First cases of coronavirus disease 2019 (COVID-19) in France: surveillance, investigations and control measures, January 2020.

A novel coronavirus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) causing a cluster of respiratory infections (coronavirus disease 2019, COVID-19) in Wuhan, China, was identified on 7 January 2020. The epidemic quickly disseminated from Wuhan and as at 12 February 2020, 45,179 cases have been confirmed in 25 countries, including 1,116 deaths. Strengthened surveillance was implemented in France on 10 January 2020 in order to identify imported cases early and prevent secondary transmission. Three categories of risk exposure and follow-up procedure were defined for contacts. Three cases of COVID-19 were confirmed on 24 January, the first cases in Europe. Contact tracing was immediately initiated. Five contacts were evaluated as at low risk of exposure and 18 at moderate/high risk. As at 12 February 2020, two cases have been discharged and the third one remains symptomatic with a persistent cough, and no secondary transmission has been identified. Effective collaboration between all parties involved in the surveillance and response to emerging threats is required to detect imported cases early and to implement adequate control measures.

Long-term air pollution exposure is associated with increased severity of rhinitis in 2 European cohorts.

BACKGROUND: Very few studies have examined the association between long-term outdoor air pollution and rhinitis severity in adults. OBJECTIVE: We sought to assess the cross-sectional association between individual long-term exposure to air pollution and severity of rhinitis. METHODS: Participants with rhinitis from 2 multicenter European cohorts (Epidemiological Study on the Genetics and Environment on Asthma and the European Community Respiratory Health Survey) were included. Annual exposure to NO2, PM10, PM2.5, and PMcoarse (calculated by subtracting PM2.5 from PM10) was estimated using land-use regression models derived from the European Study of Cohorts for Air Pollution Effects project, at the participants' residential address. The score of rhinitis severity (range, 0-12), based on intensity of disturbance due to symptoms reported by questionnaire, was categorized into low (reference), mild, moderate, and high severity. Polytomous logistic regression models with a random intercept for city were used. RESULTS: A total of 1408 adults with rhinitis (mean age, 52 years; 46% men, 81% from the European Community Respiratory Health Survey) were included. The median (1st quartile-3rd quartile) score of rhinitis severity was 4 (2-6). Higher exposure to PM10 was associated with higher rhinitis severity (adjusted odds ratio [95% CI] for a 10 µg/m3 increase in PM10: for mild: 1.20 [0.88-1.64], moderate: 1.53 [1.07-2.19], and high severity: 1.72 [1.23-2.41]). Similar results were found for PM2.5. Higher exposure to NO2 was associated with an increased severity of rhinitis, with similar adjusted odds ratios whatever the level of severity. Adjusted odds ratios were higher among participants without allergic sensitization than among those with, but interaction was found only for NO2. CONCLUSIONS: People with rhinitis who live in areas with higher levels of pollution are more likely to report more severe nasal symptoms. Further work is required to elucidate the mechanisms of this association.

The Role of Socioeconomic Status in the Association of Lung Function and Air Pollution-A Pooled Analysis of Three Adult ESCAPE Cohorts.

Ambient air pollution is a leading environmental risk factor and its broad spectrum of adverse health effects includes a decrease in lung function. Socioeconomic status (SES) is known to be associated with both air pollution exposure and respiratory function. This study assesses the role of SES either as confounder or effect modifier of the association between ambient air pollution and lung function. Cross-sectional data from three European multicenter adult cohorts were pooled to assess factors associated with lung function, including annual means of home outdoor NO2. Pre-bronchodilator lung function was measured according to the ATS-criteria. Multiple mixed linear models with random intercepts for study areas were used. Three different factors (education, occupation and neighborhood unemployment rate) were considered to represent SES. NO2 exposure was negatively associated with lung function. Occupation and neighborhood unemployment rates were not associated with lung function. However, the inclusion of the SES-variable education improved the models and the air pollution-lung function associations got slightly stronger. NO2 associations with lung function were not substantially modified by SES-variables. In this multicenter European study we could show that SES plays a role as a confounder in the association of ambient NO2 exposure with lung function.

Outdoor air pollution, exhaled 8-isoprostane and current asthma in adults: the EGEA study.

