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. 2018 Jul 17;15(7):1505.
doi: 10.3390/ijerph15071505.

Waterborne Disease Outbreak Detection: A Simulation-Based Study

Damien Mouly  1 , Sarah Goria  2 , Michael Mounié  3 , Pascal Beaudeau  4 , Catherine Galey  5 , Anne Gallay  6 , Christian Ducrot  7 , Yann Le Strat  8
Affiliations

Waterborne Disease Outbreak Detection: A Simulation-Based Study

Damien Mouly et al. Int J Environ Res Public Health. .

Abstract

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.

Keywords: health insurance data; simulation study; space–time detection; waterborne disease outbreak.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Algorithm of the overall process for simulation of baseline data and WBDOs. SNIRAM: Système national d’information inter régimes de l’Assurance maladie (the French Health Insurance Administrative Database); AGI: acute gastrointestinal infection.
Figure 2
Figure 2
Simulation of time series of incident AGI cases before the inclusion of the simulated WBDO: daily number of observed AGI cases from the French Health Insurance Administrative Database (SNIIRAM) between 1 January 2010 and 31 December 2013 (n = 8677) (top), number of estimated expected cases (middle), and number of simulated cases (bottom) for a zip code with 18,541 inhabitants.
Figure 3
Figure 3
Illustration of two simulated outbreaks starting on 22 September 2011 in a zip code of 18,541 inhabitants serviced by only one DZ, with a variation of incidence ratio (VI) of 1% (top) and 2% (bottom), and with a 20-day duration.
Figure 4
Figure 4
Sensitivity of detection method according to outbreak size (number of simulated AGI cases) and season (winter: December, January, February, March).
See this image and copyright information in PMC

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