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Bulletin of mathematical biology
Feb 21, 2025;87 (4): 47.

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

Shi Zhao, Zihao Guo, Kai Wang, Shengzhi Sun, Dayu Sun, Weiming Wang, Daihai He, Marc Kc Chong, Yuantao Hao, Eng-Kiong Yeoh
Author Information
  1. Shi Zhao: School of Public Health, Tianjin Medical University, Tianjin, 300070, China. zhaoshi.cmsa@gmail.com. ORCID
  2. Zihao Guo: Centre for Health Systems and Policy Research, Chinese University of Hong Kong, Hong Kong, 999077, China.
  3. Kai Wang: School of Public Health, Xinjiang Medical University, Urumqi, 830017, China.
  4. Shengzhi Sun: School of Public Health, Capital Medical University, Beijing, 100069, China.
  5. Dayu Sun: Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, IN, USA.
  6. Weiming Wang: School of Mathematics and Statistics, Huaiyin Normal University, Huaian, 223300, China.
  7. Daihai He: Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, 999077, China.
  8. Marc Kc Chong: Centre for Health Systems and Policy Research, Chinese University of Hong Kong, Hong Kong, 999077, China.
  9. Yuantao Hao: Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, 100191, China.
  10. Eng-Kiong Yeoh: Centre for Health Systems and Policy Research, Chinese University of Hong Kong, Hong Kong, 999077, China.
PMID: 39982579 DOI: 10.1007/s11538-025-01421-5

Abstract

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.

Keywords

R Contact tracing Infectious disease Superspreading Transmission heterogeneity

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MeSH Term

Humans
Contact Tracing
Communicable Diseases
Mathematical Concepts
Basic Reproduction Number
Software
Epidemiological Models
Disease Outbreaks
Models, Biological
Computer Simulation
Models, Statistical
Journal Article
Article has an altmetric score of 2

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