Associations between outdoor air pollution and asthma in adults are still scarce, and the underlying biological mechanisms are poorly understood. Our aim was to study the associations between 1) long-term exposure to outdoor air pollution and current asthma, 2) exhaled 8-isoprostane (8-iso; a biomarker related to oxidative stress) and current asthma, and 3) outdoor air pollution and exhaled 8-iso.Cross-sectional analyses were conducted in 608 adults (39% with current asthma) from the first follow-up of the French case-control and family study on asthma (EGEA; the Epidemiological study of the Genetic and Environmental factors of Asthma). Data on nitrogen dioxide, nitrogen oxides, particulate matter with a diameter ≤10 and ≤2.5 µm (PM10 and PM2.5), road traffic, and ozone (O3) were from ESCAPE (European Study of Cohorts for Air Pollution Effects) and IFEN (French Institute for the Environment) assessments. Models took account of city and familial dependence.The risk of current asthma increased with traffic intensity (adjusted (a)OR 1.09 (95% CI 1.00-1.18) per 5000 vehicles per day), with O3 exposure (aOR 2.04 (95% CI 1.27-3.29) per 10 µg·m-3) and with exhaled 8-iso concentration (aOR 1.50 (95% CI 1.06-2.12) per 1 pg·mL-1). Among participants without asthma, exhaled 8-iso concentration increased with PM2.5 exposure (adjusted (a)ß 0.23 (95% CI 0.005-0.46) per 5 µg·m-3), and decreased with O3 and O3-summer exposures (aß -0.20 (95% CI -0.39- -0.01) and aß -0.52 (95% CI -0.77- -0.26) per 10 µg·m-3, respectively).Our results add new insights into a potential role of oxidative stress in the associations between outdoor air pollution and asthma in adults.

Association between air pollution and rhinitis incidence in two European cohorts.

BACKGROUND: The association between air pollution and rhinitis is not well established. AIM: The aim of this longitudinal analysis was to study the association between modeled air pollution at the subjects' home addresses and self-reported incidence of rhinitis. METHODS: We used data from 1533 adults from two multicentre cohorts' studies (EGEA and ECRHS). Rhinitis incidence was defined as reporting rhinitis at the second follow-up (2011 to 2013) but not at the first follow-up (2000 to 2007). Annual exposure to NO2, PM10 and PM2.5 at the participants' home addresses was estimated using land-use regression models developed by the ESCAPE project for the 2009-2010 period. Incidence rate ratios (IRR) were computed using Poisson regression. Pooled analysis, analyses by city and meta-regression testing for heterogeneity were carried out. RESULTS: No association between long-term air pollution exposure and incidence of rhinitis was found (adjusted IRR (aIRR) for an increase of 10 µg·m-3 of NO2: 1.00 [0.91-1.09], for an increase of 5 µg·m-3 of PM2.5: 0.88 [0.73-1.04]). Similar results were found in the two-pollutant model (aIRR for an increase of 10 µg·m-3 of NO2: 1.01 [0.87-1.17], for an increase of 5 µg·m-3 of PM2.5: 0.87 [0.68-1.08]). Results differed depending on the city, but no regional pattern emerged for any of the pollutants. CONCLUSIONS: This study did not find any consistent evidence of an association between long-term air pollution and incident rhinitis.

Cancer incidence in adults living in the vicinity of nuclear power plants in France, based on data from the French Network of Cancer Registries.

Nuclear power plants (NPPs) release toxic emissions into the environment that may affect neighboring populations. This ecologic study was designed to investigate the possibility of an excess incidence of cancer in the vicinity of French NPPs by examining the incidence by municipality of 12 types of cancer in the population aged 15 years and older during the 1995-2011 period. Population exposure to pollution was estimated on the basis of distance from towns of residence to the NPP. Using regression models, we assessed the risk of cancer in a 20-km zone around NPPs and observed an excess incidence of bladder cancer (Relative Risk (RR), 95% Credibility Interval (95% CI)) in men and women (RRmen = 1.08; 95% CI: 1.00, 1.17 and RRwomen = 1.19; 95% CI: 1.02, 1.39). Women living within the 20-km proximity areas had a significantly reduced risk of thyroid cancer (RRwomen = 0.86; 95% CI: 0.77, 0.96). No excess risk of hematologic malignancies in either sex was seen. The higher than expected incidence of bladder cancer may be due to an excess incidence localized around the Flamanville NPP and the nearby La Hague nuclear waste treatment center, which is a source of chemical contaminants, many (including arsenic) of them known risk factors for bladder cancer. Differences in medical practices could explain the reduced risk of thyroid cancer. In this first study of adults living near NPPs in France, cancer incidence is significantly higher than in the references populations for one of the cancer types studied: bladder cancer.

Socioeconomic position and outdoor nitrogen dioxide (NO2) exposure in Western Europe: A multi-city analysis.

