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Chapter 117 : Quantitative Microbial Risk Assessment Model for : Summary of Methods and Results

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Quantitative Microbial Risk Assessment Model for : Summary of Methods and Results, Page 1 of 2

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Abstract:

Quantitative microbial risk assessment (QMRA) for can provide a means of setting risk based limits on air concentration or risk based limits on the concentrations in water. Guinea pigs provide a reasonable animal model and dose-response data on which to base human risk projections due to similarities in the course of the disease in guinea pigs and humans and in vitro uptake and replication rates of in human and guinea pig alveolar macrophages. Most mouse and rat strains appear to be relatively resistant to infection due to less compliant alveolar macrophages. A two-zone box model was used to estimate the air concentrations in CFU/m, with stochastic input distributions using Monte Carlo simulation to yield results as probability distributions. The respective exposure distributions were fed into the dose-response model using Monte Carlo simulation. The resulting estimated risk distributions were then compared to the reported rates for the outbreaks. The guinea pig infection data adequately predict the reported subclinical (seroprevalence) rates. For the outbreaks used for model evaluation, the reported rates of disease span an order of magnitude. Thus, the QMRA may not extrapolate to other species and strains.

Citation: W. Armstrong T, N. Haas C. 2006. Quantitative Microbial Risk Assessment Model for : Summary of Methods and Results, p 486-488. In Cianciotto N, Kwaik Y, Edelstein P, Fields B, Geary D, Harrison T, Joseph C, Ratcliff R, Stout J, Swanson M (ed), . ASM Press, Washington, DC. doi: 10.1128/9781555815660.ch117

Key Concept Ranking

Quantitative Risk Assessment
0.53497446
Legionella pneumophila
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References

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1. Anonymous. 2003. Legionellosis, April 1999-December 2002, Japan. IASR 24:2728.
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Tables

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TABLE 1

Summary of results of the evaluation of the calculated versus reported risks for the three outbreaks used for model validation

Citation: W. Armstrong T, N. Haas C. 2006. Quantitative Microbial Risk Assessment Model for : Summary of Methods and Results, p 486-488. In Cianciotto N, Kwaik Y, Edelstein P, Fields B, Geary D, Harrison T, Joseph C, Ratcliff R, Stout J, Swanson M (ed), . ASM Press, Washington, DC. doi: 10.1128/9781555815660.ch117

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