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

Mohsen, Ahmed A.; Al-Husseiny, Hassan Fadhil; Zhou, Xueyong; Hattaf, Khalid

doi:10.3934/publichealth.2020047

Cited by 37 publications

(40 citation statements)

References 16 publications

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“…For the growth eigenvector, the ratios among the compartments determine an average overall . Multiple mode reproduction numbers in COVID-19 are also noted 26 , 27 . These numbers primarily drive the rate of growth of the infection in the population, which early in the expansion is measured by the doubling time.…”

Section: Methodsmentioning

confidence: 97%

Lies, Gosh Darn Lies, and not enough good statistics: why epidemic model parameter estimation fails

Platt

Parida

Zalloua

2021

Sci Rep

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We sought to investigate whether epidemiological parameters that define epidemic models could be determined from the epidemic trajectory of infections, recovery, and hospitalizations prior to peak, and also to evaluate the comparability of data between jurisdictions reporting their statistics. We found that, analytically, the pre-peak growth of an epidemic underdetermines the model variates, and that the rate limiting variables are dominated by the exponentially expanding eigenmode of their equations. The variates quickly converge to the ratio of eigenvector components of the positive growth mode, which determines the doubling time. Without a sound epidemiological study framework, measurements of infection rates and other parameters are highly corrupted by uneven testing rates, uneven counting, and under reporting of relevant values. We argue that structured experiments must be performed to estimate these parameters in order to perform genetic association studies, or to construct viable models accurately predicting critical quantities such as hospitalization loads.

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Section: Methodsmentioning

confidence: 97%

Lies, Gosh Darn Lies, and not enough good statistics: why epidemic model parameter estimation fails

Platt

Parida

Zalloua

2021

Sci Rep

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“…These conditions can be adapted to urban or country town cases in the implementation in real conditions. Below we describe these conditions in more details, where the first three constitute random processes and the fourth one just a set of given constant parameters [17,18,19]. In Fig.…”

Section: Simulation Methodologymentioning

confidence: 99%

Novel Approach for Monte Carlo Simulation of the new COVID-19 Spread Dynamics

Maltezos

Georgakopoulou

2020

Preprint

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A Monte Carlo simulation in a novel approach is used for studying the problem of the outbreak and spread dynamics of the new COVID-19 pandemic in this work. In particular, our goal was to generate epidemiological data based on natural mechanism of transmission of this disease assuming random interactions of a large-finite number of individuals in very short distance ranges. In the simulation we also take into account the stochastic character of the individuals in a finite population and given densities of people. On the other hand, we include in the simulation the appropriate statistical distributions for the parameters characterizing this disease. An important outcome of our work, besides the generated epidemic curves, is the methodology of determining of the effective reproductive number during the main part of the new daily cases of the epidemic. Since this quantity constitutes a fundamental parameter of the SIR-based epidemic models, we also studied how it is affected by small variations of the incubation time and the crucial distance distributions, and furthermore, by the degree of quarantine measures. In addition, we compare our qualitative results with those of selected real epidemiological data.

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“…So, media-induced fear has a negative effect on the disease reproduction rate. Recently, Mohsen et al [21] studied the global stability of a COVID-19 model with quarantine strategy and media coverage effects. According to Ahorsu et al [22], one unique feature of pandemic viral infections is the fear that they can instill across large swathes of the population.…”

Section: Introductionmentioning

confidence: 99%

Impact of Media-Induced Fear on the Control of COVID-19 Outbreak: A Mathematical Study

Maji

2021

International Journal of Differential Equations

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The COVID-19 pandemic has put the world in threat for a long time. It was first identified in Wuhan, China, in December 2019 and has been declared a pandemic by the WHO. This disease is mainly caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). So far, no vaccine or medicine has been developed for the proper treatment of this disease, so people are afraid of getting infected. The pandemic has placed many nations at the door of socioeconomic emergencies. Therefore, it is very important to predict the development trend of this epidemic, and we know mathematical modelling is a basic tool to research the dynamic behaviour of disease and predict the spreading trend of the disease. In this study, we have formulated a mathematical model for the COVID-19 outbreak by introducing a quarantine class with media-induced fear in the disease transmission rate to analyze the dynamic behaviour of this epidemic. We have calculated the basic reproduction number R0, and we observed that when R0 < 1, disease-free equilibrium is globally stable whereas if R0> 1, then the system is permanent and there exists a unique endemic equilibrium point. Global stability of the endemic equilibrium point is developed by using Li and Muldowney’s high-dimensional Bendixson criterion. Finally, some numerical simulations are performed using MATLAB to verify our analytical results.

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

Cited by 37 publications

References 16 publications

Lies, Gosh Darn Lies, and not enough good statistics: why epidemic model parameter estimation fails

Lies, Gosh Darn Lies, and not enough good statistics: why epidemic model parameter estimation fails

Novel Approach for Monte Carlo Simulation of the new COVID-19 Spread Dynamics

Impact of Media-Induced Fear on the Control of COVID-19 Outbreak: A Mathematical Study

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