The metric people fixate on tells you a lot about their frame of reference

That is, after all, the whole point of selecting metrics. Remember, data never got it’s driver’s license.

For instance, recently someone I loved showed hesitancy to get the COVID-19 vaccine. I was so surprised. They were an engineer by training. What was the cause?

Turns out, they’d heard about a statistic on the Chinese American news world: 5% of those who got the COVID-19 vaccine died!

Whoa. Well, if that were true, I suppose I’d understand the hesitancy. I mean, abstinence is 100% guaranteed risk management, right?

I care about this person, so I asked them… where is this coming from? They didn’t remember the source, but they pointed me to a CDC website and expressed that we can’t trust the CDC: after all, they told us to not wear masks. How silly was that? Of course you wear masks! Everyone in Asia (and Africa for that matter) knows how to handle an outbreak. We’ve got the practice.

I looked up the data and dug into the methodology. Turns out, the denominator was out of all self-reported cases of side effects from COVID-19 vaccines. If you dug into the disaggregated data, there was a 5% reported change of dying from the vaccine, yes, but that was about 0.005% of all vaccinated individuals in that age group. But in that same age group, the death rate after contraction was 5%.

I mean… I’ll take the odds of the vaccine. And guess what: so will they.

First published April 13, 2021. Edited April 26, 2021 to correct some typos and grammatical errors.