state doubling in days Guam 2.4507118742 Rhode_Island 3.9468661952 Texas 4.9776569339 New_Mexico 5.1506057772 South_Dakota 5.3592656446 Alabama 5.4241476357 Mississippi 5.715764637 Massachusetts 5.7239838454 Pennsylvania 6.102194282 Maryland 6.1541184725 Connecticut 6.3795498182 Iowa 6.6594433606 Virginia 6.6741950606 Arizona 6.780725208 Oklahoma 6.9115105295 Nebraska 6.968235808 Puerto_Rico 7.1299124744 Idaho 7.365068418 Colorado 7.4730554834 Kentucky 7.621385874 South_Carolina 7.6768325486 Illinois 8.0810284491 West_Virginia 8.4688522893 […]
Maxima
On March 6, I predicted that the worldwide total number of confirmed cases would reach 1 million by March 28. The prediction used a doubling number of four days. Today is April 2 and the total number of confirmed cases reached 1 million. So my prediction was off by five […]
I forked data from Tom White’s github, and graphed it,Tom White Covid19 database I formatted the data, and baselined the timeline to January 1, 2020. UK Covid 19 Data
I forked data from the New York times, and graphed it,NY Times Covid19 database I formatted the data, and baselined the timeline to January 1, 2020. A C D, F, G and H I and K L M N O, P, and R S, T, and U V and W
I forked data from the New York times, and graphed it,NY Times Covid19 database I formatted the data, and baselined the timeline to January 1, 2020. This is what the Florida dataset looks like when input to Maxima: (%i37) Florida; (%o37) [[2020-03-01, 2], [2020-03-02, 2], [2020-03-03, 3], [2020-03-04, 3], [2020-03-05, […]
In my post of Doubling Numbers – part 3 I predicted one million cases worldwide on March 28, 2020 — today. Well, I was wrong — there are 660,000 confirmed cases and 30K dead. That prediction was made on March 7, twenty one days ago when there were 21K cases. […]
I downloaded the data from the New York Times for confirmed cases covid19 state data from March 1 thru March 26, 2020. Then I plotted this in Maxima. (%i14) plot2d([discrete,NYlog],[title,"NY confirmed cases"], [xlabel,"March 2020 date"],[ylabel,"log souls"], [png_file,"nylog.png"]) (%o14) [/home/nicks/maxout.gnuplot, /home/nicks/nylog.png] (%o14) loveny.mac From eyeballing the graph, one can see that […]
The logistic equation is another model at which the finite population size starts limiting the process. As the number of cases approaches the population size, the rate slows. (%i8) diff(f(x),x)=gamma*f(x)*(G-f(x)); d (%o8) -- (f(x)) = (G - f(x)) f(x) gamma dx Here G is the total population size. As the […]
After a month of indecision, action has come. By restricting peoples’ movement and association, transmission of the virus can be delayed, or stopped. Makes sense in theory — the rapid growth of cases will peak and then subside. That’s the idea. But what does that mean practically? From a numerical […]
In my post on February 10 I predicted that there would be a million cases of coronavirus by March 1. Today, March 6, I am looking at the number of cases outside China reported as 2400 on February 24 and 1200 on February 20. One can use these values to […]
In my post on February 10 I predicted that there would be a million cases of coronavirus by March 1. It was a simplistic back-of-the-envelope calculation. On the same day, Donald Trump made the prediction, “Now, the virus that we’re talking about having to do — you know, a lot […]
a[0]:0; recaman:set(0); recaman_next(n):=block([x:a[n-1]-n], if (x > 0) and not elementp(x, recaman) then ( a[n]:x, recaman:adjoin(x, recaman)) else ( a[n]:a[n-1]+n, recaman:adjoin(a[n], recaman))); for i:1 thru 30 do (recaman_next(i), print(i,"=",a[i])); 1 = 1 2 = 3 3 = 6 4 = 2 5 = 7 6 = 13 7 = 20 8 […]