Journal
EPIDEMIOLOGY AND INFECTION
Volume 136, Issue 6, Pages 761-770Publisher
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0950268807008771
Keywords
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Funding
- POLYMOD
- Sixth Framework Programme [SSP22-CT-2004502084]
- National Institute of Health Sciences, Japan
- Center for Food Safety, University of Georgia, USA
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The infectivity of pathogenic microorganisms is a key factor in the transmission of an infectious disease in a susceptible population. Microbial infectivity is generally estimated from dose-response studies in human volunteers. This can only be done with mildly pathogenic organisms. Here a hierarchical Beta-Poisson dose-response model is developed utilizing data from human outbreaks. On the lowest level each outbreak is modelled separately and these are then combined at a second level to produce a group dose-response relation. The distribution of foodborne pathogens often shows strong heterogeneity and this is incorporated by introducing an additional parameter to the dose-response model, accounting for the degree of overdispersion relative to Poisson distribution. It Was found that heterogeneity considerably influences the shape of the dose-response relationship and increases uncertainty in predicted risk. This uncertainty is greater than previously reported surrogate and outbreak models using a single level of analysis. Monte Carlo parameter samples (alpha, beta of the Beta-Poisson model) can be readily incorporated in risk assessment models built using tools Such LIS S-plus and @Risk.
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