BACKGROUND: Inconsistent associations between socioeconomic position (SEP) and outdoor air pollution have been reported in Europe, but methodological differences prevent any direct between-study comparison. OBJECTIVES: Assess and compare the association between SEP and outdoor nitrogen dioxide (NO2) exposure as a marker of traffic exhaust, in 16 cities from eight Western European countries. METHODS: Three SEP indicators, two defined at individual-level (education and occupation) and one at neighborhood-level (unemployment rate) were assessed in three European multicenter cohorts. NO2 annual concentration exposure was estimated at participants' addresses with land use regression models developed within the European Study of Cohorts for Air Pollution Effects (ESCAPE; http://www.escapeproject.eu/). Pooled and city-specific linear regressions were used to analyze associations between each SEP indicator and NO2. Heterogeneity across cities was assessed using the Higgins' I-squared test (I2). RESULTS: The study population included 5692 participants. Pooled analysis showed that participants with lower individual-SEP were less exposed to NO2. Conversely, participants living in neighborhoods with higher unemployment rate were more exposed. City-specific results exhibited strong heterogeneity (I2>76% for the three SEP indicators) resulting in variation of the individual- and neighborhood-SEP patterns of NO2 exposure across cities. The coefficients from a model that included both individual- and neighborhood-SEP indicators were similar to the unadjusted coefficients, suggesting independent associations. CONCLUSIONS: Our study showed for the first time using homogenized measures of outcome and exposure across 16 cities the important heterogeneity regarding the association between SEP and NO2 in Western Europe. Importantly, our results showed that individual- and neighborhood-SEP indicators capture different aspects of the association between SEP and exposure to air pollution, stressing the importance of considering both in air pollution health effects studies.

Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data.

Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models, all including local traffic and land use variables, were compared (LUR without SAT or CTM, with SAT only, with CTM only, and with both SAT and CTM). LUR models were developed using two monitoring data sets: PM2.5 and NO2 ground level measurements from the European Study of Cohorts for Air Pollution Effects (ESCAPE) and from the European AIRBASE network. LUR PM2.5 models including SAT and SAT+CTM explained ~60% of spatial variation in measured PM2.5 concentrations, substantially more than the LUR model without SAT and CTM (adjR2: 0.33-0.38). For NO2 CTM improved prediction modestly (adjR2: 0.58) compared to models without SAT and CTM (adjR2: 0.47-0.51). Both monitoring networks are capable of producing models explaining the spatial variance over a large study area. SAT and CTM estimates of PM2.5 and NO2 significantly improved the performance of high spatial resolution LUR models at the European scale for use in large epidemiological studies.

Spatial variation of PM elemental composition between and within 20 European study areas--Results of the ESCAPE project.

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements. We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning. PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10. Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM.

Association between long-term exposure to air pollution and mortality in France: A 25-year follow-up study.

INTRODUCTION: Long-term exposure to air pollution (AP) has been shown to have an impact on mortality in numerous countries, but since 2005 no data exists for France. OBJECTIVES: We analyzed the association between long-term exposure to air pollution and mortality at the individual level in a large French cohort followed from 1989 to 2013. METHODS: The study sample consisted of 20,327 adults working at the French national electricity and gas company EDF-GDF. Annual exposure to PM10, PM10­2.5, PM2.5, NO2, O3, SO2, and benzene was assessed for the place of residence of participants using a chemistry-transport model and taking residential history into account. Hazard ratios were estimated using a Cox proportional-hazards regression model, adjusted for selected individual and contextual risk factors. Hazard ratios were computed for an interquartile range (IQR) increase in air pollutant concentrations. RESULTS: The cohort recorded 1967 non-accidental deaths. Long-term exposures to b aseline PM2.5, PM10-25, NO2 and benzene were associated with an increase in non-accidental mortality (Hazard Ratio, HR = 1.09; 95% CI: 0.99, 1.20 per 5.9 µg/m3, PM10-25; HR=1.09; 95% CI: 1.04, 1.15 per 2.2 µg/m3, NO2: HR=1.14; 95% CI: 0.99, 1.31 per 19.3 µg/m3 and benzene: HR=1.10; 95% CI: 1.00, 1.22 per 1.7 µg/m3).The strongest association was found for PM10: HR = 1.14; 95% CI: 1.05, 1.25 per 7.8 µg/m3. PM10, PM10-25 and SO2 were associated with non-accidental mortality when using time varying exposure. No significant associations were observed between air pollution and cardiovascular and respiratory mortality. CONCLUSION: Long-term exposure to fine particles, nitrogen dioxide, sulfur dioxide and benzene is associated with an increased risk of non-accidental mortality in France. Our results strengthen existing evidence that outdoor air pollution is a significant environmental risk factor for mortality. Due to the limited sample size and the nature of our study (occupational), further investigations are needed in France with a larger representative population sample.

