Surveillance Algorithms Research Articles

Cooperative Reactive Persistent Surveillance Algorithm Using Multiple UAVs Considering Incident Arrivals

A reactive persistent surveillance algorithm using multiple unmanned aerial vehicles in 2D mission space is proposed considering incident arrivals. Overall coverage is accomplished by target based approach. The algorithm considering incident detection and reduction are used to compute probability distribution which is used to determine revisit time. Multi-agent flocking issue is also considered. Numerical simulation is performed to demonstrate the performance of the proposed algorithm. The proposed algorithm is compared to the existing surveillance motion planner in two aspects: overall coverage and mean incident count.

Postoperative recurrence of adult renal cell carcinoma associated with Xp11.2 translocation/TFE3 gene fusion.

ObjectiveTo analyze the postoperative recurrence of renal cell carcinoma associated with Xp11.2 translocation/TFE3 gene fusion (Xp11.2 tRCC).MethodsThis retrospective study was approved by the institutional review board and performed in accordance with the ethical standards established by the institution. Demographic, clinical, pathological, and follow-up data were compiled for the study cohort.ResultsDuring a mean follow-up of 41.3 months (range, 3–104 months), 8 of 34 patients with Xp11.2 tRCC were confirmed to have recurrence. Three of these patients died with poor outcomes due to a vena cava tumor embolus, and one died of distant metastasis 48 months after the initial nephrectomy during which lymph node metastasis was found. Three patients survived after cytoreduction surgery. One patient was diagnosed with lung metastasis 11 months postoperatively.ConclusionsThe TNM classification provides significant prognostic information for Xp11.2 tRCC. A relatively active surveillance algorithm is recommended, and cytoreduction surgery is an effective approach for recurrent Xp11.2 tRCC. Larger studies are required to more extensively investigate the recurrence of these potentially aggressive tumors.

Evaluation of Exposure-Type Stratification to Improve Poison Center Surveillance

ObjectiveOur objective was to determine if the detection performance ofcurrent surveillance algorithms to detect call clusters is improved bystratifying by exposure category.IntroductionThe Centers for Disease Control and Prevention (CDC) uses theNational Poison Data System (NPDS) to conduct surveillance ofcalls to United States poison centers (PCs) to identify clusters ofreports of hazardous exposures and illnesses. NPDS stores basicinformation from PC calls including call type (information requestonly or call reporting a possible chemical exposure), exposure agent,demographics, clinical, and other variables.CDC looks for anomalies in PC data by using automated algorithmsto analyze call and clinical effect volume, and by identifying callsreporting exposures to pre-specified high priority agents. Algorithmsanalyzing call and clinical effect volume identify anomalies when thenumber of calls exceeds a threshold using the historical limits method(HLM). Clinical toxicologists and epidemiologists at the AmericanAssociation of Poison Control Centers and CDC apply standardizedcriteria to determine if the anomaly is a potential incident of publichealth significance (IPHS) and then notify the respective healthdepartments and PCs as needed. Discussions with surveillance systemusers and analysis of past IPHS determined that call volume-basedsurveillance results in a high proportion of false positive anomalies.A study assessing the positive predictive value (PPV) of thisapproach determined that fewer than four percent of anomalies over afive-year period were IPHS.1A low PPV can cause an unnecessarywaste of staff time and resources. We hypothesized that first stratifyingcall volume by exposure category would reduce the number of falsepositives. With the help of medical toxicologists, we created 20toxicologically-relevant exposure categories to test this hypothesis.MethodsTo compare cluster detection performance between the twoapproaches, we used a historical testbed of hourly exposure callcounts with and without initial stratification by exposure categoryfrom 10 selected PCs from Jan 1, 2006 - Jul 31, 2015. We ran theHLM for both non-stratified and stratified testbeds to estimate themonthly number of anomalies triggered (i.e., alert burden). Our targetsignals to assess detection performance consisted of call samples fromthree large public health events: the 2009 Salmonella food poisoningevent from contaminated peanut butter, the 2012 Hurricane Sandy-associated carbon monoxide poisonings in New Jersey, and the 2014Elk River contaminated water spill in West Virginia (WV). Foreach event, we chose 30 random calls one thousand times to obtain1000 random sets of inject clusters. Each inject cluster was iterativelyadded into the testbed with and without initial stratification byexposure category. We then applied the HLM for each iteration to seeif the algorithm identified the inject cluster. The sensitivity for eachapproach for each PC was calculated as the proportion of iterationswhere the algorithm identified the inject cluster. We reported mediansensitivities from the ten PCs for each of the time windows of 1, 2,4, 8, and 24 hours.ResultsFigure 1 summarizes results for the WV event with markersshowing anomaly burden (x-axis) and sensitivity (y-axis) using thestratified (Δ) and the non-stratified (o) approach by different timewindows (hrs). The results from the other two events are not shownbut established similar patterns. Anomaly burden is shown as theestimated monthly anomaly count for each approach. For example,markers linked by the arrow show that with a 4-hour time window,the stratified approach achieves nearly perfect sensitivity with ~10anomalies as the monthly anomaly burden while sensitivity of thenon-stratified approach is below 20% with ~40 monthly anomalies.The stratified approach gave improved overall sensitivity across alltime windows, and reduced anomaly burden for 1-, 2-, and 4-hourtime windows.ConclusionsWe found a consistent detection advantage (higher sensitivityand lower anomaly burden) for the stratified vs traditional non-stratified approach for 1-, 2-, and 4-hour time windows. Furtherresearch should focus on refining the stratified approach and thespecific surveillance parameters (such as time windows) that increasealgorithm performance.Figure 1: Detection performance comparison: stratified vs non-stratifiedapproach; 2014 Elk River contaminated water spill in West Virginia scenario

