations for these models were e0.78897+0.0944x and 2.2011e0.0944x respectively. In terms of confirmed cases in individual State, quadratic, cubic, compound, growth, power and exponential models generally best describe the official data for many states except for the state of Kogi which is best fitted with S-curve and inverse models.  The error between the model and the official data curve is quite small especially for compound, power, growth and exponential models. The computed models will help to realized forward prediction and backward inference of the epidemic situation in Nigeria, and the relevant analysis help Federal and State governments to make vital decisions on how to manage the lockdown in the country.

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 Transmission potential of the novel coronavirus (COVID-19) onboard the Diamond Princess Cruises Ship, 2020

2020 ◽  
Author(s):  
Kenji Mizumoto ◽  
Gerardo Chowell
Keyword(s):  
Mathematical Modeling ◽  
Time Series ◽  
Reproduction Number ◽  
Transmission Dynamics ◽  
The Novel ◽  
Epidemic Threshold ◽  
Transmission Potential ◽  
Incidence Data ◽  
The Mean ◽  
Novel Coronavirus

AbstractAn outbreak of COVID-19 developed aboard the Princess Cruises Ship during January-February 2020. Using mathematical modeling and time-series incidence data describing the trajectory of the outbreak among passengers and crew members, we characterize how the transmission potential varied over the course of the outbreak. Our estimate of the mean reproduction number in the confined setting reached values as high as ∼11, which is higher than mean estimates reported from community-level transmission dynamics in China and Singapore (approximate range: 1.1-7). Our findings suggest that Rt decreased substantially compared to values during the early phase after the Japanese government implemented an enhanced quarantine control. Most recent estimates of Rt reached values largely below the epidemic threshold, indicating that a secondary outbreak of the novel coronavirus was unlikely to occur aboard the Diamond Princess Ship.

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 Modelling based in the stochastic dynamics for the time evolution of the COVID-19

2020 ◽  
Author(s):  
Leonardo dos Santos Lima
Keyword(s):  
Differential Equation ◽  
Evolution Equation ◽  
Stochastic Model ◽  
Stochastic Differential Equation ◽  
Stochastic Dynamics ◽  
Planck Equation ◽  
Time Dynamics ◽  
Health Agencies ◽  
System Of Particles ◽  
Effective Description

Abstract The stochastic differential equation (SDE) corresponding to nonlinear Fokker-Planck equation where the nonlinearity appearing in this evolution equation can be interpreted as providing an effective description of a system of particles interacting is obtained. Additionally, we propose a stochastic model for time dynamics of the COVID-19 based in the set of data supported by the Brazilian health agencies.

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