Update (3/22/2020): After falling under much scrutiny, Medium has deleted Ginn’s post. Of note, Ginn is a former 2012 Romney digital campaign staffer with no background in medicine or infectious disease.
We are leaving it up for anyone who wants to read, while also including a thread from a biologist who has refuted it. Click on the tweet below to read.
1. I hate to invest precious time on taking apart the atrocious @aginnt article pictured below, but it is getting too much traction here and even in traditional media.— Carl T. Bergstrom (@CT_Bergstrom) March 22, 2020
This thread could be far longer than it is, but I'm doing my best to only discuss the most glaring flaws. pic.twitter.com/EFA7ATQRbX
After watching the outbreak of COVID-19 for the past two months, I’ve followed the pace of the infection, its severity, and how our world is tackling the virus. While we should be concerned and diligent, the situation has dramatically elevated to a mob-like fear spreading faster than COVID-19 itself.
When 13% of Americans believe they are currently infected with COVID-19 (mathematically impossible), full-on panic is blocking our ability to think clearly and determine how to deploy our resources to stop this virus. Over three-fourths of Americans are scared of what we are doing to our society through law and hysteria, not of infection or spreading COVID-19 to those most vulnerable.
The following article is a systematic overview of COVID-19 driven by data from medical professionals and academic articles that will help you understand what is going on (sources include CDC, WHO, NIH, NHS, University of Oxford, Stanford, Harvard, NEJM, JAMA, and several others). I’m quite experienced at understanding virality, how things grow, and data. In my vocation, I’m most known for popularizing the “growth hacking movement” in Silicon Valley that specializes in driving rapid and viral adoption of technology products. Data is data. Our focus here isn’t treatments but numbers. You don’t need a special degree to understand what the data says and doesn’t say. Numbers are universal.
I hope you walk away with a more informed perspective on how you can help and fight back against the hysteria that is driving our country into a dark place. You can help us focus our scarce resources on those who are most vulnerable, who need our help.
Note: The following graphs and numbers are as of mid-March 2020. Things are moving quickly, so I update this article twice a day. Most graphs are as of March 20th, 2020.
Total cases are the wrong metric
A critical question to ask yourself when you first look at a data set is, “What is our metric for success?”.
Let’s start at the top. How is it possible that more than 20% of Americans believe they will catch COVID-19? Here’s how. Vanity metrics — a single data point with no context. Wouldn’t this picture scare you?
Look at all of those large red scary circles!
These images come from the now infamous John Hopkins COVID-19 tracking map. What started as a data transparency effort has now molded into an unintentional tool for hysteria and panic.
An important question to ask yourself is what do these bubbles actually mean? Each bubble represents the total number of COVID-19 cases per country. The situation looks serious, yet we know that this virus is over four months old, so how many of these cases are active?
Immediately, we now see that just under half of those terrifying red bubbles aren’t relevant or actionable. The total number of cases isn’t illustrative of what we should do now. This is a single vanity data point with no context; it isn’t information or knowledge. To know how to respond, we need more numbers to tell a story and to paint the full picture. As a metaphor, the daily revenue of a business doesn’t tell you a whole lot about profitability, capital structure, or overhead. The same goes for the total number of cases. The data isn’t actionable. We need to look at ratios and percentages to tell us what to do next — conversion rate, growth rate, and severity.
Time lapsing new cases gives us perspective
Breaking down each country by the date of the first infection helps us track the growth and impact of the virus. We can see how total cases are growing against a consistent time scale.
Here are new cases time lapsed by country and date of first 100 total cases.
Here is a better picture of US confirmed case daily growth.
The United States is tracking with other European nations at doubling every three days or so. As we measure and test more Americans, this will continue to grow. Our time-lapse growth is lower than China, but not as good as South Korea, Japan, Singapore, or Taiwan. All are considered models of how to beat COVID-19. The United States is performing average, not great, compared to the other modern countries by this metric.
Still, there is a massive blindspot with this type of graph. None of these charts are weighted on a per-capita basis. It treats every country as a single entity, as we will see this fails to tell us what is going on in several aspects.
On a per-capita basis, we shouldn’t be panicking
Every country has a different population size which skews aggregate and cumulative case comparisons. By controlling for population, you can properly weigh the number of cases in the context of the local population size. Viruses don’t acknowledge our human borders. The US population is 5.5X greater than Italy, 6X larger than South Korea, and 25% the size of China. Comparing the US total number of cases in absolute terms is rather silly.
Rank ordering based on the total number of cases shows that the US on a per-capita basis is significantly lower than the top six nations by case volume. On a 1 million citizen per-capita basis, the US moves to above mid-pack of all countries and rising, with similar case volume as Singapore (385 cases), Cyprus (75 cases), and United Kingdom(3,983 cases). This is data as of March 20th, 2020.
But total cases even on a per-capita basis will always be a losing metric. The denominator (total population) is more or less fixed. We aren’t having babies at the pace of viral growth. Per-capita won’t explain how fast the virus is moving and if it is truly “exponential”.
COVID-19 is spreading, but probably not accelerating
Growth rates are tricky to track over time. Smaller numbers are easy to move than larger numbers. As an example, GDP growth of 3% for the US means billions of dollars while 3% for Bermuda means millions. Generally, growth rates decline over time, but the nominal increase may still be significant. This holds true of daily confirmed case increases. Daily growth rates declined over time across all countries regardless of particular policy solutions, such as shutting the borders or social distancing.
Source: Tyler Durden | ZeroHedge
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