A hierarchical Bayesian quantitative microbiological risk assessment model for Salmonella in the sheep meat food chain. (June 2022)
- Record Type:
- Journal Article
- Title:
- A hierarchical Bayesian quantitative microbiological risk assessment model for Salmonella in the sheep meat food chain. (June 2022)
- Main Title:
- A hierarchical Bayesian quantitative microbiological risk assessment model for Salmonella in the sheep meat food chain
- Authors:
- Rawson, Thomas
- Abstract:
- Abstract: Multiple foodborne routes of Salmonella infection have been observed; however, the majority of the literature to date has been dominated by research into the most frequently observed reservoirs, such as chicken, beef, and pork. While less commonly observed, outbreaks of Salmonella within sheep meat still occur, requiring extensive investigation by food safety inspectors. Risk assessment models inform policy makers and investigators of the risks posed by pathogens at each stage of the food chain, and help suggest at which stages in the food chain outbreaks are likely induced. This work is the first risk assessment into the prevalence of Salmonella throughout the sheep meat food chain, from farm to fork. A Bayesian evidence-synthesis model is used, informed by data gathered from 27 individual studies - an exhaustive search of the existing literature, to express and enumerate the current understanding of Salmonella prevalence in the sheep meat food chain in the form of probabilities of colonisation throughout the food chain. The resulting posterior estimate projects that 9 (0–29 95% HDI) UK individuals are likely to fall ill with salmonellosis due to sheep meat every year. A variance-based sensitivity analysis reveals that the abattoir module is the stage of greatest bacterial proliferation, highlighting it as the most probable source of outbreaks, though not to the exclusion of other factors. Highlights: The first exhaustive assessment of data regarding risk ofAbstract: Multiple foodborne routes of Salmonella infection have been observed; however, the majority of the literature to date has been dominated by research into the most frequently observed reservoirs, such as chicken, beef, and pork. While less commonly observed, outbreaks of Salmonella within sheep meat still occur, requiring extensive investigation by food safety inspectors. Risk assessment models inform policy makers and investigators of the risks posed by pathogens at each stage of the food chain, and help suggest at which stages in the food chain outbreaks are likely induced. This work is the first risk assessment into the prevalence of Salmonella throughout the sheep meat food chain, from farm to fork. A Bayesian evidence-synthesis model is used, informed by data gathered from 27 individual studies - an exhaustive search of the existing literature, to express and enumerate the current understanding of Salmonella prevalence in the sheep meat food chain in the form of probabilities of colonisation throughout the food chain. The resulting posterior estimate projects that 9 (0–29 95% HDI) UK individuals are likely to fall ill with salmonellosis due to sheep meat every year. A variance-based sensitivity analysis reveals that the abattoir module is the stage of greatest bacterial proliferation, highlighting it as the most probable source of outbreaks, though not to the exclusion of other factors. Highlights: The first exhaustive assessment of data regarding risk of Salmonella in sheep meat. Bayesian model utilised in light of low data availability. Overall risk to consumers of sheep meat is very low. Abattoir handling is identified as the point at which proliferation is most likely. … (more)
- Is Part Of:
- Food microbiology. Volume 104(2022)
- Journal:
- Food microbiology
- Issue:
- Volume 104(2022)
- Issue Display:
- Volume 104, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 104
- Issue:
- 2022
- Issue Sort Value:
- 2022-0104-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-06
- Subjects:
- Salmonella -- Risk assessment -- Mathematical modelling -- Bayesian statistics -- Food microbiology
Food Microbiology -- Periodicals
Aliments -- Microbiologie -- Périodiques
Food -- Microbiology
Periodicals
Food -- Microbiology -- Periodicals
Food contamination -- Periodicals
664.001579 - Journal URLs:
- http://firstsearch.oclc.org ↗
http://firstsearch.oclc.org/journal=0740-0020;screen=info;ECOIP ↗
http://www.sciencedirect.com/science/journal/07400020 ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.fm.2021.103975 ↗
- Languages:
- English
- ISSNs:
- 0740-0020
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3981.300000
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