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Control fast or control smart: When should invading pathogens be controlled?

Robin N Thompson1,2,3,4, Christopher A Gilligan1, Nik J Cunniffe1

  • 1Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom.

Plos Computational Biology
|February 17, 2018
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Summary
This summary is machine-generated.

The Control Smart Algorithm (CSA) optimizes disease outbreak control by balancing early intervention benefits against later, more informed decisions. This data-driven approach improves pathogen management strategies for agricultural and public health applications.

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Infectious Disease Modeling

Background:

  • Rapid response to pathogen outbreaks is intuitive but may not be optimal.
  • Later epidemic stages offer more precise data for transmission characterization and forecasting.
  • The decision to intervene involves balancing immediate control costs against potential future spread and information gains.

Purpose of the Study:

  • To introduce a generic, data-driven algorithm for real-time decision-making in pathogen outbreak control.
  • To resolve the trade-off between early intervention and waiting for more information.
  • To optimize the timing and level of control interventions.

Main Methods:

  • Development of the Control Smart Algorithm (CSA), a data-driven framework.
  • Parameter estimation and outbreak simulation for real-time decision support.
  • Application of a generic mathematical model for pathogen transmission in agricultural settings.

Main Results:

  • The CSA effectively balances the benefits of immediate versus delayed control interventions.
  • The algorithm optimizes the timing and intensity of vaccination or chemical control strategies.
  • CSA outperforms simpler, threshold-based intervention strategies, even when those are pre-optimized.

Conclusions:

  • Strategic timing of disease management is crucial for emerging outbreaks.
  • The CSA provides a concrete framework for optimizing control decisions in real-time.
  • This approach enhances the precision and effectiveness of pathogen control strategies.