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<p>The theory of complex networks provides a powerful and versatile framework for analyzing the structure, behavior, and evolution of interconnected systems. In this review, we provide a historical development of pairwise network models in epidemiology, focusing on their ability to capture local interaction dynamics in networks. We investigate the main approximation methods used to capture higher-order correlations that emerge in the early phase of an epidemic and analyze how network clustering influences the epidemic threshold. Finally, we highlight potential future research directions.</p>

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Pairwise network models in epidemiology: a review of approximations, dynamics, and applications

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月5日

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  • Muhammad Shafii Abubakar,
  • Kazeem Olalekan Aremu,
  • Maggie Aphane

摘要

The theory of complex networks provides a powerful and versatile framework for analyzing the structure, behavior, and evolution of interconnected systems. In this review, we provide a historical development of pairwise network models in epidemiology, focusing on their ability to capture local interaction dynamics in networks. We investigate the main approximation methods used to capture higher-order correlations that emerge in the early phase of an epidemic and analyze how network clustering influences the epidemic threshold. Finally, we highlight potential future research directions.