Epidemiologic estimates of hepatitis E virus infection in European countries

Accepted Manuscript

Epidemiologic estimates of Hepatitis E Virus infection in European countries Johannes Horn , Mahrrouz Hoodgarzadeh , Carolina J Klett-Tammen , Rafael T Mikolajczyk , Gerard Krause , ´ Jordis J Ott ¨ PII: DOI: Reference:

S0163-4453(18)30285-8 https://doi.org/10.1016/j.jinf.2018.09.012 YJINF 4172

To appear in:

Journal of Infection

Received date: Accepted date:

16 May 2018 20 September 2018

Please cite this article as: Johannes Horn , Mahrrouz Hoodgarzadeh , Carolina J Klett-Tammen , Rafael T Mikolajczyk , Gerard Krause , Jordis J Ott , Epidemiologic estimates of Hepatitis E Virus in´ ¨ fection in European countries, Journal of Infection (2018), doi: https://doi.org/10.1016/j.jinf.2018.09.012

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Title: Epidemiologic estimates of Hepatitis E Virus infection in European countries Running Title: Hepatitis E Virus infection in European countries Authors names and affiliations:

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Johannes Horn1*, Mahrrouz Hoodgarzadeh2,3*, Carolina J Klett-Tammen4, Rafael T Mikolajczyk1,5, Gérard Krause2,6,7**, Jördis J Ott2,6. ¹Institute for Medical Epidemiology, Biometrics, and Informatics (IMEBI), Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Magdeburger Str. 8, 06110 Halle (Saale), Germany 2

Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Inhoffenstraße 7, 38124 Braunschweig, Germany PhD Programme “Epidemiology,” Braunschweig-Hannover, Germany

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Centre for Public Health and Healthcare, Hannover Medical School, Carl-Neuberg-Straße 1, 30625 Hannover, Germany 5

German Centre for Infection Research (DZIF), Hannover-Braunschweig site, Germany

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Hannover Medical School, Carl-Neuberg-Straße 1, 30625 Hannover, Germany

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*Equally contributed to this study

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E-Mail address

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TI Epidemiology German Centre for Infection Research

JH: [email protected]

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MH: [email protected] CKT: [email protected]

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RTM: [email protected]

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GK: [email protected] JO: [email protected] **Corresponding author: Prof. Dr. Gérard Krause Department of Epidemiology, Helmholtz Centre for Infection Research (HZI) Braunschweig 38124, Germany E-Mail: [email protected] Phone: +49 (531) 6181-3100 1

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Abstract (200/200) Objectives: Reliable epidemiologic estimates of Hepatitis E Virus (HEV) infection and evidence on factors determining country-differences are sparse. We systematically assessed and extracted research data on three HEV infection markers and identified factors influencing HEV-positivity

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to generated adjusted EU/EEA country-specific estimates by a meta-analysis.

Methods: Reports on HEV published 2005-2015 for EU/EEA countries were obtained from PubMed, Embase, Scopus, and Cochrane databases. Utilizing data on anti-HEV IgG, IgM and

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HEV-RNA we estimated HEV sero-prevalence, recent and acute HEV infections. Respective magnitude of factors influencing HEV-positivity was characterized using deviance. Countryspecific estimates were generated by multivariable logistic regression.

Results: Of 4,980 records, 165 covering 18 EU/EEA countries met inclusion criteria. The

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majority of collected data were published in Germany, France, United Kingdom, The Netherlands, and Spain. Most influential factor for anti-HEV IgG was assay (42% of total

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deviance); IgM and HEV-RNA were predominately determined by studied population (34%, 74%). Adjusted country-specific estimates for anti-HEV IgG ranged from 1.82%-17.06%, IgM

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was visible.

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0.14%-6.54%, and HEV-RNA 0.00%-0.10%. No general geographical pattern of HEV-positivity

Conclusions: Our analysis revealed a high heterogeneity regarding data availability and HEV-

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seropositivity across EU/EEA countries. Determinants of HEV-estimates including assay are to be considered when interpreting HEV-epidemiology and its burden.

Keywords Hepatitis E Virus; HEV infection marker; HEV positivity; Epidemiology; Europe; EU/EEA; Sero-prevalence 2

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Introduction Estimations revealed 20 million new hepatitis E virus (HEV) infections per year1 and around 70,000 hepatitis E-related deaths worldwide.1-2 In addition, increasing numbers of new HEV infections acquired across EU/EEA were reported recently, indicating that indigenous HEV

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infections are more common than formerly expected in high-income countries.3-6 These factors and the distinct features characterizing HEV make it an important contributor to the global hepatitis burden and relevant for epidemiologic investigation. Transmission of HEV occurs

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genotype-specific: HEV genotype 1 and 2 cause HEV epidemics in low-resource countries via feacal-oral transmission whereas genotype 3 is predominately transmitted by consumption of undercooked HEV contaminated pork products7 and responsible for indigenous sporadic cases in Europe.3,8 Sources for HEV data in general are sparse; 17 of 31 countries of the European Union

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(EU) and European Economic Area (EEA) had HEV national notification procedures with varying case definitions,9 consisting of clinical appearance and/or detection of certain infection

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markers such as anti-HEV IgG, IgM, and HEV-RNA.10 These data, however are influenced by the often asymptomatic nature of HEV infection in immunocompetent individuals4 and a similar

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clinical picture caused by hepatitis A virus,11 which leads to a frequent underreporting of new

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HEV cases.12 Other data sources like serological surveys or epidemiologic studies on HEV are even more limited. The absence of a “gold-standard” assay for detecting HEV infection

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additionally complicates HEV epidemiologic assessment,13 particularly with regards to anti-HEV IgG surveyed as marker for HEV-seroprevalence. Previous comparative analyses on anti-HEV IgG seroprevalence show unexplained variations across Europe,14 but a comprehensive assessment of the epidemiologic situation of HEV in Europe, paralleled by an analysis of explanatory factors for HEV differences and including all HEV infection markers, is lacking. Restrictions in published studies in this field apply to geographical region,1,15 language of 3

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publication,1,15 HEV sub-genotypes,1 single infection markers,14 or lacking systematic searches.3,6 Therefore, the aim of this study is to profile the HEV epidemic in EU/EEA countries by means of a systematic assessment and pooling of available research data on HEV infection markers. Differences across European countries are thereby evaluated, as well as their potentially

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explanatory factors.

