Diversity of vaccination-induced immune responses can prevent the spread of vaccine escape mutants
Bouman, J. A.; Capelli, C.; Regoes, R.
Show abstract
Pathogens that are resistant against drug treatment are widely observed. In contrast, pathogens that escape the immune response elicited upon vaccination are rare. Previous studies showed that the prophylactic character of vaccines, the multiplicity of epitopes to which the immune system responds within a host, and their diversity between hosts delay the evolution and emergence of escape mutants in a vaccinated population. By extending previous mathematical models, we find that, depending on the cost of the escape mutations, there even exist critical levels of immune response diversity that completely prevent vaccine escape. Furthermore, to quantify the potential for vaccine escape below these critical levels, we propose a concept of escape depth which measures the fraction of escape mutants that can spread in a vaccinated population. Determining this escape depth for a vaccine could help to predict its sustainability in the face of pathogen evolution.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Mathematical Model of a Personalized Neoantigen Cancer Vaccine and the Human Immune System: Evaluation of Efficacy 97%
- The importance of non-pharmaceutical interventions during the COVID-19 vaccine rollout 97%
- Age-structured non-pharmaceutical interventions for optimal control of COVID-19 epidemic 96%
Similar papers in this journal
- The trade-off between mobility and vaccination for COVID-19 control: a metapopulation modeling approach 97%
- Modelling COVID-19 mutant dynamics: understanding the interplay between viral evolution and disease transmission dynamics 97%
- Vaccine escape in a heterogeneous population: insights for SARS-CoV-2 from a simple model 97%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.