Risk and socio-economic impact for Staphylococcus aureus foodborne illness by ready-to-eat salad consumption
DC Field | Value | Language |
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dc.contributor.author | Lee, Yewon | - |
dc.contributor.author | Oh, Hyemin | - |
dc.contributor.author | Seo, Yeongeun | - |
dc.contributor.author | Kang, Joohyun | - |
dc.contributor.author | Park, Eunyoung | - |
dc.contributor.author | Yoon, Yohan | - |
dc.date.accessioned | 2023-11-08T08:49:16Z | - |
dc.date.available | 2023-11-08T08:49:16Z | - |
dc.date.issued | 2022-08 | - |
dc.identifier.issn | 2352-3522 | - |
dc.identifier.issn | 2352-3530 | - |
dc.identifier.uri | https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/152586 | - |
dc.description.abstract | Microbial risk assessment is a valuable tool to provide scientific evidence to control food safety. Therefore, this study evaluated the risk of foodborne illness caused by Staphylococcus aureus in ready-to-eat (RTE) salad products and economic impact. The prevalence of S. aureus in salads, the RTE salad consumption, and distribution conditions (time and temperature) in market parameters were determined, and the data were analysed using the @RISK program to determine the appropriate probabilistic distribution. Predictive models were developed to describe the fate of S. aureus under distribution conditions. A simulation model was prepared with the collected data to calculate the risk of illness per person per day, and this risk was used to calculate the economic impact. S. aureus was detected in 2% of RTE salads, and the initial contamination level was calculated using the Beta distribution. Baranyi model was used to calculate the maximum specific growth rate (μmax), lag phase duration (LPD), and the secondary models well described the temperature effect on LPD and μmax with R2 values of 0.973–0.979. Also, the root mean square error values of 0.362 suggested that the model performance was appropriate. Lognormal distribution estimated that the average daily consumption amount and ratio was 137.7 g and 9.8%, respectively. The simulation model showed that the average probability of S. aureus foodborne illness following RTE salad consumption was 2.1 × 10−9 per person per day. The probability was used to estimate the socio-economic burden, and the annual socio-economic cost was calculated as $48,343. © 2022 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Elsevier B.V. | - |
dc.title | Risk and socio-economic impact for Staphylococcus aureus foodborne illness by ready-to-eat salad consumption | - |
dc.type | Article | - |
dc.publisher.location | 네델란드 | - |
dc.identifier.doi | 10.1016/j.mran.2022.100219 | - |
dc.identifier.scopusid | 2-s2.0-85130312302 | - |
dc.identifier.wosid | 000814786500009 | - |
dc.identifier.bibliographicCitation | Microbial Risk Analysis, v.21 | - |
dc.citation.title | Microbial Risk Analysis | - |
dc.citation.volume | 21 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalResearchArea | Food Science & Technology | - |
dc.relation.journalResearchArea | Microbiology | - |
dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
dc.relation.journalWebOfScienceCategory | Food Science & Technology | - |
dc.relation.journalWebOfScienceCategory | Microbiology | - |
dc.subject.keywordPlus | AUREUS | - |
dc.subject.keywordAuthor | Foodborne illness | - |
dc.subject.keywordAuthor | Ready-to-eat salads | - |
dc.subject.keywordAuthor | Risk assessment | - |
dc.subject.keywordAuthor | Staphylococcus aureus | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/abs/pii/S2352352222000196?via%3Dihub | - |
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