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<p>Infectious disease superspreading is a phenomenon where few primary cases generate unexpectedly large numbers of secondary cases. Superspreading, is frequently documented in epidemiology literature, and is considered a consequence of heterogeneity in transmission. Since understanding the risks of superspreading became a rising concern from both statistical modelling and public health aspects, the <Emphasis FontCategory="NonProportional">R</Emphasis> package <Emphasis FontCategory="NonProportional">modelSSE</Emphasis> provides comprehensive analytical tools to characterize transmission heterogeneity. The package <Emphasis FontCategory="NonProportional">modelSSE</Emphasis> integrates recent advances in statistical methods, such as decomposition of reproduction number, for modelling infectious disease superspreading using various types and sources of contact tracing data that allow models to be grounded in real-world observations. This study provided an overview of the theoretical background and implementation of <Emphasis FontCategory="NonProportional">modelSSE</Emphasis>, designed to facilitate learning infectious disease transmission, and explore novel research questions for transmission risks and superspreading potentials. Detailed examples of classic, historical infectious disease datasets are given for demonstration and model extensions.</p>

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modelSSE: An R Package for Characterizing Infectious Disease Superspreading from Contact Tracing Data

  • 期刊论文

  • 发表日期：

    2025年2月21日

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  • Shi Zhao,
  • Zihao Guo,
  • Kai Wang,
  • Shengzhi Sun,
  • Dayu Sun,
  • Weiming Wang,
  • Daihai He,
  • Marc KC Chong,
  • Yuantao Hao,
  • Eng-Kiong Yeoh

摘要

Infectious disease superspreading is a phenomenon where few primary cases generate unexpectedly large numbers of secondary cases. Superspreading, is frequently documented in epidemiology literature, and is considered a consequence of heterogeneity in transmission. Since understanding the risks of superspreading became a rising concern from both statistical modelling and public health aspects, the R package modelSSE provides comprehensive analytical tools to characterize transmission heterogeneity. The package modelSSE integrates recent advances in statistical methods, such as decomposition of reproduction number, for modelling infectious disease superspreading using various types and sources of contact tracing data that allow models to be grounded in real-world observations. This study provided an overview of the theoretical background and implementation of modelSSE, designed to facilitate learning infectious disease transmission, and explore novel research questions for transmission risks and superspreading potentials. Detailed examples of classic, historical infectious disease datasets are given for demonstration and model extensions.