Multi-state epidemic processes on complex networks

Naoki Masuda*, Norio Konno

*この研究の対応する著者

研究成果査読

66 被引用数 (Scopus)

抄録

Infectious diseases are practically represented by models with multiple states and complex transition rules corresponding to, for example, birth, death, infection, recovery, disease progression, and quarantine. In addition, networks underlying infection events are often much more complex than described by meanfield equations or regular lattices. In models with simple transition rules such as the SIS and SIR models, heterogeneous contact rates are known to decrease epidemic thresholds. We analyse steady states of various multi-state disease propagation models with heterogeneous contact rates. In many models, heterogeneity simply decreases epidemic thresholds. However, in models with competing pathogens and mutation, coexistence of different pathogens for small infection rates requires network-independent conditions in addition to heterogeneity in contact rates. Furthermore, models without spontaneous neighbor-independent state transitions, such as cyclically competing species, do not show heterogeneity effects.

本文言語English
ページ(範囲)64-75
ページ数12
ジャーナルJournal of Theoretical Biology
243
1
DOI
出版ステータスPublished - 2006 11 7
外部発表はい

ASJC Scopus subject areas

  • 統計学および確率
  • モデリングとシミュレーション
  • 生化学、遺伝学、分子生物学(全般)
  • 免疫学および微生物学(全般)
  • 農業および生物科学(全般)
  • 応用数学

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