Interventions designed to limit the spread of COVID have been rolled back around the world. In New Zealand, the government removed all remaining public health measures last week. But although the emergency is over and the disease is rapidly becoming endemic, the risk of new variants remains. COVID is still causing a significant health burden.
The basic reproduction number
Back in 2020, we heard a lot about the basic reproduction number or R0. This is the average number of people someone infects when the whole population is susceptible to the disease. With a susceptible population, if R0 is above 1 the disease spreads exponentially.
This situation prompted governments around the world to implement intensive response measures, including lockdowns, to prevent health systems from becoming completely overwhelmed.
Controlling the disease
Unlike measles or polio, it’s impossible to eliminate COVID with the tools currently available. But that doesn’t mean we can’t reduce its impacts. Effective control measures should reduce the number of contacts infectious people have, or the risk of infection per contact. And this should lower the level of the endemic equilibrium, meaning there are fewer infections.
That’s certainly true, but how much effect do control measures realistically have for a virus like SARS-CoV-2?
The maths of immunity
People may have acquired immunity through vaccination, but the protection vaccines provide against infection with current Omicron variants is relatively low and short-lived.
The majority of immunity comes from previous infections, including infections in vaccinated people. This is called “hybrid immunity” and it provides better protection than infection or vaccination alone.
A consequence of this is that the fraction of the population that is immune at a given point in time is proportional to the number of infections per year. It turns out this allows us to estimate the benefit of interventions.
Targeted protection
The arguments above come from a mathematical model that captures the processes behind disease transmission in a simple way. Reality is more complicated. The susceptible-immune binary is a simplification because immunity is not black and white but shades of grey.
