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Measuring distance through dense weighted networks: The case of hospital-associated pathogens

Hospital networks, formed by patients visiting multiple hospitals, affect the spread of hospital-associated infections, resulting in differences in risks for hospitals depending on their network position. These networks are increasingly used to inform strategies to prevent and control the spread of...

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Autores principales: Donker, Tjibbe, Smieszek, Timo, Henderson, Katherine L., Johnson, Alan P., Walker, A. Sarah, Robotham, Julie V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5542422/
https://www.ncbi.nlm.nih.gov/pubmed/28771581
http://dx.doi.org/10.1371/journal.pcbi.1005622
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author Donker, Tjibbe
Smieszek, Timo
Henderson, Katherine L.
Johnson, Alan P.
Walker, A. Sarah
Robotham, Julie V.
author_facet Donker, Tjibbe
Smieszek, Timo
Henderson, Katherine L.
Johnson, Alan P.
Walker, A. Sarah
Robotham, Julie V.
author_sort Donker, Tjibbe
collection PubMed
description Hospital networks, formed by patients visiting multiple hospitals, affect the spread of hospital-associated infections, resulting in differences in risks for hospitals depending on their network position. These networks are increasingly used to inform strategies to prevent and control the spread of hospital-associated pathogens. However, many studies only consider patients that are received directly from the initial hospital, without considering the effect of indirect trajectories through the network. We determine the optimal way to measure the distance between hospitals within the network, by reconstructing the English hospital network based on shared patients in 2014–2015, and simulating the spread of a hospital-associated pathogen between hospitals, taking into consideration that each intermediate hospital conveys a delay in the further spread of the pathogen. While the risk of transferring a hospital-associated pathogen between directly neighbouring hospitals is a direct reflection of the number of shared patients, the distance between two hospitals far-away in the network is determined largely by the number of intermediate hospitals in the network. Because the network is dense, most long distance transmission chains in fact involve only few intermediate steps, spreading along the many weak links. The dense connectivity of hospital networks, together with a strong regional structure, causes hospital-associated pathogens to spread from the initial outbreak in a two-step process: first, the directly surrounding hospitals are affected through the strong connections, second all other hospitals receive introductions through the multitude of weaker links. Although the strong connections matter for local spread, weak links in the network can offer ideal routes for hospital-associated pathogens to travel further faster. This hold important implications for infection prevention and control efforts: if a local outbreak is not controlled in time, colonised patients will appear in other regions, irrespective of the distance to the initial outbreak, making import screening ever more difficult.
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spelling pubmed-55424222017-08-12 Measuring distance through dense weighted networks: The case of hospital-associated pathogens Donker, Tjibbe Smieszek, Timo Henderson, Katherine L. Johnson, Alan P. Walker, A. Sarah Robotham, Julie V. PLoS Comput Biol Research Article Hospital networks, formed by patients visiting multiple hospitals, affect the spread of hospital-associated infections, resulting in differences in risks for hospitals depending on their network position. These networks are increasingly used to inform strategies to prevent and control the spread of hospital-associated pathogens. However, many studies only consider patients that are received directly from the initial hospital, without considering the effect of indirect trajectories through the network. We determine the optimal way to measure the distance between hospitals within the network, by reconstructing the English hospital network based on shared patients in 2014–2015, and simulating the spread of a hospital-associated pathogen between hospitals, taking into consideration that each intermediate hospital conveys a delay in the further spread of the pathogen. While the risk of transferring a hospital-associated pathogen between directly neighbouring hospitals is a direct reflection of the number of shared patients, the distance between two hospitals far-away in the network is determined largely by the number of intermediate hospitals in the network. Because the network is dense, most long distance transmission chains in fact involve only few intermediate steps, spreading along the many weak links. The dense connectivity of hospital networks, together with a strong regional structure, causes hospital-associated pathogens to spread from the initial outbreak in a two-step process: first, the directly surrounding hospitals are affected through the strong connections, second all other hospitals receive introductions through the multitude of weaker links. Although the strong connections matter for local spread, weak links in the network can offer ideal routes for hospital-associated pathogens to travel further faster. This hold important implications for infection prevention and control efforts: if a local outbreak is not controlled in time, colonised patients will appear in other regions, irrespective of the distance to the initial outbreak, making import screening ever more difficult. Public Library of Science 2017-08-03 /pmc/articles/PMC5542422/ /pubmed/28771581 http://dx.doi.org/10.1371/journal.pcbi.1005622 Text en © 2017 Donker et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Donker, Tjibbe
Smieszek, Timo
Henderson, Katherine L.
Johnson, Alan P.
Walker, A. Sarah
Robotham, Julie V.
Measuring distance through dense weighted networks: The case of hospital-associated pathogens
title Measuring distance through dense weighted networks: The case of hospital-associated pathogens
title_full Measuring distance through dense weighted networks: The case of hospital-associated pathogens
title_fullStr Measuring distance through dense weighted networks: The case of hospital-associated pathogens
title_full_unstemmed Measuring distance through dense weighted networks: The case of hospital-associated pathogens
title_short Measuring distance through dense weighted networks: The case of hospital-associated pathogens
title_sort measuring distance through dense weighted networks: the case of hospital-associated pathogens
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5542422/
https://www.ncbi.nlm.nih.gov/pubmed/28771581
http://dx.doi.org/10.1371/journal.pcbi.1005622
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