In his Akimbo podcast, Seth Godin teaches us how to adopt a posture of possibility, change the culture, and choose to make a difference. Here are my takeaways from the episode.

In this podcast, Seth discusses the percentages behind our public health events and why we need to interpret the math correctly. There are two crucial questions Seth wanted to dissect.

First, why should we bother with an intervention with a 90% success rate when 99% of the people recover eventually? That is an oversimplification of the 99% recovery rate and projects a false sense of security.

With a population of 300 million in the US, one percent of death from a disease means that approximately three million Americans will die. That is a considerable number, and if any other disease or natural disaster had a death toll number like that, everyone would be paying attention. 99% sounds like an excellent survival rate unless you are one of the 1%.

Another argument says that a vaccine’s 90% efficacy rate is not worth the effort if 99% of the people recover. When we compare two percentages like those, it might feel appropriate, but it is not. When we attempt to compare two percentage numbers, we need to dig deeper into the numbers.

While the 90% efficacy rate seems to be less impressive than the 99% recovery rate, they mean differently because they cover two overlapping but still different segments of the population. If 1% of the population faces a certain doom without the vaccine, the 90% efficacy rate can still make a marked difference. By vaccinating the people, we have an opportunity to save 2.7M (90% out of 3M population) people from certain death.

The second question has to do with why bother getting the second dose of the vaccine if it is only going to increase the efficacy by 15%, from 80% to 95%? Again, we like to do short-cut with the numbers, but that often leads to bias.

In a town of 1,000 people, an 80% efficacy rate means 200 people will get sick. If everyone gets the second vaccination shot and reaches an overall 95% efficacy rate, 50 people will probably get sick. When looking at the number from an individual perspective, the 15% difference rate might not seem like a lot. When we factor in a much larger population, even small percentages start to become significant.

While we may wish we had a perfect answer to our public health crisis right from the start, practicing public health always faces two significant obstacles. First, science does not look good when we look at it in real-time, and science is about failing and stumbling our way to getting it right. The second obstacle is that public health, by its nature, deals with vast numbers of people. Frequently, people who might not be us in any given situation over more extended periods.

It is easy to take public health for granted for those two reasons, but public health is still one of our modern triumphs. Public health has done many good things for a large number of people and deserves our support. We need not take the public health officials and scientists at their word, but the math speaks for itself.

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