Localized contacts between hosts reduce pathogen diversity

A Nunes1, M M Telo da Gama, M G M Gomes

  • 1Centro de Física Teórica e Computacional and Departamento de Física, Faculdade de Ciências da Universidade de Lisboa, P-1649-003 Lisboa Codex, Portugal. anunes@ptmat.fc.ul.pt

Insights

This study shows that local contacts in host networks reduce infection prevalence and pathogen diversity. Small-world networks limit invading strains more than well-mixed populations.

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Network Science

Background:

  • Pathogen strains can invade populations with existing infections.
  • Immunity, both homologous and cross-protective, influences reinfection dynamics.
  • Host contact networks impact disease transmission and evolution.

Purpose of the Study:

  • To investigate how host contact network structure affects pathogen strain invasion dynamics.
  • To understand the role of local versus global contacts in disease spread and pathogen diversity.
  • To develop a mean-field model for small-world networks in epidemiological dynamics.

Main Methods:

  • Agent-based simulations on small-world networks.
  • Modeling pathogen invasion with homologous and cross-immunity.
  • Analysis of infection prevalence and strain coexistence under different network structures.

Main Results:

  • Increased local contacts in small-world networks significantly reduce infection prevalence compared to well-mixed populations.
  • The parameter space for invading strain establishment and coexistence with existing strains is smaller in small-world networks.
  • Network structure critically influences the potential for pathogen diversity and evolution.

Conclusions:

  • Host contact network topology, particularly the proportion of local interactions, is a key factor in epidemiological outcomes.
  • Small-world networks can limit pathogen diversity by restricting the conditions for strain coexistence.
  • An effective mean-field model can capture the effects of small-world network structures on epidemiological dynamics.

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