If we don’t analyse statistics for a living, it’s easy to be taken in by misinformation about COVID-19 statistics on social media, especially if we don’t have the right context.
For instance, we may cherry pick statistics supporting our viewpoint and ignore statistics showing we are wrong. We also still need to correctly interpret these statistics.
It’s easy for us to share this misinformation. Many of these statistics are also interrelated, so misunderstandings can quickly multiply.
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Here’s how we can avoid five common errors, and impress friends and family by getting the statistics right.
1. It’s the infection rate that’s scary, not the death rate
But these posts miss COVID-19’s infectiousness. For that, we need to look at the infection fatality rate (IFR) — the number of COVID-19 deaths divided by all those infected (a number we can only estimate at this stage, see also point 3 below).
Second, and more importantly, we need to look at the basic reproduction number (R₀) for each virus. This is the number of extra people one infected person is estimated to infect.
Flu’s R₀ is about 1.3. Although COVID-19 estimates vary, its R₀ sits around a median of 2.8. Because of the way infections grow exponentially (see below), the jump from 1.3 to 2.8 means COVID-19 is vastly more infectious than flu.
When you combine all these statistics, you can see the motivation behind our public health measures to “limit the spread”. It’s not only that COVID-19 is so deadly, it’s deadly and highly infectious.