Methods

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Search strategy and study selection

The systematic literature search in PubMed, Embase, Scopus, and Cochrane Library (Wiley platform) was performed independently by two investigators of the European Centre for Disease Prevention and Control (ECDC) (search strategies see Table SM1). Considered were studies in

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humans, published between 2005 and August 2015. No language and no geographical restrictions were applied in the search strings. An initial screening of all identified records was conducted by

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ECDC excluding studies from non-EU/EEA countries, single-case reports, case series with less than ten cases, animal studies, and interventional studies (e.g. clinical trial) or environmental

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analyses (e.g. meta-analysis). Records reported in a non-English language (e.g. Estonian, and

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Hungarian) were read and assessed for inclusion eligibility by native speakers. Identified records based on the initial screening were uploaded into an EndNote database for a subsequent full text

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screening (EndNote version X 7·1). We performed a full text screening to identify records with relevant reported HEV research data and eligible for our statistical analysis. Records e.g. on duplicated data or with imprecise reporting of tested HEV infection markers were excluded from analysis. In addition, we manually searched in reference section of records included in the full text screening for additional publications meeting inclusion criteria. 4

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Data extraction, data items, and synthesis The data extraction of all relevant reports into a specifically created EXCEL® sheet was carried out independently by two extractors (CKT, MH) for the following variables: first author, year of publication, EU/EEA country name, geographic location of study, number of tested as well as

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seropositive subjects for each HEV infection marker (anti-HEV IgG, anti-HEV IgM, and HEVRNA) by year of blood collection (year start, end), age (min, max), sex, underlying (study) population (Table 1), laboratory test method, and brand name of laboratory test method. Risk of bias was assessed done using “Joanna Briggs Institute Critical Appraisal Checklist for Studies

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Reporting Prevalence”16 with ten items. The response options were either “yes”,” no”, “unclear” or “not applicable”. We categorized the risk of bias by creating three groups: low (0 to 1 item answered with no/unclear); intermediate (2 to 4 items answered with no/unclear), and high (more

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than 4 items answered with no/unclear). The data extraction was carried out based on published information by using data points describing the smallest reported unit, e.g. smallest reported age-

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categories, sex-specific data, time of blood collection and underlying population whereby one row of the excel sheet corresponds to one data point.

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We extracted data on HEV markers without any restrictions like additional required positive

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confirmatory tests (e.g. confirmed by immunoblot analysis or Western blot). Inconsistencies in the EXCEL® databases were solved in discussions between the two extractors; the third reviewer

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(JJO) arbitrated persisting disagreements. Data-points referring only to positive samples, which were subsequently tested with another test, were excluded from statistical analyses. In case of partly or completely reported duplicated data only the most detailed data version or older original publication was selected. Studies that specifically compared two or more different commercial assays on one sample were labelled as validation studies. Statistical analysis 5

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As outcome variables we estimated the positivity of three HEV infection markers: for estimating the HEV prevalence across EU/EEA we considered data on anti-HEV IgG, and for identifying recent HEV infections we used data on anti-HEV IgM and HEV-RNA. In order to identify variables influencing HEV positivity (exposure variables), we conducted a forward selection of

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variables (based on Akaike information criterion (AIC)) in multivariable logistic regression analyses, for each HEV infection marker separately. In case of missing data on age, default ageranges were applied: adult population and blood donors 18 to 65 years, pupils 5 to 15 years, pregnant women 15 to 49 years, and army personnel 18 to 45 years of age. Respective midpoints

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of the reported age-ranges were used in regression analysis. For calculating country-specific estimates for each HEV infection markers we performed a meta-analysis using multivariable logistic regression based on all data points and including identified variables affecting HEV-

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positivity.

To allow assessment of the relation between relevant variables and potential biases, unadjusted

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findings obtained from univariable logistic regression analysis (data not shown) were additionally compared to findings from the multivariable analysis.

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Adjusted country-specific estimates of each HEV infection markers were visualized using the

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package ggmap (version 2·6·1·1) of R statistical platform. Categories representing the endemicity level for each HEV infection marker were defined as follows: low (anti-HEV IgG:

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0% to ≤4.99%; anti-HEV IgM: 0% to ≤1.99%; HEV-RNA: 0% to ≤0·03%), intermediate (antiHEV IgG: 5% to ≤9·99%; anti-HEV IgM: 2% to ≤3·99%; HEV-RNA:0·04% to ≤0·07%), and high (anti-HEV IgG: ≥10%; anti-HEV IgM: ≥4%; HEV-RNA: ≥0.08%). For investigating the influence of the population studied, “blood donors” were selected as reference since this group provides the highest number of data points, i.e. anti-HEV IgG and HEV-RNA serologically tested individuals. For age, the reference value used was 40 years, and the reference for assay was the 6

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mean positivity of each HEV infection marker across all applied assays among the included studies. To visualize the magnitude of identified factors significantly affecting HEV-positivity, deviance was calculated and presented in a pie-chart. Furthermore, the dominating effect of applied assay on anti-HEV IgG seropositivity was validated by considering only data of studies

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which directly compared different assays. Based on these data, odds ratios (OR) with corresponding 95% confidence intervals (95%-CI) were calculated for each respective populations and setting (ORCA). These ORsCA were then compared to respective OR from multivariable regression analysis using the whole dataset (ORMA). All statistical analyses were

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conducted using the R statistical platform (version 3·4·2).

