Next Article in Journal
Understanding the Influence of Crop Residue Burning on PM2.5 and PM10 Concentrations in China from 2013 to 2017 Using MODIS Data
Next Article in Special Issue
Drinking Water Nitrate and Human Health: An Updated Review
Previous Article in Journal
Use of an E2SFCA Method to Measure and Analyse Spatial Accessibility to Medical Services for Elderly People in Wuhan, China
Previous Article in Special Issue
A Physiologically-Based Pharmacokinetic Modeling Approach Using Biomonitoring Data in Order to Assess the Contribution of Drinking Water for the Achievement of an Optimal Fluoride Dose for Dental Health in Children
Open AccessArticle

Waterborne Disease Outbreak Detection: A Simulation-Based Study

1
Santé Publique France, the French National Public Health Agency, 94 410 Saint-Maurice, France
2
Unité D’évaluation Médico-Economique, Université Paul Sabatier, CHU 31059 Toulouse, France
3
Institut National de la Recherche Agronomique, UR346-Unité d’Épidémiologie Animale, 63 122 Saint Genès Champanelle, France
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2018, 15(7), 1505; https://doi.org/10.3390/ijerph15071505
Received: 24 June 2018 / Revised: 7 July 2018 / Accepted: 10 July 2018 / Published: 17 July 2018
(This article belongs to the Special Issue Drinking Water Quality and Human Health)
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. View Full-Text
Keywords: waterborne disease outbreak; simulation study; health insurance data; space–time detection waterborne disease outbreak; simulation study; health insurance data; space–time detection
Show Figures

Figure 1

MDPI and ACS Style

Mouly, D.; Goria, S.; Mounié, M.; Beaudeau, P.; Galey, C.; Gallay, A.; Ducrot, C.; Le Strat, Y. Waterborne Disease Outbreak Detection: A Simulation-Based Study. Int. J. Environ. Res. Public Health 2018, 15, 1505.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop