ArticleApplied mathematical modelling2021
Fractional model for the spread of COVID-19 subject to government intervention and public perception.
Article in Applied mathematical modelling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- On the optimal presence strategies for workplace during pandemics: A COVID-19 inspired probabilistic model.PloS one · 2023Article
- Global stability and analysing the sensitivity of parameters of a multiple-susceptible population model of SARS-CoV-2 emphasising vaccination drive.Mathematics and computers in simulation · 2023Article
- Defining factors in hospital admissions during COVID-19 using LSTM-FCA explainable model.Artificial intelligence in medicine · 2022Article
- On fractal-fractional Covid-19 mathematical model.Chaos, solitons, and fractals · 2022Article
- Stability Analysis of an Extended SEIR COVID-19 Fractional Model with Vaccination Efficiency.Computational and mathematical methods in medicine · 2022Article
- Influencing factors for public risk perception of COVID-19 --perspective of the pandemic whole life cycle.International journal of disaster risk reduction : IJDRR · 2022Article
- Analysis of Delayed Vaccination Regimens: A Mathematical Modeling Approach.Epidemiologia (Basel, Switzerland) · 2021Article
- On study of fractional order epidemic model of COVID-19 under non-singular Mittag-Leffler kernel.Results in physics · 2021Article
- Analysis of Key Factors of a SARS-CoV-2 Vaccination Program: A Mathematical Modeling Approach.Epidemiologia (Basel, Switzerland) · 2021Article
- Stability and Hopf Bifurcation Analysis of an Epidemic Model with Time Delay.Computational and mathematical methods in medicine · 2021Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
COVID-19 pandemic has impacted people all across the world. As a result, there has been a collective effort to monitor, predict, and control the spread of this disease. Among this effort is the development of mathematical models that could capture accurately the available data and simulate closely the futuristic scenarios. In this paper, a fractional-order memory-dependent model for simulating the spread of COVID-19 is proposed. In this model, the impact of governmental interventions and public perception are incorporated as part of the nonlinear time-varying transmission rate. In addition, an algorithm for approximating the optimal values of the fractional order and strength of governmental interventions is provided. This approach makes our model suitable for capturing the given data set and consequently reliable for future predictions. The model simulation is performed using the two-step generalized exponential time-differencing method and tested for data from Mainland China, Italy, Saudi Arabia and Brazil. The simulation results demonstrate that the fractional order model calibrates to the data better than its integer order counterpart. This observation is further endorsed by the calculated error metrics.
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