Готові списки джерел за темами / SVNIR MODEL

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Добірка наукової літератури з теми "SVNIR MODEL"

Автор: Grafiati

Опубліковано: 11 вересня 2023

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Статті в журналах з теми "SVNIR MODEL"

Septiansyah, Gian, Muhammad Ahsar Karim, and Yuni Yulida. "PEMODELAN MATEMATIKA PENYEBARAN COVID-19 DENGAN MODEL SVEIR." EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN 16, no. 2 (December 1, 2022): 101. http://dx.doi.org/10.20527/epsilon.v16i2.6496.

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Анотація:

Coronavirus disease 2019 or also known as Covid-19 is a disease caused by a type of coronavirus called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) or better known as the corona virus. Covid-19 become a pandemic since 2020 and has been widely studied, one of which is in mathematical modeling. In this study, the spread of Covid-19 is modeled using the SVEIR (Susceptible, Vaccination, Exposed, Infected, and Recovered) model. The purpose of this study explains the formation of the Covid-19 SVEIR model, determines the equilibrium point, determines the basic reproduction number, and analyzes the stability of the Covid-19 SVEIR model. The purpose of this study explains the formation of the Covid-19 SVEIR model, determines the equilibrium point, the basic reproduction number, and analyzes the stability of the Covid-19 SVEIR model. The result of this study is to explain the formation of the Covid-19 SVEIR model and obtained two equilibrium points, the disease-free equilibrium point and the endemic equilibrium point. Furthermore, the basic reproduction number is obtained through the Next Generation Matrix method. The results of the stability analysis at the disease-free equilibrium point were locally asymptotically stable with conditions while at the endemic equilibrium point local asymptotically stable with conditions . The natural death rate is greater than the effective contact rate. A numerical simulation is presented to show a comparison spread of Covid-19 by providing different levels of vaccine effectiveness using the Runge-Kutta Order method.

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Harianto, Joko, Titik Suparwati, and Inda Puspita Sari. "DINAMIKA LOKAL MODEL EPIDEMI SVIR DENGAN IMIGRASI PADA KOMPARTEMEN VAKSINASI." BAREKENG: Jurnal Ilmu Matematika dan Terapan 14, no. 2 (September 7, 2020): 297–304. http://dx.doi.org/10.30598/barekengvol14iss2pp297-304.

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Анотація:

Abstrak Artikel ini termasuk dalam ruang lingkup matematika epidemiologi. Tujuan ditulisnya artikel ini untuk mendeskripsikan dinamika lokal penyebaran suatu penyakit dengan beberapa asumsi yang diberikan. Dalam pembahasan, dianalisis titik ekuilibrium model epidemi SVIR dengan adanya imigrasi pada kompartemen vaksinasi. Dengan langkah pertama, model SVIR diformulasikan, kemudian titik ekuilibriumnya ditentukan, selanjutnya, bilangan reproduksi dasar ditentukan. Pada akhirnya, kestabilan titik ekuilibirum yang bergantung pada bilangan reproduksi dasar ditentukan secara eksplisit. Hasilnya adalah jika bilangan reproduksi dasar kurang dari satu maka terdapat satu titik ekuilbirum dan titik ekuilbrium tersebut stabil asimtotik lokal. Hal ini berarti bahwa dalam kondisi tersebut penyakit akan cenderung menghilang dalam populasi. Sebaliknya, jika bilangan reproduksi dasar lebih dari satu, maka terdapat dua titik ekuilibrium. Dalam kondisi ini, titik ekuilibrium endemik stabil asimtotik lokal dan titik ekuilibrium bebas penyakit tidak stabil. Hal ini berarti bahwa dalam kondisi tersebut penyakit akan tetap ada dalam populasi. Kata Kunci : Model SVIR, Stabil Asimtotik Lokal Abstract This article is included in the scope of mathematical epidemiology. The purpose of this article is to describe the dynamics of the spread of disease with some assumptions given. In this paper, we present an epidemic SVIR model with the presence of immigration in the vaccine compartment. First, we formulate the SVIR model, then the equilibrium point is determined, furthermore, the basic reproduction number is determined. In the end, the stability of the equilibrium point is determined depending on the number of basic reproduction. The result is that if the basic reproduction number is less than one then there is a unique equilibrium point and the equilibrium point is locally asymptotically stable. This means that in those conditions the disease will tend to disappear in the population. Conversely, if the basic reproduction number is more than one, then there are two equilibrium points. The endemic equilibrium point is locally asymptotically stable and the disease-free equilibrium point is unstable. This means that in those conditions the disease will remain in the population. Keywords: SVIR Model, Locally Asymptotically stable.

