Predicting the dynamical behavior of COVID-19 epidemic and the effect of control strategies

Shakhany, Mohammad Qaleh; Salimifard, Khodakaram

doi:10.1016/j.chaos.2021.110823

Cited by 19 publications

(5 citation statements)

References 63 publications

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“…With the work of Kermack and McKendrick [ 13 ], mathematical models have since been used to provide framework for understanding the dynamics of infectious diseases. COVID-19 transmission dynamics models are flourishing and abound in the literature [ 14 – 19 ], to cite a few and the references therein. With the availability of COVID-19 vaccine and its known high efficacy, there is an urgent need to assess the impact of such vaccines with imperfect transmission-blocking effects [ 6 ] and potentially refine previous mathematical models of COVID-19 that incorporated the potential impact of an imperfect vaccine [ 2 , 8 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

A Mathematical Model of COVID-19 with Vaccination and Treatment

Diagne

Rwezaura

Tchoumi

et al. 2021

Computational and Mathematical Methods in Medicine

101

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We formulate and theoretically analyze a mathematical model of COVID-19 transmission mechanism incorporating vital dynamics of the disease and two key therapeutic measures—vaccination of susceptible individuals and recovery/treatment of infected individuals. Both the disease-free and endemic equilibrium are globally asymptotically stable when the effective reproduction number R 0 v is, respectively, less or greater than unity. The derived critical vaccination threshold is dependent on the vaccine efficacy for disease eradication whenever R 0 v > 1 , even if vaccine coverage is high. Pontryagin’s maximum principle is applied to establish the existence of the optimal control problem and to derive the necessary conditions to optimally mitigate the spread of the disease. The model is fitted with cumulative daily Senegal data, with a basic reproduction number R 0 = 1.31 at the onset of the epidemic. Simulation results suggest that despite the effectiveness of COVID-19 vaccination and treatment to mitigate the spread of COVID-19, when R 0 v > 1 , additional efforts such as nonpharmaceutical public health interventions should continue to be implemented. Using partial rank correlation coefficients and Latin hypercube sampling, sensitivity analysis is carried out to determine the relative importance of model parameters to disease transmission. Results shown graphically could help to inform the process of prioritizing public health intervention measures to be implemented and which model parameter to focus on in order to mitigate the spread of the disease. The effective contact rate b , the vaccine efficacy ε , the vaccination rate v , the fraction of exposed individuals who develop symptoms, and, respectively, the exit rates from the exposed and the asymptomatic classes σ and ϕ are the most impactful parameters.

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Section: Introductionmentioning

confidence: 99%

A Mathematical Model of COVID-19 with Vaccination and Treatment

Diagne

Rwezaura

Tchoumi

et al. 2021

Computational and Mathematical Methods in Medicine

101

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“… Parameter Meanings Baseline value Reference Λ Net inflow of susceptibles 242 Assumed β Transmission rate 0. 468 · 10 −4 [44] γ Fraction of exposed class who become infective 0.1818 [45] k Factor of vaccine ineffectiveness 0.05 Estimated λ Rate of the information-dependent vaccination 0.2 [36] ε Recovery rate for infected individual 0.278 [46] g Limited extent of the global information influence on the susceptible individuals 0.5 [36] θ Fraction of individuals who are vaccinated 0.011 [32] ρ Rate of losing vaccine immunity 0.005 Estimated d Natural death rate 1.07 · 10 −2 [47] T the average information delays 30 Estimated a Fraction of information coverage 0.8 [48] B the sensitivity of vaccinating behavior to changes in prevalence 0.1 Estimated μ Decay rate of information due to the decreasing quality of the information 1/3 [48] …”

Section: Methodsmentioning

confidence: 99%

Exploring epidemic voluntary vaccinating behavior based on information-driven decisions and benefit-cost analysis

Zuo

Ling

Zhu³

et al. 2023

Applied Mathematics and Computation

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“…Using mathematical formulations to model the transmission of infectious diseases like COVID-19 is a well-established approach to analysing individuals and their infections in communities. Several studies have been published examining the dynamics of the COVID-19 epidemic worldwide [14] , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [30] , [32] , [35] , [36] , [37] , [38] , [39] , [41] , [42] , [43] , [44] , [45] , [46] , [47] , [48] , [49] , [50] , [52] , [53] , [54] , [55] , [57] , [58] , [59] , [60] , [61] , [62] , [63] , [64] , [65] , [66] , [67] , [68] , [69] , [70] , [71] , [72] , [73] , [74] , [75] , [76] , [77] , [78] , [79] , [80] , [81] , [82] , [83] . Vaccination’s impact on the spread of COVID-19 has been the subject of several articles [40] , [51] .…”

Section: Introductionmentioning

confidence: 99%