Douglas G. Frank according to his social media, is a “scientist, inventor, entrepreneur, libertarian, teacher, musician, daddy, husband, and servant of Christ.” He is also President of Precision Analytical Instruments, Inc., which “specializes in the design, manufacture, and development of custom analytical and control instrumentation.”
Frank, a brilliant mathematician, has developed mathematical models of the COVID-19 spread. Over the next few weeks, we will be following his model and his comments in an attempt to keep listeners supplied with one man’s attempt to provide a solid model (and thus hope). Neither we nor Mr. Frank claim anything more than what a mathematical model can provide. Mathematical models have their well-known inherent limitations. However, the world coronavirus pandemic has provided a plethora of data that both can and should be used to understand the trajectory of this worldwide threat to physical and financial well-being.
We encourage you to come back to our blog each day for a new post with newly updated charts.
Here are the current numbers that are important to the average USA audience:
Location | Projected Peak | Projected Cases | Projected New Cases Per Day at Peak | Projected Deaths |
Worldwide | 9-Apr | 2,500,000 | 210000 | 105,000 |
USA | 28-Mar | 180,000 | 13000 | 1400 |
Below are Mr. Frank’s charts, in no particular order. See below the charts for some comments from Mr. Frank.
Covid-19 “A Note About Predictions, or What’s Gonna Happen Next?”
- by Douglas G. Frank
I love making predictions using mathematics. Been doing it most of my life. I predict elections, epidemics, sun spots, weather, global warming, even the orbits of the moon. Great fun, and excellent pedagogy in the classroom. And I’ve become quite proficient at it; I am usually right because the mathematics usually works. Statistics can be powerful, used properly.
(For example, I predicted Trump’s win in 2016 over a year in advance, and I documented that prediction here. People thought I was crazy, but I stuck with the math.)
Predicting real-life phenomena is straightforward when natural phenomena are in control, or when enough things are happening such that the various cases can all average out. Nearly anything can be modeled if enough things are going on, and if you make lots of reasonable assumptions. (Scientists call these “Fermi calculations.”)
This is why all the epidemics have such a similar shape. They are the composite of myriad circumstances. When big enough, they average to a binomial distribution. (A “bell curve.”)
So a month ago, my Head of School came to me and she asked, “Your class has been modeling the Coronavirus epidemic. What do your calculations say about our planned class trip to the Baltic States?”
I told her that the pandemic would be peaking in Europe around April 1st (we nailed it). I told her that our children were at very little health risk (almost zero mortality rates for youngsters). But those were the easy predictions. Now for the hard question:
What would the various governments be doing *in response* at that time?
Well, it was logical to assume that they would be in panic mode, right in the middle of their pandemic. We would not be able to predict what actions they would take, but lots of them could be bad for us. President Trump had already started shutting down flights from other countries, so we could get stranded there. Local governments could quarantine our group if one of us coughed. We would be out of control of such variables, and would have fifteen lovely high schoolers under our care. So, we cancelled the trip.
Our mathematical models informed us to make some prudent decisions. But our math did not tell us what the various governments would do, only provide useful insight to guide our logic and reason. My Head of School is quite rational, and we work together on problems like this all time. Wow, did we make the right decision.
So, to the point. Even though the models are working splendidly, and assuming they continue to do so, we can’t predict what our federal and state governments are going to do. Nearly all of this should be over next month. We will have to be careful about secondary infections, of course, but basically we should be able to go back to work.
But… this is the hard part, sort of. Can we predict what the government will do? I think some governments, yes. Some, no. But just because we know the status of the pandemic doesn’t mean we know the status of our politicians. I have always said (ask my students) that whenever politics gets tangled up with science, it is a disaster.
Welcome to Disasterville.
This is great!
Well this is very interesting… where did you get the mortality rates by state, e.g. 2.5% for Louisiana? Also which stat pack are you using? your graphs are prettier than mine. Mike Rescoe
This is all the work of Douglas G. Frank, who has public posts on Facebook. He may be able to answer your questions, though I know he has been inundated with requests.
Do you have the equations for Michigan? I’d like to delve deeper into my state data
Funny how wrong you were looking at predictions back on 3/22sean
This didn’t age well. Now this guy is also an expert on election fraud.
I’m here for the ratio. I see that your predictions are incorrect. Scientifically, your predictions are proven false. I see now, why you’ve been chosen as the latest election ” expert”.
Dr. Frank hasn’t done anything significant in Physics since the early 1990’s. Now, he’s using his past to add legitimacy to his voter and Covid conspiracies. I suppose it is easier to pander than do real science. Hey, Dr. Frank, are you also a young earth creationist?