Waterborne disease outbreak detection: an integrated approach using health administrative databases

Abstract

Hundreds of waterborne disease outbreaks (WBDO) of acute gastroenteritis (AGI) due to contaminated tap water are reported in developed countries each year. Such outbreaks are probably under-detected. The aim of our study was to develop an integrated approach to detect and study clusters of AGI in geographical areas with homogeneous exposure to drinking water. Data for the number of AGI cases are available at the municipality level while exposure to tap water depends on drinking water networks (DWN). These two geographical units do not systematically overlap. This study proposed to develop an algorithm which would match the most relevant grouping of municipalities with a specific DWN, in order that tap water exposure can be taken into account when investigating future disease outbreaks. A space-time detection method was applied to the grouping of municipalities. Seven hundred and fourteen new geographical areas (groupings of municipalities) were obtained compared with the 1,310 municipalities and the 1,706 DWN. Eleven potential WBDO were identified in these groupings of municipalities. For ten of them, additional environmental investigations identified at least one event that could have caused microbiological contamination of DWN in the days previous to the occurrence of a reported WBDO.

Waterborne Disease Outbreak Detection: A Simulation-Based Study

“…These results suggest a strong improvement in detection ability for WBDOs with more than 10 AGI cases and a variation of incidence greater than 2%. These values are consistent with the previous study’s results which described the detection algorithm and its application to real health data [ 11 ]. Of the 11 clusters detected in this study, the values of the medication rate in the population (indicator close to the variation of incidence) ranged from 0.7% to 4.8%, and the cluster size from 21 to 67 AGI cases.…”

“…The WBDO detection method used is detailed elsewhere [ 11 ]. First, an algorithm was used for grouping zip codes (and corresponding AGI cases) which share the same DZ so that tap water exposure could be taken into account in the detection process.…”

“…By so doing, an integrated approach to detect and localize WBDOs using medicalized AGI cases from SNIIRAM data was published in 2017 by Coly et al [ 11 ]. The authors’ approach relied on a space–time statistical method developed by Kulldorff [ 12 ] used to detect local outbreaks of AGIs.…”

“…The objective of our study was therefore to evaluate, through simulations, the performance of the integrated approach developed by Coly et al for WBDO detection [ 11 ] and to highlight the DZ and outbreak features which most influence WBDO detection.…”

The Effectiveness of Syndromic Surveillance for the Early Detection of Waterborne Outbreaks: A Systematic Review

“…A summary of the study characteristics of the included studies is presented in Additional File 1. Of these included articles, 10 were retrospective studies assessing either historical outbreaks or data of cases of gastrointestinal illness and data signals for early detection of waterborne outbreaks (18)(19)(20)(21)(22)(23)(24)(25)(26)(27), and six were simulation studies evaluating the system performance of different SyS systems (28)(29)(30)(31)(32). The included studies originated from Sweden (n = 2), France (n = 5), the USA (n = 4), and the United Kingdom (n = 4), with one study assessing data from several European countries suggesting a common surveillance approach (25), covering an overall study period of 1997 to 2013, with multiple agents causing waterborne outbreaks or illness.…”