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Bayesian Source Attribution of Salmonellosis in South Australia.

Authors :
Glass K
Fearnley E
Hocking H
Raupach J
Veitch M
Ford L
Kirk MD
Source :
Risk analysis : an official publication of the Society for Risk Analysis [Risk Anal] 2016 Mar; Vol. 36 (3), pp. 561-70. Date of Electronic Publication: 2015 Jul 01.
Publication Year :
2016

Abstract

Salmonellosis is a significant cause of foodborne gastroenteritis in Australia, and rates of illness have increased over recent years. We adopt a Bayesian source attribution model to estimate the contribution of different animal reservoirs to illness due to Salmonella spp. in South Australia between 2000 and 2010, together with 95% credible intervals (CrI). We excluded known travel associated cases and those of rare subtypes (fewer than 20 human cases or fewer than 10 isolates from included sources over the 11-year period), and the remaining 76% of cases were classified as sporadic or outbreak associated. Source-related parameters were included to allow for different handling and consumption practices. We attributed 35% (95% CrI: 20-49) of sporadic cases to chicken meat and 37% (95% CrI: 23-53) of sporadic cases to eggs. Of outbreak-related cases, 33% (95% CrI: 20-62) were attributed to chicken meat and 59% (95% CrI: 29-75) to eggs. A comparison of alternative model assumptions indicated that biases due to possible clustering of samples from sources had relatively minor effects on these estimates. Analysis of source-related parameters showed higher risk of illness from contaminated eggs than from contaminated chicken meat, suggesting that consumption and handling practices potentially play a bigger role in illness due to eggs, considering low Salmonella prevalence on eggs. Our results strengthen the evidence that eggs and chicken meat are important vehicles for salmonellosis in South Australia.<br /> (© 2015 Society for Risk Analysis.)

Details

Language :
English
ISSN :
1539-6924
Volume :
36
Issue :
3
Database :
MEDLINE
Journal :
Risk analysis : an official publication of the Society for Risk Analysis
Publication Type :
Academic Journal
Accession number :
26133008
Full Text :
https://doi.org/10.1111/risa.12444