The model seems not far off estimating peak hospitalization date, at least for states that are currently peaking like CA and NY. The peaks in places that are close to peaking can be pretty accurately estimated just with curve fitting though, I assume that being fit to past data is why the model works OK for this.
It’s clearly overly optimistic about the rate of drop-off after the peak in deaths, at least in some cases. Look at Spain and Italy. Right now here’s how they look:
Italy: graph shows 610 deaths on April 9. Predicts 335 on April 10, 281 on April 11. Actual is 570 on April 10, 619 on April 11.
Spain: graph shows 683 on April 8, Predicts 372, 304, 262 on next three days. Actual 655, 634, 525.
The model for New York says deaths will be down to 48, 6% of the peak, in 15 days. Italy is 15 days from it’s peak of 919 and is only down to 619, 67% of the peak.
The model for the US as a whole is a little less obviously over-optimistic, assuming the peak really was April 10. it’s only predicting 40% decline in the next 15 days. California model predicts an even slower decline. It seems to think fast growth in cases in the outbreak phase leads to fast recovery, which has not been borne out thus far in Italy and Spain.
This increases my estimated odds of the federal government attempting to suppress positive test numbers via defunding and not collecting statistics.
Italy seems to me to have stalled in decreasing R at about R=0.9. China and South Korea both got down to R=0.5. I have a concern that the UK has stalled at about R=1.3 (25% confidence) but I suspect that a few days more data may disprove this.
The US appears to still be on a downwards trajectory (currently just above R=1) but where exactly it stops will make a huge difference to the final tally. If I were to be making a model then this is the main place where I would focus my attention to give reasonable confidence intervals.
We need a new model I think. The purpose of the IHME was to figure out how to allocate hospital resources at the peak. Now we are roughly at or past the peak and we need to figure out how to re-open and what calculated risks are worth taking to ensure that businesses don’t get devastated even more. Hopefully someone is working on it.
Below is a simplified COVID-19 framework:
Data acquiring ---> social engineering based on model ----> better result
Yes. A better model will be definitely helpful. However, (as pointed out indirectly earlier by someone else), to my best knowledge, there were no good and robust model for large lag dynamic systems. Such kind of model could lead to Chaos and random like result easily. Thus, I believed that increasing the data acquiring capability was the key (South Korea’s approach).