Objectives We aimed to assess the level of prior SARS-CoV-2 infection in socially deprived neighbourhoods after the first wave of the pandemic, and to identify factors associated with seropositivity. Design A cross-sectional study. Setting Three socially deprived neighbourhoods of the city of Perpignan, in the south of France, where large settled Roma communities live. Participants People aged 6 years old or over, living in the study area. 700 people were included in the study using two-stage stratified sampling design. Interventions The study included a questionnaire and SARS-CoV-2 antibody testing by the Roche Elecsys immunoassay between 29 June and 17 July 2020. Primary and secondary outcome measures SARS-CoV-2 antibody seroprevalence was estimated from weighted data. Associated factors and reported symptoms were investigated using univariable and multivariable logistic regressions. Results The seroprevalence of anti-SARS-CoV-2 antibodies was 35.4% (95% CI 30.2% to 41.0%). People aged 15–64 years old had increased odds of being seropositive than those aged 65 years or over. Obese people had higher odds of being seropositive (adjusted OR (aOR)=2.0, 95% CI 1.1 to 3.8). The odds of being seropositive were higher in households with clinical COVID-19 cases (one case: aOR=2.5, 95% CI 1.3 to 5.0; several cases: aOR=6.9, 95% CI 3.1 to 15.2). In the neighbourhood with the highest measured seroprevalence, people living in a dwelling with one to two rooms had higher odds of being seropositive than those living in a four-room house (aOR=2.8, 95% CI 1.2 to 6.3). Working during the lockdown was associated with lower odds of being seropositive (aOR=0.2, 95% CI 0.03 to 1.0). Conclusion Transmission of SARS-COV-2 in this vulnerable population was very high during the COVID-19 pandemic’s first wave. Our results highlight the need to strengthen and adapt preventive measures taking into account all social determinants of health, especially housing conditions.

Background: Waterborne disease outbreaks (WBDO) associated with tap water consumption are probably underestimated in France. Aim: In order to improve their detection, Santé publique France launched a surveillance system in 2019, based on the periodical analysis of health insurance data for medicalised acute gastroenteritis (mAGE). Methods: Spatio-temporal cluster detection methods were applied to mAGE cases to prioritise clusters for further investigation. These investigations determined the plausibility that infection is of waterborne origin and the strength of association. Results: Between January 2010 and December 2019, 3,323 priority clusters were detected (53,878 excess mAGE cases). They involved 3,717 drinking water supply zones (WSZ), 15.4% of all French WSZ. One third of these WSZ (33.4%; n = 1,242 WSZ) were linked to repeated clusters. Moreover, our system detected 79% of WBDO voluntarily notified to health authorities. Conclusion: Environmental investigations of detected clusters are necessary to determine the plausibility that infection is of waterborne origin. Consequently, they contribute to identifying which WSZ are linked to clusters and for which specific actions are needed to avoid future outbreaks. The surveillance system incorporates three priority elements: linking environmental investigations with water safety plan management, promoting the systematic use of rainfall data to assess waterborne origin, and focusing on repeat clusters. In the absence of an alternative clear hypothesis, the occurrence of a mAGE cluster in a territory completely matching a distribution zone indicates a high plausibility of water origin.

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.

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.

An outbreak of Legionnaires’ disease affected 18 people in Montpellier, a town of the south of France, between December 2016 and July 2017. All cases were diagnosed by a positive urinary antigen test. No deaths were reported. Epidemiological, environmental and genomic investigations (nested Sequence-Based Typing (nSBT) and whole genome sequencing) were undertaken. For the cases for which we had information, four had a new isolate (ST2471), one had a different new isolate (ST2470), one had a genomic pattern compatible with the ST2471 identified by nSBT (flaA = 3), and one had a genomic pattern not compatible with two previous identified STs (pilE = 6). The analysis conducted on the pool of an aquatic therapy center revealed seven isolates of Legionella pneumophila. Whole genome analysis confirmed the link between the environmental and clinical isolates for both ST2470 and ST2471. As the outbreak occurred slowly, with several weeks between new cases, it was not possible to immediately identify a common source. The sixth case was the first to report having aquatic therapy care. Of the 18 cases, eight had attended the aquatic therapy center and the other 10 were inhabitants who lived, worked or walked close to the center. The main cause for this outbreak was the lack of facility maintenance. This investigation highlights the risk to public health of aquatic therapy centers for users and nearby populations, and emphasizes the need for risk reduction measures with specific guidelines to improve health and safety in aquatic facilities.

The French national public health agency (Santé publique France) has used data from the national health insurance reimbursement system (SNDS) to identify medicalised acute gastroenteritis (mAGE) for more than 10 years. This paper presents the method developed to evaluate this system: performance and characteristics of the discriminatory algorithm, portability in mainland and overseas French departments, and verification of the mAGE database updating process. Pharmacy surveys with certified mAGE from 2012 to 2015 were used to characterise mAGE and to estimate the sensitivity and predictive positive value (PPV) of the algorithm. Prescription characteristics from these pharmacy surveys and from 2014 SNDS prescriptions in six mainland and overseas departments were compared. The sensitivity (0.90) and PPV (0.82) did not vary according to the age of the population or year. Prescription characteristics were similar within all studied departments. This confirms that the algorithm can be used in all French departments, for both paediatric and adult populations, with stability and durability over time. The algorithm can identify mAGE cases at a municipal level. The validated system has been implemented in a national waterborne disease outbreaks surveillance system since 2019 with the aim of improving the prevention of infectious disease risk attributable to localised tap water systems.