California has substantially more healthcare capacity than necessary to manage the pandemic under the stay at home order.
I have updated Model 3.0 to Model 3.1.
- Daily new confirmed cases will peak in the State data from April 4th to April 6th.
- Hospitalizations will peak between April 6th and April 11th. From that point forward, the curve will be flat or bent. This is the critical timeline for assessing the effectiveness of the stay at home order.
- The State will need a total of 4300 hospital beds to manage the peak.
- Fatalities will peak between April 21st and 26th.
My modeling shows that California will have substantial unused healthcare system capacity under the stay at home order.
I have updated the Model once again to address updates in the State’s reporting. Notably, the State quietly reported yesterday that it had substantially cleared its testing backlog. As I previously assumed in Models 1.0 and 3.0, the overwhelming majority of cases in the backlog were negative. This is clear from the fact that the number of confirmed new cases went down on the day the backlog was cleared. As a result of the reduction in the backlog, I was able to accurately estimate the typical lag between the date of a test and its reporting by the State. Right now, the lag appears to be 4 to 5 days. Accordingly, I simply re-calculated the lag built into my model to align it with the State’s reporting so that I am comparing predicted apples to actual apples.
The Models appear to be performing quite well.