Interpretation of effective reproduction number R=1 as a stability threshold frequently fails and misclassifies complex dynamics.

The study addresses the interpretation of the effective reproduction number (R) as a stability threshold for infectious disease spread. It evaluates how common definitions of R perform when assessing stability in transmission dynamics. The analysis focuses on the limitations of using R=1 as a standard benchmark for stability.

Results indicate that the interpretation of R=1 as a stability threshold frequently fails. Specifically, this approach conceals early-warning signals of resurgence and generates false positive stability thresholds by misclassifying complex dynamics as noise. Additionally, a popular alternative transmissibility definition using next-generation matrices was found to overcorrect the issue, producing false negative stability signals by amplifying stochastic variation.

In contrast, an adapted statistic, E, derived from R using experimental design theory, tightly constrains the set of scenarios consistent with stability. This adapted statistic remains robust to noise. Using E=1 as a real-time threshold is described as more practical and meaningful than relying on R=1.

The study notes that R typically averages over groups with heterogeneous characteristics, which contributes to its failure as a stability threshold. While safety data and specific adverse events were not reported, the primary limitation highlighted is the statistical misclassification inherent in current definitions. The practice relevance lies in adopting more robust metrics to avoid false stability signals.