I added up all the illnesses on the “onset” chart, and by 03/26 I got a total of 82625. That coincided with a the total reported (confirmed and presumed) cases as of the that date on the total cases chart showing that on 03/26 the total cases had reached 85356.

I still don’t know what it means but at least the addition works and looks sane.

https://www.nytimes.com/2020/04/06/nyregion/bronx-zoo-tiger-coronavirus.html

How did Tigers catch it from their keeper? Or is this related to the virus thats killing the big cats in Africa, decimating the population.
The question is, can a human catch it from the tiger? Cats?

BTW,
Local medical reserve, are on the way to New York from Utah.
The largest convention center just installed 250 medical beds and equipment in case the hospitals in the area need more room.
Unlikely, my daughter is a nurse and they have a few patients. The hospital has been running drills to keep the staff busy and alert. Their focusing on the cross training specialties.

F16 Guy: Great catch. I am including this in a post I am just finishing.

J Fincannon: Mosquitoes carry and transmit the disease directly to humans and are ubiquitous. Bats are not ubiquitous, nor can they transmit directly without significant human action and assistance. They are not in any way similar to mosquitoes. The comparison is apples and oranges.

https://www.msn.com/en-us/news/other/a-google-plan-to-wipe-out-mosquitoes-appears-to-be-working/ar-BB12ejxB

It seems a precedent for this exists for this kind of extermination with the mosquito. You can’t deny they are “virus reservoirs” just like bats.

“Just for a moment, why don’t we stop all the hype, the press briefings, the models, the bending of the curve and get down to brass tacks? It would seem that a reality check is needed, here. As Americans sit home a la Betsy Ross and dust-off Grandma’s sewing machine to make masks, perhaps some data is in order. The best place to begin is with a Coronavirus state tracker outlining deaths, trends, and more.

Stat reports on health and medicine and offers a lot in the way of data concerning COVID-19 and little in terms of opinion. It could be just what America might need at this odd time in our history. Here’s their snapshot of the virus statistics in the U.S. as of April 5.

Total cases reported – 337,646

Deaths attributed to COVID-19 – 9,648

Current U.S. death rate – 2.9%

New York, as everyone knows, has been hit the hardest. Here are the Empire State numbers:

Total cases reported – 123,160

Deaths attributed to COVID-19 – 4,159

Current NY death rate – 3.4%

This tells us that 43% of U.S. deaths attributed to the Coronavirus have occurred in the state of New York. Now let’s hop on over to the second-highest infected state – that of New Jersey:

Total cases reported – 37,505

Deaths attributed to COVID-19 – 917

Current NJ death rate – 2.4%

Thus, we can ascertain by these numbers that 53% of all U.S. Coronavirus deaths are coming from the two states of New York and New Jersey. The state with the third-highest infection rate is Michigan, and frankly, it’s not in the same league as the first two. Total cases reported in Michigan are 15,718. Next comes California with 15,158 and Louisiana with 13,010.

Data shows the death rate is still bouncing up and down in New York and New Jersey. On April 3, 835 people passed away from COVID-19 then on April 4, New York reported 347 deaths, and on April 5, their numbers shot up again to 594. New Jersey is experiencing a similar situation with 182 who died on April 2, 109 on April 3 and 200 on April 4. The data for April 5 in New Jersey shows just 71 deaths.

If you throw out the numbers for the top five and bottom five states, removing the extreme highs and lows – the other 40 U.S. states (including Puerto Rico) will have suffered an average of 70 deaths from Coronavirus.

It seems worth the effort to look dispassionately at these numbers so Americans can determine whether the national response to the Coronavirus has been appropriate or disproportionate to the crisis at hand.”

Note that “exponential growth as a straight line” is not a feature of the log-log scale (though it would come from a semi-log scale). It is instead from the graph being in essence that of f-dot vs. f — that is, the time derivative of a function vs the function itself — with f being either Confirmed Cases or Reported Deaths, and as we all know, the derivative of an exponentiation function is some multiple of that function, with that multiple representing growth rate. (The ordinate is actually weekly growth, done to smooth the random daily fluctuations.) True to its name, it does a great job of revealing incipient trends. Unfortunately, “USA is Number One” here (and not in a good way, as in its International Country Calling Code). Switch to Linear Scale and it stands out even more, but note that it displays total numbers, not per capita figures (say, cases per million people), and the US is rather populous. Still, it’s the shape of the trends which matter.

Compare the state-by-state results of Australia and the US. I had thought that the US was initially a week or two ahead of Australia with regard to infection rate, but Australia really seem to have turned it around.

Time isn’t on the static map, but is instead revealed via animation when you press the “Play” button at bottom left. I think Charles Joseph Minard would approve.

3/22 is the last date on Graph #2 that has compete reporting. So the only concrete comparison to Graph #1 would be to look at that chunk from 03/22. 03/22 reported in with 33,000 plus “new” illnesses. CAVEAT “* Data include both confirmed and presumptive positive cases of COVID-19 reported to CDC or tested at CDC” I quote the note above Graph #1.

We are left with the chart apparently telling us that out of 33,000 plus new cases of COVID-19 only a little over 4200 people actually reported the “onset of illness”.

So,…. maybe? Possibly? Could it be that out of 33,000 new cases only 4280 people actually got sick?

Hmm, no that can’t be right. That would not include the gestation/incubation period. Which according to https://www.worldometers.info/coronavirus/coronavirus-incubation-period/, which is a practically useless metric. Okay it’s a range.

If that is just two days incubation then we would go back to 03/20 annnnnd, we get 4200 plus illness onset vs. 18,000 new cases. Go back 14 days and we get 420 new cases reported. Okay how does that happen. Ten times as many illness onsets than actual cases reported?

Hmmm.

