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Changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens
The current paradigm for hospital outbreak detection and investigation is based on methodology first developed over 150 years ago. Daily surveillance to detect patients positive for pathogens of particular importance for nosocomial infection is supported by epidemiological investigation to determine...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611365/ https://www.ncbi.nlm.nih.gov/pubmed/30052172 http://dx.doi.org/10.1099/mic.0.000700 |
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author | Peacock, Sharon J. Parkhill, Julian Brown, Nicholas M. |
author_facet | Peacock, Sharon J. Parkhill, Julian Brown, Nicholas M. |
author_sort | Peacock, Sharon J. |
collection | PubMed |
description | The current paradigm for hospital outbreak detection and investigation is based on methodology first developed over 150 years ago. Daily surveillance to detect patients positive for pathogens of particular importance for nosocomial infection is supported by epidemiological investigation to determine their relationship in time and place, and to identify any other factor that could link them. The antibiotic resistance pattern is commonly used as a surrogate for bacterial relatedness, although this lacks sensitivity and specificity. Typing may be used to define bacterial relatedness, although routine methods lack sufficient discriminatory power to distinguish relatedness beyond the level of bacterial clones. Ultimately, the identification of an outbreak remains a predominately subjective process reliant on the intuition of experienced infection control professionals. Here, we propose a redesign of hospital outbreak detection and investigation in which bacterial species associated with nosocomial transmission and infection undergo routine prospective whole-genome sequencing. Further investigation is based on the probability that isolates are associated with an outbreak, which is based on the degree of genetic relatedness between isolates. Evidence is provided that supports this model based on studies of MRSA (methicillin-resistant Staphylococcus aureus), together with the benefits of a ‘Sequence First’ approach. The feasibility of implementation is discussed, together with residual barriers that need to be overcome prior to implementation. |
format | Online Article Text |
id | pubmed-7611365 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76113652021-07-26 Changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens Peacock, Sharon J. Parkhill, Julian Brown, Nicholas M. Microbiology (Reading) Article The current paradigm for hospital outbreak detection and investigation is based on methodology first developed over 150 years ago. Daily surveillance to detect patients positive for pathogens of particular importance for nosocomial infection is supported by epidemiological investigation to determine their relationship in time and place, and to identify any other factor that could link them. The antibiotic resistance pattern is commonly used as a surrogate for bacterial relatedness, although this lacks sensitivity and specificity. Typing may be used to define bacterial relatedness, although routine methods lack sufficient discriminatory power to distinguish relatedness beyond the level of bacterial clones. Ultimately, the identification of an outbreak remains a predominately subjective process reliant on the intuition of experienced infection control professionals. Here, we propose a redesign of hospital outbreak detection and investigation in which bacterial species associated with nosocomial transmission and infection undergo routine prospective whole-genome sequencing. Further investigation is based on the probability that isolates are associated with an outbreak, which is based on the degree of genetic relatedness between isolates. Evidence is provided that supports this model based on studies of MRSA (methicillin-resistant Staphylococcus aureus), together with the benefits of a ‘Sequence First’ approach. The feasibility of implementation is discussed, together with residual barriers that need to be overcome prior to implementation. 2018-10-01 2018-07-27 /pmc/articles/PMC7611365/ /pubmed/30052172 http://dx.doi.org/10.1099/mic.0.000700 Text en https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | Article Peacock, Sharon J. Parkhill, Julian Brown, Nicholas M. Changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens |
title | Changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens |
title_full | Changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens |
title_fullStr | Changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens |
title_full_unstemmed | Changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens |
title_short | Changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens |
title_sort | changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611365/ https://www.ncbi.nlm.nih.gov/pubmed/30052172 http://dx.doi.org/10.1099/mic.0.000700 |
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