Model: Columbia University - CU-scenario_high

    Name: scenario_high
    Abbreviation: CU-scenario_high
    Owner: covid19hub
    Team name: Columbia University
    Description: We produce different intervention scenarios, assuming various interventions and rates of compliance are implemented in the future. This projection assumes relatively high transmission.
    Contributors: Sen Pei, Teresa Yamana, Sasikiran Kandula, Wan Yang, Marta Galanti, Jeffrey Shaman <jls106@cumc.columbia.edu>
    License: Apache license 2.0
    Notes: other
    Citation: https://doi.org/10.1101/2020.03.21.20040303
    Methods: This metapopulation county-level SEIR model makes projections of future COVID-19 incidence and deaths. We produce a number of different intervention scenarios, each assuming various interventions and rates of compliance are implemented in the future. November 8 - present: 'season4': This scenario assumes seasonal changes to R(t). In the summer months, it assumed a seasonal decrease in disease transmission leading to a weekly 4% decrease in reproductive number R(t). In the winter, it assumes a weekly 2% increase in reproductive number R(t). October 4 - November 5: '5_2xhold' This scenario assumes a weekly 5% increase in contact rates for two weeks. The following week, the reproduction number R is set to 1 for the remainder of the projection. August 23 - September 27:'1x5p' We project a one-time 5% increase in contact rates due to loosening restrictions as states continue to reopen economically, applied at the beginning of the projection. July18 - August 22: '5_2xhold' This scenario assumes a weekly 5% increase in contact rates for two weeks. The following week, the reproduction number R is set to 1 for the remainder of the projection. June 14 - July 18: '1x5p' We project a one-time 5% increase in contact rates due to loosening restrictions as states continue to reopen economically, applied at the beginning of the projection. May 3 - June 7: '80contact1x10p' For states maintaining or increasing current social distancing restrictions, we apply a 20% weekly reductions of contact rates, as described above. However, in states that reopen, we apply an increase to the contact rates of counties in those states. In the first scenario, we apply a one-time 10% increase to the contact rates during the week that the state is scheduled to reopen and maintain these new increased rates for the remainder of the projection. April 12 - April 26: '80contact' This scenario mimics adaptive adjustments in contact imposed both by government regulations (e.g. school closures, restrictions on mass gatherings) and population self-regulation (e.g. isolation, mask wearing, social distancing). Upon initiation of projections, all counties with 10 or more confirmed cases impose a 20% contact rate reduction. Each week following, if a county newly exceeds 10 confirmed cases, a 20% contact rate reduction is imposed, depending on the projection scenario. Counties that had previously exceeded 10 confirmed cases and also experience an increase in the number of weekly reported confirmed cases impose a further, multiplicative 20% contact rate reduction, depending on the projection scenario.
    Home: https://blogs.cuit.columbia.edu/jls106/publications/covid-19-findings-simulations/
    Auxiliary data: https://github.com/shaman-lab/COVID-19Projection

    Forecasts (95)

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    2020-11-08 2020-11-08-CU-scenario_high.csv 2020-11-11 21:36:40 UTC 2020-11-11 12:00:00 UTC
    2020-11-05 2020-11-05-CU-scenario_high.csv 2020-11-11 21:33:45 UTC 2020-11-11 12:00:00 UTC
    2020-11-12 2020-11-12-CU-scenario_high.csv 2020-11-15 18:32:21 UTC 2020-11-15 12:00:00 UTC
    2020-11-15 2020-11-15-CU-scenario_high.csv 2020-11-17 06:42:31 UTC 2020-11-17 12:00:00 UTC
    2020-11-17 (No data)
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    2020-11-22 2020-11-22-CU-scenario_high.csv 2020-11-24 00:54:37 UTC 2020-11-23 12:00:00 UTC
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    2020-12-03 2020-12-03-CU-scenario_high.csv 2020-12-08 06:53:34 UTC 2020-12-08 12:00:00 UTC
    2020-12-06 2020-12-06-CU-scenario_high.csv 2020-12-08 06:50:31 UTC 2020-12-08 12:00:00 UTC
    2020-12-05 (No data)
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    2020-12-10 2020-12-10-CU-scenario_high.csv 2020-12-13 00:32:46 UTC 2020-12-12 12:00:00 UTC
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    2020-12-20 2020-12-20-CU-scenario_high.csv 2020-12-22 17:04:06 UTC 2020-12-22 12:00:00 UTC
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    2020-12-24 2020-12-24-CU-scenario_high.csv 2020-12-26 06:30:45 UTC 2020-12-26 12:00:00 UTC
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    2020-12-27 2020-12-27-CU-scenario_high.csv 2020-12-29 07:08:54 UTC 2020-12-29 12:00:00 UTC
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    2021-01-10 2021-01-10-CU-scenario_high.csv 2021-01-12 02:09:40 UTC 2021-01-11 12:00:00 UTC
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    2021-01-17 2021-01-17-CU-scenario_high.csv 2021-01-19 07:10:57 UTC 2021-01-19 12:00:00 UTC
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    2021-01-24 2021-01-24-CU-scenario_high.csv 2021-01-26 13:05:26 UTC 2021-01-26 12:00:00 UTC
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    2021-01-31 2021-01-31-CU-scenario_high.csv 2021-02-02 00:59:39 UTC 2021-02-01 12:00:00 UTC
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    2021-02-07 2021-02-07-CU-scenario_high.csv 2021-02-09 01:16:43 UTC 2021-02-08 12:00:00 UTC
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    2021-02-14 2021-02-14-CU-scenario_high.csv 2021-02-16 01:05:48 UTC 2021-02-15 12:00:00 UTC
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    2021-02-21 2021-02-21-CU-scenario_high.csv 2021-02-23 01:30:36 UTC 2021-02-22 12:00:00 UTC
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    2021-02-28 2021-02-28-CU-scenario_high.csv 2021-03-02 01:46:02 UTC 2021-03-01 12:00:00 UTC
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    2021-03-07 2021-03-07-CU-scenario_high.csv 2021-03-09 01:34:07 UTC 2021-03-08 12:00:00 UTC
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    2021-03-14 2021-03-14-CU-scenario_high.csv 2021-03-16 02:38:53 UTC 2021-03-15 12:00:00 UTC
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    2021-03-21 2021-03-21-CU-scenario_high.csv 2021-03-23 01:32:16 UTC 2021-03-22 12:00:00 UTC
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    2021-03-28 2021-03-28-CU-scenario_high.csv 2021-03-30 00:36:22 UTC 2021-03-29 12:00:00 UTC
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    2021-04-04 2021-04-04-CU-scenario_high.csv 2021-04-06 00:42:18 UTC 2021-04-05 12:00:00 UTC
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    2021-04-11 2021-04-11-CU-scenario_high.csv 2021-04-13 00:31:29 UTC 2021-04-12 12:00:00 UTC
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    2021-04-18 2021-04-18-CU-scenario_high.csv 2021-04-20 01:15:50 UTC 2021-04-19 12:00:00 UTC
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    2021-05-09 2021-05-09-CU-scenario_high.csv 2021-05-11 01:04:32 UTC 2021-05-10 12:00:00 UTC
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    2021-05-23 2021-05-23-CU-scenario_high.csv 2021-05-25 18:31:29 UTC 2021-05-25 18:31:29 UTC
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