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Cardim Falcao R, Edwards MR, Hurst M, Fraser E, Otterstatter M. A Review on Microbiological Source Attribution Methods of Human Salmonellosis: From Subtyping to Whole-Genome Sequencing. Foodborne Pathog Dis 2024; 21:137-146. [PMID: 38032610 PMCID: PMC10924193 DOI: 10.1089/fpd.2023.0075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023] Open
Abstract
Salmonella is one of the main causes of human foodborne illness. It is endemic worldwide, with different animals and animal-based food products as reservoirs and vehicles of infection. Identifying animal reservoirs and potential transmission pathways of Salmonella is essential for prevention and control. There are many approaches for source attribution, each using different statistical models and data streams. Some aim to identify the animal reservoir, while others aim to determine the point at which exposure occurred. With the advance of whole-genome sequencing (WGS) technologies, new source attribution models will greatly benefit from the discriminating power gained with WGS. This review discusses some key source attribution methods and their mathematical and statistical tools. We also highlight recent studies utilizing WGS for source attribution and discuss open questions and challenges in developing new WGS methods. We aim to provide a better understanding of the current state of these methodologies with application to Salmonella and other foodborne pathogens that are common sources of illness in the poultry and human sectors.
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Affiliation(s)
- Rebeca Cardim Falcao
- British Columbia Centre for Disease Control, Vancouver, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, Canada
| | - Megan R Edwards
- British Columbia Centre for Disease Control, Vancouver, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, Canada
| | - Matt Hurst
- Public Health Agency of Canada, Guelph, Canada
| | - Erin Fraser
- British Columbia Centre for Disease Control, Vancouver, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, Canada
| | - Michael Otterstatter
- British Columbia Centre for Disease Control, Vancouver, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, Canada
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Fastl C, De Carvalho Ferreira HC, Babo Martins S, Sucena Afonso J, di Bari C, Venkateswaran N, Pires SM, Mughini-Gras L, Huntington B, Rushton J, Pigott D, Devleesschauwer B. Animal sources of antimicrobial-resistant bacterial infections in humans: a systematic review. Epidemiol Infect 2023; 151:e143. [PMID: 37577944 PMCID: PMC10540179 DOI: 10.1017/s0950268823001309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 08/02/2023] [Accepted: 08/05/2023] [Indexed: 08/15/2023] Open
Abstract
Bacterial antimicrobial resistance (AMR) is among the leading global health challenges of the century. Animals and their products are known contributors to the human AMR burden, but the extent of this contribution is not clear. This systematic literature review aimed to identify studies investigating the direct impact of animal sources, defined as livestock, aquaculture, pets, and animal-based food, on human AMR. We searched four scientific databases and identified 31 relevant publications, including 12 risk assessments, 16 source attribution studies, and three other studies. Most studies were published between 2012 and 2022, and most came from Europe and North America, but we also identified five articles from South and South-East Asia. The studies differed in their methodologies, conceptual approaches (bottom-up, top-down, and complex), definitions of the AMR hazard and outcome, the number and type of sources they addressed, and the outcome measures they reported. The most frequently addressed animal source was chicken, followed by cattle and pigs. Most studies investigated bacteria-resistance combinations. Overall, studies on the direct contribution of animal sources of AMR are rare but increasing. More recent publications tailor their methodologies increasingly towards the AMR hazard as a whole, providing grounds for future research to build on.
