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Modeling Approach Influences Dynamics of a Vector-Borne Pathogen System.

Allison K Shaw1, Morganne Igoe2,3, Alison G Power4

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Summary

Choosing a modeling approach impacts results. An individual-based model (IBM) revealed non-random insect vector distribution, affecting plant virus spread differently than an ordinary differential equation (ODE) model.

Keywords:
Barley yellow dwarf virusIndividual-based modelMean fieldOrdinary differential equationVector-borne plant pathogen

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Area of Science:

  • Ecological modeling
  • Epidemiology
  • Mathematical biology

Background:

  • Modeling approaches significantly influence the understanding of biological systems.
  • Different modeling techniques, such as individual-based models (IBM) and ordinary differential equation (ODE) models, have distinct assumptions and capabilities.
  • The spread of vector-borne plant viruses is a complex ecological process influenced by vector behavior and host interactions.

Purpose of the Study:

  • To compare an individual-based model (IBM) with an ordinary differential equation (ODE) model for describing vector-borne plant virus transmission.
  • To investigate how modeling approach choice affects the interpretation of insect vector traits on virus spread.
  • To evaluate the efficacy of different control strategies using the developed models.

Main Methods:

  • Development of an individual-based model (IBM) to simulate insect vector behavior and plant virus transmission.
  • Comparison of IBM results with a pre-existing ordinary differential equation (ODE) model of the same biological system.
  • Analysis of insect vector distribution, population dynamics, and pathogen spread under different modeling assumptions.

Main Results:

  • The IBM captured a non-random distribution of insect vectors across plant hosts, which was not represented in the ODE model.
  • This non-random distribution resulted in a slower vector population growth but a faster pathogen spread.
  • The IBM identified removing virus-infected hosts as a more effective control strategy than removing vector-infested hosts.

Conclusions:

  • The choice of modeling approach critically influences the outcomes and biological interpretations of plant virus transmission dynamics.
  • Individual-based models can reveal emergent phenomena, like non-random host distribution, missed by aggregate models.
  • Careful consideration of modeling approaches is essential for accurate ecological and epidemiological research.