Are epidemic growth rates more informative than reproduction numbers?

statistics, often derived from simplified models of epidemic spread, inform public health policy in real time. The instantaneous reproduction number, $R_t$ , is predominant among these statistics, measuring the average ability of an infection to multiply. However, $R_t$ encodes no temporal information and is sensitive to modelling assumptions. Consequently, some have proposed the epidemic growth rate, $r_t$ , that is, the rate of change of the log-transformed case incidence, as a more temporally meaningful and model-agnostic policy guide. We examine this assertion, identifying if and when estimates of $r_t$ are more informative than those of $R_t$ . We assess their relative strengths both for learning about pathogen transmission mechanisms and for guiding public health interventions in real time.