Incorporating anal dysplasia screening and management into a surgical practice

Screening practices for anal dysplasia with the use of anal cytology and high-resolution anoscopy (HRA) has become a topic of increased interest to colon and rectal surgeons. However, screening continues to be practiced by a minority of clinicians. One major hurdle is how to incorporate anal cytology screening programs into busy colorectal surgical practices. In this article, I highlight my early experience treating anal dysplasia and review my current approach and practice pattern for treating anal dysplasia. I also suggest a few paradigms for implementing screening into various clinical settings, and offer surveillance algorithms for individual patients with anal dysplasia based on risk factors.

Automated detection of hospital outbreaks: A systematic review of methods.

ObjectivesSeveral automated algorithms for epidemiological surveillance in hospitals have been proposed. However, the usefulness of these methods to detect nosocomial outbreaks remains unclear. The goal of this review was to describe outbreak detection algorithms that have been tested within hospitals, consider how they were evaluated, and synthesize their results.MethodsWe developed a search query using keywords associated with hospital outbreak detection and searched the MEDLINE database. To ensure the highest sensitivity, no limitations were initially imposed on publication languages and dates, although we subsequently excluded studies published before 2000. Every study that described a method to detect outbreaks within hospitals was included, without any exclusion based on study design. Additional studies were identified through citations in retrieved studies.ResultsTwenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). The evaluation of the algorithms was often solely descriptive (n = 15), but more complex epidemiological criteria were also investigated (n = 10). The performance measures varied widely between studies: e.g., the sensitivity of an algorithm in a real world setting could vary between 17 and 100%.ConclusionEven if outbreak detection algorithms are useful complementary tools for traditional surveillance, the heterogeneity in results among published studies does not support quantitative synthesis of their performance. A standardized framework should be followed when evaluating outbreak detection methods to allow comparison of algorithms across studies and synthesis of results.

Surveillance after resection of pancreatic ductal adenocarcinoma with curative intent - a multicenter survey in Germany and review of the literature.

Background Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with high risk of relapse even after curative-intended resection. There are no evidence-based recommendations for surveillance in actual guidelines. Given this situation and as a basis for prospective studies, we wanted to determine the current practice of surveillance after pancreatic cancer resection in German institutions. Methods A web-based questionnaire was sent in 2015 to 300 German institutions (hospitals, outpatient clinics, and private practices) experienced in the care of patients with PDAC. The questionnaire comprised 23 items including the respective institution, the level of care, the annual case load of pancreatic cancer surgery, the surveillance algorithms used, and the most frequently used means for surveillance as well as their evaluation by the users with respect to the effectiveness of these means. Additionally, we perform a review of the literature. Results The final analysis comprised 161 questionnaires (response rate 53.7 %). Mainly high-volume centers (82.5 % with > 300 hospital beds) participated. In 46.6 % of centers, more than 80 % of patients received adjuvant chemotherapy after surgery. Between 60 - 80 % of these patients completed the recommended 6 months of adjuvant treatment, and 47 % of the patients received the whole treatment (surgery, adjuvant therapy) and surveillance in the same center. Upon completion of adjuvant treatment, 96 % of centers survey their patients, and 82 % of these centers already employ diagnostic means during the course of adjuvant chemotherapy. The most commonly used diagnostic means were taking patient history, conducting physical examination, performing laboratory tests including CA19 - 9, and imaging. Of those employed, CA19 - 9 and imaging followed by patient history were considered the most efficient to detect disease relapse by the centers. Half of the institutions perform surveillance for 5 years after surgery. Conclusion This is the first systematic analysis of self-reported surveillance strategies used in Germany after resection of PDAC with curative intent. Surveillance after resection of PDAC with curative intent is common in Germany. Alterations of CA19 - 9 levels as well as imaging and taking patient history are considered the most efficient means to detect relapse of disease by the physicians participating in our survey.