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Seydou, Moussa, and Ousmane Moussa Tessa. "A Stochastic SVIR Model for Measles." Applied Mathematics 12, no. 03 (2021): 209–23. http://dx.doi.org/10.4236/am.2021.123013.

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Harianto, Joko, and Inda Puspita Sari. "Local Dynamics of an SVIR Epidemic Model with Logistic Growth." CAUCHY 6, no. 3 (November 19, 2020): 122–32. http://dx.doi.org/10.18860/ca.v6i3.9891.

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Анотація:

Discussion of local stability analysis of SVIR models in this article is included in the scope of applied mathematics. The purpose of this discussion was to provide results of local stability analysis that had not been discussed in some articles related to the SVIR model. The SVIR models discussed in this article involve logistics growth in the vaccinated compartment. The results obtained, i.e. if the basic reproduction number less than one and m is positive, then there is one equilibrium point i.e. E0 is locally asymptotically stable. In the field of epidemiology, this means that the disease will disappear from the population. However, if the basic reproduction number more than one and b1 more than b, then there are two equilibrium points i.e. disease-free equilibrium point denoted by E0 and the endemic equilibrium point denoted by E1*. In this case the endemic equilibrium point E1* is locally asymptotically stable. In the field of epidemiology, this means that the disease will remain in the population. The numerical simulation supports these results.

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Wyss, Alejandra, and Arturo Hidalgo. "Modeling COVID-19 Using a Modified SVIR Compartmental Model and LSTM-Estimated Parameters." Mathematics 11, no. 6 (March 16, 2023): 1436. http://dx.doi.org/10.3390/math11061436.

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Анотація:

This article presents a modified version of the SVIR compartmental model for predicting the evolution of the COVID-19 pandemic, which incorporates vaccination and a saturated incidence rate, as well as piece-wise time-dependent parameters that enable self-regulation based on the epidemic trend. We have established the positivity of the ODE version of the model and explored its local stability. Artificial neural networks are used to estimate time-dependent parameters. Numerical simulations are conducted using a fourth-order Runge–Kutta numerical scheme, and the results are compared and validated against actual data from the Autonomous Communities of Spain. The modified model also includes explicit parameters to examine potential future scenarios. In addition, the modified SVIR model is transformed into a system of one-dimensional PDEs with diffusive terms, and solved using a finite volume framework with fifth-order WENO reconstruction in space and an RK3-TVD scheme for time integration. Overall, this work demonstrates the effectiveness of the modified SVIR model and its potential for improving our understanding of the COVID-19 pandemic and supporting decision-making in public health.

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Das, Anjana, and M. Pal. "Modeling and Analysis of an Imprecise Epidemic System with Optimal Treatment and Vaccination Control." Biophysical Reviews and Letters 13, no. 02 (June 2018): 37–60. http://dx.doi.org/10.1142/s1793048018500042.

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Анотація:

In this paper, we propose and analyze a Susceptible-Vaccinated-Exposed-Infected-Recovered (SVEIR) type infectious disease model with imprecise parameters. Introducing the interval numbers in functional form, the SVEIR model is proposed and formulated. The existence of possible equilibrium points with their feasibility criteria and an explicit value of basic reproduction number is obtained. The asymptotic stability of the system at different equilibrium points are also discussed. Next by considering treatment and vaccination as two control parameters, an optimal control problem is formulated and solved. Finally, some computer simulation works are given in support of our analytical results.

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Ahaya, Sitty Oriza Sativa Putri, Emli Rahmi, and Nurwan Nurwan. "Analisis dinamik model SVEIR pada penyebaran penyakit campak." Jambura Journal of Biomathematics (JJBM) 1, no. 2 (December 25, 2020): 57–64. http://dx.doi.org/10.34312/jjbm.v1i2.8482.

