A hybrid stochastic-deterministic approach to explore multiple infection and evolution in HIV.

ABSTRACT: To study viral evolutionary processes within patients, mathematical models have been instrumental. Yet, the need for stochastic simulations of minority mutant dynamics can pose computational challenges, especially in heterogeneous systems where very large and very small sub-populations coexist. Here, we describe a hybrid stochastic-deterministic algorithm to simulate mutant evolution in large viral populations, such as acute HIV-1 infection, and further include the multiple infection of cells. We demonstrate that the hybrid method can approximate the fully stochastic dynamics with sufficient accuracy at a fraction of the computational time, and quantify evolutionary end points that cannot be expressed by deterministic models, such as the mutant distribution or the probability of mutant exi

SUBMITTER: Kreger J 

PROVIDER: S-EPMC8730440 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature