Model: QJHong - QJHong-Encounter

    Name: Encounter
    Abbreviation: QJHong-Encounter
    Owner: covid19hub
    Team name: QJHong
    Description: today's "Daily New Confirmed Cases" + today's "Encounter Density" ==> today's newly infected Cases ==> next 2-3 weeks' "Daily New Confirmed Cases"
    Contributors: Qi-Jun Hong <qhong@alumni.caltech.edu>
    License: Creative Commons Attribution 4.0
    Notes: primary
    Citation: https://github.com/qjhong/covid19
    Methods: today's "Daily New Confirmed Cases" + today's "Encounter Density" ==> today's newly infected Cases ==> next 2-3 weeks' "Daily New Confirmed Cases" (Encounter Density D data source: Unacast's Social Distancing Scoreboard, which analyzes cell phone location data, counts "Human Encounters", defined as two cell phone devices that were in the same place at the same time, and then derives the probability and "Encounter Density".) My model uses current "Encounter Density" D to predict future "Reproductive Number" R and "Daily New Confirmed Cases". This is the most fundamental idea and assumption in this model. The strong correlation between R and D (D is shifted by 22 days) is evident. While social distancing quickly brought down R, easing policy is slowly increasing R back above 1. Using (1) R and D relation in the past as a training set, (2) future D as input, and (3) machine learning / regression, my model can predict future R, and ultimately future Daily New Cases.
    Home: https://qjhong.github.io
    Auxiliary data: https://github.com/qjhong/covid19

    Forecasts (27)

    Timezero Data Source Upload Time
    2019-12-30 (No data)
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    2020-06-24 2020-06-24-QJHong-Encounter.csv 2020-06-26 22:23:39 EDT
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    2020-06-30 2020-06-30-QJHong-Encounter.csv 2020-07-01 11:00:01 EDT
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