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Swab Sampling Method for the Detection of Human Norovirus on Surfaces
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Fitting outbreak models to data from many small norovirus outbreaks.

Eamon B O'Dea1, Kim M Pepin2, Ben A Lopman3

  • 1Section of Integrative Biology, University of Texas at Austin, 1 University Station C0930, Austin, TX 78712, USA.

Epidemics
|March 6, 2014
PubMed
Summary

This study presents a generalized linear model to accurately estimate epidemic parameters from multiple small infectious disease outbreaks. The method enhances understanding of transmission dynamics and variations between outbreaks.

Keywords:
Generalized linear modelHealth-care-associated infectionNorovirusParameter estimationStochastic epidemic model

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Infectious Disease Modeling

Background:

  • Infectious disease outbreaks are often small and isolated, limiting parameter estimation for standard epidemic models.
  • Accurate estimation of epidemic model parameters is crucial for understanding disease spread and implementing control measures.

Purpose of the Study:

  • To develop a generalized linear model approach for accurate parameter estimation from numerous small, diverse infectious disease outbreaks.
  • To characterize variations in transmission rates, initial growth rates, susceptible populations, and contact patterns between outbreaks.

Main Methods:

  • Utilized standard stochastic epidemic models for individual outbreaks.
  • Incorporated a linear predictor to allow parameters to vary across outbreaks, forming a generalized linear model.
  • Simulated data to assess robustness to discrete data collection and imputation of infectious periods.

Main Results:

  • The generalized linear model accurately estimates epidemic parameters from combined small outbreak data.
  • Estimates of initial growth rates revealed variations in susceptible individuals or contact patterns.
  • Baseline regression estimates: 0.0037 transmissions/infective-susceptible day, 0.27 initial growth rate/infective day, 3.35 days symptomatic period.
  • Norovirus outbreaks in long-term-care facilities showed higher transmission and initial growth rates than in hospitals.

Conclusions:

  • The generalized linear model provides a robust framework for analyzing multiple small outbreaks.
  • This approach enhances the ability to characterize heterogeneity in infectious disease dynamics across different settings.
  • Findings highlight significant differences in transmission patterns between long-term-care facilities and hospitals.