Model: COVID Alliance at MIT - MITCovAlliance-SIR

    Name: Two-Stage SIR
    Abbreviation: MITCovAlliance-SIR
    Owner: covid19hub
    Team name: COVID Alliance at MIT
    Description: SIR model trained on public heath regions. SIR parameters are functions of static demographic and time-varying mobility features. Two-stage approach that first learns magnitude of peak infections.
    Contributors: Jackie Baek (MIT) <baek@mit.edu>, Vivek Farias (MIT) <vivekf@mit.edu>, Andreea Georgescu (MIT) <andreeag@mit.edu>, Retsef Levi (MIT) <retsef@mit.edu>, Deeksha Sinha (MIT) <deeksha.sinha7@gmail.com>, Josh Wilde (MIT) <josh.t.wilde@gmail.com>, Andy Zheng (MIT) <atz@mit.edu>
    License: Creative Commons Attribution 4.0
    Notes: primary
    Citation: https://arxiv.org/abs/2006.06373
    Methods: A SIR model trained at the public heath region level. SIR parameters are functions of over 60 static demographic features and time-varying dynamic features that measure changes in mobility patterns. This model proposes a two stage approach to overcome the inherent difficulty in learning the magnitude of the peak infection rate. The first stage treats the total susceptible population as an unknown parameter and learns this parameter for regions that have not yet seen a peak in cumulative infections. The second stage fits a typical SIR model with time and location varying contact parameters.
    Home: http://infectiontrajectory.covidalliance.com/
    Auxiliary data: Missing

    Forecasts (24)

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    2021-04-19 2021-04-19-MITCovAlliance-SIR.csv 2021-04-20 00:32:59 UTC 2021-04-19 12:00:00 UTC
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