Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne Diseases
With increased interest in source attribution of foodborne pathogens, there is a need to sort and assess the applicability of currently available methods. Herewith we reviewed the most frequently applied methods for source attribution of foodborne diseases, discussing their main strengths and weakne...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2019-11-01
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| Series: | Frontiers in Microbiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fmicb.2019.02578/full |
| _version_ | 1818493102638235648 |
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| author | Lapo Mughini-Gras Lapo Mughini-Gras Pauline Kooh Philippe Fravalo Jean-Christophe Augustin Laurent Guillier Julie David Anne Thébault Frederic Carlin Alexandre Leclercq Nathalie Jourdan-Da-Silva Nicole Pavio Isabelle Villena Moez Sanaa Laurence Watier |
| author_facet | Lapo Mughini-Gras Lapo Mughini-Gras Pauline Kooh Philippe Fravalo Jean-Christophe Augustin Laurent Guillier Julie David Anne Thébault Frederic Carlin Alexandre Leclercq Nathalie Jourdan-Da-Silva Nicole Pavio Isabelle Villena Moez Sanaa Laurence Watier |
| author_sort | Lapo Mughini-Gras |
| collection | DOAJ |
| description | With increased interest in source attribution of foodborne pathogens, there is a need to sort and assess the applicability of currently available methods. Herewith we reviewed the most frequently applied methods for source attribution of foodborne diseases, discussing their main strengths and weaknesses to be considered when choosing the most appropriate methods based on the type, quality, and quantity of data available, the research questions to be addressed, and the (epidemiological and microbiological) characteristics of the pathogens in question. A variety of source attribution approaches have been applied in recent years. These methods can be defined as top–down, bottom–up, or combined. Top–down approaches assign the human cases back to their sources of infection based on epidemiological (e.g., outbreak data analysis, case-control/cohort studies, etc.), microbiological (i.e., microbial subtyping), or combined (e.g., the so-called ‘source-assigned case-control study’ design) methods. Methods based on microbial subtyping are further differentiable according to the modeling framework adopted as frequency-matching (e.g., the Dutch and Danish models) or population genetics (e.g., Asymmetric Island Models and STRUCTURE) models, relying on the modeling of either phenotyping or genotyping data of pathogen strains from human cases and putative sources. Conversely, bottom–up approaches like comparative exposure assessment start from the level of contamination (prevalence and concentration) of a given pathogen in each source, and then go upwards in the transmission chain incorporating factors related to human exposure to these sources and dose-response relationships. Other approaches are intervention studies, including ‘natural experiments,’ and expert elicitations. A number of methodological challenges concerning all these approaches are discussed. In absence of an universally agreed upon ‘gold’ standard, i.e., a single method that satisfies all situations and needs for all pathogens, combining different approaches or applying them in a comparative fashion seems to be a promising way forward. |
| first_indexed | 2024-12-10T17:50:49Z |
| format | Article |
| id | doaj.art-d5012bafb57b463090e50ccfd0488f16 |
| institution | Directory Open Access Journal |
| issn | 1664-302X |
| language | English |
| last_indexed | 2024-12-10T17:50:49Z |
| publishDate | 2019-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Microbiology |
| spelling | doaj.art-d5012bafb57b463090e50ccfd0488f162022-12-22T01:39:04ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2019-11-011010.3389/fmicb.2019.02578475117Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne DiseasesLapo Mughini-Gras0Lapo Mughini-Gras1Pauline Kooh2Philippe Fravalo3Jean-Christophe Augustin4Laurent Guillier5Julie David6Anne Thébault7Frederic Carlin8Alexandre Leclercq9Nathalie Jourdan-Da-Silva10Nicole Pavio11Isabelle Villena12Moez Sanaa13Laurence Watier14Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, NetherlandsFaculty of Veterinary Medicine, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, NetherlandsDepartment of Risk Assessment, French Agency for Food, Environmental and Occupational Health and Safety, Maisons-Alfort, FranceResearch Chair in Meat-Safety, Faculty of Veterinary Medicine, University of Montreal, Saint-Hyacinthe, QC, CanadaEcole Nationale Vétérinaire d’Alfort, Maisons-Alfort, FranceLaboratory for Food Safety, French Agency for Food, Environmental and Occupational Health