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Affiliation(s)
- Christina Fastl
- Global Burden of Animal Diseases Programme, University of Liverpool, Liverpool, UK
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
| | | | - Sara Babo Martins
- Global Burden of Animal Diseases Programme, University of Liverpool, Liverpool, UK
- Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Neston, UK
| | - João Sucena Afonso
- Global Burden of Animal Diseases Programme, University of Liverpool, Liverpool, UK
- Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Neston, UK
| | - Carlotta di Bari
- Global Burden of Animal Diseases Programme, University of Liverpool, Liverpool, UK
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
- Department of Translational Physiology, Infectiology and Public Health, Ghent University, Merelbeke, Belgium
| | - Narmada Venkateswaran
- Global Burden of Animal Diseases Programme, University of Liverpool, Liverpool, UK
- Institute for Health Metrics and Evaluation, Department of Health Metrics Sciences, University of Washington, Seattle, WA, USA
| | | | - Lapo Mughini-Gras
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Faculty of Veterinary Medicine, Utrecht University, Institute for Risk Assessment Sciences (IRAS), Utrecht, The Netherlands
| | - Ben Huntington
- Global Burden of Animal Diseases Programme, University of Liverpool, Liverpool, UK
- Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Neston, UK
- Pengwern Animal Health Ltd, Wallasey, UK
| | - Jonathan Rushton
- Global Burden of Animal Diseases Programme, University of Liverpool, Liverpool, UK
- Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Neston, UK
| | - David Pigott
- Global Burden of Animal Diseases Programme, University of Liverpool, Liverpool, UK
- Institute for Health Metrics and Evaluation, Department of Health Metrics Sciences, University of Washington, Seattle, WA, USA
| | - Brecht Devleesschauwer
- Global Burden of Animal Diseases Programme, University of Liverpool, Liverpool, UK
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
- Department of Translational Physiology, Infectiology and Public Health, Ghent University, Merelbeke, Belgium
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Nouws S, Verhaegen B, Denayer S, Crombé F, Piérard D, Bogaerts B, Vanneste K, Marchal K, Roosens NHC, De Keersmaecker SCJ. Transforming Shiga toxin-producing Escherichia coli surveillance through whole genome sequencing in food safety practices. Front Microbiol 2023; 14:1204630. [PMID: 37520372 PMCID: PMC10381951 DOI: 10.3389/fmicb.2023.1204630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 06/22/2023] [Indexed: 08/01/2023] Open
Abstract
Introduction Shiga toxin-producing Escherichia coli (STEC) is a gastrointestinal pathogen causing foodborne outbreaks. Whole Genome Sequencing (WGS) in STEC surveillance holds promise in outbreak prevention and confinement, in broadening STEC epidemiology and in contributing to risk assessment and source attribution. However, despite international recommendations, WGS is often restricted to assist outbreak investigation and is not yet fully implemented in food safety surveillance across all European countries, in contrast to for example in the United States. Methods In this study, WGS was retrospectively applied to isolates collected within the context of Belgian food safety surveillance and combined with data from clinical isolates to evaluate its benefits. A cross-sector WGS-based collection of 754 strains from 1998 to 2020 was analyzed. Results We confirmed that WGS in food safety surveillance allows accurate detection of genomic relationships between human cases and strains isolated from food samples, including those dispersed over time and geographical locations. Identifying these links can reveal new insights into outbreaks and direct epidemiological investigations to facilitate outbreak management. Complete WGS-based isolate characterization enabled expanding epidemiological insights related to circulating serotypes, virulence genes and antimicrobial resistance across different reservoirs. Moreover, associations between virulence genes and severe disease were determined by incorporating human metadata into the data analysis. Gaps in the surveillance system were identified and suggestions for optimization related to sample centralization, harmonizing isolation methods, and expanding sampling strategies were formulated. Discussion This study contributes to developing a representative WGS-based collection of circulating STEC strains and by illustrating its benefits, it aims to incite policymakers to support WGS uptake in food safety surveillance.
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Affiliation(s)
- Stéphanie Nouws
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
- IDlab, Department of Information Technology, Ghent University—IMEC, Ghent, Belgium
| | - Bavo Verhaegen
- National Reference Laboratory for Shiga Toxin-Producing Escherichia coli (NRL STEC) and for Foodborne Outbreaks (NRL FBO), Foodborne Pathogens, Sciensano, Brussels, Belgium
| | - Sarah Denayer
- National Reference Laboratory for Shiga Toxin-Producing Escherichia coli (NRL STEC) and for Foodborne Outbreaks (NRL FBO), Foodborne Pathogens, Sciensano, Brussels, Belgium
| | - Florence Crombé
- National Reference Centre for Shiga Toxin-Producing Escherichia coli (NRC STEC), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, Brussels, Belgium
| | - Denis Piérard
- National Reference Centre for Shiga Toxin-Producing Escherichia coli (NRC STEC), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, Brussels, Belgium
| | - Bert Bogaerts
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Kevin Vanneste
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Kathleen Marchal
- IDlab, Department of Information Technology, Ghent University—IMEC, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
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Mughini-Gras L, Kooh P, Fravalo P, Augustin JC, Guillier L, David J, Thébault A, Carlin F, Leclercq A, Jourdan-Da-Silva N, Pavio N, Villena I, Sanaa M, Watier L. Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne Diseases. Front Microbiol 2019; 10:2578. [PMID: 31798549 PMCID: PMC6861836 DOI: 10.3389/fmicb.2019.02578] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 10/24/2019] [Indexed: 12/29/2022] Open
Abstract
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.
