Mea culpa.
Back in March, I compared the actual timeline of the disease's progress in Italy with a projection of what progress for the disease should be expected for the upcoming timeline in the United States.
That was like comparing a grape to a watermelon.
Sure, they're both fruits, but have vastly different sizes and seed counts.
I should have compared Italy, the country in Europe, to only the state of California in the USA, as both are of similar geographic size and population.
Perhaps I will do so later today.
For now, it's correct to realize that what I did by using solely Italy in my faulty comparison is akin to treating all of Europe and the Middle East as a single entity.
For the many countries, including Italy, in those two areas of the world, none were exposed to the novel coronavirus SARS-CoV-2 at the same time; none had those exposures become cases of coronavirus infection disease (COVID-19) at the same time; none have been handling preventative measures in the same manner; and so all have had differences in the graphs of their data.
In other words, although all are traveling on the same time line, they are at different places in monitoring the spread of the respiratory disease throughout their individual countries.
Looking at the graphs posted daily on the websites of the BBC, the CDC, and the Johns Hopkins University, I realized my doctoral work was good preparation for what I needed to do now.
For my PHD in analytical chemistry, I had tracked the tensile strength of several linear polyethylenes against their molecular weights. Even though the plastics had been subjected to different heat treatments, I discovered an interesting phenomenon: the curves evidenced for the individual data sets could be overlaid. In layman's terms, once I knew how heat treatments affected tensile strength for one molecular weight, I could predict how the curves would look for samples of different molecular weights.
Last month, I began focusing on nine different states in my one country in order to track the disease in a way that was more meaningful to me.
The states chosen were Georgia, Florida, California, Michigan, Texas, Louisiana, Pennsylvania, New York, and New Jersey.
I wanted to see when each state began its 14-day downward trend which would, in turn, be the indicator of when that state should re-open its businesses, in accordance with the "Guidelines For Opening Up America Again", as defined by the White House.
The first four states have been the ones I primarily focused on though I have been including TX for its comparison to GA.
The last two states monitored (NY and NJ) have so many more cases of infected people than the others that, when those values are included on a graph, they skew the scale too far upward to make the graph of use in looking for trends in the data of the others.
As I've said before and have recently repeated, I try to only monitor the data every two to three days, as I have done in the past during hurricane threats, as a proven effort to maintain my sanity.
Today, the fact that the states I monitor are on different timelines became clear.
Here, I show the maps posted by JHU for data gathered over a month's time.
The first map shows the information collected for April 13, 2020, the Monday after Easter.
The second map contains the data for today, May 14, 2020.
Looking at the data in that manner will better demonstrate decreases in propagation of the disease.
The two states with the lowest rate values are Louisiana and New York, with 1.7 and 1.8.
What that shows is their number of cases is not quite doubling over a thirty-day span.
Michigan, with a rate of 2.0, is exactly doubling.
their numbers of infected people have more than tripled, placing them as much more hazardous at this point in time.
Georgia and Pennsylvania, with rates of 2.9 and 2.8, are quickly approaching tripling status.
Florida and New Jersey, which each have a rate of 2.3, have more than doubled their number of cases, but are doing so at a clearly slower pace than that of GA and PA.
The differences in rate are reflected in the graphs I have been preparing this past month for number of people infected versus time, including the one I posted on Monday.
It's important to remember that the stipulation for the re-opening of a state's businesses is no increases over a continuous 14-day period.
That is, zero increases in COVID-19 cases over a continuous 14-day period - reflecting a rate of 1.0 - is mandated before each state can have resumption of non-essential businesses, such as shopping malls, hair salons, and bowling alleys.
Let's consider Georgia, as it's my state of residency, making me a citizen under its regulations and a registered and active voter in its elections.
Georgia reopened many businesses on April 24th, when it had 22,491 people infected with COVID-19.
Looking backward 14-days to April 9th, Georgia had 10,000 such persons.
That means Georgia had an infection rate of 2.2 (rounded down from 2.2491, of course) when nonessential businesses were allowed to resume operation.
Was April 24th too early?
It most certainly was, as reflected in the change of rate of infection.
Instead of continuing on its former path of more than doubling, Georgia is right at tripling its rate.
Confused about what that means still?
Let me put it this way: every person who has the virus is now giving it to three others, who are giving it to three others, who then give it to three others...
sheer madness.
Tomorrow, I have to buy groceries - an essential need - and now deal with an increased risk of becoming ill just because the governor wanted his hairdresser to go back to work.
Sheer madness.
At least I understand to be even more cautious than I had been.
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