"Sickenin' in the rain" - increased risk of gastrointestinal and respiratory infections after urban pluvial flooding in a population-based cross-sectional study in the Netherlands.

BACKGROUND: Climate change is expected to increase the chance of extreme rainfall events in the Northern Hemisphere and herewith, there is an increased chance of urban pluvial flooding. Urban pluvial flooding often consists of street flooding and/or flooding of combined sewerage systems, leading to contamination of the floodwater with several gastrointestinal and/or respiratory pathogens. An increase in flooding events therefore pose a health risk to those exposed to urban floodwater. We studied the association between exposure to pluvial floodwater and acute gastroenteritis (AGE) and acute respiratory infection (ARI). METHODS: We performed a retrospective, cross-sectional survey during the summer of 2015 in 60 locations in the Netherlands with reported flooding. Two weeks after the flooding, questionnaires were sent to households in these locations, collecting data on self-reported AGE and ARI and information on floodwater exposure in the previous 2 weeks. Multivariable generalized estimating equations (GEE) regression models, accounting for the clustered data structure, were used to identify risk factors for AGE and ARI. RESULTS: In total, 699 households with 1,656 participants (response rate 21%) returned the questionnaire. Contact with floodwater was significantly associated with AGE (aOR 4.2, 95%CI 2.1-8.4) and ARI (aOR 3.3, 95%CI 2.0-5.4). Risk factors for AGE were skin contact with floodwater (aOR 4.0, 95%CI 1.8-9.0), performing post-flooding cleaning operations (aOR 8.6, 95%CI 3.5-20.9) and cycling through floodwater (aOR 2.3, 95%CI 1.0-5.0). Skin contact with floodwater (aOR 3.6, 95%CI 1.9-6.9) and performing post-flooding cleaning operations (aOR 5.5, 95%CI 3.0-10.3) were identified as risk factors for ARI. CONCLUSIONS: Results suggest an association between direct exposure to pluvial floodwater and AGE and ARI. As it is predicted that the frequency of pluvial flooding events will increase in the future, there is a need for flood-proof solutions in urban development and increased awareness among stakeholders and the public about the potential health risks. Future prospective studies are recommended to confirm our results.

HEVnet: a One Health, collaborative, interdisciplinary network and sequence data repository for enhanced hepatitis E virus molecular typing, characterisation and epidemiological investigations.

Hepatitis E virus (HEV) is a common cause of acute hepatitis worldwide. In Europe, HEV is a zoonosis transmitted via contaminated pork meat or other pork food products. Genotype 3 is the most prevalent HEV type in the animal reservoir, as well as in humans. Despite an increased incidence of hepatitis E across Europe, much remains unknown about its spread, sources and transmission routes. A One Health approach is crucial to better understand the (molecular) epidemiology of HEV. HEVnet was established in April 2017 as a network and database for sharing sequences and accompanying metadata collected from human, animal, food and environmental sources. HEVnet members working in the public health, veterinary health, food, environmental and blood safety sectors have submitted 1,615 HEV sequences from nine countries as at January 2019. Most are from humans (89%), and sequences of animal (5%), food (6%) or environmental (0.3%) origin are rare. Metadata for human sequences capture mostly sex (93%), year of birth (92%) and sampling (100%); data on region of sampling (37%) and clinical information (hospitalisation 27%, symptoms 20% or mortality 8%) are limited. HEVnet aims to expand into a global network capable of performing cross-sectoral and supranational studies, with a joint repository of molecular and epidemiological data on HEV.

Outbreak of Salmonella Bovismorbificans associated with the consumption of uncooked ham products, the Netherlands, 2016 to 2017.

In January 2017, an increase in reported Salmonellaenterica serotype Bovismorbificans cases in the Netherlands was observed since October 2016. We implemented a case-control study to identify the source, including all cases after December 2016. Adjusted odds ratios were calculated using logistic regression analysis. We traced back the distribution chain of suspected food items and sampled them for microbiological analysis. Human and food isolates were sequenced using whole genome sequencing (WGS). From October 2016 to March 2017, 54 S. Bovismorbificans cases were identified. Sequencing indicated that all were infected with identical strains. Twenty-four cases and 37 controls participated in the study. Cases were more likely to have consumed ham products than controls (aOR = 13; 95% CI: 2.0-77) and to have shopped at a supermarket chain (aOR = 7; 95% CI: 1.3-38). Trace-back investigations led to a Belgian meat processor: one retail ham sample originating from this processor tested positive for S. Bovismorbificans and matched the outbreak strain by WGS. All ham products related to the same batch were removed from the market to prevent further cases. This investigation illustrates the importance of laboratory surveillance for all Salmonella serotypes and the usefulness of WGS in an outbreak investigation.

Livestock-associated spatial risk factors for human salmonellosis and campylobacteriosis.

AIMS: Most human infections with non-typhoid Salmonella (NTS) or Campylobacter are zoonotic in nature and acquired though consumption of contaminated food of mainly animal origin. However, individuals may also acquire salmonellosis or campylobacteriosis through non-foodborne transmission pathways, such as those mediated by the environment. This emphasizes the need to consider both direct and indirect exposure to livestock sources as a possible transmission route for NTS and Campylobacter. Therefore, this study aimed at assessing whether salmonellosis and campylobacteriosis incidence is spatially associated with exposure to livestock (i.e. small ruminants, dairy cows, veal calves, laying hens, broiler chickens and pigs) in the Netherlands for the years 2007-2019 and 2014-2019 respectively. METHODS AND RESULTS: Risk factors (population-weighted number of animals) and their population attributable fractions were determined using a Poisson regression model with a log-link function fitted using integrated nested Laplace approximation. The analyses were performed for different hexagonal sizes (90, 50, 25 and 10 km2) and accounted for geographical coverage of the diagnostic laboratory catchment areas. Moreover, serological data were used to look into the possible effects of acquired immunity due to repeated exposure to the pathogen through the environment that would potentially hinder the analyses based on the incidence of reported cases. A linear mixed-effects model was then fitted where the postal code areas were included as a random effect. Livestock was not consistently significantly associated with acquiring salmonellosis or campylobacteriosis in the Netherlands. CONCLUSIONS: Results showed that living in livestock-rich areas in the Netherlands is not a consistently significant, spatially restricted risk factor for acquiring salmonellosis or campylobacteriosis, thereby supporting current knowledge that human infections with Salmonella and Campylobacter are mainly foodborne.

Profiling the fecal microbiome and its modulators across the lifespan in the Netherlands.

Defining what constitutes a healthy microbiome throughout our lives remains an ongoing challenge. Understanding to what extent host and environmental factors can influence it has been the primary motivation for large population studies worldwide. Here, we describe the fecal microbiome of 3,746 individuals (0-87 years of age) in a nationwide study in the Netherlands, in association with extensive questionnaires. We validate previous findings, such as infant-adult trajectories, and explore the collective impact of our variables, which explain over 40% of the variation in microbiome composition. We identify associations with less explored factors, particularly those ethnic related, which show the largest impact on the adult microbiome composition, diversity, metabolic profiles, and CAZy (carbohydrate-active enzyme) repertoires. Understanding the sources of microbiome variability is crucial, given its potential as a modifiable target with therapeutic possibilities. With this work, we aim to serve as a foundational element for the design of health interventions and fundamental research.