In this section
@article{Parag:2026:10.1038/s42005-026-02631-6,
author = {Parag, K and Santillana, M and Cori, A and Obolski, U},
doi = {10.1038/s42005-026-02631-6},
journal = {Communications Physics},
title = {The R = 1 threshold can misclassify epidemic stability},
url = {http://dx.doi.org/10.1038/s42005-026-02631-6},
volume = {9},
year = {2026}
}
TY - JOUR
AB - The effective reproduction number, R, is a predominant statistic for tracking infectious disease spread and informing health policies. An estimated R = 1 is universally interpreted as a stability threshold distinguishing epidemic growth (R > 1) from control (R < 1). We demonstrate that this interpretation frequently fails because R typically averages over groups with heterogeneous characteristics. We find that R = 1 conceals valuable early-warning signals of resurgence and misclassifies complex dynamics as noise, generating false positive stability thresholds that diminish predictive and policymaking value. We further illustrate that a popular alternative transmissibility definition (using next-generation matrices) overcorrects this issue, producing false negative stability signals by amplifying stochastic variation. We address these limitations by adapting a recently developed statistic, E, derived from R using experimental design theory. We show that E tightly constrains the set of scenarios consistent with stability, while remaining robust to noise and establish E = 1 as a more practical and meaningful real-time threshold.
AU - Parag,K
AU - Santillana,M
AU - Cori,A
AU - Obolski,U
DO - 10.1038/s42005-026-02631-6
PY - 2026///
SN - 2399-3650
TI - The R = 1 threshold can misclassify epidemic stability
T2 - Communications Physics
UR - http://dx.doi.org/10.1038/s42005-026-02631-6
VL - 9
ER -
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