The cynic in me is thinking of that great meme. “Lies, Damned Lies, and statistics.

There is nothing I can do to make any sense of this data, and not just assume that the whole darn thing is just made up. I do not want to go there.

Between age and being in recovery from recent surgery, he is certainly in a high risk category, but even in the highest age groups, recovery is still the mostly likely result. Best of luck to you and yours. We are thinking of you.

Looking forward to your next Boots on the Ground report.

I think including “presumptive” new cases of COVID-19 is the key to over inflating the numbers. BUT,… that is just me guessing. When it comes to data and charts my “guesses” suck.

But this is definitely a dichotomy here that needs an answer, and so far it looks like most of us are still scratching our heads and trying to come up with a plausible “guess”.

The time for Citizen Journalists has clearly arrived.

Robert’s point about the recent period not including all illnesses is important to keep in mind, while analyzing the second chart. This means that the first chart may have more importance for analyzing where we are right now. Although this chart shows a decrease in the new-cases rate on Saturday, there is a risk that weekend data collection may be not as complete as weekday collection. We will have to see what happens on Monday, when the next weekday data collection occurs. Since it is based upon report-date, we may see a jump, rather than the slow-down between Friday and Saturday.

I certainly hope that we are now reaching a knee in the rates. We may be able to end this fiasco, someday.

J Fincannon: Picking on bats in this case would be looking for a scapegoat, and intellectually dishonest, to a point of absurdity.

But then, humans have done such things before, and they will again.

After this is over (if ever), there has to be a fall guy. And given how bats carry things like Ebola and other nasty viruses (rabies, SARS), the Big Finger will be pointed at bats. It may be suggested as public policy to take it out on these little guys. Sure it might have consequences in our ecology, but then do people want more viruses? Who else to blame? Or, better, who else will accept blame?

Then, we can add to the list other bacteria and virus carrying animals such as armadillos (leprosy) and pangolins.

Humans are “apparently” good at making animals go extinct (UN says that 150-200 species of plant, insect, bird and mammal become extinct every 24 hours. https://www.huffpost.com/entry/un-environment-programme-_n_684562 ), so perhaps we should focus this expertise on the lethal ones.

A while ago I suggested Sweden might not be a good “poster boy” for those opposed to government imposed measures, because the numbers for Sweden weren’t looking too good compared to Norway, but I may have been influenced by biased BBC media reports, as you’re actually there you’ll know how Swede’s are actually reacting to the threat posed by the disease, I suspect they’re far less casual about it than was the impression given in the BBC report.

https://www.worldometers.info/coronavirus/country/us/

It’s more complete information but doesn’t attempt to ascertain date of onset of illness, it’s just the date the illness was reported.

It should be noted that n for the first graph is over 304,000, while n for the second is only 63,995, so the information for the second graph is very incomplete (not many peoples information on when they first noticed symptoms got as far as the CDC graph), and as Mr. Zimmerman notes, the numbers at the tail of the graph are very under represented.

Andrew-Winter: I should add that in further inspection, the graph also does include a major caveat. For the March 23 to April 2 period, when the numbers of new cases drops precipitously, the graph notes that “illnesses that began during this time may not yet be reported.”

This would suggest that the data is incomplete, and that the drop therefore is deceptive. At the same time, the flattening of the curve in the week prior to this time period does suggest that the peak had been reached.

If this analysis is correct, then we will find out in only a matter of days whether the disease is now fading.

Andrew-Winter: I will admit to being a bit puzzled myself, mostly by the second graph. The first is obvious. It shows the cumulative number of COVID-19 cases in the U.S.

The second graph, titled “COVID-19 cases in the United States by date of illness onset” appears I think to show the number of illnesses that have appeared, on each date. If this guess on my part is correct, then the illness has not only already peaked in the U.S., but has almost completely stopped spreading. The curve shows a rough bell curve, with a tiny number of new cases during the past week.

This conclusion seems impossible, based on all recent reporting by all the press as well as all government officials. I would love it if some of my more analytical readers would chime in with an analysis.

I should point out that if this true, however, than our leaders and mainstream press have been doing us such a disservice that some should be drawn and quartered.

I have a request. This is serious. I am absolutely terrible at analyzing charts and data. At this CDC link are two charts, near the botton. One chart are the total number of cases “reported” which includes “presumptive cases” in addition to “confirmed cases”. The second chart shows the number of cases by “Illness Onset”.

https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html

I have a guess as to what I am looking at when I try to relate the two charts. But, I am so far out of my depth that I don’t even want to say what that guess is.

Can someone look at this and tell us just how these two charts relate to each other and what they are telling us? Please fell free to email me directly, oh commentors can’t, … darn. I am at a total loss over this.

Maybe Mr Zimmerman can, and maybe he can tell us what these charts mean.

Yes, Lee S, I hope all is improving.

What you state is absolutely true………..in the 2 dimensional TV watching, Judge Judy Pedestrian Realm.

However, the 3 dimensional Political Realm, which includes military strategies requires that you consider ALL potentials as they might relate to the situation that you have before you. This is S.O.M. theory.

When someone is not willing to or refuses to consider the darker side of domestic or international political or military strategy then what you have done is empowered your potential adversaries because you have willfully blinded yourself. Do you think that those in the 3D, even 4D alphabet agencies and the Pentagon are not looking at this current world wide situation in these terms?

These asymmetrical strategy potentials must be considered, like it or not. Especially since this event has brought China very much along in their stated agenda related to the domination of the planet by 2039 with apparently very little down side for themselves. And that is not IMO hyperbolic conspiracy theory that is stated Chinese agenda.

Lee S: Many times auto correct will insert a word that I do not intend, but this case I spelled the word incorrectly :)

How are things progressing over there?