Model name: Auquan Intervention assumptions: These projections do not make specific assumptions about which interventions have been implemented or will remain in place. Methods: Fitted SEIR model Forecasts submitted: Deaths
Model name: Yu_Group Intervention assumptions: This model assumes that the effects of interventions are reflected in the observed data and will continue going forward. Methods: Ensemble of combined linear and exponential predictors (CLEP) Forecasts submitted: Cases
Model name: BPagano Intervention assumptions: These projections assume that the effects of interventions are reflected in the observed data and will continue going forward. Methods: SIR model Forecasts submitted: Deaths
Model name: CMU Intervention Assumptions: These projections do not make specific assumptions about which interventions have been implemented or will remain in place. Methods: Autoregressive time-series model Forecasts submitted: Cases, deaths
Model name: CDDEP Intervention Assumptions: This model assumes that the effects of interventions are reflected in the observed data and will continue going forward. Methods: Bayesian SEIR model Forecasts submitted: Cases
Model name: Columbia Intervention assumptions: This model assumes that contact rates will increase 5% during the first week of the forecast period. Following week 1, the reproductive number is then set to 1.0. Hospitalization assumptions: The model uses state-specific hospitalization data, when available. In states without hospitalization data, the model uses the national average value for hospitalization data. Methods: Metapopulation SEIR model Forecasts submitted: Cases, hospitalizations, deaths
Model name: Columbia-UNC Intervention assumptions: This model assumes that transmission intensity will peak in early July and then gradually decline. Methods: Statistical survival-convolutional model Forecasts submitted: Cases, deaths
Model name: Covid19Sim Intervention assumptions: This model is based on assumptions about how levels of social distancing will change in the future. Hospitalization assumptions: The number of new hospitalizations per day are estimated from the number of infections, using state-specific hospitalization rates. Methods: SEIR model Forecasts submitted: Cases, hospitalizations, deaths
Model name: CAN Intervention assumptions: These projections do not make any specific assumptions about which interventions have been implemented or will remain in place. Methods: Fitted SEIR model Forecasts submitted: Hospitalizations, deaths