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Exploration of Superspreading Events in 2015 MERS-CoV Outbreak in Korea by Branching Process Models

Seoyun Choe1, Hee-Sung Kim2, Sunmi Lee3

  • 1Department of Mathematics, University of Central Florida, Orlando, FL 32816, USA.

International Journal of Environmental Research and Public Health
|August 28, 2020
PubMed

Insights

South Korea

Area of Science:

  • Epidemiology
  • Infectious Disease Dynamics
  • Public Health

Background:

  • The 2015 Middle East Respiratory Syndrome (MERS) coronavirus outbreak in South Korea was the largest outside the Arabian Peninsula.
  • This outbreak was characterized by nosocomial (hospital-acquired) infections and significant superspreading events.

Purpose of the Study:

  • To analyze the behavioral and epidemiological characteristics of superspreaders during the 2015 MERS-CoV outbreak.
  • To model the heterogeneity in secondary case generation using a branching process model.
  • To evaluate the impact of control interventions on MERS-CoV transmission dynamics.

Main Methods:

  • Utilized a branching process model, specifically the Lloyd-Smith model, to incorporate individual heterogeneity.
  • Estimated key epidemiological parameters, including the reproduction number and dispersive parameter, from empirical MERS-CoV transmission data.
  • Investigated the influence of superspreader characteristics and hospital-related factors on outbreak dynamics.

Main Results:

  • Superspreaders played a critical role in the high heterogeneity observed during the outbreak.
  • Hospital conditions and multiple hospital visits were identified as crucial factors contributing to superspreading events.
  • The study quantified the impact of superspreaders on MERS-CoV transmission.

Conclusions:

  • Understanding superspreader dynamics is essential for controlling infectious disease outbreaks.
  • Intervention strategies should consider hospital environments and patient movement to mitigate superspreading.
  • The findings provide valuable insights for preventing future large-scale outbreaks.
Keywords:
MERS-CoV transmission dynamicsbranching process modelscontrol measuressuperspreading events

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