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Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus
Methicillin-resistant Staphylococcus aureus (MRSA) is a continued threat to human health in both community and healthcare settings. In hospitals, control efforts would benefit from accurate estimation of asymptomatic colonization and infection importation rates from the community. However, developin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298769/ https://www.ncbi.nlm.nih.gov/pubmed/30560786 http://dx.doi.org/10.7554/eLife.40977 |
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author | Pei, Sen Morone, Flaviano Liljeros, Fredrik Makse, Hernán Shaman, Jeffrey L |
author_facet | Pei, Sen Morone, Flaviano Liljeros, Fredrik Makse, Hernán Shaman, Jeffrey L |
author_sort | Pei, Sen |
collection | PubMed |
description | Methicillin-resistant Staphylococcus aureus (MRSA) is a continued threat to human health in both community and healthcare settings. In hospitals, control efforts would benefit from accurate estimation of asymptomatic colonization and infection importation rates from the community. However, developing such estimates remains challenging due to limited observation of colonization and complicated transmission dynamics within hospitals and the community. Here, we develop an inference framework that can estimate these key quantities by combining statistical filtering techniques, an agent-based model, and real-world patient-to-patient contact networks, and use this framework to infer nosocomial transmission and infection importation over an outbreak spanning 6 years in 66 Swedish hospitals. In particular, we identify a small number of patients with disproportionately high risk of colonization. In retrospective control experiments, interventions targeted to these individuals yield a substantial improvement over heuristic strategies informed by number of contacts, length of stay and contact tracing. |
format | Online Article Text |
id | pubmed-6298769 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-62987692018-12-18 Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus Pei, Sen Morone, Flaviano Liljeros, Fredrik Makse, Hernán Shaman, Jeffrey L eLife Computational and Systems Biology Methicillin-resistant Staphylococcus aureus (MRSA) is a continued threat to human health in both community and healthcare settings. In hospitals, control efforts would benefit from accurate estimation of asymptomatic colonization and infection importation rates from the community. However, developing such estimates remains challenging due to limited observation of colonization and complicated transmission dynamics within hospitals and the community. Here, we develop an inference framework that can estimate these key quantities by combining statistical filtering techniques, an agent-based model, and real-world patient-to-patient contact networks, and use this framework to infer nosocomial transmission and infection importation over an outbreak spanning 6 years in 66 Swedish hospitals. In particular, we identify a small number of patients with disproportionately high risk of colonization. In retrospective control experiments, interventions targeted to these individuals yield a substantial improvement over heuristic strategies informed by number of contacts, length of stay and contact tracing. eLife Sciences Publications, Ltd 2018-12-18 /pmc/articles/PMC6298769/ /pubmed/30560786 http://dx.doi.org/10.7554/eLife.40977 Text en © 2018, Pei et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Computational and Systems Biology Pei, Sen Morone, Flaviano Liljeros, Fredrik Makse, Hernán Shaman, Jeffrey L Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus |
title | Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus |
title_full | Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus |
title_fullStr | Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus |
title_full_unstemmed | Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus |
title_short | Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus |
title_sort | inference and control of the nosocomial transmission of methicillin-resistant staphylococcus aureus |
topic | Computational and Systems Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298769/ https://www.ncbi.nlm.nih.gov/pubmed/30560786 http://dx.doi.org/10.7554/eLife.40977 |
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