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In this article, we analyze the dynamics of measles transmission model with vaccination via an SVEIR epidemic model. The total population is divided into five compartments, namely the Susceptible, Vaccinated, Exposed, Infected, and Recovered populations. Firstly, we determine the equilibrium points and their local asymptotically stability properties presented by the basic reproduction number R0. It is found that the disease free equilibrium point is locally asymptotically stable if satisfies R01 and the endemic equilibrium point is locally asymptotically stable when R01. We also show the existence of forward bifurcation driven by some parameters that influence the basic reproduction number R0 i.e., the infection rate α or proportion of vaccinated individuals θ. Lastly, some numerical simulations are performed to support our analytical results.

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WANG, JINLIANG, SHENGQIANG LIU, and YASUHIRO TAKEUCHI. "THRESHOLD DYNAMICS IN A PERIODIC SVEIR EPIDEMIC MODEL." International Journal of Biomathematics 04, no. 04 (December 2011): 493–509. http://dx.doi.org/10.1142/s1793524511001490.

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In this paper, we investigate the dynamical behavior of a class of periodic SVEIR epidemic model. Since the nonautonomous phenomenon often occurs as cyclic pattern, our model is then a periodic time-dependent system. It follows from persistence theory that the basic reproduction number is the threshold parameter above which the disease is uniformly persistent and below which disease-free periodic solution is globally asymptotically stable. The threshold dynamics extends the classic results for the corresponding autonomous model. Furthermore, we show that eradication policy on the basis of the basic reproduction number of the autonomous system may overestimate the infectious risk when the disease follows periodic behavior. The according simulation results are also given.

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Harianto, Joko, and Titik Suparwati. "SVIR Epidemic Model with Non Constant Population." CAUCHY 5, no. 3 (December 5, 2018): 102. http://dx.doi.org/10.18860/ca.v5i3.5511.

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Анотація:

In this article, we present an SVIR epidemic model with deadly deseases and non constant population. We only discuss the local stability analysis of the model. Initially the basic formulation of the model is presented. Two equilibrium point exists for the system; disease free and endemic equilibrium point. The local stability of the disease free and endemic equilibrium exists when the basic reproduction number less or greater than unity, respectively. If the value of R0 less than one then the desease free equilibrium point is locally asymptotically stable, and if its exceeds, the endemic equilibrium point is locally asymptotically stable. The numerical results are presented for illustration.

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Parhusip, Hanna Arini, Suryasatriya Trihandaru, Bernadus Aryo Adhi Wicaksono, Denny Indrajaya, Yohanes Sardjono, and Om Prakash Vyas. "Susceptible Vaccine Infected Removed (SVIR) Model for COVID-19 Cases in Indonesia." Science and Technology Indonesia 7, no. 3 (July 28, 2022): 400–408. http://dx.doi.org/10.26554/sti.2022.7.3.400-408.

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Анотація:

Analysis of data on COVID-19 cases in Indonesia is shown by using the Susceptible Vaccine Infected Removed (SVIR) in this article. In the previous research, cases in the period March-May 2021 were studied, and the reproduction number was computed based on the Susceptible Infected Removed (SIR) model. The prediction did not agree with the real data. Therefore the objective of this article is to improve the model by adding the vaccine variable leading to the new model called the SVIR model as the novelty of this article. The used data are collected from COVID-19 cases of the Indonesian population published by the Indonesian government from March 2020-April 2022. However, the vaccinated persons with COVID-19 cases have been recorded since January 2022. Therefore the models rely on the period January 2021-March 2022, where the parameters in the SIR and SVIR models are determined in this period. The method used is discretizing the models into linear systems, and these systems are solved by Ordinary Least Square (OLS) for time-dependent parameters. It is assumed that the birth rate and death rate in the considered period are constant. Additionally, individuals who have recovered from COVID-19 will not be infected again, and vaccination is not necessarily twice. Furthermore, individuals who have been vaccinated will not be infected with the COVID-19 virus. The SVIR model has captured 3 waves of COVID-19 cases that are appropriate to the real situation in Indonesia from January 2021-March 2022. Additionally, the reproduction numbers as functions of time have been generated. The fluctuations of reproduction numbers agree with the real data. For further research, different regions such as districts in Java and other islands will also be analyzed as the implication of this research.

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Більше джерел

Дисертації з теми "SVNIR MODEL"

ANSHUL and SEEMA. "MODELLING THE IMPACT OF RUMORS ON STUDENT ATTENDANCE IN COLLEGE CLASSES." Thesis, 2023. http://dspace.dtu.ac.in:8080/jspui/handle/repository/20146.

