Literature DB >> 31207816

Use of Epidemiologic and Food Survey Data To Estimate a Purposefully Conservative Dose-Response Relationship for Listeria monocytogenes Levels and Incidence of Listeriosis .

Robert L Buchanan1, William G Damert1, Richard C Whiting1, Michael van Schothorst2.   

Abstract

The development of effective quantitative microbial risk-assessment models for foodborne pathogens depends on the availability of data on the consumers' exposure to a biological agent and the dose-response relationship that relates levels of the biological agent ingested with frequency of infection or disease. Information on the latter has historically been acquired from human volunteer feeding studies. However, such studies are not feasible for pathogens that either have a significant risk of being life threatening or for which morbidity is primarily associated with high-risk populations (i.e., immunocompromised persons). For these pathogens, it is proposed that purposefully conservative dose-response relationships can be estimated on the basis of combining available epidemiologic data with food-survey data for a ready-to-eat product. As an example, data on the incidence of listeriosis in Germany were combined with data on the levels of Listeria monocytogenes in smoked fish to generate a dose-response curve for this foodborne pathogen.

Entities:  

Keywords:  Smoked fish; immunocompromised; risk assessment

Year:  1997        PMID: 31207816     DOI: 10.4315/0362-028X-60.8.918

Source DB:  PubMed          Journal:  J Food Prot        ISSN: 0362-028X            Impact factor:   2.077


  2 in total

Review 1.  Predictive Modeling for Estimation of Bacterial Behavior from Farm to Table.

Authors:  Shigenobu Koseki
Journal:  Food Saf (Tokyo)       Date:  2016-06-17

2.  Comparing listeriosis risks in at-risk populations using a user-friendly quantitative microbial risk assessment tool and epidemiological data.

Authors:  L E Falk; K A Fader; D S Cui; S C Totton; A M Fazil; A M Lammerding; B A Smith
Journal:  Epidemiol Infect       Date:  2016-03-28       Impact factor: 4.434

  2 in total

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