team_name: IEM Health
model_name: CovidProjections
model_abbr: IEM_Health-CovidProject
model_contributors: Brad Suchoski (IEM) <bradley.suchoski@iem.com>, Steve Stage (IEM) <steve.stage@iem.com>,
  Heidi Gurung (IEM) <heidi.gurung@iem.com>, Sid Baccam (IEM) <sid.baccam@iem.com> 
website_url: https://iem-modeling.com/ 
license: cc-by-4.0
team_model_designation: primary
methods: SEIR model projections for daily incident confirmed COVID cases and deaths by using AI to fit actual cases observed.
data_inputs: JHU reported daily confirmed cases and deaths
methods_long: "IEM is currently using an AI model to fit data from various sources \
  \ and project new cases of COVID-19. We do not assume the average number of secondary \
  \ infections (R-value) stays the same over time. Our model makes projections for \
  \ over 375 individual counties in the U.S., all 50 states, the District of Columbia, \
  \ 3 U.S. territories, and 32 European countries. For each jurisdiction, our model runs 4 million simulations \
  \ to find the best R value that would allow the SEIR model to fit the data for confirmed \
  \ cases. Our model assumes that the R value changes quite rapidly over time due to changes \
  \ in human behavior. Our model uses a sliding window to fit the data and find the best \
  \ R values for each of the windows."