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Rumors are an inherent aspect of human communication and can profoundly influence individuals' attitudes and behaviors. Particularly in a college environment, rumors can wield a significant influence on student attendance in classes. This research paper aims to delve into the repercussions of rumors on student attendance in college classrooms. Rumors are a frequent occurrence on college campuses and possess the power to shape students' behaviors and perceptions. To comprehensively analyze the impact of rumors on student attendance, we propose a mathematical model known as the SVNIR model. The SVNIR model categorizes the population into four compartments: susceptible (S), students in proximity who have been exposed to the rumor (V), students outside the vicinity who have heard the rumor (N), and students who have attended class (R). The study's findings demonstrate that rumors can wield a considerable impact on student attendance. Negative rumors result in a decline in attendance, while positive rumors lead to an increase in attendance. Overall, this research underscores the significance of comprehending the influence of rumors on student attendance in college classes. It introduces a fresh and innovative approach by employing the SIR model to depict the dynamics of rumors. This accentuates the importance of recognizing the role of rumors in shaping student attendance in college classes. Educators should be cognizant of the potential consequences of rumors on student attendance and proactively take measures to address them. These measures may include providing accurate information and fostering trust among students.

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Hsiao-Ping, Yeh, and 葉小萍. "The Transmission Dynamics of an SVIR Model." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/94275163978758499959.

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碩士
東吳大學
數學系
102
We consider asymptotic properties of an SVIR model of influenza. It is proved that if the basic reproduction number , there is no endemic equilibrium and the the disease free equilibrium is always globally asymptotically stable. When , there is a unique endemic equilibrium. And it is locally asymptotically stable if the vaccination efficacy is small, and we present some numerical examples to investigate the global stability of the endemic equilibrium.

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Частини книг з теми "SVNIR MODEL"

Gamboa, Maria, Martín López-García, and Maria Jesus Lopez-Herrero. "A Stochastic SVIR Model with Imperfect Vaccine and External Source of Infection." In Lecture Notes in Computer Science, 197–209. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91825-5_12.

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Kachhawa, Nitin Singh, Prasit Girish Agnihotri, and Azazkhan Ibrahimkhan Pathan. "Rainfall-Runoff Simulation and Storm Water Management Model for SVNIT Campus Using EPA SWMM 5.1." In Intelligent Computing & Optimization, 832–42. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93247-3_79.

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Song, Xiuchao, Miaohua Liu, Hao Song, and Jinshen Ren. "Dynamical Behavior of an SVIR Epidemiological Model with Two Stage Characteristics of Vaccine Effectiveness and Numerical Simulation." In Advances in Intelligent Systems and Computing, 238–42. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34387-3_29.

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"SVIR Model Implementation." In Mathematical Modeling of Virus Infection, 85–160. WORLD SCIENTIFIC, 2021. http://dx.doi.org/10.1142/9789811236648_0004.

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"SVIR Model Formulation." In Mathematical Modeling of Virus Infection, 75–83. WORLD SCIENTIFIC, 2021. http://dx.doi.org/10.1142/9789811236648_0003.

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Тези доповідей конференцій з теми "SVNIR MODEL"

Bekiryazici, Zafer, Mehmet Merdan, and Tulay Kesemen. "Generalized beta parameters for a SVEIR-type random model of Polio transmission." In 7TH INTERNATIONAL EURASIAN CONFERENCE ON MATHEMATICAL SCIENCES AND APPLICATIONS (IECMSA-2018). Author(s), 2018. http://dx.doi.org/10.1063/1.5078459.

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Widyaningsih, Purnami, Laila F. Aminni, and Dewi R. S. Saputro. "Measles free prediction and control strategy to achieve measles elimination target in Indonesia based on SVEIR model." In INTERNATIONAL CONFERENCE OF MATHEMATICS AND MATHEMATICS EDUCATION (I-CMME) 2021. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0116992.

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Kuo, Chun-Lin, Wai Kin Victor Chan, and Mengxuan Chen. "Impact of Vaccination Strategies For Epidemic Node-level SVIR Probabilistic Model : Pandemic simulation on social networks under various vaccination strategies." In 2020 International Conference on Public Health and Data Science (ICPHDS). IEEE, 2020. http://dx.doi.org/10.1109/icphds51617.2020.00063.

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