A practical generation interval-based approach to inferring the strength of epidemics from their speed

Infectious-disease outbreaks are often characterized by the reproductive number and 𝓡 exponential rate of growth r . 𝓡 provides information about out-break control and predicted final size. Directly estimating 𝓡 is difficult, while r can often be estimated from incidence data. These quantities are linked by the generation interval – the time between when an individual is infected by an infector, and when that infector was infected. It is often infeasible to ob-tain the exact shape of a generation-interval distribution, and to understand how this shape affects estimates of 𝓡. We show that estimating generation interval mean and variance provides insight into the relationship between and 𝓡 r . We use examples based on Ebola, rabies and measles to explore approximations based on gamma-distributed generation intervals, and find that use of these simple approximations are often sufficient to capture the r – 𝓡 relationship and provide robust estimates of 𝓡 .