Results

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Included study data

The systematic search provided 4,978 potentially relevant publications; additional manual search

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revealed two records (Figure 1). After preliminary screening according to initial exclusion criteria, 287 full text articles were identified and read. Of these, 122 reports were excluded for the

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following reasons: duplicated data, sample collection prior to 2003 or other publication types

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(outbreak investigations, reviews or meta-analyses). In all, 165 studies (755 data-points) from 18 countries were deemed eligible for inclusion in our analyses, with blood collected between 2003

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and 2014. The highest number of studies were available for Germany (n=34) and France (n=34). No relevant data on any HEV infection marker was available from the EU/EEA countries: Cyprus, Czech Republic, Finland, Iceland, Ireland, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Norway, Slovakia, and Slovenia. The majority of the publications had an intermediate risk of bias (anti-HEV IgG: 57.0% (n=77); anti-HEV IgM: 65.3% (n=49); HEVRNA: 51.3% (n=41)). Especially publications reporting HEV-RNA data were associated with a 7

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high risk of bias (anti-HEV IgG: 28.2% (n=38); anti-HEV IgM: 25.3% (n=19); HEV-RNA: 41.3% (n=33)). While anti-HEV IgG, indicating the HEV seroprevalence, was the most frequently reported infection marker (137 reports), HEV-RNA was most frequently measured according to the number of tested individuals (n=931,521 tested individuals) (Table 1). The most

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frequently studied population for anti-HEV IgG and HEV-RNA were blood donors (32% and 98%, respectively) (Table 2). This was not true for anti-HEV IgM. Here, the most frequently studied population was characterized by individuals with clinically symptomatic hepatitis virus infection (25%). The most frequently used assay for anti-HEV IgG and IgM detection was

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Wantai followed by Mikrogen, and MP|Genelabs, in case of HEV-RNA it was Qiagen (Table SM2). Variables influencing HEV positivity

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To identify variables affecting the HEV positivity, forward selection was performed using logistic regression analysis, revealing an association between underlying population, country, and

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assay with all three HEV infection markers (Table SM3). Age (mid-point) was associated with anti-HEV IgG and IgM but not with HEV-RNA positivity. Age-ranges, which were only

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available for anti-HEV IgG, revealed an almost linear relation, i.e. a constantly increasing risk of

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infection with age (Figure SM1). Sex-specific data were only reported in 24% (n=32) of studies on anti-HEV IgG, in 15% (n=11) on IgM and in 9% (n=7) on HEV-RNA. Accordingly, no

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detailed sex-specific statistical analyses were performed. We found an association between “year of blood collection” and anti-HEV IgG/IgM positivity. But, since the time-dependent change of both estimates were opposite (decrease anti-HEV IgG and increase IgM) as well as the unadjusted findings (data not shown) were reversed to findings from the multivariable analysis (increase in anti-HEV IgG and decrease in IgM), indicating a high risk of potential bias, we did not considered this variable for country-specific estimates. 8

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Adjusted country-specific HEV estimates The adjusted estimate for anti-HEV IgG positivity for 18 EEA/EU countries ranged between 1.8% and 17.1% (Table 1). Low and intermediate levels of anti-HEV IgG prevalence were found in seven countries (Figure 2). Four countries had a high endemicity; these were predominantly

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located in Eastern Europe. The highest anti-HEV IgG prevalence was detected in Poland (based on 182 tested sero-samples) (Table 1). Anti-HEV IgM seropositivity was calculated for 12 countries and ranged from 0.1% to 6.5%. The geographical patterns of anti-HEV IgG and IgM were similar, with Portugal, UK, Belgium, Greece, and Hungary characterized by low endemicity

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level. France and Italy had an intermediate level and Germany, Bulgaria, and Sweden a high antiHEV IgM level. HEV-RNA relevant data was found for nine countries with a positivity up to 0.1%. Similar to anti-HEV IgG, Portugal, UK, Belgium, and Austria showed a low level for

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HEV-RNA positivity. Germany had an intermediate level, whereas France, Italy, and the Netherlands had a high level of HEV-RNA positivity. In contrast to anti-HEV IgG and IgM,

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Sweden was characterized by low HEV-RNA positivity. We compared unadjusted and adjusted HEV estimates for each HEV infection marker (Table S4). Depending on the country some

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estimates were considerably lower after adjustment (e.g. Austria: unadjusted anti-HEV IgG

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14.3% adjusted 4.3%; Belgium: unadjusted HEV-RNA 2.5%, adjusted 0.01%) or occasionally higher (e.g. Sweden: unadjusted anti-HEV IgM 3.2%, adjusted 6.0%).

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Magnitude of variables significantly affecting HEV-positivity Applied HEV-assay was the most important variable influencing anti-HEV IgG positivity and explained 41.9% of the total deviance (Figure 3). The variable underlying population explained the largest fraction of the total variance of HEV-RNA (74.3%) and anti-HEV IgM (33.9%) positivity, respectively, with especially symptomatic hepatitis patients and individuals with occupational exposure having higher HEV-RNA positivity than other populations. The variable 9

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country, on the other hand, explained 18.2% of anti-HEV IgG and 27.9% of anti-HEV IgM variation. While age was explanatory for 10.3% of the total variance of anti-HEV IgG, it was less or not important for anti-HEV IgM and for HEV-RNA, respectively. Almost one third of the total variance of anti-HEV IgM (33.8%), and about one fourth of anti-HEV IgG (27.2%) and HEV-

Effect of applied assay on anti-HEV IgG seropositivity

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RNA (17.9%) could not be explained by any of the extracted variables (unexplained variance).

Eleven reports were identified comparing at least two different anti-HEV IgG assays.17-27 In order to directly assess the impact of HEV-assay on anti-HEV IgG positivity, data of these studies were

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used to calculate separate ORs (ORCA, grey diamonds, Figure 4) and compared with OR from multivariable logistic regression analysis for all studies (ORMA, black circles, Figure 4) using MP|Genelabs as reference (OR: 1·0, black line). Dia.Pro and Adaltis were not directly compared

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to MP|Genelabs. Accordingly, the ORs for these assays evolve from indirect comparison. Across both analyses, Wantai (ORCA: 12.7; ORMA: 10.4) and Mikrogen (ORCA: 5·5; ORMA: 4·0)

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provided comparable findings (no significant differences), indicating a high portion of the variation in anti-HEV IgG seropositivity is related to the applied assay. In contrast, for Abbott

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(ORCA: 0·6; ORMA: 1·4), Adaltis (ORCA: 4·5; ORMA: 1·6), and Dia.Pro (ORCA: 0·4; ORMA: 2·5)

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the ORs differed, suggesting that the results from multivariable analysis might be still biased by confounding variables. However, because of the small number of studies directly comparing

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assays (Abbott n=1, Dia.Pro n=1, Adaltis n=2), the ORs are affected by uncertainty resulting in wide 95%-CI. Since only three reports were identified which compare different anti-HEV IgM assays and none for HEV-RNA assays, no analysis for these two HEV infection markers was performed.

