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Model NameMethods Intervention AssumptionsModeling GroupLinkMisc.
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GT_CHHSABMThis model assumes that once stay-at-home orders are lifted, contact rates will gradually increase. It also assumes that households containing symptomatic cases will self-quarantine.Georgia Institute of Technology, Center for Health and Humanitarian Systems https://github.com/pkeskinocak/COVID19GAGeorgia forecasts only; For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/GT_CHHS-COVID19/metadata-GT_CHHS-COVID19.txt
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NotreDame-FREDABMThese projections assume that current interventions will not change during the forecasted period.Notre Dame Universityhttps://github.com/confunguido/covid19_ND_forecastingState-level forecasts only; For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/NotreDame-FRED/metadata-NotreDame-FRED.txt
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CDDEPABMCenter for Disease Dynamics, Economics & Policyhttps://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/CDDEP-GlobalAgentBasedModel/metadata-CDDEP-GlobalAgentBasedModel.txt
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MultiagentsABMQuantori modelinghttps://github.com/reichlab/covid19-forecast-hub/tree/master/data-processed/Quantori-MultiagentsFor more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/Quantori-Multiagents/metadata-Quantori-Multiagents.txt
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Imperialstochastic compartmental models & ABMsThese projections do not make specific assumptions about which interventions have been implemented or will remain in place.Imperial Collegehttps://mrc-ide.github.io/covid19-short-term-forecasts/index.htmlMore on methods: ensembles of mechanistic transmission models, fit to different parameter assumptions; national-level forecasts only; see also: https://www.nature.com/articles/d41586-020-01003-6; for even more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/Imperial-ensemble2/metadata-Imperial-ensemble2.txt
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AuquanSEIRThese projections do not make specific assumptions about which interventions have been implemented or will remain in place.Auquan Data Sciencehttps://covid19-infection-model.auquan.com/For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/Auquan-SEIR/metadata-Auquan-SEIR.txt
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ColumbiaMetapopulation SEIR This model assumes that contact rates will increase 5% per week over the next two weeks. The reproductive number is then set to 1 for the remainder of the projection period.Columbia Universityhttps://blogs.cuit.columbia.edu/jls106/publications/covid-19-findings-simulations/For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/CU-select/metadata-CU-select.txt
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CANSEIRThis model assumes that the effects of current interventions are reflected in the observed data and that those effects will continue going forward.COVID Act Now https://covidactnow.org/State-level forecasts only
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Covid19SimSEIRThis model is based on assumptions about how levels of social distancing will change in the future. It assumes a 20% increase in mobility as each state reopens.COVID-19 Simulator Consortiumhttps://www.covid19sim.org/For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/Covid19Sim-Simulator/metadata-Covid19Sim-Simulator.txt
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CovidScenarioPipelinestochastic metapopulation SEIRThis model assumes that the effectiveness of interventions is reduced after shelter-in-place orders are lifted.Johns Hopkins University, Infectious Disease Dynamics Labhttps://github.com/HopkinsIDD/COVIDScenarioPipelineFor more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/JHU_IDD-CovidSP/metadata-JHU_IDD-CovidSP.txt
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LSHTMage-structured SEIRThese projections assume that current interventions will not change during the forecasted period.London School of Hygiene and Tropical Medicine (LSHTM), Centre for the Mathematical Modeling of Infectious Diseases (CMMID)https://github.com/epiforecasts/covid-us-forecastsMethods specifically = renewal equation, using estimates of the time-varying reproductive number.See also: https://github.com/epiforecasts/covid-us-deaths and https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667%2820%2930073-6/fulltext and https://github.com/epiforecasts/covid-us-forecasts. For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/epiforecasts-ensemble1/metadata-epiforecasts-ensemble1.txt
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MITSEIRThe projections assume that current interventions will remain in place indefinitely.MIThttps://www.covidanalytics.io/projectionsFor more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/MIT_CovidAnalytics-DELPHI/metadata-MIT_CovidAnalytics-DELPHI.txt
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MOBS metapopulation, age-structured SLIRThe projections assume that social distancing policies in place at the date of calibration are extended for the future weeks.Northeastern University (Laboratory for the Modeling of Biological and Socio-technical Systems)https://covid19.gleamproject.org/See also: https://www.mobs-lab.org/; For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/MOBS_NEU-GLEAM_COVID/metadata-MOBS_NEU-GLEAM_COVID.txt
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NotreDame-mobilitySEIR-likeNotre Dame Universityhttps://github.com/TAlexPerkins/covid19_NDmobility_forecastingThis is an ensemble of nine models that are identical except that they are driven by different mobility indices from Apple and Google. The model underlying each is a deterministic, SEIR-like model. For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/NotreDame-mobility/metadata-NotreDame-mobility.txt
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NavigatorSEIRThese projections assume that current interventions, will remain unchanged during the forecasted period.Pandemic Navigator (aka Oliver Wyman)https://pandemicnavigator.oliverwyman.com/For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/OliverWyman-Navigator/metadata-OliverWyman-Navigator.txt
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PSIstochastic SEIRXThese projections assume that current interventions will not change during the forecasted period.Predictive Science Inc. https://github.com/predsci/DRAFT
