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Otoo, Dominic; Opoku, Patrick; Sebil, Charles; Kingsley, Asekiya Prince

doi:10.1016/j.idm.2019.11.001

Cited by 13 publications

(9 citation statements)

References 13 publications

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“…2) SV C sy C Asy IR Model: A modified version of SIR model with addition of three more parameters, namely vaccinated individual V , symptomatic carrier C sy , asymptomatic carrier C Asy is known as SV C sy C Asy IR Model [24]. These parameters at time t are denoted as S(t), V (t), C sy (t), C Asy (t), I(t) and R(t).…”

Section: A Compartment Modelmentioning

confidence: 99%

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A Survey on Mathematical, Machine Learning and Deep Learning Models for COVID-19 Transmission and Diagnosis

John

Ponnusamy

Chandrasekaran

et al. 2022

IEEE Rev. Biomed. Eng.

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COVID-19 is a life threatening disease which has a enormous global impact. As the cause of the disease is a novel coronavirus whose gene information is unknown, drugs and vaccines are yet to be found. For the present situation, disease spread analysis and prediction with the help of mathematical and data driven model will be of great help to initiate prevention and control action, namely lockdown and qurantine. There are various mathematical and machinelearning models proposed for analyzing the spread and prediction. Each model has its own limitations and advantages for a particluar scenario. This article reviews the state-of-the art mathematical models for COVID-19, including compartment models, statistical models and machine learning models to provide more insight, so that an appropriate model can be well adopted for the disease spread analysis. Furthermore, accurate diagnose of COVID-19 is another essential process to identify the infected person and control further spreading. As the spreading is fast, there is a need for quick auotomated diagnosis mechanism to handle large population. Deep-learning and machine-learning based diagnostic mechanism will be more appropriate for this purpose. In this aspect, a comprehensive review on the deep learning models for the diagnosis of the disease is also provided in this article.

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Section: A Compartment Modelmentioning

confidence: 99%

“…In this model, betweenfarm and within-farm spread for swine fever is modelled. Authors of [24] proposed SV C sy C Asy IR model to consider susceptible, vaccinated individual, symptomatic carrier, asymptomatic carrier, infected individual and recovered individual at time t.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Mathematical, Machine Learning and Deep Learning Models for COVID-19 Transmission and Diagnosis

John

Ponnusamy

Chandrasekaran

et al. 2022

IEEE Rev. Biomed. Eng.

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“…In 2020, Otoo et al analysed a model of pneumonia spread by bacteria. The analysis determined the effects of vaccination to control the disease [ 18 ]. In 2020, Zephaniah et al presented the dynamics of mathematical models for pneumonia, showing the result graphically [ 19 ].…”

Section: Literature Surveymentioning

confidence: 99%

Modeling the transmission dynamics of delayed pneumonia-like diseases with a sensitivity of parameters

et al. 2021

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Pneumonia is a highly transmitted disease in children. According to the World Health Organization (WHO), the most affected regions include South Asia and sub-Saharan Africa. 15% deaths of children are due to pneumonia. In 2017, 0.88 million children were killed under the age of five years. An analysis of pneumonia disease is performed with the help of a delayed mathematical modelling technique. The epidemiological system contemplates subpopulations of susceptible, carriers, infected and recovered individuals, along with nonlinear interactions between the members of those subpopulations. The positivity and the boundedness of the ongoing problem for nonnegative initial data are thoroughly proved. The system possesses pneumonia-free and pneumonia existing equilibrium points, whose stability is studied rigorously. Moreover, the numerical simulations confirm the validity of these theoretical results.

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“…Penelitian lain dilakukan oleh Fajar [4] dengan memperhatikan faktor host yaitu kondisi imun lemah dan vaksinasi sebagai faktor pengendali penyakit pneumonia. Beberapa penelitian lain yang membahas masalah pneumonia dalam perspektif pemodelan dapat dilihat pada [9,11,12].…”

Section: Pendahuluanunclassified

SEIPR-Mathematical Model of the Pneumonia Spreading in Toddlers with Immunization and Treatment Effects

Imran

Resmawan

Achmad

et al. 2020

JMSK

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This research discussed the SEIPR mathematical model on the spread of pneumonia among children under five years old. The development of the model was done by considering factors of immunization and treatment factors, in an effort to reduce the rate of spread of pneumonia. In this research, mathematical model construction, stability analysis, and numerical simulation were carried out to see the dynamics of pneumonia cases in the population. The model analysis produces two equilibrium points, which are the equilibrium point without the disease, the endemic equilibrium point, and the basic reproduction number ( ) as the threshold value for disease spread. The point of equilibrium without disease reaches a stable state at the moment , which indicates that pneumonia will disappear from the population, while the endemic equilibrium point reaches a stable state at that time , which indicates that the disease will spread in the population. Furthermore, numerical simulations show that increasing the rate parameters of infected individuals undergoing treatment ( ), the treatment success rate ( ), and the immunization proportion ( ), could suppress the basic reproductive number so that control of the disease spread rate can be accelerated.

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Deterministic epidemic model for (SVCSyCAsyIR) pneumonia dynamics, with vaccination and temp

Cited by 13 publications

References 13 publications

A Survey on Mathematical, Machine Learning and Deep Learning Models for COVID-19 Transmission and Diagnosis

A Survey on Mathematical, Machine Learning and Deep Learning Models for COVID-19 Transmission and Diagnosis

Modeling the transmission dynamics of delayed pneumonia-like diseases with a sensitivity of parameters

SEIPR-Mathematical Model of the Pneumonia Spreading in Toddlers with Immunization and Treatment Effects

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