team_name: CovidAnalytics at MIT
model_name: DELPHI
model_abbr: MIT_CovidAnalytics-DELPHI
model_contributors:
  - name: Michael Lingzhi Li
  - name: Hamza Tazi Bouardi
  - name: Dimitris Bertsimas
website_url: https://www.covidanalytics.io/
repo_url: https://github.com/COVIDAnalytics/DELPHI
license: apache-2.0
team_model_designation: primary
data_inputs: JHU, New York Times
methods: This model makes predictions for future cases based on a heavily modified
  SEIR model taking into account underdetection and government intervention. Current
  interventions are assumed to continue.
methods_long: This model makes predictions for future cases based on a heavily modified
  SEIR model. New states are added to the SEIR model to account for cases that went
  undetected, and an explicit death state is included. The infection rate is corrected
  with a nonlinear curve that represents the governmental and societal response (which
  is assumed) to continue until the end of the pandemic). Key parameters for the disease
  are fixed using a metanalysis conducted by the CovidAnalytics group of over 150
  parameters while epidemiological parameters are fitted to hisorical death counts
  and detected cases.
citation: https://www.covidanalytics.io/DELPHI_documentation_pdf