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Eco-evolutionary control of pathogens.

Michael Lässig1, Ville Mustonen2

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Summary
This summary is machine-generated.

This study introduces a model for eco-evolutionary pathogen control using antibody dosage, identifying optimal strategies and an error threshold for successful intervention. It highlights how mutation rates and forecasting impact control efficiency.

Keywords:
biophysicscontrol theoryimmune systemspopulation genetics

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Area of Science:

  • Eco-evolutionary dynamics
  • Pathogen control strategies
  • Mathematical modeling in biology

Background:

  • Pathogen control strategies can influence pathogen population size and drive evolutionary changes.
  • Understanding these eco-evolutionary dynamics is crucial for effective disease management.

Purpose of the Study:

  • To develop a payoff model for eco-evolutionary control of pathogens.
  • To determine optimal antibody dosage protocols for pathogen control.
  • To establish a framework for predicting control outcomes based on measurable parameters.

Main Methods:

  • Development of a payoff model integrating evolution, regulation, and computational forecasting.
  • Application of the model to antibody-antigen binding with tunable antibody dosage.
  • Analytical solution to derive optimal dosage protocols and a phase diagram.

Main Results:

  • Identification of optimal dosage protocols and an error threshold for control success.
  • Determination of key measurable fitness parameters predicting control outcomes.
  • Analysis of the influence of mutation rate, population size, and forecasting on control strategies.

Conclusions:

  • Optimal pathogen control strategies are dependent on pathogen characteristics and monitoring capabilities.
  • The developed model provides a foundation for an emerging eco-evolutionary control theory.
  • Results are applicable to general systems beyond specific pathogen-antibody interactions.