A stochastic analysis for a triple delayed SIQR epidemic model with vaccination and elimination strategies

Fatini, Mohamed El; Pettersson, Roger; Sekkak, Idriss; Taki, Regragui

doi:10.1007/s12190-020-01380-1

Cited by 25 publications

(8 citation statements)

References 26 publications

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“…Several compartmental epidemiological models have been expanded to include quarantined individuals 9 – 12 . The classical approaches assume general homogeneous populations and equally probable interactions among people.…”

Section: Introductionmentioning

confidence: 99%

“…Compartmental models have been extended to include quarantined individuals [9][10][11][12]. Although time dependent parameters have been used to simulate people's mobility [13], most of the implementations do not include the actual geographical spread, assuming in general homogeneous populations and equally probable interactions among individuals.…”

Section: Introductionmentioning

confidence: 99%

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Detecting infected asymptomatic cases in a stochastic model for spread of Covid-19: the case of Argentina

Barreiro

Govezensky

Bolcatto

et al. 2021

Sci Rep

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We have studied the dynamic evolution of the Covid-19 pandemic in Argentina. The marked heterogeneity in population density and the very extensive geography of the country becomes a challenge itself. Standard compartment models fail when they are implemented in the Argentina case. We extended a previous successful model to describe the geographical spread of the AH1N1 influenza epidemic of 2009 in two essential ways: we added a stochastic local mobility mechanism, and we introduced a new compartment in order to take into account the isolation of infected asymptomatic detected people. Two fundamental parameters drive the dynamics: the time elapsed between contagious and isolation of infected individuals ($$\alpha$$ α ) and the ratio of people isolated over the total infected ones (p). The evolution is more sensitive to the $$p-$$ p - parameter. The model not only reproduces the real data but also predicts the second wave before the former vanishes. This effect is intrinsic of extensive countries with heterogeneous population density and interconnection.The model presented has proven to be a reliable predictor of the effects of public policies as, for instance, the unavoidable vaccination campaigns starting at present in the world an particularly in Argentina.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Detecting infected asymptomatic cases in a stochastic model for spread of Covid-19: the case of Argentina

Barreiro

Govezensky

Bolcatto

et al. 2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…If this statement is false, then there exists a pair of constants and such that Thus there is an integer such that Let and consider the -function as follows for a positive constant a . We note that is a nonnegative function verified from the fact that Then by the Dynkin formula [ 2 ], we obtain for all that where is given by Hence which implies that Choose such that , it yields where is the following positive number Substituting ( 10 ) into ( 9 ), we obtain Similar to the method developed in the study conducted by [ 1 , 9 ], we obtain which is a contradiction. So,we must have a.s. Consequently, s ( t ), u ( t ), q ( t ) and c ( t ) are positive and the solution of ( 2 ) is global.…”

Section: Existence and Uniqueness Of The Global Positive Solutionmentioning

confidence: 79%

Understanding death risks of Covid-19 under media awareness strategy: a stochastic approach

Taki

Fatini

Khalifi

et al. 2021

J Anal

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The coronavirus disease 2019 (COVID-19) is rapidly spreading in the world and the mortality rate is getting higher and higher. Due to the outbreak of such epidemic disease, many countries imposed stricter measures among which is social distancing and enforced isolation. The present study tries to establish a realistic model to characterize the dynamics of COVID-19 and explicitly parameterize the intervention effects of control measures. In so doing, it takes into account stochastic perturbation and investigates the effects of media coverage on the transmission dynamics. This paper seeks to study the existence and uniqueness of the global positive solution to the proposed model and establish conditions for extinction and persistence in mean of the disease. Numerical simulations are presented to show the theoretical results obtained from this study.

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“…In fact, the COVID-19 epidemic model is unavoidably subjected to the environmental noise, which made the parameters involved in the system often fluctuate randomly around some average values as the surrounding environment fluctuation. See [1] , [2] , [3] , [5] , [6] , [7] , [16] , [25] and references therein for epidemic models with environmental noise. Therefore, it is necessary to include random fluctuations in the process of COVID-19 modelling.…”

Section: Model and Preliminariesmentioning

confidence: 99%

Dynamics of a stochastic coronavirus (COVID-19) epidemic model with Markovian switching

Boukanjime

Caraballo

Fatini

et al. 2020

Chaos, Solitons & Fractals

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In this paper, we analyze a stochastic coronavirus (COVID-19) epidemic model which is perturbed by both white noise and telegraph noise incorporating general incidence rate. Firstly, we investigate the existence and uniqueness of a global positive solution. Then, we establish the stochastic threshold for the extinction and the persistence of the disease. The data from Indian states, are used to confirm the results established along this paper.

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A stochastic analysis for a triple delayed SIQR epidemic model with vaccination and elimination strategies

Cited by 25 publications

References 26 publications

Detecting infected asymptomatic cases in a stochastic model for spread of Covid-19: the case of Argentina

Detecting infected asymptomatic cases in a stochastic model for spread of Covid-19: the case of Argentina

Understanding death risks of Covid-19 under media awareness strategy: a stochastic approach

Dynamics of a stochastic coronavirus (COVID-19) epidemic model with Markovian switching

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