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Affiliation(s)
- Lapo Mughini-Gras
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.,Faculty of Veterinary Medicine, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | - Pauline Kooh
- Department of Risk Assessment, French Agency for Food, Environmental and Occupational Health and Safety, Maisons-Alfort, France
| | - Philippe Fravalo
- Research Chair in Meat-Safety, Faculty of Veterinary Medicine, University of Montreal, Saint-Hyacinthe, QC, Canada
| | | | - Laurent Guillier
- Laboratory for Food Safety, French Agency for Food, Environmental and Occupational Health and Safety, Maisons-Alfort, France
| | - Julie David
- Ploufragan-Plouzané Laboratory, French Agency for Food, Environmental and Occupational Health and Safety, Ploufragan, France
| | - Anne Thébault
- Department of Risk Assessment, French Agency for Food, Environmental and Occupational Health and Safety, Maisons-Alfort, France
| | - Frederic Carlin
- UMR 408 SQPOV "Sécurité et Qualité des Produits d'Origine Végétale" INRA, Avignon Université, Avignon, France
| | - Alexandre Leclercq
- Institut Pasteur, Biology of Infection Unit, National Reference Centre and WHO Collaborating Centre for Listeria, Paris, France
| | | | - Nicole Pavio
- Laboratory for Animal Health, French Agency for Food, Environmental and Occupational Health and Safety, Maisons-Alfort, France
| | - Isabelle Villena
- Laboratory of Parasitology-Mycology, EA ESCAPE, University of Reims Champagne-Ardenne, Reims, France
| | - Moez Sanaa
- Department of Risk Assessment, French Agency for Food, Environmental and Occupational Health and Safety, Maisons-Alfort, France
| | - Laurence Watier
- Department 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, France
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Abstract
Source attribution and microbial risk assessment methods have been widely applied for the control of several foodborne pathogens worldwide by identifying (i) the most important pathogen sources and (ii) the risk represented by specific foods and the critical points in these foods' production chains for microbial control. Such evidence has proved crucial for risk managers to identify and prioritize effective food safety and public health strategies. In the context of antimicrobial resistance (AMR) from livestock and pets, the utility of these methods is recognized, but a number of challenges have largely prevented their application and routine use. One key challenge has been to define the hazard in question: Is it the antimicrobial drug use in animals, the antimicrobial-resistant bacteria in animals and foods, or the antimicrobial resistance genes that can be transferred between commensal and pathogenic bacteria in the animal or human gut or in the environment? Other important limitations include the lack of occurrence and transmission data and the lack of evidence to inform dose-response relationships. We present the main principles, available methods, strengths, and weaknesses of source attribution and risk assessment methods, discuss their utility to identify sources and estimate risks of AMR from livestock and pets, and provide an overview of conducted studies. In addition, we discuss remaining challenges and current and future opportunities to improve methods and knowledge of the sources and transmission routes of AMR from animals through food, direct contact, or the environment, including improvements in surveillance and developments in genotypic typing methods.
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Mughini-Gras L, Kooh P, Augustin JC, David J, Fravalo P, Guillier L, Jourdan-Da-Silva N, Thébault A, Sanaa M, Watier L. Source Attribution of Foodborne Diseases: Potentialities, Hurdles, and Future Expectations. Front Microbiol 2018; 9:1983. [PMID: 30233509 PMCID: PMC6129602 DOI: 10.3389/fmicb.2018.01983] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Accepted: 08/06/2018] [Indexed: 11/21/2022] Open
Affiliation(s)
- Lapo Mughini-Gras
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.,Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands
| | - Pauline Kooh
- Risk Assessment Department, French Agency for Food, Environmental and Occupational Health & Safety (Anses), Maisons-Alfort, France
| | | | - Julie David
- Ploufragan-Plouzané Laboratory, French Agency for Food, Environmental and Occupational Health & Safety (Anses), Ploufragan, France
| | - Philippe Fravalo
- NSERC Industrial Research Chair in Meat-Safety (CRSV), Faculty of Veterinary Medicine, University of Montreal, Saint-Hyacinthe, QC, Canada
| | - Laurent Guillier
- Laboratory for Food Safety, French Agency for Food, Environmental and Occupational Health & Safety (Anses), Maisons-Alfort, France
| | | | - Anne Thébault
- Risk Assessment Department, French Agency for Food, Environmental and Occupational Health & Safety (Anses), Maisons-Alfort, France
| | - Moez Sanaa
- Risk Assessment Department, French Agency for Food, Environmental and Occupational Health & Safety (Anses), Maisons-Alfort, France
| | - Laurence Watier
- Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), Inserm, UVSQ, Institut Pasteur, Université Paris-Saclay, Paris, France
