Interplay between Evolutionary and Epidemic Timescales Challenges the Outcome of Control Policies.

The classical SIR model, assuming constant viral traits, represents the cornerstone model for computing key indicators during epidemic outbreaks, such as the expected peak of infections or the impact of control policies. Viral evolution has been reported to challenge the physics of the SIR model, changing the nature of the epidemic transitions or the early-time dynamics of outbreaks. Here we consider a minimal extension of the SIR model, allowing infectiousness to evolve, to explore how the latter mechanism affects the two aforementioned indicators. We show that evolution induces a nonmonotonic behavior of the epidemic peak with the basic reproduction number and undermines the impact of control policies, as lifting interventions too early can lead to worse epidemic scenarios than no action. We derive analytical expressions for the critical mutation rate and intervention time governing this behavior and identify a strong asymmetry between control strategies: while shortening the infectious period hinders transmission without suppressing the evolution of viral infectiousness, lowering transmission both reduces cases and slows down this evolution.