Coly S, Vincent N, Vaissiere E, Charras-Garrido M, Gallay A, Ducrot C, Mouly D
INRA, UR346 - Unité d'Épidémiologie Animale, Centre de recherche de Clermont-Ferrand, 63122 Saint Genès Champanelle, France.
French National Public Health Agency, 12 rue du Val d'Osne, 94 415 Saint-Maurice Cedex, France E-mail:
J Water Health. 2017 Aug;15(4):475-489. doi: 10.2166/wh.2017.273.
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.
发达国家每年都会报告数百起因自来水受污染导致的急性肠胃炎(AGI)水源性疾病暴发(WBDO)。此类暴发可能未被充分检测到。我们研究的目的是开发一种综合方法,以检测和研究在饮用水暴露情况相同的地理区域内的AGI聚集情况。AGI病例数的数据在市一级可得,而自来水暴露情况则取决于饮用水网络(DWN)。这两个地理单元并非系统地重叠。本研究提议开发一种算法,将最相关的市分组与特定的DWN相匹配,以便在调查未来疾病暴发时能够考虑自来水暴露情况。一种时空检测方法应用于市的分组。与1310个市和1706个DWN相比,获得了714个新的地理区域(市的分组)。在这些市的分组中识别出11起潜在的WBDO。对于其中10起,额外的环境调查确定了至少一个在报告的WBDO发生前几天可能导致DWN微生物污染的事件。