Here’s what armchair COVID experts are getting wrong

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. Here's how we can avoid five common errors, and impress friends and family by getting the statistics right. It's the infection rate that's scary, not the death rate. Social media posts comparing COVID-19 to other causes of death, such as the flu , imply COVID-19 isn't really that deadly. 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). While the jury is still out , COVID-19 has a higher IFR than the flu. Posts implying a low IFR for COVID-19 most certainly underestimate it. They also miss two other points. First, if we compare the typical flu IFR of 0.1% with the most optimistic COVID-19 estimate of 0.25%, then COVID-19 remains more than twice as deadly as the flu. Second, and more importantly, we need to look at the basic reproduction number (R?) for each virus. This is the number of extra people one infected person is estimated to infect. Flu's R?