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).
California’s COVID-19 Hospitalizations Continue to Decrease as Predicted
April 5, 2020
Finally, someone with a clue. Sadly, the lemmings don’t believe in science or reason.
April 6, 2020
Thank you for doing this – I’m visiting your site daily and have been recommending it to others. Glad to see you are being recognized and appreciated on reddit. (r/coronavirus)
April 6, 2020
Thank you very much. I am glad you find it helpful and the community as well.