The chart below compares the predictions made in Models 1.0, 3.0, and 3.1 to the actual trajectory of the COVID-19 virus in California based on confirmed and suspected COVID-19 hospitalizations (i.e., bed count) as reported by the State at the end of each day.
Please note: The State began reporting this data on March 30th.
Conclusions as of April 16th:
- Model 1 was more accurate at predicting the required number of hospital beds, but it predicted the peak too late.
- Models 3.0 and 3.1 were much more accurate at predicting the arc of the curve, but they undercounted suspected hospitalizations (likely because the lag in clearing the test results for those patients is even greater than the lag built into the models).