A general framework for modelling the impact of co-infections on pathogen evolution
1Department of Biology, Emory University , Atlanta, GA , USA.
Journal of the Royal Society, Interface
|June 27, 2019
Summary
Mixed-strain pathogen infections drive evolution. A new framework shows co-infection R0 predicts evolutionary emergence, with strain dominance crucial for mutant invasion and saving maladapted strains.
Area of Science:
- Evolutionary biology
- Infectious disease dynamics
- Theoretical ecology
Background:
- Mixed-strain infections (co-infections) are recognized as significant drivers of pathogen evolution.
- Understanding the within-host dynamics of co-infections is complex, hindering generalizable insights into their evolutionary impact.
- Existing theoretical models often oversimplify the intricate interactions occurring during co-infections.
Purpose of the Study:
- To develop a generalized framework for analyzing within-host co-infection dynamics.
- To identify key outcomes of co-infections that influence pathogen evolution.
- To establish a predictive relationship between co-infection characteristics and evolutionary emergence.
Main Methods:
- Developed a general framework to condense complex within-host co-infection dynamics into key outcomes, focusing on the overall basic reproduction number (R0).
- Utilized a within-host model to explore how strain interactions generate dominance.
- Employed an epidemiological model to test the predictive power of dominance for evolutionary emergence.
Main Results:
- The overall R0 of a co-infection is a product of individual strain R0 values, modulated by within-host interactions.
- Strain dominance within co-infections emerges from these within-host dynamics.
- Dominance was demonstrated as a robust predictor of a mutant strain's ability to facilitate the evolutionary emergence of a maladapted wild-type strain.
Conclusions:
- Co-infection dynamics can be simplified into a framework centered on overall R0 and strain dominance.
- Strain dominance, arising from within-host interactions, is a critical factor in predicting pathogen evolutionary trajectories.
- This framework offers a powerful tool for understanding how co-infections influence pathogen evolution and the emergence of new strains.
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