Discussion 10

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We found a high heterogeneity across EU/EEA countries in terms of availability and nature of HEV research data, which was also reflected in the generated country-specific HEV estimates. Far more publications were available and included from Western (e.g. Germany and France) compared to Eastern European countries (e.g. Poland and Romania). This could be related to

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different levels of awareness, blood screening practices, and notification rules.9 In fact, for all Western European countries with a large population and a HEV notification rules in place, like Germany, France, and Italy more studies were available than for other countries.

In our investigation, no obvious geographical pattern of HEV-positivity across European

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countries was identifiable for any of the three infection markers. Even though the HEV endemicity greatly varied across the EU/EEA countries, the anti-HEV IgG (seroprevalence) levels for some countries like France (high) and the UK (low) are similar to the findings of Hartl

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et al 14. In contrast, our estimated anti-HEV IgG seroprevalence level for Italy (intermediate) was higher and the level for Denmark was lower (intermediate) than previously reported 14. However,

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despite the variation between and within the countries regarding the three HEV markers, we identified the UK, Portugal, Austria and Belgium with consistent low endemicity level across all

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three infection markers. The comparatively low and heterogeneous availability for HEV research

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data constitutes a challenge in identifying potential geographical patterns of the HEV endemicity across EU/EEA countries.

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The epidemiological situation of HEV in EU/EEA countries was recently described based on expert opinion and data from national surveillance systems. 9 The authors observed an increase of reported new HEV cases among Western EU/EEA countries; in case of France the numbers of laboratory-confirmed cases of HEV were nearly 10-times higher in 2014/2015 than compared to 2009.9 In our study using research data from studies, we found a time-dependent increase of antiHEV IgG seropositivity, and a small decline of IgM positivity using unadjusted estimates (Figure 11

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SM2). Since these findings were reversed to the adjusted estimates from our multivariable analysis (decrease anti-HEV IgG, increase IgM), we did not specifically investigate timedependent changes of HEV-positivity. In addition, the time-depended changes of HEV-positivity are likely to be biased by applied assay, in particular by predominant use of the Wantai assay in

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more recent years, which can explain both, higher HEV-prevalence and lower anti-HEV IgM positivity (Figure SM2). Figure SM2 further illustrates that the preferences according to applied assays changed over time, and as long as no standardized HEV testing strategy exists, it will change again due to the continuously optimization of HEV detection approaches to improve the

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sensitivity and specificity. In line with findings from other studies,13-14,28-30 our results confirm that the applied HEV-assay is the most important factor for the observed variation of anti-HEV IgG seropositivity, Furthermore, our additional analysis on 11 studies, which directly compare

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assays and were used as validation studies confirms the differences due to applied assays (Figure 4).Wantai was the most frequently applied assay in the included studies for our investigation

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(Table 2) and is expected to be more sensitive in detecting anti-HEV IgG seroprevalence compared to other assays (Figure SM2).14,29,31 According to our analyses, the predicted

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proportion of individuals with previous HEV infection is likely to vary by a factor of almost ten,

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depending on the applied anti-HEV IgG assay. In this context, Dreier and colleagues discussed differing expression systems of HEV antigens and the viral strain origin as potential explanations

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for assay variation.32 In specific, the applied HEV-assay antigens were mostly derived from HEV genotype 1 or 2, suggesting a lower reactivity towards genotype 3.32-34 Other studies indicated that assays based on genotype 1 and 2 antigens also suffice for the detection of genotype 3.35-36 However, assays with homologous antigens seemed to induce a stronger reactivity and might be more sensitive for the related HEV genotype.37 These findings and the fact that there is no “gold standard” for anti-HEV IgG and IgM detection,13-14 need to be kept in mind when interpreting 12

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HEV country-estimates. In this sense, a statistical adjustment for assay is indispensable, however, since some assays were almost exclusively applied in certain countries (Mikrogen (Germany), Biokit (Spain), Dia.Pro (Italy)) the separation of country and assay effects is only possible to some extent. The strong association we found between country and applied assay, especially in

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countries using the Wantai assay, could explain considerable differences between the adjusted and unadjusted country estimates in some countries, e.g. for anti-HEV IgG in Austria (Table S4). In contrast to anti-HEV IgG, our data revealed the applied assay has a much lower effect on the anti-HEV IgM and HEV-RNA positivity (Figure 3). Especially with regard to the diagnosis of

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recent HEV infection, undistorted detection of these markers is of great importance.

In comparison to anti-HEV IgG and IgM, data on HEV-RNA is missing from research studies in Eastern EU/EEA countries. The proportion of HEV-RNA positivity ranges from 4 per 10,000 in

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blood donors to 121 per 1,000 in study populations with symptomatic hepatitis. The observed discrepancy between anti-HEV IgM and HEV-RNA (Figure 2, Table 2) demonstrate that the anti-

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HEV IgM titer is not only a marker for acute but also for recent infection. In addition, a reexposure to HEV, which already had the disease or contact with thermal devitalized HEV

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through cooked meat, could be reason of immune response without evidence of viral replication.

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We did not apply any exclusion criteria regarding the population studied. Depending on the population group examined in studies, the HEV-positivity differed, especially regarding anti-

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HEV IgM and HEV-RNA. This needs to be taken into account when interpreting unadjusted estimates for countries that are based on studies conducted mostly among persons vulnerable to HEV due to occupational exposure, as in the case of farmers,38 or individuals with chronic diseases or taking immunosuppressive drugs.3 For example, the difference between unadjusted and adjusted HEV-RNA estimates for Belgium (Table S4) is due to the fact that only symptomatic hepatitis persons were investigated in the included studies (Table 1). 13

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We examined the effects of risk of bias using a quality assessment tool in included studies. However, risk of bias did not have impact on any infection marker, indicating that the applied tool with its classification levels (low, intermediate and high) might be insufficient for fully disentangling possible influences on HEV estimates.

