Are epidemic growth rates more informative than reproduction numbers?

Journal article

Summary 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.

Authors: Parag, KV; Thompson, RN; Donnelly, CA

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Journal of the Royal Statistical Society: Series A
• Volume: 185
• Issue: S1
• Pages: S5-S15
• Publication date: 2022-05-26
• Acceptance date: 2022-04-22
• DOI: 10.1111/rssa.12867
• EISSN: 1467-985X
• ISSN: 0964-1998
• Language: English
• Keywords: reproduction number; COVID-19; infectious disease; situational awareness; growth rate; FFR; epidemic modelling