Better estimates of R0, a critical disease dynamics parameter

When a single infectious individual is introduced into a wholly susceptible population, it causes a number of secondary cases.

This number, the basic reproductive ratio or R0, determines whether an epidemic is likely (R0 greater than 1) or not (R0 less than 1); it also affects how long the epidemic will last and the number of cases that occur.

The proportion of the population that needs to be vaccinated to prevent an epidemic can be estimated from R0. Estimating R0 is therefore a useful step towards understanding and managing disease spread.

R0 has classically been difficult to estimate consistently from real-time incidence data, instead relying heavily on parameters estimated from prior epidemics.

Matt Ferrari (above) and Ottar Bjørnstad — together with a collaborator from Princeton — propose a new method for estimating R0 from incidence data and correcting for some of the biases that result from measurement errors and the pooling of data into discrete time bins (weekly, monthly etc).