To see all blogs in this series, click here.
Dr. Douglas G. Frank is the scientist/mathematician behind this blog.
Dr. Frank received a B.A. in Chemistry from Westmont College in Santa Barbara, California. He qualified for his doctorate at the University of California, Santa Barbara before transferring to the University of Cincinnati in 1986 as part of the Ohio Eminent Scholar program. In 1990, he received a Ph.D. in Surface Analytical Chemistry. After graduating, he formed “ADAM Instrument Company, Inc.,” named for the new surface analysis technique he discovered during his graduate studies. The “ADAM” technique brought him international acclaim, and his work was featured in several scientific books and international journals, including cover articles in Science and Naturwissenschaften. He has over 50 scientific publications, and is internationally regarded as an expert in Auger spectroscopy.
Dr. Frank currently serves as the Math and Science Chair at the Schilling School for Gifted Children in Cincinnati, OH. He is also the President of Precision Analytical Instruments.
Good news about chart and commentary availability:
A facebook group called “Dr. Frank models” has now been established. This will enable you to follow the thought stream of Dr. Frank, and to receive the models as they become available. This blog will remain as the “reader’s digest” for those who do not have Facebook or prefer a “once-daily dose.” The Facebook group can be accessed by clicking here and then requesting membership in the group.
“How old are you? – Fermi II”
Let’s say you and I are meeting for the first time, and I am curious how old you are. I could just ask, but that would take the fun out of it. (Let’s pretend you are 40.)
So, obviously, you are not an infant, and not elderly. Not 1, not 70. Average those two: 35.
Now I see some grey in your hair, and an onset of wrinkles. I know you have kids in their teens. Not 30, not 50. Average 40 with 35, now we’re at 38.
So with just a few assumptions, I’ve already narrowed your age down to within 10%. The more assumptions I make, and then average, the more I will converge on the correct answer.
That is the way Fermi calculations work. And there are lots of clever ways to do them. Clearly, I’ve mastered a few of them, because I predicted about where the Covid-19 peak would be in the US over a month in advance. I’m not a prophet. It’s just math, combined with experience and a bit of art.
For State graphs, click the state below:
Each state is updated daily, or as often as Dr. Frank supplies an updated chart.
Alabama Alaska Arizona Arkansas California. Colorado Connecticut Delaware Florida Georgia Hawaii Idaho Illinois
Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri
Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota. Tennessee Texas Utah Vermont. Virginia. Washington West Virginia Wisconsin Wyoming
Publisher’s Note: All words below this line are compiled from Dr. Frank. Other than ordering and organizing the comments and the charts, we (DPH) have not edited any of his comments because that would be out of our area of expertise. The comments were given in a social media context, so they have a friendly, conversational tone.
Latest World and USA Model:
(Note: Click on the heading to get a page of past charts for that heading)
I’ve mentioned and implied it in comments, but it makes sense to say it explicitly.
We’ve nailed the front side of the USA cases peak (“climbing up”). What will the back side look like? Well, if there are no secondary infections, like rest homes and the like, then the back side of the peak will be the mirror image of the front side.
But experience teaches us that there are often breakout infections. How many? Difficult to say. I could do a Fermi calculation, but not now.
Because the spot-infections are typically small compared to everything else, they end up stretching out the backside of the peak. This is normal, and it will show up in the graphs.
For expediency, I made no assumptions about this in my initial forcasts, so don’t be surprised if the model doesn’t quite line up. Here, we are counting on Fermi to do our work for us; some states will have unfortunate breakout infections, and some won’t. Others will come out less than I’d forecast, others more.
Provided for completeness. Revised for 3/29.
As I have said on multiple occasions, this graph makes it obvious that we can think of the US as a combination of NY and US49. The “Deaths reconciliation” graph confirms this. We don’t expect the earlier proposed model (shown here) to be lining up now. Continuing to show this graph clearly reveals which of our original assumptions was incorrect. This graph is useful for that purpose. It shows the scientific method at work.
Covid-19 “US Deaths Tracking”
Note: for worldwide models we are only adding the latest graphs. We are not keeping updated records and comments as we are doing for the states.
Covid-19 “Quick Look at Australia”
Covid-19 “Quick Look at France”
Covid-19 “Model Update for S Korea”
Covid-19 “Italy Model Update”
Covid-19 “Quick Look at India”
Covid-19 “Model Update for Iran”
Just added data, but also marked the inflection point in the graph. When things settle down, I can teach y’all the calculus that makes inflection points quantitatively obvious (not just visually).The inflection point is where the progress of Iran’s epidemic suddenly deviated from a model it had followed dead on for weeks. So we suspected a significant second infection.
Covid-19 “Model Update for the UK”
Sounding the alarm. Just added data. Cases up, in tandem with deaths. Time to pray for a small infection.
Covid-19 Model Spain
Covid-19 Model for Cambodia
Covid-19 Model for the Philippines
Covid-19 Model for the Netherlands
This is sad. I understand people desperately want “good news” and Dr Franks is apparently trying to provide it, no matter how inaccurate and unreliable it may be. Here is all you need to know about his predictions – a little over a week ago he was predicting the peak in the daily cases would hit the US around today (3/31). He also predicted total US deaths of 1.400 – which has recently been “updated” to a prediction of 5,800. Wouldn’t every single American wish that to be true? Yet, Dr Franks is literally the ONLY person in the world making those types of predictions. According to almost all the other MEDICAL experts, the peak is still at least 2-3 weeks away and the death toll will be a factor of 10-50 times his predictions.
Would you prefer to simply trust that graph the governor showed, or do you prefer the imperfection that comes with science that takes a model and build from it, and gives feedback each step of the way. Those following Dr. Frank know exactly why he has changed numbers from time to time, and you can follow every change, every thought, every move. If you would rather blindly trust Dr. Fauci’s swings from “a bad flu” to “200,000 dead,” go for it.
Just a couple of questions – any thoughts on why the S Korea cases and deaths are deviating from the prediction, and could the cases deviation be tied to increased testing?
Just concerned that the US is getting close to the point on the graph where this started to occur in S Korea and wondering if we will see a similar divergence.
I expect that the US Cases (and Cases/day) will increase above the predicted curve, due to the increasing availability of testing and the significantly greater number of non-symptomatic cases that will reveal. Any thoughts on how to manage that issue in the prediction? It should not affect the death prediction, although I am concerned about that too – see comment above regarding the S Korea numbers.
What happened in S. Korea could happen in the USA. Here are Dr. Frank’s comments from March 24, concerning South Korea, which had a secondary infection, mostly centered in one nursing facility:
Covid-19 “Model Update for S Korea”
Just added the data. Notice that their secondary infection (red squares) is leveling off. Perfect: a single secondary infection based in a elder care facility was contained. Much higher death rate there, of course.
We are pleased that S Korea was on top of this. We need to learn from their example.
I like having examples like this available, because things like this are certain to happen in the US, and our eyes will be trained to recognize them in the data.
Thanks, Randy. I don’t know that this explanation fits what the S Korea chart is showing, since the trend has continued upwards rather than resuming the curve at a higher level. Back on 3/24 this was a good guess but the last 6 days of data doesn’t fit that explanation.
Why have the updated model graphs ceased?
I would be interested to see how the model predictions are changing.
The population must wear mask to reduce spreading, infection and deaths. Work to get the WHO and CDC to implement 100% mask for everyone so we can get the world economy back on track.