Pathogen diversity emerging from coevolutionary dynamics in interconnected systems

TL;DR

This paper introduces a multiscale coevolutionary model combining transmission on networks and mutation in strain space to understand pathogen diversity and dynamics.

Contribution

It develops a novel framework linking immune-mediated competition, network structure, and pathogen evolution, revealing mechanisms driving antigenic diversity.

Findings

Identifies a critical region controlling outbreak and endemic states.

Derives a dynamical landscape for strain evolution.

Shows host heterogeneity enhances long-term diversity.

Abstract

The spread of infectious disease and the evolution of antigenically distinct strains are often modeled separately, despite strong feedbacks mediated by host immune memory and heterogeneous contacts. To tackle this challenging problem, we introduce a coevolutionary framework in which transmission occurs on a metapopulation network while mutational exploration of strain space follows a mutation network. In this multiscale model, cross-immunity is encoded by similarity in the latent diffusion geometry of the strain network, so that nearby strains confer partial immune protection. We first identify an effective critical region that controls the transition between extinction, recurrent outbreak episodes, and long-lived endemic persistence, thus characterizing the resulting strain-turnover dynamics. We then derive a replicator-mutator-like equation for strain composition and an explicit dynamical evolutionary landscape induced by the coupling of mutation and transmission. Finally, allowing host heterogeneity to modulate the local mutation structure, we show that spreading across demes can effectively connect otherwise disconnected components of strain space, increasing long-term endemic diversity while producing a non-monotonic change in overall prevalence. Together, our results isolate minimal mechanisms by which immune-mediated competition and network structure can shape antigenic diversification.