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Spatial spread of infectious diseases with conditional vector preferences.

Frédéric M Hamelin1, Frank M Hilker2, Yves Dumont3,4,5

  • 1Institut Agro, Univ Rennes, INRAE, IGEPP, 35000, Rennes, France. frederic.hamelin@institut-agro.fr.

Journal of Mathematical Biology
|August 3, 2023
PubMed
Summary
This summary is machine-generated.

Conditional vector preferences can lead to disease persistence and spatial spread, even when the infection rate is low. This study reveals how non-random host-seeking behavior influences disease dynamics in vector-borne infections.

Keywords:
Backward bifurcationBistabilityFront reversalPushed and pulled wavesSpreading speedTravelling waveVector bias

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Ecology

Background:

  • Vector-borne infections are a significant global health concern.
  • Vector behavior, particularly host-seeking patterns, is crucial in disease transmission dynamics.
  • Limited understanding exists on how conditional vector preferences impact spatial disease spread.

Purpose of the Study:

  • To investigate the role of conditional vector preferences in the spatial spread of vector-borne diseases.
  • To analyze how non-random host attraction by vectors influences disease persistence and spatial dynamics.
  • To explore the conditions under which bistability and traveling waves emerge in disease models.

Main Methods:

  • Development of a mathematical model using partial differential equations to describe vector-borne disease spread.
  • Analysis of a non-spatial model to understand local dynamics and bistability.
  • Inclusion of vector diffusion to study spatial spread and traveling wave phenomena.
  • Investigation of the impact of vector preferences for infected versus uninfected hosts.

Main Results:

  • Conditional vector preferences alone can induce bistability between disease-free and endemic states.
  • A backward bifurcation may allow disease persistence even with a basic reproductive number less than one.
  • Bistability can lead to traveling waves with positive or negative spatial spread (invasion or retreat).
  • Disease spreading speed is influenced by vector preferences, particularly in monostable scenarios.

Conclusions:

  • Vector behavior, specifically conditional host preferences, is a critical factor in determining disease spread and persistence.
  • Mathematical modeling provides valuable insights into complex epidemiological dynamics.
  • Findings have implications for managing vector-borne plant diseases and understanding broader ecological transmission patterns.