Analysis of a Model for Coronavirus Spread

Belgaid, Youcef; Helal, Mohamed; Venturino, Ezio

doi:10.3390/math8050820

Cited by 13 publications

(12 citation statements)

References 16 publications

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“…Some authors [ 16 , 17 ] estimated the mean reproduction number for COVID-19 in the early phase of outbreak, which is slightly higher than that for SARS-CoV. Still other works where the basic reproduction number is estimated for different countries can be found in [ [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] ].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity and elasticity analysis of novel corona virus transmission model: A mathematical approach

Das¹,

Kumar²,

Reddy³

et al. 2021

Sensors International

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The deadly corona virus continues to pound the globe mercilessly compelling mathematical models and computational simulations which might prove effective tools to enable global efforts to estimate key transmission parameters involved in the system. We propose a mathematical model using a set of non-linear differential equations to account for the spread of the COVID-19 infection with special compartment class isolation or quarantine and estimate the model parameters by fitting the model with reported data of the ongoing pandemic situation in India. The basic reproduction number is defined and local stability analysis is carried out at each equilibrium point in terms of the reproduction number . The model is fitted mathematically and makes the data India specific. Additionally, we examined sensitivity analysis of the model. These outcomes recommend how to control the spread of corona, keeping in mind contact and recovery rate. Also we have investigated the elasticity of the basic reproduction number as a measure of control parameters of the dynamical system. Numerical simulations were also done to show that the proposed model is valid for the type and spread of the outbreak which happened in India.

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Section: Introductionmentioning

confidence: 99%

Sensitivity and elasticity analysis of novel corona virus transmission model: A mathematical approach

Das¹,

Kumar²,

Reddy³

et al. 2021

Sensors International

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“…The first term in equation (5) corresponds to horizontal recruitment in the hospitalized human population. The second and third terms represent the arrival of new hospitalized after testing an infectious (at rate (1 − p) q) and disease worsening for quarantined (at rate α 2 ).…”

Section: Introductionmentioning

confidence: 99%

“…The first group addressed the problem of forecasting the disease in order to help decision makers to better evaluate the logistic challenges they will face [1, 3, 4, 16, 15, 24, 25, 28, 29, 37, 38, 39, 41, 45, 47, 48, 51, 61, 62]. The second category of papers focused on evaluating the effectiveness of mitigations measures prescribed by the WHO and different governments in order to define better fighting strategies [5, 9, 12, 13, 14, 29, 34, 37, 41, 44, 45, 46, 50, 53, 55, 54, 60, 62]. The last set of papers studied the social and the economical impacts of the pandemic [35, 59].…”

Section: Introductionmentioning

confidence: 99%

Estimation and optimal control of the multi-scale dynamics of the Covid-19

Fotsa-Mbogne

Tchoumi

Kouakep

et al. 2021

Preprint

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This work aims at a better understanding and the optimal control of the spread of the new severe acute respiratory corona virus 2 (SARS-CoV-2). We first propose a multi-scale model giving insights on the virus population dynamics, the transmission process and the infection mechanism. We consider 10 compartments in the human population in order to take into accounts the effects of different specific mitigation policies. The population of viruses is also partitioned into 10 compartments corresponding respectively to each of the first nine human population compartments and the free viruses available in the environment. We show the global stability of the disease free equilibrium if a given threshold T_0 is less or equal to 1 and we provide how to compute the basic reproduction number R_0. A convergence index T_1 is also defined in order to estimate the speed at which the disease extincts and an upper bound to the time of extinction is given. The existence of the endemic equilibrium is conditional and its description is provided. We evaluate the sensitivity of R_0, T_0 and T_1 to control parameters such as the maximal human density allowed per unit of surface, the rate of disinfection both for people and environment, the mobility probability, the wearing mask probability or efficiency, and the human to human contact rate which results from the previous one. According to a functional cost taking into consideration economic impacts of SARS-CoV-2, we determine and discuss optimal fighting strategies. The study is applied to available data from Cameroon.

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“…Bentout et al [8] developed an susceptible exposed infectious recovered model to estimation and prediction for COVID-19 in Algeria. Belgaid et al [9] suggested and analysis of a model for Coronavirus spread. Owolabi et al [10] proposed and analyzed a nonlinear epidemiological model for SARS CoV-2 virus with quarantine class.…”

Section: Introductionmentioning

confidence: 99%

Global stability of COVID-19 model involving the quarantine strategy and media coverage effects

Mohsen¹,

Al-Husseiny²,

Zhou³

et al. 2020

AIMS Public Health

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In this paper, we build and analyze a mathematical model of COVID-19 transmission considering media coverage effects. Due to transmission characteristics of COVID-19, we can divided the population into five classes. The first class describes the susceptible individuals, the second class is exposed individuals, the third class is infected individuals, the fourth class is quarantine class and the last class is recovered individuals. The existence, uniqueness and boundedness of the solutions of the model are discussed. The basic reproduction number is obtained. All possible equilibrium points of the model are investigated and their local stability is discussed under some conditions. The disease-free equilibrium is local asymptotically stable when and unstable when . The globally asymptotical stability of all point is verified by Lyapunov function. Finally, numerical simulations are carried out to confirm the analytical results and understand the effect of varying the parameters on spread of COVID-19. These findings suggested that media coverage can be considered as an effective way to mitigate the COVID-19 spreading.

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Analysis of a Model for Coronavirus Spread

Cited by 13 publications

References 16 publications

Sensitivity and elasticity analysis of novel corona virus transmission model: A mathematical approach

Sensitivity and elasticity analysis of novel corona virus transmission model: A mathematical approach

Estimation and optimal control of the multi-scale dynamics of the Covid-19

Global stability of COVID-19 model involving the quarantine strategy and media coverage effects

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