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The main limitations of this systematic review are related to the availability of published HEV research data across EU/EEA member states and the fact that only records up to 2015 were included. Potentially relevant HEV data have been published after that date, e.g. from EU/EEA countries for which no data meeting our inclusion criteria were (e.g. Iceland39 or Finland40).

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Particularly from Eastern Europe, such as Poland, recent data on HEV seroprevalence (anti-HEV IgG) were published and reporting a comparatively higher values (blood donors 49.6% and HIV patients 50.8%).41 Further, the majority of collected data were published in five (Germany,

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France, UK, The Netherlands, and Spain) out of 18 EU/EEA countries, by why a comprehensive picture of the HEV situation across EU/EEA is not possible. The quality and the level of detail of

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reported data varied not only by country but also by study. Age- and sex-specific data were rarely reported, especially for children; this restricted age-specific assessments. In addition, some

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studies did not provide detailed information on the studied population or used various population

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groups at different risk for HEV-infection. A further fact, which we clearly confirmed with our analyses, is the lack of a standardized diagnostic assay to detect each HEV infection marker,

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which also influences the provided estimates. Due to inconsistent verification processes (e.g. confirmed by immunoblot analysis or Western blot) we extracted and analysed only direct and not re-confirmed results for the HEV markers. A challenge in our investigation was the application of a meta-analysis. As already discussed in detail, HEV available data were heterogonous across EU/EEA countries, different variable (such as applied assay) has a strong influence on the HEV-positivity, and the strong correlations 14

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between multiple variables (especially assay and country) make a distinct identification of effects of each variable on HEV-positivity very difficult. As mentioned, the serological assays underwent improvement over time making an investigation on timely trends of the HEV prevalence almost impossible. Furthermore, we did not consider in the meta-analysis the

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variation within countries, even though high variation of the seroprevalence depending on the geographical area has been reported.42 Nonetheless, we were the first to take this step and performed a meta-analysis using multivariable regression with the existing data and adjusted for all relevant variables showing a homogeneous collection of HEV-relevant data is urgently

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required.

In light of recent HEV outbreaks in Europe,43-46 there is an increasing awareness for HEV as a public health issue. Comparable epidemiologic measure assist in designing HEV treatment and

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screening in donated blood.49

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prevention strategies, for example regarding the vaccination,47 food safety,48 and HEV-RNA

Conclusion

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Country estimates on HEV prevalence for different infection markers provided from this study

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serve as basis for a comparison of the country-specific HEV epidemiology in Europe. Results can assist in targeting preventive HEV measures including vaccine prevention, e.g. with regards to

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population groups at risk. In order to build up a detailed profile of HEV for Europe, our results underpin the need for taking the performance of the assays into account; specifically for those assays, which have been applied in HEV studies and for notification.

Acknowledgements Funding information 15

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ECDC funded the extraction of the data. ECDC had no role in, or influence on the scientific analyses conducted. Data analysis, interpretation, and writing of the report were done independently by the authors. ECDC takes no responsibility for data analysis, presentation and interpretation and cannot be held liable for conclusions or opinions drawn.

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Authors’ contributors

JJO guided the project including data extraction, analyses and interpretation and supervised the manuscript preparation. JH and MH drafted and revised the manuscript, with contributions from JJO. CKT and MH screened full texts for inclusion, conducted the data extraction and created the

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final research database. JH did data checks and together with RTM, developed the statistical analysis strategy; JH conducted the analysis, supervised by RTM; GK supported the interpretation and project conduct. Authors GK, CKT and RTM read the manuscript and

Declaration of interests

Acknowledgments

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We declare no competing interests.

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provided relevant comments.

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ECDC initiated the project, developed the initial search strategy and performed the first steps of

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the systematic review until data extraction.

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References 1.

Rein DB, Stevens GA, Theaker J, Wittenborn JS, Wiersma ST. The global burden of

hepatitis E virus genotypes 1 and 2 in 2005. Hepatology. 2012;55(4):988-97. 2.

Mortality GBD, Causes of Death C. Global, regional, and national age-sex specific all-

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cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;385(9963):117-71. 3.

Clemente-Casares P, Ramos-Romero C, Ramirez-Gonzalez E, Mas A. Hepatitis E Virus

4.

AN US

in Industrialized Countries: The Silent Threat. Biomed Res Int. 2016;2016:9838041.

Dalton HR, Bendall R, Ijaz S, Banks M. Hepatitis E: an emerging infection in developed

countries. Lancet Infect Dis. 2008;8(11):698-709. 5.

Sayed IM, Vercouter AS, Abdelwahab SF, Vercauteren K, Meuleman P. Is hepatitis E

6.

M

virus an emerging problem in industrialized countries? Hepatology. 2015;62(6):1883-92. Lapa D, Capobianchi MR, Garbuglia AR. Epidemiology of Hepatitis E Virus in European

ED

Countries. Int J Mol Sci. 2015;16(10):25711-43. Kupferschmidt K. Europe's new hepatitis problem. Science. 2016;353(6302):862-3.

8.

Sridhar S, Lau SK, Woo PC. Hepatitis E: A disease of reemerging importance. J Formos

PT

7.

9.

CE

Med Assoc. 2015;114(8):681-90. Adlhoch C, Avellon A, Baylis SA, Ciccaglione AR, Couturier E, de Sousa R, et al.

AC

Hepatitis E virus: Assessment of the epidemiological situation in humans in Europe, 2014/15. J Clin Virol. 2016;82:9-16. 10.

Aggarwal R. Diagnosis of hepatitis E. Nat Rev Gastroenterol Hepatol. 2013;10(1):24-33.

11.

Echevarria JM. Light and Darkness: Prevalence of Hepatitis E Virus Infection among the

General Population. Scientifica (Cairo). 2014;2014:481016.

17

ACCEPTED MANUSCRIPT

12.

Pischke S, Behrendt P, Bock CT, Jilg W, Manns MP, Wedemeyer H. Hepatitis E in

Germany--an under-reported infectious disease. Dtsch Arztebl Int. 2014;111(35-36):577-83. 13.

