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<p>To effectively control the spread of major infectious diseases, it is essential to quantitatively assess the transmission risk. Addressing the fuzziness and uncertainty in such assessments, this paper presents a dynamic and comprehensive risk assessment model grounded in set pair analysis (SPA). First, a risk assessment indicator system containing 20 indicators is constructed from six dimensions: suddenness of epidemic transmission, dynamics of transmission risk, complexity of disaster-breeding environment, viral transmission destructiveness, vulnerability of population infection, and sustainability of medical service. Second, SPA is used to quantify the proximity between indicator values and risk levels, and a dynamic calculation method for the difference degree coefficient is developed to reflect continuous sample changes. On this basis, a comprehensive assessment model is established using the risk index method. Finally, using COVID-19 data from Hubei Province as a case study, the applicability of the proposed model is examined in a representative epidemic context. The results show that the model can quantitatively characterize transmission risk evolution, with the assessed risk stages broadly consistent with the observed epidemic progression. The study provides a methodological reference for monitoring, early warning, and adaptive management in public health practice.</p>

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Research on risk assessment of major infectious disease transmission based on set pair analysis algorithm

  • 期刊论文

  • 发表日期：

    2026年6月29日

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  • Sulin Pang,
  • Dabin Pan,
  • Wenli Li

摘要

To effectively control the spread of major infectious diseases, it is essential to quantitatively assess the transmission risk. Addressing the fuzziness and uncertainty in such assessments, this paper presents a dynamic and comprehensive risk assessment model grounded in set pair analysis (SPA). First, a risk assessment indicator system containing 20 indicators is constructed from six dimensions: suddenness of epidemic transmission, dynamics of transmission risk, complexity of disaster-breeding environment, viral transmission destructiveness, vulnerability of population infection, and sustainability of medical service. Second, SPA is used to quantify the proximity between indicator values and risk levels, and a dynamic calculation method for the difference degree coefficient is developed to reflect continuous sample changes. On this basis, a comprehensive assessment model is established using the risk index method. Finally, using COVID-19 data from Hubei Province as a case study, the applicability of the proposed model is examined in a representative epidemic context. The results show that the model can quantitatively characterize transmission risk evolution, with the assessed risk stages broadly consistent with the observed epidemic progression. The study provides a methodological reference for monitoring, early warning, and adaptive management in public health practice.