Food- and waterborne diseases

Hepatitis A is an acute infection of the liver caused by hepatitis A virus (HAV). Molecular detection and typing of the HAV VP1/P2A genomic region is used for genotyping and outbreak investigations. After a large hepatitis A outbreak in Latvia in 2007–08, only sporadic cases were registered until 2017 when a rise in cases occurred. During 2017–19, 179 laboratory-confirmed hepatitis A cases were notified in Latvia.

To investigate the observed increase in hepatitis A cases during 2017 and to determine whether these cases were linked to one another, to risk groups, or to other outbreaks. The majority of HAV samples (69.8%) were typed.

The VP1/P2A genomic region of HAV was amplified and sequenced for 125 case serum samples. Information about hepatitis-related symptoms, hospitalisation, vaccination, a possible source of infection and suspected countries of origin of the virus were analysed for sequenced cases.

Most HAV strains were subgenotype IA (n = 77), of which 41 were strains circulating among men who have sex with men (MSM) populations in Europe (VRD_521_2016 (n = 32), RIVM-HAV16–090 (n = 7) or V16–25801 (n = 2)). Forty-four cases were subgenotype IB and four cases subgenotype IIIA. However, other clusters and sporadic cases were detected with or without identifying the epidemiological link.

This work represents molecular epidemiological data of hepatitis A cases in Latvia from 2017 to 2019. Molecular typing methods allow identification of clusters for public health needs and establishing links with other outbreaks, and to compare Latvian strains with reported strains from other countries.

Healthcare-associated foodborne outbreaks (HA-FBO) may have severe consequences, especially in vulnerable groups.

The aim was to describe the current state of HA-FBO and propose public health recommendations for prevention.

We searched PubMed, the Outbreak Database (Charité, University Medicine Berlin), and hand-searched reference lists for HA-FBO with outbreak onset between 2001 and 2018 from Organisation for Economic Co-operation and Development (OECD) countries and HA-FBO (2012–2018) from the German surveillance system. Additionally, data from the European Food Safety Authority were analysed.

The literature search retrieved 57 HA-FBO from 16 OECD countries, primarily in the US (n = 11), Germany (n = 11) and the United Kingdom (n = 9). In addition, 28 HA-FBO were retrieved from the German surveillance system. Based on the number of outbreaks, the top three pathogens associated with the overall 85 HA-FBO were Salmonella (n = 24), norovirus (n = 22) and Listeria monocytogenes (n = 19). Based on the number of deaths, L. monocytogenes was the main pathogen causing HA-FBO. Frequently reported implicated foods were ‘mixed foods’ (n = 16), ‘vegetables and fruits’ (n = 15) and ‘meat and meat products’ (n = 10). Consumption of high-risk food by vulnerable patients, inadequate time-temperature control, insufficient kitchen hygiene and food hygiene and carriers of pathogens among food handlers were reported as reasons for HA-FBO.

To prevent HA-FBO, the supply of high-risk food to vulnerable people should be avoided. Well working outbreak surveillance facilitates early detection and requires close interdisciplinary collaboration and exchange of information between hospitals, food safety and public health authorities.

Campylobacter is one of the most frequent causes of bacterial gastroenteritis. Campylobacter outbreaks are rarely reported, which could be a reflection of a surveillance without routine molecular typing. We have previously shown that numerous small outbreak-like clusters can be detected when whole genome sequencing (WGS) data of clinical Campylobacter isolates was applied.

Typing-based surveillance of Campylobacter infections was initiated in 2019 to enable detection of large clusters of clinical isolates and to match them to concurrent retail chicken isolates in order to react on ongoing outbreaks.

We performed WGS continuously on isolates from cases (n = 701) and chicken meat (n = 164) throughout 2019. Core genome multilocus sequence typing was used to detect clusters of clinical isolates and match them to isolates from chicken meat.

Seventy-two clusters were detected, 58 small clusters (2–4 cases) and 14 large clusters (5–91 cases). One third of the clinical isolates matched isolates from chicken meat. One large cluster persisted throughout the whole year and represented 12% of all studied Campylobacter cases. This cluster type was detected in several chicken samples and was traced back to one slaughterhouse, where interventions were implemented to control the outbreak.

Our WGS-based surveillance has contributed to an improved understanding of the dynamics of the occurrence of Campylobacter strains in chicken meat and the correlation to clusters of human cases.

The trend in reported case counts of invasive Listeria monocytogenes (Lm), a potentially severe food-borne disease, has been increasing since 2008. In 2015, 2,224 cases were reported in the European Union/European Economic Area (EU/EEA). We aimed to validate the microbiological and epidemiological aspects of an envisaged EU/EEA-wide surveillance system enhanced by routine whole genome sequencing (WGS). Methods: WGS and core genome multilocus sequence typing (cgMLST) were performed on isolates from 2,726 cases from 27 EU/EEA countries from 2010–15. Results: Quality controls for contamination, mixed Lm cultures and sequence quality classified nearly all isolates with a minimum average coverage of the genome of 55x as acceptable for analysis. Assessment of the cgMLST variation between six different pipelines revealed slightly less variation associated with assembly-based analysis compared to reads-based analysis. Epidemiological concordance, based on 152 isolates from 19 confirmed outbreaks and a cluster cutoff of seven allelic differences, was good (sensitivity > 95% for two cgMLST schemes of 1,748 and 1,701 loci each; PPV 58‒68%). The proportion of sporadic cases was slightly below 50%. Of remaining isolates, around one third were in clusters involving more than one country, often spanning several years. Detection of multi-country clusters was on average several months earlier when pooling the data at EU/EEA level, compared with first detection at national level. Conclusions: These findings provide a good basis for comprehensive EU/EEA-wide, WGS-enhanced surveillance of listeriosis. Time limits should not be used for hypothesis generation during outbreak investigations, but should be for analytical studies.

Human enteric viruses are resistant in the environment and transmitted via the faecal-oral route. Viral shedding in wastewater gives the opportunity to track emerging pathogens and study the epidemiology of enteric infectious diseases in the community. Aim: The aim of this study was to monitor the circulation of enteric viruses in the population of the Clermont-Ferrand area (France) by analysis of urban wastewaters. Methods: Raw and treated wastewaters were collected between October 2014 and October 2015 and concentrated by a two-step protocol using tangential flow ultrafiltration and polyethylene glycol precipitation. Processed samples were analysed for molecular detection of adenovirus, norovirus, rotavirus, parechovirus, enterovirus (EV), hepatitis A (HAV) and E (HEV) viruses. Results: All wastewater samples (n = 54) contained viruses. On average, six and four virus species were detected in, respectively, raw and treated wastewater samples. EV-positive samples were tested for EV-D68 to assess its circulation in the community. EV-D68 was detected in seven of 27 raw samples. We collected data from clinical cases of EV-D68 (n = 17), HAV (n = 4) and HEV infection (n = 16) and compared wastewater-derived sequences with clinical sequences. We showed the silent circulation of EV-D68 in September 2015, the wide circulation of HAV despite few notifications of acute disease and the presence in wastewater of the major HEV subtypes involved in clinical local cases. Conclusion: The environmental surveillance overcomes the sampling bias intrinsic to the study of infections associated with hospitalisation and allows the detection in real time of viral sequences genetically close to those reported in clinical specimens.