Anal Neoplasia in Inflammatory Bowel Disease: Classification Proposal, Epidemiology, Carcinogenesis, and Risk Management Perspectives.

Patients with inflammatory bowel disease [IBD] may develop, similarly to individuals from general population, rare cases of human papilloma virus [HPV]-related anal canal squamous cell carcinoma [SCC] and intra-epithelial precursor lesions, as well as very rare cases of anal canal adenocarcinoma. Patients with chronic perianal Crohn's disease [CD] are at substantial risk of developing SCC or adenocarcinoma from the fistula-lining epithelium, as well as SCC or adenocarcinoma arising from chronic anorectal ulcerations or strictures. Based on this lesion stratification, we provide in this review tailored incidence estimates and we propose an IBD-specific classification of all types of anal neoplasia that may occur in patients with IBD. After reviewing putative carcinogenesis of all types of neoplasia, we conclude that HPV vaccination could reduce the incidence of HPV-related lesions, although an anal screening programme related to these lesions is not mandatory on the sole basis of IBD. By contrast, we point out that all patients with chronic perianal CD should be explored in depth, including biopsies under anaesthesia and fistula curettage when necessary, in case of any change in anal symptoms ─in particular new, increasing, unexplained pain. Finally, we conclude that there is an urgent need for elaborating and evaluating surveillance algorithms in patients with chronic perianal CD, in order to avoid cancers with late diagnosis and poor prognosis.

정밀 감시정찰을 위한 자동 군집화 기법 개발

In this paper, we propose a coarse-to-fine approach-based automatic clustering algorithm for precision reconnaissance and surveillance. In order to improve the strengths and compensate for the weaknesses of the basic sequential algorithm and K-means clustering algorithm (the first one is simple to implement but may generate significant noise, whereas the second one returns precise results although the number of clusters needs to be known in advance), the proposed algorithm was developed by fusing them. It was validated and verified in a MATLAB simulation and embedded processing. As a result, it can be used to shrink the data effectively in a large dataset.

Evaluation of prothrombin induced by vitamin K absence, macrophage migration inhibitory factor and Golgi protein-73 versus alpha fetoprotein for hepatocellular carcinoma diagnosis and surveillance

Hepatocellular carcinoma (HCC) represents a challenging malignancy of worldwide importance. It is the third most common cause of cancer-related death globally as most patients present with unresectable disease. Alpha-fetoprotein (AFP) is the widely and solely used biomarker for HCC diagnosis; yet, its usefulness is hampered by low sensitivity and specificity. We aimed to identify more sensitive biomarkers for HCC diagnosis and a surveillance algorithm that may facilitate early detection of HCC. A total of 305 Egyptian and Saudi participants grouped as healthy controls, cancer controls, benign hepatic lesions, chronic viral hepatitis and HCC were included. Serum AFP, prothrombin induced by vitamin K absence-II (PIVKA-II), macrophage migration inhibitory factor (MIF) and Golgi protein-73 (GP-73) levels were quantitated by enzyme immunoassay. Significantly higher levels of GP-73 and PIVKA-II were detected in the HCC group than in all other groups, while MIF showed a highly significant increase in HCC from all groups except the cancer control group. The HCC group showed no significant difference between the studied biomarkers and the type of chronic viral hepatitis. On the basis of multiple ROC curve analyses, GP-73 and PIVKA-II showed the highest sensitivity and specificity for surveillance and diagnosis. In conclusion, PIVKA-II and GP-73 offer an effective approach for early HCC diagnosis and surveillance of high-risk groups with a higher accuracy than AFP. MIF may serve as a promising screening tumor marker for the detection of gastrointestinal tract (GIT) malignancy.

A Heuristic Learning Algorithm for Preferential Area Surveillance by Unmanned Aerial Vehicles

A heuristic learning algorithm is presented in this paper to solve the problem of persistent preferential surveillance by an Unmanned Aerial Vehicle (UAV). The algorithm helps a UAV perform surveillance as per quantitative priority specifications over a known area. It allows the specification of regional priorities either as percentages of visitation to be made by a UAV to each region or as percentages of surveillance time to be spent within each. Additionally, the algorithm increases the likelihood of target detection in an unknown area. The neighborhood of a detected target is suspected to be a region of a high likelihood of target detection, and the UAV plans its path accordingly to verify this suspicion. Similar to using the target information, the algorithm uses the risk information to reduce the frequency of visits to risky regions. The technique of using risk map to avoid risky regions is adapted from the existing geometric reinforcement learning technique. The effectiveness of this algorithm is demonstrated using simulation results.

Tailored algorithms for hepatocellular carcinoma surveillance: Is one-size-fits-all strategy outdated?