Norder H, Karlsson M, Mellgren A, Konar J, Sandberg E, Lasson A, et al. Diagnostic

Performance of Five Assays for Anti-Hepatitis E Virus IgG and IgM in a Large Cohort Study. J

14.

CR IP T

Clin Microbiol. 2016;54(3):549-55.

Hartl J, Otto B, Madden RG, Webb G, Woolson KL, Kriston L, et al. Hepatitis E

Seroprevalence in Europe: A Meta-Analysis. Viruses. 2016;8(8). 15.

Aggarwal R. The global prevalence of hepatitis E virus infection and susceptibility: A

AN US

systematic review. Report produced for the World Health Organization, Dept. of Immunization, Vaccines and Biologicals. WHO/IVB/10.14: WHO, Geneva, Switzerland; 2014 [cited 2017 13.03]. Available from:

16.

M

http://apps.who.int/iris/bitstream/10665/70513/1/WHO_IVB_10.14_eng.pdf. Whiting P, Rutjes AW, Reitsma JB, Bossuyt PM, Kleijnen J. The development of

ED

QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol. 2003;3:25. Holm DK, Moessner BK, Engle RE, Zaaijer HL, Georgsen J, Purcell RH, et al. Declining

PT

17.

67.

Sauleda S, Ong E, Bes M, Janssen A, Cory R, Babizki M, et al. Seroprevalence of

AC

18.

CE

prevalence of hepatitis e antibodies among Danish blood donors. Transfusion. 2015;55(7):1662-

hepatitis E virus (HEV) and detection of HEV RNA with a transcription-mediated amplification assay in blood donors from Catalonia (Spain). Transfusion. 2015;55(5):972-79. 19.

Pischke S, Bremer B, Malehsa D, Gisa A, Behrendt P, Rahbarian S, et al. Increased anti

HEV seroprevalence rates in heart transplant recipients: Comparison of two seroassays. Journal of Hepatology. 2014;60(1):S292. 18

ACCEPTED MANUSCRIPT

20.

Pischke S, Schwarze-Zander C, Bremer B, Lehmann P, Spengler U, Gisa A, et al. Anti-

HEV seroprevalence rates in HIV-infected patients determined by two commercially available assays. Hepatology. 2013;58(4):1309A. 21.

Krumbholz A, Joel S, Dremsek P, Neubert A, Johne R, Dürrwald R, et al. Seroprevalence

Microbiology and Immunology. 2014;203(4):273-82. 22.

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of hepatitis E virus (HEV) in humans living in high pig density areas of Germany. Medical

Tabibi R, Baccalini R, Barassi A, Bonizzi L, Brambilla G, Consonni D, et al.

Occupational exposure to zoonotic agents among agricultural workers in Lombardy Region,

23.

AN US

Northern Italy. Annals of Agricultural and Environmental Medicine. 2013;20(4):676-81.

Vernier M, Rossi-Tamisier M, Richet H, Brouqui P, Parola P, Bouamri Y, et al. Anti-

hepatitis E virus antibody prevalence in French expatriate workers. International Journal of

24.

M

Infectious Diseases. 2013;17(11):1082-84.

Wenzel JJ, Preiss J, Schemmerer M, Huber B, Jilg W. Test performance characteristics of

ED

anti-HEV IgG assays strongly influence hepatitis e seroprevalence estimates. Journal of Infectious Diseases. 2013;207(3):497-500. Rossi-Tamisier M, Moal V, Gerolami R, Colson P. Discrepancy between anti-hepatitis E

PT

25.

CE

virus immunoglobulin G prevalence assessed by two assays in kidney and liver transplant recipients. Journal of Clinical Virology. 2013;56(1):62-64. Dremsek P, Wenzel JJ, Johne R, Ziller M, Hofmann J, Groschup MH, et al.

AC

26.

Seroprevalence study in forestry workers from eastern Germany using novel genotype 3- and rat hepatitis E virus-specific immunoglobulin G ELISAs. Medical Microbiology and Immunology. 2012;201(2):189-200.

19

ACCEPTED MANUSCRIPT

27.

Bouwknegt M, Engel B, Herremans MMPT, Widdowson MA, Worm HC, Koopmans

MPG, et al. Bayesian estimation of hepatitis E virus seroprevalence for populations with different exposure levels to swine in The Netherlands. Epidemiology and Infection. 2008;136(4):567-76. 28.

Kodani M, Kamili NA, Tejada-Strop A, Poe A, Denniston MM, Drobeniuc J, et al.

CR IP T

Variability in the performance characteristics of IgG anti-HEV assays and its impact on reliability of seroprevalence rates of hepatitis E. J Med Virol. 2017;89(6):1055-61. 29.

Sommerkorn FM, Schauer B, Schreiner T, Fickenscher H, Krumbholz A. Performance of

Hepatitis E Virus (HEV)-antibody tests: a comparative analysis based on samples from

AN US

individuals with direct contact to domestic pigs or wild boar in Germany. Med Microbiol Immunol. 2017. 30.

Wenzel JJ, Preiss J, Schemmerer M, Huber B, Jilg W. Test performance characteristics of

M

Anti-HEV IgG assays strongly influence hepatitis E seroprevalence estimates. J Infect Dis. 2013;207(3):497-500.

Bendall R, Ellis V, Ijaz S, Ali R, Dalton H. A comparison of two commercially available

ED

31.

anti-HEV IgG kits and a re-evaluation of anti-HEV IgG seroprevalence data in developed

Dreier J, Juhl D. Autochthonous hepatitis e virus infections: a new transfusion-associated

CE

32.

PT

countries. J Med Virol. 2010;82(5):799-805.

risk? Transfus Med Hemother. 2014;41(1):29-39. Herremans M, Bakker J, Duizer E, Vennema H, Koopmans MP. Use of serological assays

AC

33.

for diagnosis of hepatitis E virus genotype 1 and 3 infections in a setting of low endemicity. Clin Vaccine Immunol. 2007;14(5):562-8. 34.

