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Threshold conditions for infection persistence in complex host-vectors interactions

Luiz Fernandes Lopez1, Francisco Antonio Bezerra Coutinho, Marcelo Nascimento Burattini

  • 1School of Medicine, University of São Paulo, LIM01/HCFMUSP, Av. Dr. Arnaldo 455, São Paulo 01246-903, SP, Brazil.

Comptes Rendus Biologies
|January 1, 2003
PubMed

Insights

The basic reproduction number (R0) for diseases with multiple vectors or hosts is more complex than the classical definition. A single R0 value is insufficient; instead, infection persistence depends on a composite threshold.

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Disease Ecology

Background:

  • The classical Basic Reproduction Number (R0) is defined for diseases with a single vector and host.
  • R0 determines the invasion potential of a disease into a susceptible population.
  • For simple systems, R0 directly indicates the threshold for endemic disease establishment.

Purpose of the Study:

  • To examine epidemic dynamics in systems with multiple vectors and/or hosts.
  • To investigate the limitations of the classical R0 in complex disease transmission scenarios.
  • To propose alternative methods for calculating infection persistence thresholds.

Main Methods:

  • Analysis of epidemic models with varying numbers of vectors and hosts.
  • Comparison of classical R0 calculations with new threshold metrics.
  • Application of the R0NGO definition (Diekmann, Heesterbeek, and Metz) for threshold calculation.

Main Results:

  • In complex systems (multiple vectors/hosts), a single R0 is not sufficient to predict disease establishment.
  • A composite threshold, derived from multiple factors, is necessary for complex scenarios.
  • The R0NGO definition offers an alternative approach to calculating infection persistence thresholds.

Conclusions:

  • The classical R0 is inadequate for diseases involving multiple vectors or hosts.
  • New metrics are required to accurately assess infection persistence in complex epidemiological systems.
  • The R0NGO provides a valuable alternative for determining disease establishment thresholds in intricate transmission networks.

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