Model: University of California Merced MESA Lab - UCM_MESALab-FoGSEIR

    Name: Fractional order Generalized SEIR model
    Abbreviation: UCM_MESALab-FoGSEIR
    Owner: covid19hub
    Team name: University of California Merced MESA Lab
    Description: FoGSEIR model is a modification of integer order SEIR model considering fractional integrals. The model considers the age structure and reopening intervention to minimize infections and deaths.
    Contributors: YangQuan Chen (Department of Engineering, University of California, Merced) <ychen53@ucmerced.edu> Yanting Zhao (Department of Automation, University of Science and Technology of China) <zyt9lsb@mail.ustc.edu.cn> Lihong Guo (Institute of Mathematics, Jilin University) <guolh17@mails.jlu.edu.cn>
    License: Creative Commons Attribution 4.0
    Notes: primary
    Citation: Missing
    Methods: The fractional order generalized SEIR model considers the power law functions of infection cases, as well as the recovery and death. It is necessary to introduce the fractional integral with long memory property based on the integer order SEIR model. Through the time-weighted performance index (ITSE) of the model fitting and parameter sensitivity analysis of the model using Simulink Design Optimization (SLDO), it is proved that the fractional order model is superior to the integer order model in terms of short-term prediction. In our model, the more accurate prediction errors of incident death and cumulative death are provided. Based on this model, we can also study the optimization control problem. By studying mobility data, the lock-down and release policies of different countries, states and counties are changed accordingly. Control infection rates to reduce cumulative infections and deaths effectively. The model can not only fit the prediction of infection cases, but also achieve a balance between the scale of infection and the socioeconomic status by developing age-based re-open intervention through the study of social mobility.
    Home: http://mechatronics.ucmerced.edu/covid19
    Auxiliary data: Missing

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