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Waterborne Disease Outbreak Detection: A Simulation-Based Study
Waterborne disease outbreaks (WBDOs) remain a public health issue in developed countries, but to date the surveillance of WBDOs in France, mainly based on the voluntary reporting of clusters of acute gastrointestinal infections (AGIs) by general practitioners to health authorities, is characterized...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068474/ https://www.ncbi.nlm.nih.gov/pubmed/30018195 http://dx.doi.org/10.3390/ijerph15071505 |
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author | Mouly, Damien Goria, Sarah Mounié, Michael Beaudeau, Pascal Galey, Catherine Gallay, Anne Ducrot, Christian Le Strat, Yann |
author_facet | Mouly, Damien Goria, Sarah Mounié, Michael Beaudeau, Pascal Galey, Catherine Gallay, Anne Ducrot, Christian Le Strat, Yann |
author_sort | Mouly, Damien |
collection | PubMed |
description | Waterborne disease outbreaks (WBDOs) remain a public health issue in developed countries, but to date the surveillance of WBDOs in France, mainly based on the voluntary reporting of clusters of acute gastrointestinal infections (AGIs) by general practitioners to health authorities, is characterized by low sensitivity. In this context, a detection algorithm using health insurance data and based on a space–time method was developed to improve WBDO detection. The objective of the present simulation-based study was to evaluate the performance of this algorithm for WBDO detection using health insurance data. The daily baseline counts of acute gastrointestinal infections were simulated. Two thousand simulated WBDO signals were then superimposed on the baseline data. Sensitivity (Se) and positive predictive value (PPV) were both used to evaluate the detection algorithm. Multivariate regression was also performed to identify the factors associated with WBDO detection. Almost three-quarters of the simulated WBDOs were detected (Se = 73.0%). More than 9 out of 10 detected signals corresponded to a WBDO (PPV = 90.5%). The probability of detecting a WBDO increased with the outbreak size. These results underline the value of using the detection algorithm for the implementation of a national surveillance system for WBDOs in France. |
format | Online Article Text |
id | pubmed-6068474 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-60684742018-08-07 Waterborne Disease Outbreak Detection: A Simulation-Based Study Mouly, Damien Goria, Sarah Mounié, Michael Beaudeau, Pascal Galey, Catherine Gallay, Anne Ducrot, Christian Le Strat, Yann Int J Environ Res Public Health Article Waterborne disease outbreaks (WBDOs) remain a public health issue in developed countries, but to date the surveillance of WBDOs in France, mainly based on the voluntary reporting of clusters of acute gastrointestinal infections (AGIs) by general practitioners to health authorities, is characterized by low sensitivity. In this context, a detection algorithm using health insurance data and based on a space–time method was developed to improve WBDO detection. The objective of the present simulation-based study was to evaluate the performance of this algorithm for WBDO detection using health insurance data. The daily baseline counts of acute gastrointestinal infections were simulated. Two thousand simulated WBDO signals were then superimposed on the baseline data. Sensitivity (Se) and positive predictive value (PPV) were both used to evaluate the detection algorithm. Multivariate regression was also performed to identify the factors associated with WBDO detection. Almost three-quarters of the simulated WBDOs were detected (Se = 73.0%). More than 9 out of 10 detected signals corresponded to a WBDO (PPV = 90.5%). The probability of detecting a WBDO increased with the outbreak size. These results underline the value of using the detection algorithm for the implementation of a national surveillance system for WBDOs in France. MDPI 2018-07-17 2018-07 /pmc/articles/PMC6068474/ /pubmed/30018195 http://dx.doi.org/10.3390/ijerph15071505 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Mouly, Damien Goria, Sarah Mounié, Michael Beaudeau, Pascal Galey, Catherine Gallay, Anne Ducrot, Christian Le Strat, Yann Waterborne Disease Outbreak Detection: A Simulation-Based Study |
title | Waterborne Disease Outbreak Detection: A Simulation-Based Study |
title_full | Waterborne Disease Outbreak Detection: A Simulation-Based Study |
title_fullStr | Waterborne Disease Outbreak Detection: A Simulation-Based Study |
title_full_unstemmed | Waterborne Disease Outbreak Detection: A Simulation-Based Study |
title_short | Waterborne Disease Outbreak Detection: A Simulation-Based Study |
title_sort | waterborne disease outbreak detection: a simulation-based study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068474/ https://www.ncbi.nlm.nih.gov/pubmed/30018195 http://dx.doi.org/10.3390/ijerph15071505 |
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