A stochastic model for immune response with mutations and evolution: the non-spatial setting

TL;DR

This paper introduces a stochastic model for pathogen evolution under immune response, analyzing survival thresholds, effects of mutations, and the balance between immune escape and mutational load.

Contribution

It provides explicit criteria for pathogen survival considering mutation effects and immune response in a non-spatial stochastic framework.

Findings

Explicit phase transition between survival and extinction.

Survival depends on mutation rate and beneficial/deleterious mutation balance.

Intermediate mutation probabilities optimize pathogen survival.

Abstract

We consider a stochastic model for a pathogen population in the presence of an immune response, in which pathogen types are partially ordered by ancestry and the immune system must eliminate ancestor types before it can eliminate their descendants. In this model, pathogens reproduce independently at rate $\lambda>0$ and, at each birth, a mutation occurs with probability $r\in(0,1]$, producing a novel type that is antigenically distinct and whose elimination by the immune system is delayed relative to its ancestors. We provide an explicit characterization of the survival--extinction phase transition and compute the expected total progeny in the subcritical regime. We then extend the model by allowing mutations to be deleterious: conditional on mutation, with probability $p\in(0,1]$ the mutation is beneficial and with probability $1-p$ it is deleterious, producing a sterile offspring. For this extension, we obtain an explicit survival criterion in terms of $(\lambda,r,p)$ and identify parameter regimes in which survival is possible only for an intermediate range of mutation probabilities, reflecting the balance between immune escape and mutational load.