(4/29/20) The world continues its recovery and the U.S., including the hot-bed states, appear to have reached their peak with the possible exception of NJ. Our advisory for the earliest date to implement easing of social restrictions range from 5/14/20 for WA to 6/2/20 for NJ.
Be sure to read Post 11. Recommended Guidelines for Easing of Social Distancing
We maintain the same format as our previous weekly updates We’ll continue our routine of presenting the death rates internationally and domestically and from that and other conditions and assumptions detailed in our Model from previous postings we forecast total deaths, prevalence and incidence of cases and easing dates. We also compare our forecasts with that of the heralded UW IHME model.
The plots below show the familiar death rate curves for hot-bed countries and for U.S. states. We dropped China and Korea as now being “uninteresting.” But we may add Sweden as a country that has flouted government mandated restrictions allowing voluntary behavioral changes. Though they claim it to be a success they are in my estimation in trouble with a rising death rate and already a cumulative death count of 222/million, which exceeds the U.S. at 172/million and is closing in on Italy, Spain, France, and the U.K. who range from 311/million (U.K.) to 503/million (Spain).
We did not upgrade any countries (3-color ranking) though the U.S., France and the U.K are on the cusp of one and we anticipate if trends continue, we will do so next week. We did upgrade NY from red to orange and MI and LA should get an upgrade next week.
We make the following comments:
- Most countries and states have clearly advanced past the peak of the death rate curve. NJ appeared to reach that summit, but today had its greatest daily death count at 398.
- We have noticed that most U.S. states and some European countries oscillate in their daily reported deaths with low numbers on the weekends and high numbers on Mondays and Tuesdays. So, we now see that some of the daily fluctuations may be due to reporting or data processing diligence.
- The symmetric Gaussian model is starting to break down on the downside of the death rate curve progressing slower than anticipated. Of course, nothing is really anticipated as pandemics and how the population responds are not predictable. Consequently, we are planning to build in an asymmetry factor.
Next is our familiar table for forecasted total deaths, prevalence (current cases), and incidence (new cases) along with their values per capita (per million people) as well as dates we consider to be the earliest to begin a graduate easing of social distancing. We will continue to call this an easing date and not a safe date to dampen excessive hopefulness.
We repeat from last week that as a rough rule of thumb the easing date cannot be before the point when the prevalence count drops to less than what it was when the death rate took off. Roughly the easing date should be about 4-5 weeks after the death peak, the range depending on how severe the outbreak was for a particular population. Our date is based on when the total active case count (prevalence) is forecasted to drop to 100/million. This should be adjusted for population density as this number for sparce populations is probably safe, but for dense populations, e.g., NY, it would be prudent to add a few days.
Continued public and political pressure will surely lead to premature easing, which as Fauci has said “could backfire.” So please read my posting: “11. Recommended Guidelines for Easing of Social Distancing” proposing a three-phased easing with check-gates at each step. And of course, please give me your thoughts.
We now close by comparing our results to that of the Institute for Health Metrics and Evaluation (IHME) at the University of Washington (UW), which has emerged as perhaps the leading model for informing our nation on the state of COVID-19 (http://www.healthdata.org/covid/).
We continue to track closely to the IHME model indicating that there must be components of each model that are similar. We tend to forecast a little earlier from peak rates and as a result we forecast somewhat higher total deaths. Whereas the accuracy of forecasts should improve as we traverse the peak in the death rate curve, we are learning that the downward side of the curve is not symmetric but stretched out in time, which will elevate the actual statistics relative to a symmetric forecast. As noted above we have added an asymmetry factor to account for this effect.