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SWCBayesian SEIRThese projections do not make specific assumptions about which interventions have been implemented or will remain in place.Snyder Wilson Consultinghttps://github.com/tsnyder701/terminus
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ERDCSEIR mechanisticThese projections assume that current interventions will not change during the forecasted period.US Army Engineer Research and Development Centerhttps://github.com/erdc-cv19/covid19-forecast-hubFor more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/USACE-ERDC_SEIR/metadata-USACE-ERDC_SEIR.txt
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UA-EpiCovDASIR mechanistic with data assimilationThis model assumes that current interventions will remain in effect for at least four weeks after the forecasts are made.University of Arizonahttps://jocelinelega.github.io/EpiGro/For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/UA-EpiCovDA/metadata-UA-EpiCovDA.txt
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SuEIRmodified SEIRThese projections assume that current interventions will not change during the forecasted period.UCLAhttps://covid19.uclaml.org/For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/UCLA-SuEIR/metadata-UCLA-SuEIR.txt
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UMASS-MBBayesian SEIRD These projections do not make specific assumptions about which interventions have been implemented or will remain in place.University of Massachusetts, Amhersthttps://reichlab.io/For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/UMass-MechBayes/metadata-UMass-MechBayes.txt
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ParamSearchSEIS mechanisticThe model accounts for individual state-by-state re-openings and their impact on infections and deaths.Youyang Gu (YYG) https://covid19-projections.com/about/For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/YYG-ParamSearch/metadata-YYG-ParamSearch.txt
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UTSEIR and curve-fittingThis model estimates the extent of social distancing using geolocation data from mobile phones and assumes that the extent of social distancing will not change during the period of forecasting. The model is designed to predict confirmed COVID-19 deaths resulting from only a single wave of transmission.Univeristy of Austin COVID-19 Consortiumhttps://covid-19.tacc.utexas.edu/projections/More specificially nonlinear Bayesian hierarchical regression with a negative-binomial model for daily variation in death rates. For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/UT-Mobility/metadata-UT-Mobility.txt
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ISUandPKUExtended varying coefficient SEIRCollaborative team of Iowa State and Peking Universityhttps://yumouqiu.shinyapps.io/covid-predict/For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/ISUandPKU-vSEIdR/metadata-ISUandPKU-vSEIdR.txt
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TerminusCMmechanistic compartmental Snyder Wilson Consultinghttps://github.com/reichlab/covid19-forecast-hub/tree/master/data-processed/SWC-TerminusCMFor more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/SWC-TerminusCM/metadata-SWC-TerminusCM.txt
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DRAFTSEIRXPredictive Science Inchttps://github.com/reichlab/covid19-forecast-hub/tree/master/data-processed/PSI-DRAFTFor more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/PSI-DRAFT/metadata-PSI-DRAFT.txt
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CovidILage-structured SEIRUniversity of Chicagohttps://github.com/cobeylab/covid_ILFor more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/UChicago-CovidIL/metadata-UChicago-CovidIL.txt
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CHIMEmodified SIRPenn Medicine (Predictive Healthcare)https://penn-chime.phl.io/See also: https://github.com/pennsignals/chime_sims
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COVID-19 ScenariosSIRSee: https://covid19-scenarios.org/aboutUniversity of Baselhttps://covid19-scenarios.org/See also: https://github.com/neherlab/covid19_scenarios
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GT-DeepCOVIDDeep learningThis model assumes that the effects of interventions are reflected in the observed data and will continue going forward.Georgia Institute of Technology, College of Computinghttps://www.cc.gatech.edu/~badityap/covid.htmlFor more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/GT-DeepCOVID/metadata-GT-DeepCOVID.txt
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IHMEcombination of a mechanistic disease transmission model and a curve-fitting approachProjections are adjusted to reflect differences in aggregate population mobility and community mitigation policies.Institute of Health Metrics and Evaluationhttps://covid19.healthdata.org/united-states-of-americaFor more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/IHME-CurveFit/metadata-IHME-CurveFit.txt
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STEMnonparametric spatiotemporalThe projections assume that the data used is reliable, the future will continue to follow the current pattern, and current interventions will remain the same till the end of forecasting period.Iowa State - Lily Wang's Research Grouphttps://covid19.stat.iastate.eduFor more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/IowaStateLW-STEM/metadata-IowaStateLW-STEM.txt
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GrowthRatestatistical dynamical growth model accounting for population susceptibilityThis model assumes that currently implemented interventions and corresponding reductions in transmission will continue, resulting in an overall decrease in the growth rate of COVID-19 deaths.Los Alamos National Labshttps://covid-19.bsvgateway.org/For more on methods and inputs see: https://github.com/reichlab/covid19-forecast-hub/blob/master/data-processed/LANL-GrowthRate/metadata-LANL-GrowthRate.txt
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Genevaexponential and linear statistical models fit to the recent growth rate of cumulative deathsThe projections assume that social distancing policies in place at the date of calibration are extended for the future weeks.University of Geneva / Swiss Data Science Centerhttps://renkulab.shinyapps.io/COVID-19-Epidemic-Forecasting/Nation one-week ahead forecasts only
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