#15,365
The CDC's hospitalization forecasts - which they began publishing in late May - utilize far fewer models than their cumulative death estimates, are less `mature', and have yielded a much wider range of forecast outcomes.
For most of June, the models predicted between 1,000 to 15,000 new hospitalizations per day 4 weeks into the future. A 15-fold difference. Last week the numbers consolidated a bit, and ranged between 2,000 and 10,000 in month's time.
These forecasts rely on a ensemble of models, each of which takes a different approach. Over time, it is hoped that one or more of these models will prove reliable. For now, we have to take these model runs with a large grain of salt.
This week, the models remain highly divergent, with 3 predicting stable numbers while 3 others predict substantial increases. Overall, the forecast has shifted markedly higher four weeks hence (August 10th), with the `low' estimate raised from 2,000 to 4,500 while the `high' estimate has jumped from 10,000 to 13,000.
Despite these continued wide variances, this 3-fold difference is the `tightest' these models have been since their inception.
While I don't put a lot of faith in the actual numbers produced by these models, they can be useful in forecasting general trends. And right now, that trend for August is not encouraging.
Hospitalization Forecasts
Updated July 15, 2020
Interpretation of Forecasts of New Hospitalizations
- This week, three national forecasts suggest an increase in the number of new hospitalizations per day over the next four weeks, while three other forecasts predict stable numbers or slight declines. On August 10, the forecasts estimate 4,500 to 13,000 new COVID-19 hospitalizations per day.
- State-level forecasts also show a high degree of variability, which results from multiple factors. Hospitalization forecasts use different sources of data for COVID-19 cases or deaths, with different limitations, and make different assumptions about social distancing.
National Forecasts
- The six national forecasts show the predicted number of new COVID-19 hospitalizations per day for the next four weeks in the United States.
- The forecasts make different assumptions about hospitalization rates and levels of social distancing and other interventions and use different methods to estimate the number of new hospitalizations. See models below for details.
State Forecasts
Seven state-level models predicting the number of new hospitalizations were submitted this week. These forecasts show the predicted number of new COVID-19 hospitalizations per day for the next four weeks in each state. Each state forecast uses a different scale, due to differences in the number of new COVID-19 cases occurring per day in each state.
Forecast Assumptions
These forecasts make different assumptions about social distancing measures and use different methods and data sets to estimate the number of new hospitalizations. Individual models are described in more detail below.
Social distancing is incorporated into the forecasts in two different ways:
- The national and state-level forecasts from Columbia University, the COVID-19 Simulator Consortium, and the Johns Hopkins University Infectious Disease Dynamics Lab (JHU) make assumptions about how levels of social distancing will change in the future.
- The national and state-level forecasts from the Georgia Institute of Technology, College of Computing, the US Army Engineer Research and Development Center (ERDC), and the University of California, Los Angeles (UCLA), and state-level forecasts from the Los Alamos National Laboratory (LANL) assume that existing social distancing measures in each state will continue through the projected four-week time period.
The rate of new hospitalizations is estimated using two approaches:
- The forecasts from Columbia University, the COVID-19 Simulator Consortium, ERDC, JHU, LANL, and UCLA assume that a certain fraction of infected people will be hospitalized.
- The forecast from the Georgia Institute of Technology, College of Computing, uses COVID-19 hospitalization data reported by some states to forecast future hospitalizations.