Ambient air pollution and adult asthma incidence in six European cohorts (ESCAPE).

BACKGROUND: Short-term exposure to air pollution has adverse effects among patients with asthma, but whether long-term exposure to air pollution is a cause of adult-onset asthma is unclear. OBJECTIVE: We aimed to investigate the association between air pollution and adult onset asthma. METHODS: Asthma incidence was prospectively assessed in six European cohorts. Exposures studied were annual average concentrations at home addresses for nitrogen oxides assessed for 23,704 participants (including 1,257 incident cases) and particulate matter (PM) assessed for 17,909 participants through ESCAPE land-use regression models and traffic exposure indicators. Meta-analyses of cohort-specific logistic regression on asthma incidence were performed. Models were adjusted for age, sex, overweight, education, and smoking and included city/area within each cohort as a random effect. RESULTS: In this longitudinal analysis, asthma incidence was positively, but not significantly, associated with all exposure metrics, except for PMcoarse. Positive associations of borderline significance were observed for nitrogen dioxide [adjusted odds ratio (OR) = 1.10; 95% CI: 0.99, 1.21 per 10 µg/m3; p = 0.10] and nitrogen oxides (adjusted OR = 1.04; 95% CI: 0.99, 1.08 per 20 µg/m3; p = 0.08). Nonsignificant positive associations were estimated for PM10 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 10 µg/m3), PM2.5 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 5 µg/m3), PM2.5absorbance (adjusted OR = 1.06; 95% CI: 0.95, 1.19 per 10-5/m), traffic load (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 4 million vehicles × meters/day on major roads in a 100-m buffer), and traffic intensity (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 5,000 vehicles/day on the nearest road). A nonsignificant negative association was estimated for PMcoarse (adjusted OR = 0.98; 95% CI: 0.87, 1.14 per 5 µg/m3). CONCLUSIONS: Results suggest a deleterious effect of ambient air pollution on asthma incidence in adults. Further research with improved personal-level exposure assessment (vs. residential exposure assessment only) and phenotypic characterization is needed.

Performance of multi-city land use regression models for nitrogen dioxide and fine particles.

BACKGROUND: Land use regression (LUR) models have been developed mostly to explain intraurban variations in air pollution based on often small local monitoring campaigns. Transferability of LUR models from city to city has been investigated, but little is known about the performance of models based on large numbers of monitoring sites covering a large area. OBJECTIVES: We aimed to develop European and regional LUR models and to examine their transferability to areas not used for model development. METHODS: We evaluated LUR models for nitrogen dioxide (NO2) and particulate matter (PM; PM2.5, PM2.5 absorbance) by combining standardized measurement data from 17 (PM) and 23 (NO2) ESCAPE (European Study of Cohorts for Air Pollution Effects) study areas across 14 European countries for PM and NO2. Models were evaluated with cross-validation (CV) and hold-out validation (HV). We investigated the transferability of the models by successively excluding each study area from model building. RESULTS: The European model explained 56% of the concentration variability across all sites for NO2, 86% for PM2.5, and 70% for PM2.5 absorbance. The HV R2s were only slightly lower than the model R2 (NO2, 54%; PM2.5, 80%; PM2.5 absorbance, 70%). The European NO2, PM2.5, and PM2.5 absorbance models explained a median of 59%, 48%, and 70% of within-area variability in individual areas. The transferred models predicted a modest-to-large fraction of variability in areas that were excluded from model building (median R2: NO2, 59%; PM2.5, 42%; PM2.5 absorbance, 67%). CONCLUSIONS: Using a large data set from 23 European study areas, we were able to develop LUR models for NO2 and PM metrics that predicted measurements made at independent sites and areas reasonably well. This finding is useful for assessing exposure in health studies conducted in areas where no measurements were conducted.

A review of the epidemiological methods used to investigate the health impacts of air pollution around major industrial areas.

