Within-host phenotypic evolution and the population-level control of chronic viral infections by treatment and prophylaxis
Dmitry Gromov, Ethan O. Romero-Severson

TL;DR
This paper develops a mathematical framework to understand how within-host viral evolution impacts the effectiveness of population-level control strategies like treatment and prophylaxis for chronic infections.
Contribution
It introduces a model that links within-host viral phenotypic evolution to population-level control measures, enabling analysis of their combined effects.
Findings
Computed the basic reproduction number considering within-host evolution.
Extended the model to include treatment and prophylactic control efforts.
Provided expressions for endemic equilibrium under certain evolutionary constraints.
Abstract
Chronic viral infections can persist in an infected person for decades. From the perspective of the virus, a single infection can span thousands of generations, leading to a highly diverse population of viruses with its own complex evolutionary history. We propose a mathematical framework for understanding how the emergence of new viral strains and phenotype within infected persons affects the population-level control of those infections by both non-curative treatment and chemo-prophylactic measures. We consider the within-host emergence of new strains that lack phenotype novelty and also the evolution of variability in contagiousness, resistance to therapy, and efficacy of prophylaxis. Our framework balances the need for verisimilitude with our desire to retain a model that can be approached analytically. We show how to compute the population-level basic reproduction number accounting…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
