The Evolution of the Age of Onset of Resistance to Infectious Disease

Abstract

Many organisms experience an increase in disease resistance as they age, but the time of life at which this change occurs varies. Increases in resistance are partially due to prior exposure and physiological constraints, but these cannot fully explain the observed patterns of age-related resistance. An alternative explanation is that developing resistance at an earlier age incurs costs to other life-history traits. Here, we explore how trade-offs with host reproduction or mortality affect the evolution of the onset of resistance, depending on when during the host’s life cycle the costs are paid (only when resistance is developing, only when resistant or throughout the lifetime). We find that the timing of the costs is crucial to determining evolutionary outcomes, often making the difference between resistance developing at an early or late age. Accurate modelling of biological systems therefore relies on knowing not only the shape of trade-offs but also when they take effect. We also find that the evolution of the rate of onset of resistance can result in evolutionary branching. This provides an alternative, possible evolutionary history of populations which are dimorphic in disease resistance, where the rate of onset of resistance has diversified rather than the level of resistance.

Mutant emergence timing and population immunisation status impact epidemiological dynamics

“…These typically consider a population where an already established strain, the 'resident', circulates and assesses the ability of a newly introduced strain, generally called the 'mutant' (or variants in the SARS-CoV-2 case), to replace it [Geritz et al 1998;Brännström, Johansson, and Von Festenberg 2013]. One of the strong assumptions made by many of these frameworks that we need to alleviate is that of the separation between epidemiological and evolutionary timescales, meaning that the resident is assumed to reach an epidemiological equilibrium before the mutant appears [Brännström, Johansson, and Von Festenberg 2013;Buckingham and Ashby 2023]. In the SARS-CoV-2 pandemic, for example, such an equilibrium has not yet been reached since variants with different traits still emerge frequently (Figure S1).…”

Coevolution of age-structured tolerance and virulence

“…(2014), who found that these models do not typically generate diversity through polymorphism or cycling (Best et al 2014). The evolution of host resistance in age-structured populations has been theoretically explored (Ashby and Bruns 2018; Buckingham et al 2023; Buckingham and Ashby 2023), but as far as we are aware, the (co)evolution of age-structured tolerance and virulence has yet to be studied.…”