Vollmer T, Diekmann J, Eberhardt M, Knabbe C, Dreier J. Monitoring of Anti-Hepatitis

E Virus Antibody Seroconversion in Asymptomatically Infected Blood Donors: Systematic Comparison of Nine Commercial Anti-HEV IgM and IgG Assays. Viruses. 2016;8(8). 20

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35.

Legrand-Abravanel F, Thevenet I, Mansuy JM, Saune K, Vischi F, Peron JM, et al. Good

performance of immunoglobulin M assays in diagnosing genotype 3 hepatitis E virus infections. Clin Vaccine Immunol. 2009;16(5):772-4. 36.

Bendall R, Ellis V, Ijaz S, Thurairajah P, Dalton HR. Serological response to hepatitis E

CR IP T

virus genotype 3 infection: IgG quantitation, avidity, and IgM response. J Med Virol. 2008;80(1):95-101. 37.

Zhao C, Geng Y, Huang W, Ma H, Wang Y. Valuable antibody detection method for

classifying hepatitis E virus genotypes. J Med Virol. 2018;90(1):142-47.

De Schryver A, De Schrijver K, Francois G, Hambach R, van Sprundel M, Tabibi R, et al.

AN US

38.

Hepatitis E virus infection: an emerging occupational risk? Occup Med (Lond). 2015;65(8):66772.

Love A, Bjornsdottir TB, Olafsson S, Bjornsson ES. Low prevalence of hepatitis E in

M

39.

Iceland: a seroepidemiological study. Scand J Gastroenterol. 2018;53(3):293-96. Kantala T, Kinnunen PM, Oristo S, Jokelainen P, Vapalahti O, Maunula L. Hepatitis E

ED

40.

Virus Antibodies in Finnish Veterinarians. Zoonoses Public Health. 2017;64(3):232-38. Bura M, Lagiedo M, Michalak M, Sikora J, Mozer-Lisewska I. Hepatitis E virus IgG

PT

41.

CE

seroprevalence in HIV patients and blood donors, west-central Poland. Int J Infect Dis. 2017;61:20-22.

Mansuy JM, Gallian P, Dimeglio C, Saune K, Arnaud C, Pelletier B, et al. A nationwide

AC

42.

survey of hepatitis E viral infection in French blood donors. Hepatology. 2016;63(4):1145-54. 43.

Guillois Y, Abravanel F, Miura T, Pavio N, Vaillant V, Lhomme S, et al. High Proportion

of Asymptomatic Infections in an Outbreak of Hepatitis E Associated With a Spit-Roasted Piglet, France, 2013. Clin Infect Dis. 2016;62(3):351-7.

21

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44.

Said B, Ijaz S, Kafatos G, Booth L, Thomas HL, Walsh A, et al. Hepatitis E outbreak on

cruise ship. Emerg Infect Dis. 2009;15(11):1738-44. 45.

Colson P, Borentain P, Queyriaux B, Kaba M, Moal V, Gallian P, et al. Pig liver sausage

as a source of hepatitis E virus transmission to humans. J Infect Dis. 2010;202(6):825-34. Miura T, Lhomme S, Le Saux JC, Le Mehaute P, Guillois Y, Couturier E, et al. Detection

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46.

of Hepatitis E Virus in Sewage After an Outbreak on a French Island. Food Environ Virol. 2016;8(3):194-9. 47.

Wu X, Chen P, Lin H, Hao X, Liang Z. Hepatitis E virus: Current epidemiology and

48.

AN US

vaccine. Hum Vaccin Immunother. 2016;12(10):2603-10.

Nelson KE, Heaney CD, Labrique AB, Kmush BL, Krain LJ. Hepatitis E: prevention and

treatment. Curr Opin Infect Dis. 2016;29(5):478-85.

Domanovic D, Tedder R, Blumel J, Zaaijer H, Gallian P, Niederhauser C, et al. Hepatitis

M

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E and blood donation safety in selected European countries: a shift to screening? Euro Surveill.

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2017;22(16).

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Artwork and Tables with Captions Figure 1: Flow chart of records selection process UK: United Kingdom of Great Britain and Northern Ireland Colored Figure:

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Figure 2: Adjusted anti-HEV IgG, IgM and HEV-RNA positivity by EU/EEA country

Anti-HEV IgG and IgM estimates adjusted for applied assay, underlying study population and midpoint of age-range

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HEV-RNA estimates adjusted for applied assay and underlying study population Colored Figure:

Figure 3: Importance of variables for HEV seropositivity by infection marker Based on deviance in multivariable regression models

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Figure 4: Odds ratio for anti-HEV IgG based on studies comparing assays (ORCA, n=11) vs. Odds ratio from multivariable regression on all studies (ORMA, n=165).

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Reference test was MP|Genelabs (black line, OR 1·0).

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Appendix. Supplementary data

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TableExtracted study data and estimated HEV- positivity by HEV infection marker, EEA/EU countries

EV infection arker

Austria

3

21

2,272

0;2;7

Belgium

3

4

1,022

5;7

Bulgaria

1

1

741

5

Croatia

1

2

592

6;7

Denmark

2

11

1,464

2

Estonia

1

16

211

3

France

30

103

15,303

1;2;4;5;6;7;8

Germany

27

143

20,922

0;2;3;4;5;6;7;99

Greece

5

16

2,520

0;2;5;6;7

Hungary

1

1

264

7

Italy

8

29

8,114

0;2;3;5;6;7;8;99

The Netherlands

12

23

16,986

0;2;3;4;5;6;7;8

Poland

1

3

182

4;5;6

2

4

927

0;2;3;7

Romania

3

8

378

0;2

16

34

10,379

0;1;2;3;4;5;6

2

4

285

0;3;6

17+2*

57

10,345

0;2;4;5;6;7;8

135 (137)*

480

92,907

Reports

1

Datapoints2

HEV-RNA

Tested individuals3

Underlying population4

NA

NA

NA

NA

2

3

922

7

1

1

741

5

1

2

592

6;7

NA

NA

NA

NA

NA

NA

18

38

7,316

1;2;4;6;7;8

3,666

0;2;3;4;5;6;7

NA

NA

12

25

NA

NA

2 5 9

5

NA

Reports

NA

1,244

Datapoints2

Tested individuals3

Underlying population4

3

1

Positivity %7 [95%-CI] 0.02 [0.01;0.03] 0.01 [0;0.03]

