To understand the difference between exponential and linear risks, consider an example put forth by Adam Kucharski, a professor at the London School of Hygiene & Tropical Medicine who focuses on mathematical analyses of infectious-disease outbreaks. Kucharski compares a 50 percent increase in virus lethality to a 50 percent increase in virus transmissibility. Take a virus reproduction rate of about 1.1 and an infection fatality risk of 0.8 percent and imagine 10,000 active infections—a plausible scenario for many European cities, as Kucharski notes. As things stand, with those numbers, we’d expect 129 deaths in a month. If the fatality rate increased by 50 percent, that would lead to 193 deaths. In contrast, a 50 percent increase in transmissibility would lead to a whopping 978 deaths in just one month—assuming, in both scenarios, a six-day infection-generation time.

Transmissibility increases can quickly—very quickly—expand the baseline: Each new infected person potentially infects many more people. Severity increases affect only the infected person. That infection is certainly tragic, and this new variant’s lack of increase in severity or lethality thankfully means that it is not a bigger threat to the individual who may get infected. It is, however, a bigger threat to society because it can dramatically change the number of infected people. To put it another way, a small percentage of a very big number can easily be much, much bigger than a big percentage of a small number.