and Safety, Maisons-Alfort, FrancePloufragan-Plouzané Laboratory, French Agency for Food, Environmental and Occupational Health and Safety, Ploufragan, FranceDepartment of Risk Assessment, French Agency for Food, Environmental and Occupational Health and Safety, Maisons-Alfort, FranceUMR 408 SQPOV “Sécurité et Qualité des Produits d’Origine Végétale” INRA, Avignon Université, Avignon, FranceInstitut Pasteur, Biology of Infection Unit, National Reference Centre and WHO Collaborating Centre for Listeria, Paris, France0Santé Publique France (French National Public Health Agency), Saint-Maurice, France1Laboratory for Animal Health, French Agency for Food, Environmental and Occupational Health and Safety, Maisons-Alfort, France2Laboratory of Parasitology-Mycology, EA ESCAPE, University of Reims Champagne-Ardenne, Reims, FranceDepartment of Risk Assessment, French Agency for Food, Environmental and Occupational Health and Safety, Maisons-Alfort, France3Department of Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), Institut National de la Santé et de la Recherche Médicale (INSERM), UVSQ, Institut Pasteur, Université Paris-Saclay, Paris, FranceWith increased interest in source attribution of foodborne pathogens, there is a need to sort and assess the applicability of currently available methods. Herewith we reviewed the most frequently applied methods for source attribution of foodborne diseases, discussing their main strengths and weaknesses to be considered when choosing the most appropriate methods based on the type, quality, and quantity of data available, the research questions to be addressed, and the (epidemiological and microbiological) characteristics of the pathogens in question. A variety of source attribution approaches have been applied in recent years. These methods can be defined as top–down, bottom–up, or combined. Top–down approaches assign the human cases back to their sources of infection based on epidemiological (e.g., outbreak data analysis, case-control/cohort studies, etc.), microbiological (i.e., microbial subtyping), or combined (e.g., the so-called ‘source-assigned case-control study’ design) methods. Methods based on microbial subtyping are further differentiable according to the modeling framework adopted as frequency-matching (e.g., the Dutch and Danish models) or population genetics (e.g., Asymmetric Island Models and STRUCTURE) models, relying on the modeling of either phenotyping or genotyping data of pathogen strains from human cases and putative sources. Conversely, bottom–up approaches like comparative exposure assessment start from the level of contamination (prevalence and concentration) of a given pathogen in each source, and then go upwards in the transmission chain incorporating factors related to human exposure to these sources and dose-response relationships. Other approaches are intervention studies, including ‘natural experiments,’ and expert elicitations. A number of methodological challenges concerning all these approaches are discussed. In absence of an universally agreed upon ‘gold’ standard, i.e., a single method that satisfies all situations and needs for all pathogens, combining different approaches or applying them in a comparative fashion seems to be a promising way forward.https://www.frontiersin.org/article/10.3389/fmicb.2019.02578/fullsource attributionfoodborne pathogenepidemiological studiestyping methodsfrequency-matching modelspopulation genetics models |
| spellingShingle | Lapo Mughini-Gras Lapo Mughini-Gras Pauline Kooh Philippe Fravalo Jean-Christophe Augustin Laurent Guillier Julie David Anne Thébault Frederic Carlin Alexandre Leclercq Nathalie Jourdan-Da-Silva Nicole Pavio Isabelle Villena Moez Sanaa Laurence Watier Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne Diseases Frontiers in Microbiology source attribution foodborne pathogen epidemiological studies typing methods frequency-matching models population genetics models |
| title | Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne Diseases |
| title_full | Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne Diseases |
| title_fullStr | Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne Diseases |
| title_full_unstemmed | Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne Diseases |
| title_short | Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne Diseases |
| title_sort | critical orientation in the jungle of currently available methods and types of data for source attribution of foodborne diseases |
| topic | source attribution foodborne pathogen epidemiological studies typing methods frequency-matching models population genetics models |
| url | https://www.frontiersin.org/article/10.3389/fmicb.2019.02578/full |
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