Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Standard

Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark. / de Knegt, Leonardo; Pires, Sara Monteiro; Löfström, Charlotta; Sørensen, Gitte; Pedersen, Karl; Torpdahl, Mia; Nielsen, Eva M; Hald, Tine.

I: Risk Analysis, Bind 36, Nr. 3, 2016, s. 571-588.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

de Knegt, L, Pires, SM, Löfström, C, Sørensen, G, Pedersen, K, Torpdahl, M, Nielsen, EM & Hald, T 2016, 'Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark', Risk Analysis, bind 36, nr. 3, s. 571-588. https://doi.org/10.1111/risa.12483

APA

de Knegt, L., Pires, S. M., Löfström, C., Sørensen, G., Pedersen, K., Torpdahl, M., Nielsen, E. M., & Hald, T. (2016). Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark. Risk Analysis, 36(3), 571-588. https://doi.org/10.1111/risa.12483

Vancouver

de Knegt L, Pires SM, Löfström C, Sørensen G, Pedersen K, Torpdahl M o.a. Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark. Risk Analysis. 2016;36(3):571-588. https://doi.org/10.1111/risa.12483

Author

de Knegt, Leonardo ; Pires, Sara Monteiro ; Löfström, Charlotta ; Sørensen, Gitte ; Pedersen, Karl ; Torpdahl, Mia ; Nielsen, Eva M ; Hald, Tine. / Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark. I: Risk Analysis. 2016 ; Bind 36, Nr. 3. s. 571-588.

Bibtex

@article{b93c48b7d10844a9902473c11bdb491e,
title = "Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark",
abstract = "Salmonella is an important cause of bacterial foodborne infections in Denmark. To identify the main animal‐food sources of human salmonellosis, risk managers have relied on a routine application of a microbial subtyping‐based source attribution model since 1995. In 2013, multiple locus variable number tandem repeat analysis (MLVA) substituted phage typing as the subtyping method for surveillance of S. Enteritidis and S. Typhimurium isolated from animals, food, and humans in Denmark. The purpose of this study was to develop a modeling approach applying a combination of serovars, MLVA types, and antibiotic resistance profiles for the Salmonella source attribution, and assess the utility of the results for the food safety decisionmakers. Full and simplified MLVA schemes from surveillance data were tested, and model fit and consistency of results were assessed using statistical measures. We conclude that loci schemes STTR5/STTR10/STTR3 for S. Typhimurium and SE9/SE5/SE2/SE1/SE3 for S. Enteritidis can be used in microbial subtyping‐based source attribution models. Based on the results, we discuss that an adjustment of the discriminatory level of the subtyping method applied often will be required to fit the purpose of the study and the available data. The issues discussed are also considered highly relevant when applying, e.g., extended multi‐locus sequence typing or next‐generation sequencing techniques.",
keywords = "Bayesian inference, MLVA, Salmonella, source attribution, surveillance",
author = "{de Knegt}, Leonardo and Pires, {Sara Monteiro} and Charlotta L{\"o}fstr{\"o}m and Gitte S{\o}rensen and Karl Pedersen and Mia Torpdahl and Nielsen, {Eva M} and Tine Hald",
year = "2016",
doi = "10.1111/risa.12483",
language = "English",
volume = "36",
pages = "571--588",
journal = "Risk Analysis",
issn = "0272-4332",
publisher = "Wiley-Blackwell",
number = "3",

}

RIS

TY - JOUR

T1 - Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark

AU - de Knegt, Leonardo

AU - Pires, Sara Monteiro

AU - Löfström, Charlotta

AU - Sørensen, Gitte

AU - Pedersen, Karl

AU - Torpdahl, Mia

AU - Nielsen, Eva M

AU - Hald, Tine

PY - 2016

Y1 - 2016

N2 - Salmonella is an important cause of bacterial foodborne infections in Denmark. To identify the main animal‐food sources of human salmonellosis, risk managers have relied on a routine application of a microbial subtyping‐based source attribution model since 1995. In 2013, multiple locus variable number tandem repeat analysis (MLVA) substituted phage typing as the subtyping method for surveillance of S. Enteritidis and S. Typhimurium isolated from animals, food, and humans in Denmark. The purpose of this study was to develop a modeling approach applying a combination of serovars, MLVA types, and antibiotic resistance profiles for the Salmonella source attribution, and assess the utility of the results for the food safety decisionmakers. Full and simplified MLVA schemes from surveillance data were tested, and model fit and consistency of results were assessed using statistical measures. We conclude that loci schemes STTR5/STTR10/STTR3 for S. Typhimurium and SE9/SE5/SE2/SE1/SE3 for S. Enteritidis can be used in microbial subtyping‐based source attribution models. Based on the results, we discuss that an adjustment of the discriminatory level of the subtyping method applied often will be required to fit the purpose of the study and the available data. The issues discussed are also considered highly relevant when applying, e.g., extended multi‐locus sequence typing or next‐generation sequencing techniques.

AB - Salmonella is an important cause of bacterial foodborne infections in Denmark. To identify the main animal‐food sources of human salmonellosis, risk managers have relied on a routine application of a microbial subtyping‐based source attribution model since 1995. In 2013, multiple locus variable number tandem repeat analysis (MLVA) substituted phage typing as the subtyping method for surveillance of S. Enteritidis and S. Typhimurium isolated from animals, food, and humans in Denmark. The purpose of this study was to develop a modeling approach applying a combination of serovars, MLVA types, and antibiotic resistance profiles for the Salmonella source attribution, and assess the utility of the results for the food safety decisionmakers. Full and simplified MLVA schemes from surveillance data were tested, and model fit and consistency of results were assessed using statistical measures. We conclude that loci schemes STTR5/STTR10/STTR3 for S. Typhimurium and SE9/SE5/SE2/SE1/SE3 for S. Enteritidis can be used in microbial subtyping‐based source attribution models. Based on the results, we discuss that an adjustment of the discriminatory level of the subtyping method applied often will be required to fit the purpose of the study and the available data. The issues discussed are also considered highly relevant when applying, e.g., extended multi‐locus sequence typing or next‐generation sequencing techniques.

KW - Bayesian inference, MLVA, Salmonella

KW - source attribution, surveillance

U2 - 10.1111/risa.12483

DO - 10.1111/risa.12483

M3 - Journal article

VL - 36

SP - 571

EP - 588

JO - Risk Analysis

JF - Risk Analysis

SN - 0272-4332

IS - 3

ER -

ID: 192565924