| সংক্ষিপ্ত: | Summary statistics, often derived from simplified models of epidemic spread, inform public health policy in real time. The instantaneous reproduction number, R<sub>t</sub>, is predominant among these statistics, measuring the average ability of an infection to multiply. However, R<sub>t</sub> encodes no temporal information and is sensitive to modelling assumptions. Consequently, some have proposed the epidemic growth rate, r<sub>t</sub>, 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<sub>t</sub> are more informative than
those of R<sub>t</sub>. We assess their relative strengths both for learning about pathogen transmission mechanisms and for guiding public health interventions in real time.
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