3

59,045

2;6;7

0.55 [0.35;0.86] 6.54 [2.64;15.34] 0.15 [0.08;0.28]

1

1

81

7

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

21

35

114,994

2;4;6;7;8

7

2.78 [Ref.] 4.74 [3.27;6.82] NA

0.7 [0.44;1.12] 3.12 [2.21;4.39] 0.98 [0.7;1.37]

NA 0.09 [Ref.] 0.06 [0.05;0.07]

21

32

301,467

0;2;4;5;6;7

NA

NA

NA

NA

NA

NA

NA

NA

5

12

3,049

0;2;3;5;6;7;8;99

NA NA 0.08 [0.05;0.13] 0.1 [0.07;0.13]

12

3,569

0;2;5;6;7;8;99

13

6,506

0;3;4;5;6;7

9+1*

18

73,392

2;6;99

NA

NA

NA

NA

NA

NA

NA

NA

NA

0.14 [0.04;0.46]

1

2

434

2;7

0 [0;100]

NA

NA

NA

NA

NA

1

2

434

2;7

NA

NA

NA

NA

9

11

2,340

1;2;3;6;7

1

1

62

6

14+2*

29

8,086

2;4;5;6;7;8

75 (77)*

Positivity %6 [95%-CI]

142

35,478

0.88 [0.6;1.28] 5.95 [1.44;21.51] 0.25 [0.18;0.35]

10

13

11,374

0+1*

1

95,835

2

9+1*

16

271,850

2;4;5;6;8

80 (83)*

133

931,521

NA 0.04 [0.02;0.05] 0.01 [0.01;0.02] 0.03 [0.02;0.04]

0;2;3;6;7;8

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UK

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Spain Sweden

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tal

Portugal

Anti-HEV IgM Positivity % 5 [95%-CI] 4.32 [3.82;4.90] 2.71 [2.1;3.48] 8.37 [6.26;11.11] 1.83 [1.31;2.55] 7.3 [6.33;8.41] 3.28 [1.93;5.51] 11.45 [Ref.] 7.65 [7.05;8.29] 6.86 [5.6;8.38] 2.79 [1.85;4.2] 5.49 [4.78;6.29] 6.84 [6.41;7.29] 17.06 [11.92;23.82] 1.82 [1.41;2.33] 12.1 [9.18;15.78] 5.3 [4.86;5.77] 10.88 [7.61;15.32] 2.31 [2.13;2.51]

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Underlying population4

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Reports

DataTested points2 individuals3

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ountry

Anti-HEV IgG 1

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NA: not data on HEV infection marker; UK: United Kingdom of Great Britain and Northern Ireland; Ref.: reference value 1

Number of identified reports

2

Data-point: one line in the data selection sheet; smallest possible stratification for published data according to (age,

sex, population type and location) Sum of individuals tested (from all publications) for this country

4

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3

0, General population incl. health care worker (HCW); 1, Pregnant women; 2, Blood donors; 3, Population with

occupational exposure (swine worker, agricultural worker, hunters, forest worker, veterinarians); 4, Patients with liver condition; 5, Patients with a condition not related to (chronic) hepatitis virus infection (e.g. neurological

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disorder); 6, Immune compromised individuals (e.g. individuals living with HIV/AIDS, transplant recipients); 7, Individuals with clinically symptomatic hepatitis virus infection; 8, Other (e.g. injecting drug user, refugees); 99, not specified population 5

Estimated HEV prevalence in percentage using data on anti-HEV IgG adjusted by assay (reference: average value

across applied assays), underlying study population (reference: blood donors), and midpoint of age-range (reference:

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40 years of age); for estimating 95%-CI the values of France was selected as reference 6

Estimated recent HEV infection in percentage using data on anti-HEV IgM seropositivity adjusted by assay

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(reference: average value across applied assays), underlying study population (reference: blood donors), and midpoint of age-range (reference: 40 years of age); for estimating 95%-CI the values of France was selected as

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reference 7

Estimated recent HEV infection in percentage using data on anti-HEV-RNA positivity adjusted by assay (reference:

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average value across applied assays) and underlying study population (reference: blood donors); for estimating 95%CI the values of France was selected as reference

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*Four multi-country studies, each counted as one according to alphabetically first appearing country

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Table 2: Extracted study data per HEV-infection marker by underlying study population group

0 1 2 3 4 5 6 7 8 99 Total

Reports1 18 3 31 12 15 21 53 18 7 5 183

Anti-HEV IgG DataTested points2 individuals3 56 22,429 10 3,196 126 29,450 82 4,304 32 2,830 48 6,219 91 15,068 20 4,434 10 2,452 5 2,525 480 92,907

Reports1 4 2 10 3 8 8 30 21 5 1 92

Anti-HEV IgM DataTested points2 individuals3 5 2,152 3 639 26 8,798 4 479 13 1,503 18 2,605 37 6,961 28 10,780 7 1,111 1 450 142 35,478

Reports1 4 0 21 3 6 7 41 11 4 2 99

HEV-RNA DataTested points2 individuals3 4 1,075 0 0 37 913,833 3 234 9 1,028 8 746 49 11,120 11 891 5 1,015 7 1,579 133 931,521

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HEV infection marker Underlying population group

0, General population incl. HCW; 1, Pregnant women; 2, Blood donors; 3, Population with occupational exposure (swine worker, agricultural worker, hunters, forest worker, veterinarians); 4, Patients with liver condition; 5, Patients with a condition not related to (chronic) hepatitis virus infection (e.g. neurological disorder); 6, Immune

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compromised individuals (e.g. individuals living with HIV/AIDS, transplant recipients); 7, Individuals with

clinically symptomatic hepatitis virus infection; 8, Other (e.g. injecting drug user, refugees); 99, not specified population 1

Number of identified reports

2

sex, population type and location) 3

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Data-point: one line in the data selection sheet; smallest possible stratification for published data according to (age,

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Sum of individuals tested (from all publications) for this country

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