We performed a literature review to investigate how epidemiological studies have been used to assess the health consequences of living in the vicinity of industries. 77 papers on the chronic effects of air pollution around major industrial areas were reviewed. Major health themes were cancers (27 studies), morbidity (25 studies), mortality (7 studies), and birth outcome (7 studies). Only 3 studies investigated mental health. While studies were available from many different countries, a majority of papers came from the United Kingdom, Italy, and Spain. Several studies were motivated by concerns from the population or by previous observations of an overincidence of cases. Geographical ecological designs were largely used for studying cancer and mortality, including statistical designs to quantify a relationship between health indicators and exposure. Morbidity was frequently investigated through cross-sectional surveys on the respiratory health of children. Few multicenter studies were performed. In a majority of papers, exposed areas were defined based on the distance to the industry and were located from <2 km to >20 km from the plants. Improving the exposure assessment would be an asset to future studies. Criteria to include industries in multicenter studies should be defined.

Ecological study on hospitalizations for cancer, cardiovascular, and respiratory diseases in the industrial area of Etang-de-Berre in the South of France.

The Etang-de-Berre area is a large industrialized area in the South of France, exposing 300,000 inhabitants to the plumes of its industries. The possible associated health risks are of the highest concern to the population, who asked for studies investigating their health status. A geographical ecological study based on standardized hospitalizations ratios for cancer, cardiovascular, and respiratory diseases was carried out over the 2004-2007 period. Exposure to air pollution was assessed using dispersion models coupled with a geographic information system to estimate an annual mean concentration of sulfur dioxide (SO2) for each district. Results showed an excess risk of hospitalization for myocardial infarction in women living in districts with medium or high SO2 exposure, respectively, 38% [CI 95% 4 : 83] and 54% [14 : 110] greater than women living in districts at the reference level exposure. A 26% [2 : 57] excess risk of hospitalization for myocardial infarction was also observed in men living in districts with high SO2 levels. No excess risk of hospitalization for respiratory diseases or for cancer was observed, except for acute leukemia in men only. Results illustrate the impact of industrial air pollution on the cardiovascular system and call for an improvement of the air quality in the area.

Evaluation of land use regression models for NO2 and particulate matter in 20 European study areas: the ESCAPE project.

Land use regression models (LUR) frequently use leave-one-out-cross-validation (LOOCV) to assess model fit, but recent studies suggested that this may overestimate predictive ability in independent data sets. Our aim was to evaluate LUR models for nitrogen dioxide (NO2) and particulate matter (PM) components exploiting the high correlation between concentrations of PM metrics and NO2. LUR models have been developed for NO2, PM2.5 absorbance, and copper (Cu) in PM10 based on 20 sites in each of the 20 study areas of the ESCAPE project. Models were evaluated with LOOCV and "hold-out evaluation (HEV)" using the correlation of predicted NO2 or PM concentrations with measured NO2 concentrations at the 20 additional NO2 sites in each area. For NO2, PM2.5 absorbance and PM10 Cu, the median LOOCV R(2)s were 0.83, 0.81, and 0.76 whereas the median HEV R(2) were 0.52, 0.44, and 0.40. There was a positive association between the LOOCV R(2) and HEV R(2) for PM2.5 absorbance and PM10 Cu. Our results confirm that the predictive ability of LUR models based on relatively small training sets is overestimated by the LOOCV R(2)s. Nevertheless, in most areas LUR models still explained a substantial fraction of the variation of concentrations measured at independent sites.

Development of Land Use Regression models for PM(2.5), PM(2.5) absorbance, PM(10) and PM(coarse) in 20 European study areas; results of the ESCAPE project.

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.

Natural and technical factors in faecal contamination incidents of drinking water in small distribution networks, France, 2003-2004: a geographical study.

This geographical study aimed to show natural or water-processing-related factors of faecal contamination incidents (FCIs) of drinking water in continental France. We defined a FCI as the occurrence of at least 20 colony-forming Escherichia coli or enterococci among all the 100 mL samples collected for regulatory purpose within one day from a given drinking water supply zone (SZ). We explored correlations between the standardized number of FCIs per département (N_Pols) and various indicators related to weather, land cover, topography, geology and water management for three SZ size sub-classes. In 2003-2004, 2,739 FCIs occurred in SZs supplying fewer than 2,000 people, mainly with simply disinfected groundwater. N_Pols correlates with four covariates: (1) precipitation; (2) the extension of the karst outcrops; (3) the extent of disinfection; and (4) catchment protection. One hundred millimetres of yearly excess in precipitation increases the pollution risk by 28-37%, depending on the sub-class. A 10% extension of the karst areas, a 10% increase of unprotected resources, or of SZs with no disinfection, could entail a higher risk of FCI by about 10%. The correlations are reproducible over the three sub-classes and corroborate expert appraisals. These results encourage the ongoing effort to generalize disinfection and catchment protection.