Tennessee will have 1M people infected with COVID-19 before Kentucky even has 6,000.

A Tale of Two States...

The chart above about confirmed cases of #COVID-19, by Stephanie Jolly, should be a sobering and powerful motivator for all of us to #StayHome. Kentucky took the lead and implemented faster and more aggressive policies than did Tennessee and that has made all the difference.

Both Kentucky and Tennessee are literally experiencing exponential growth in the number of verified cases of #COVID19. That’s right: both the solid blue bars and the solid gold bars represent true mathematical exponential growth but, crucially, at different rates.

I’m not using ‘exponential’ as a common-language adjective for “a lot.” I’m using it mathematically precisely: following an exponential equation.

Based on the data in the chart, I computed that Tennessee’s gold curve is growing at 43% PER DAY while Kentucky’s blue curve is growing at “only” 22%. The doubling time for Tennessee is just under 2 days while the doubling time for Kentucky is 3 1/2 days. That may not seem like such a big difference, but it adds up — no, make that it multiplies up — very quickly.

At this growth rate, if nothing changes, on the day that Tennessee will likely hit 1 million confirmed cases (April 13), Kentucky will have under 6,000.

Exponential growth is like that. It surprises. It overwhelms.

To see how this is likely to play out, again, if nothing changes — and the whole point of posts like this is to get people and governments to change —it’s going to be much worse for Tennessee than for Kentucky. Let’s extrapolate from the data in the chart - every day, Kentucky’s number of confirmed cases grows by 22% (multiplied by 1.22) and Tennessee’s number grows by 43% (multiplied by 1.43):

Projected growth in infected individuals in Kentucky (left) and Tennessee (right) based on the graph above. Exponential growth is devastating when it’s a pandemic.

Please listen to the medical experts: Just Stay Home.

If you’re still interested in the math behind this, it’s actually quite simple. Just using Excel, I entered the data from the chart and plotted the log (base 10) of the number of cases for each state and used the linear interpolator to calculate the best-fit straight line as shown in the graph below:

Log-plot of the number of cases for each state over time to show they both have exponential growth.

If you graph an exponential curve on a log-plot it looks like a straight line. The reverse is also true: if a graph of data on a log-plot (like the one above) falls on a straight line, then the data is growing exponentially. The slope of the line indicates the exponent or growth rate.

For Kentucky, the slope is 0.0849 so the daily growth rate is 10⁰.⁰⁸⁴⁹ = 1.22, representing a compounding growth rate of 22%. Similarly, for Tennessee, the slope is 0.1559 so the growth rate is 10⁰.¹⁵⁵⁹ = 1.43, for a daily growth rate of 43%.

These are scary scary numbers.

#JustStayHome!