When is the R = 1 epidemic threshold meaningful?

The effective reproduction number R is a predominant statistic for tracking the transmissibility of infectious diseases and informing public health policies. An estimated R=1 is universally interpreted as indicating epidemic stability and is a critical threshold for deciding whether new infections will grow ( R >1) or fall ( R <1). We demonstrate that this threshold, which is typically computed over coarse spatial scales, rarely signifies stability because those scales integrate infections from heterogeneous groups. Groups with falling and rising infections counteract and early-warning signals from resurging groups are lost in noisy fluctuations from stable groups with large infection counts. We prove that an estimated R=1 is consistent with a vast space of epidemiologically diverse scenarios, diminishing its predictive power and policymaking value. We show that a recent statistic, E , derived from R via experimental design theory provides a more meaningful stability threshold ( E=1 ) by rigorously constraining this space of scenarios.