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Mathematical modelling of vancomycin-resistant enterococci transmission during passive surveillance and active surveillance with contact isolation highlights the need to identify and address the source of acquisition
BACKGROUND: Clinical studies and mathematical simulation suggest that active surveillance with contact isolation is associated with reduced vancomycin-resistant enterococci (VRE) prevalence compared to passive surveillance. Models using pre- and post-intervention data that account for the imperfect...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6182842/ https://www.ncbi.nlm.nih.gov/pubmed/30309313 http://dx.doi.org/10.1186/s12879-018-3388-y |
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author | Cheah, Agnes Loo Yee Cheng, Allen C. Spelman, Denis Nation, Roger L. Kong, David C. M. McBryde, Emma S. |
author_facet | Cheah, Agnes Loo Yee Cheng, Allen C. Spelman, Denis Nation, Roger L. Kong, David C. M. McBryde, Emma S. |
author_sort | Cheah, Agnes Loo Yee |
collection | PubMed |
description | BACKGROUND: Clinical studies and mathematical simulation suggest that active surveillance with contact isolation is associated with reduced vancomycin-resistant enterococci (VRE) prevalence compared to passive surveillance. Models using pre- and post-intervention data that account for the imperfect observation and serial dependence of VRE transmission events can better estimate the effectiveness of active surveillance and subsequent contact isolation; however, such analyses have not been performed. METHODS: A mathematical model was fitted to surveillance data collected pre- and post-implementation of active surveillance with contact isolation in the haematology-oncology ward. We developed a Hidden Markov Model to describe undetected and observed VRE colonisation/infection status based on the detection activities in the ward. Bayesian inference was used to estimate transmission rates. The effectiveness of active surveillance was assumed to be via increased detection and subsequent contact isolation of VRE positive patients. RESULTS: We estimated that 31% (95% credible interval: 0.33–85%) of the VRE transmissions were due to cross-transmission between patients. The ratio of transmission rates from patients with contact isolation versus those without contact isolation was 0.33 (95% credible interval: 0.050–1.22). CONCLUSIONS: The majority of the VRE acquisitions in the haematology-oncology ward was estimated to be due to background rates of VRE, rather than within ward patient to patient acquisition. The credible interval for cross-transmission was wide which results in a large degree of uncertainty in the estimates. Factors that could account for background VRE acquisition include endogenous acquisition from antibiotic selection pressure and VRE in the environment. Contact isolation was not significantly associated with reduced VRE transmission in settings where the majority of VRE acquisition was due to background acquisition, emphasising the need to identify and address the source of acquisition. As the credible interval for the ratio of VRE transmission in contact isolated versus non-contact isolated patients crossed 1, there is a probability that the transmission rate in contact isolation was not lower. Our finding highlights the need to optimise infection control measures other than active surveillance for VRE and subsequent contact isolation to reduce VRE transmission. Such measures could include antimicrobial stewardship, environmental cleaning, and hand hygiene. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-018-3388-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6182842 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61828422018-10-18 Mathematical modelling of vancomycin-resistant enterococci transmission during passive surveillance and active surveillance with contact isolation highlights the need to identify and address the source of acquisition Cheah, Agnes Loo Yee Cheng, Allen C. Spelman, Denis Nation, Roger L. Kong, David C. M. McBryde, Emma S. BMC Infect Dis Research Article BACKGROUND: Clinical studies and mathematical simulation suggest that active surveillance with contact isolation is associated with reduced vancomycin-resistant enterococci (VRE) prevalence compared to passive surveillance. Models using pre- and post-intervention data that account for the imperfect observation and serial dependence of VRE transmission events can better estimate the effectiveness of active surveillance and subsequent contact isolation; however, such analyses have not been performed. METHODS: A mathematical model was fitted to surveillance data collected pre- and post-implementation of active surveillance with contact isolation in the haematology-oncology ward. We developed a Hidden Markov Model to describe undetected and observed VRE colonisation/infection status based on the detection activities in the ward. Bayesian inference was used to estimate transmission rates. The effectiveness of active surveillance was assumed to be via increased detection and subsequent contact isolation of VRE positive patients. RESULTS: We estimated that 31% (95% credible interval: 0.33–85%) of the VRE transmissions were due to cross-transmission between patients. The ratio of transmission rates from patients with contact isolation versus those without contact isolation was 0.33 (95% credible interval: 0.050–1.22). CONCLUSIONS: The majority of the VRE acquisitions in the haematology-oncology ward was estimated to be due to background rates of VRE, rather than within ward patient to patient acquisition. The credible interval for cross-transmission was wide which results in a large degree of uncertainty in the estimates. Factors that could account for background VRE acquisition include endogenous acquisition from antibiotic selection pressure and VRE in the environment. Contact isolation was not significantly associated with reduced VRE transmission in settings where the majority of VRE acquisition was due to background acquisition, emphasising the need to identify and address the source of acquisition. As the credible interval for the ratio of VRE transmission in contact isolated versus non-contact isolated patients crossed 1, there is a probability that the transmission rate in contact isolation was not lower. Our finding highlights the need to optimise infection control measures other than active surveillance for VRE and subsequent contact isolation to reduce VRE transmission. Such measures could include antimicrobial stewardship, environmental cleaning, and hand hygiene. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-018-3388-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-11 /pmc/articles/PMC6182842/ /pubmed/30309313 http://dx.doi.org/10.1186/s12879-018-3388-y Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Cheah, Agnes Loo Yee Cheng, Allen C. Spelman, Denis Nation, Roger L. Kong, David C. M. McBryde, Emma S. Mathematical modelling of vancomycin-resistant enterococci transmission during passive surveillance and active surveillance with contact isolation highlights the need to identify and address the source of acquisition |
title | Mathematical modelling of vancomycin-resistant enterococci transmission during passive surveillance and active surveillance with contact isolation highlights the need to identify and address the source of acquisition |
title_full | Mathematical modelling of vancomycin-resistant enterococci transmission during passive surveillance and active surveillance with contact isolation highlights the need to identify and address the source of acquisition |
title_fullStr | Mathematical modelling of vancomycin-resistant enterococci transmission during passive surveillance and active surveillance with contact isolation highlights the need to identify and address the source of acquisition |
title_full_unstemmed | Mathematical modelling of vancomycin-resistant enterococci transmission during passive surveillance and active surveillance with contact isolation highlights the need to identify and address the source of acquisition |
title_short | Mathematical modelling of vancomycin-resistant enterococci transmission during passive surveillance and active surveillance with contact isolation highlights the need to identify and address the source of acquisition |
title_sort | mathematical modelling of vancomycin-resistant enterococci transmission during passive surveillance and active surveillance with contact isolation highlights the need to identify and address the source of acquisition |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6182842/ https://www.ncbi.nlm.nih.gov/pubmed/30309313 http://dx.doi.org/10.1186/s12879-018-3388-y |
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