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Karp BE, Tate H, Plumblee JR, Dessai U, Whichard JM, Thacker EL, Hale KR, Wilson W, Friedman CR, Griffin PM, McDermott PF. National Antimicrobial Resistance Monitoring System: Two Decades of Advancing Public Health Through Integrated Surveillance of Antimicrobial Resistance. Foodborne Pathog Dis 2017; 14:545-557. [PMID: 28792800 PMCID: PMC5650714 DOI: 10.1089/fpd.2017.2283] [Citation(s) in RCA: 105] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Drug-resistant bacterial infections pose a serious and growing public health threat globally. In this review, we describe the role of the National Antimicrobial Resistance Monitoring System (NARMS) in providing data that help address the resistance problem and show how such a program can have broad positive impacts on public health. NARMS was formed two decades ago to help assess the consequences to human health arising from the use of antimicrobial drugs in food animal production in the United States. A collaboration among the Centers for Disease Control and Prevention, the U.S. Food and Drug Administration, the United States Department of Agriculture, and state and local health departments, NARMS uses an integrated "One Health" approach to monitor antimicrobial resistance in enteric bacteria from humans, retail meat, and food animals. NARMS has adapted to changing needs and threats by expanding surveillance catchment areas, examining new isolate sources, adding bacteria, adjusting sampling schemes, and modifying antimicrobial agents tested. NARMS data are not only essential for ensuring that antimicrobial drugs approved for food animals are used in ways that are safe for human health but they also help address broader food safety priorities. NARMS surveillance, applied research studies, and outbreak isolate testing provide data on the emergence of drug-resistant enteric bacteria; genetic mechanisms underlying resistance; movement of bacterial populations among humans, food, and food animals; and sources and outcomes of resistant and susceptible infections. These data can be used to guide and evaluate the impact of science-based policies, regulatory actions, antimicrobial stewardship initiatives, and other public health efforts aimed at preserving drug effectiveness, improving patient outcomes, and preventing infections. Many improvements have been made to NARMS over time and the program will continue to adapt to address emerging resistance threats, changes in clinical diagnostic practices, and new technologies, such as whole genome sequencing.
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Affiliation(s)
- Beth E. Karp
- Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Heather Tate
- Office of Research, Center for Veterinary Medicine, U.S. Food and Drug Administration, Laurel, Maryland
| | - Jodie R. Plumblee
- Agricultural Research Service, United States Department of Agriculture, Athens, Georgia
| | - Uday Dessai
- Food Safety and Inspection Service, United States Department of Agriculture, Washington, District of Columbia
| | - Jean M. Whichard
- Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Eileen L. Thacker
- Agricultural Research Service, United States Department of Agriculture, Athens, Georgia
| | - Kis Robertson Hale
- Food Safety and Inspection Service, United States Department of Agriculture, Washington, District of Columbia
| | - Wanda Wilson
- Food Safety and Inspection Service, United States Department of Agriculture, Washington, District of Columbia
| | - Cindy R. Friedman
- Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Patricia M. Griffin
- Division of Foodborne, Waterborne, and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Patrick F. McDermott
- Office of Research, Center for Veterinary Medicine, U.S. Food and Drug Administration, Laurel, Maryland
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Mughini-Gras L, Franz E, van Pelt W. New paradigms for Salmonella source attribution based on microbial subtyping. Food Microbiol 2017; 71:60-67. [PMID: 29366470 DOI: 10.1016/j.fm.2017.03.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Revised: 02/24/2017] [Accepted: 03/03/2017] [Indexed: 10/19/2022]
Abstract
Microbial subtyping is the most common approach for Salmonella source attribution. Typically, attributions are computed using frequency-matching models like the Dutch and Danish models based on phenotyping data (serotyping, phage-typing, and antimicrobial resistance profiling). Herewith, we critically review three major paradigms facing Salmonella source attribution today: (i) the use of genotyping data, particularly Multi-Locus Variable Number of Tandem Repeats Analysis (MLVA), which is replacing traditional Salmonella phenotyping beyond serotyping; (ii) the integration of case-control data into source attribution to improve risk factor identification/characterization; (iii) the investigation of non-food sources, as attributions tend to focus on foods of animal origin only. Population genetics models or simplified MLVA schemes may provide feasible options for source attribution, although there is a strong need to explore novel modelling options as we move towards whole-genome sequencing as the standard. Classical case-control studies are enhanced by incorporating source attribution results, as individuals acquiring salmonellosis from different sources have different associated risk factors. Thus, the more such analyses are performed the better Salmonella epidemiology will be understood. Reparametrizing current models allows for inclusion of sources like reptiles, the study of which improves our understanding of Salmonella epidemiology beyond food to tackle the pathogen in a more holistic way.
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Affiliation(s)
- Lapo Mughini-Gras
- National Institute for Public Health and the Environment (RIVM), Centre for Infectious Disease Control (CIb), Bilthoven, The Netherlands; Utrecht University, Department of Infectious Diseases and Immunology, Utrecht, The Netherlands.
| | - Eelco Franz
- National Institute for Public Health and the Environment (RIVM), Centre for Infectious Disease Control (CIb), Bilthoven, The Netherlands
| | - Wilfrid van Pelt
- National Institute for Public Health and the Environment (RIVM), Centre for Infectious Disease Control (CIb), Bilthoven, The Netherlands
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