VirtualWright COVID-19

In Infections and Fatalities, I wondered why there is absolutely no discernible change in the cumulative U.S. Deaths curve to reflect the effect of the shutdown. Here’s a zoomed-in look at curve 5 which perfectly fit the data until everyone started inflating the data at the CDC’s request as I pointed out in Changing Lanes:

How can it be that shutting off the American economy and locking people in their homes made no effect on the curve at all? Regardless of how effectively people have followed the guidelines, no one can possibly believe that this has not been a monumental change in everyday life.

So I decided to look at the Flu Surveillance data in Cook County, Illinois where I live. (“ED Visits” means emergency department visits, where flu-like symptoms are denoted.)

There are the 3 peaks that Dr. Birx likes to talk about. The first is Influenza B, the second is Influenza A and the third is COVID-19. Sure enough, the peak of COVID-19 coincides with the shutdown, taking into account the 5-7 day incubation period. But notice how that peak looks just like the other two where there were no associated shutdowns. The upward and downward slopes look the same as do the widths of the peaks. So, if the shutdown is responsible for the downward slope in the last peak, what was responsible for the downwards slopes in the first two flu outbreaks?

The national flu-like symptoms surveillance chart looks the same:

I think we have very good reason to believe that the shutdown has had no measurable effect at all and that this virus is just going through the same pattern as the seasonal flu.

VirtualWright COVID-19

On April 14, New York announced that they would be adding more than 3,700 to the death total from the virus who were never actually tested. That’s a 50% increase. As of today, New York is reporting 8,811 confirmed deaths and 4,429 probable deaths, i.e. not tested.

This is being done because that what the CDC has requested.

So, right at the peak of deaths in this country, the CDC is asking everyone to inflate the numbers by including people who weren’t actually tested. Never mind that people who die from COVID-19 generally die of pneumonia and something like 3,600 people die every week from pneumonia in this country all throughout the year.

Here’s what it looks like on the plots of cumulative deaths. I’ve color-coded in red starting on April 14 to clearly show the impact of what I call the inflated data. My source is worldometers.info and the big jump was added there as of April 16 although some increase was already being reported before the 3,700 were added. Suddenly we’ve moved into the fast lane:

And here’s the plot of death rate where I collect 3 samples per day (with a few exceptions):

Right after what appeared to be the peak it jumps up. Nothing like changing the rules in the middle of the game. In any case, while it clearly is going to change the total numbers I don’t expect it will change the timing. Every indication is that it will essentially be over at the end of this month. And, don’t forget, deaths follow infections by about three weeks. This means the peak of the infections was as much as three weeks ago and have been declining ever since. New York, as seems to be the case with most other places, doesn’t show the true epi curve (onset of symptoms) but look at the hospitalization graph as of today:

Richard J. Wright, a chemist and information technology specialist, has been tracking the official COVID-19 disease (SARS-CoV-2 virus) data and assessing our government’s disease progression modeling, plus responses, at virtualwright.com.