Current clinical practice guidelines recommend regular hepatocellular carcinoma (HCC) surveillance with biannual ultrasound with or without serum alpha-fetoprotein uniformly applied to all patients with cirrhosis. However, clinical implementation of this one-size-fits-all strategy has been challenging as evidenced by very low application rate below 20% due to various reasons, including suboptimal performance of the surveillance modalities. Newly emerging imaging techniques such as abbreviated MRI (AMRI) and molecular HCC risk biomarkers have increasingly become available for clinical evaluation and implementation. These technologies may have a potential to reshape HCC surveillance by enabling tailored strategies. This would involve performing optimized surveillance tests according to individual HCC risk, and allocating limited medical resources for HCC surveillance based on cost-effectiveness. Tailored HCC surveillance could lead to achievement of precision HCC care and substantial improvement of the current dismal patient prognosis.

Case study on wavelet choice based on statistical image quality measures

Surveillance applications are under many negative influences, which should be suppressed, because these negative influences result in incorrectness of the motion mask. Suppression of several conflicting requirements can be optimized by a multiobjective approach. This paper proposes a multiobjective approach to selection of wavelets based on two main objectives: statistical image quality measures and execution time. Execution time is a measure of wavelets complexity. Segmentation is the final goal in order to insure precise operation of any surveillance algorithm. This paper presents a case study considering one, two, three, and four goals for wavelet selection comparison. Different wavelets are found to be an optimal choice for different weights of the objectives.

Incidence and clinical characteristics of transfusion-associated circulatory overload using an active surveillance algorithm.

The concordance of haemovigilance criteria developed for surveillance of transfusion-associated circulatory overload (TACO) with its clinical diagnosis has not been assessed. In a pilot study to evaluate an electronic screening algorithm, we sought to examine TACO incidence and application of haemovigilance criteria in patients with post-transfusion pulmonary oedema. From June to September 2014, all transfused adult inpatients at four academic hospitals were screened with an algorithm identifying chest radiographs ordered within 12 h of blood component release. Patients with post-transfusion pulmonary oedema underwent case adjudication by an expert panel. TACO incidence was calculated, and clinical characteristics were compared with other causes of post-transfusion pulmonary oedema. Among 4932 transfused patients, there were 3412 algorithm alerts, 50 cases of TACO and 47 other causes of pulmonary oedema. TACO incidence was 1 case per 100 patients transfused. TACO classification based on two sets of haemovigilance criteria (National Healthcare Safety Network and proposed revised International Society for Blood Transfusion) was concordant with expert panel diagnosis in 57% and 54% of reviewed cases, respectively. Although the majority of clinical parameters did not differentiate expert panel adjudicated TACO from other cases, improved oxygenation within 24 h of transfusion did (P = 0·01). The incidence of TACO was similar to that observed in prior studies utilizing active surveillance. Case classification by haemovigilance criteria was frequently discordant with clinical diagnoses of TACO in patients with post-transfusion pulmonary oedema. Improvements in oxygenation within 24 h of transfusion merit further evaluation in the diagnosis of TACO.

Electronic Syndromic Surveillance for Influenza-Like Illness Across Treatment Settings.

OBJECTIVE Syndromic surveillance for influenza-like illness (ILI) is predominantly performed in the outpatient setting. The objective of this study was to compare patterns of ILI activity in outpatient, emergency department (ED), and inpatient settings using an electronic syndromic surveillance algorithm. DESIGN Retrospective cohort study over 7.5 years. SETTING A large community health system comprised of 5 hospitals and >50 clinics. METHODS We applied an electronic syndromic surveillance algorithm for ILI to all primary-care outpatient visits, inpatient encounters, and ED encounters at our health system. Comparisons of ILI activity over time were performed using Spearman's rank correlation coefficient. Cross correlation was used to compare the timing of ILI activity among treatment settings. RESULTS Overall, 4,447,769 patient encounters occurred during the study period; 152,607 of these (3.4%) were consistent with ILI. The correlation coefficient for ILI activity in the outpatient versus ED setting was 0.877, and for the outpatient versus inpatient setting, the correlation coefficient was 0.699. ILI activity among outpatients preceded ILI activity among inpatients by 1 week. ILI activity among children in the outpatient setting preceded ILI activity among adults in all 3 settings by 1 week. CONCLUSIONS Syndromic surveillance for ILI in the outpatient setting yields similar results to surveillance in the ED setting, but it produces less similar results than ILI surveillance in the inpatient setting. ILI activity in the pediatric outpatient population is a potential predictor of future ILI activity in the general population. Infect Control Hosp Epidemiol 2017;38:393-398.

Clinical Impact of Frequent Surveillance Imaging in the First Year Following Chemoradiation for Locally Advanced Non–small-cell Lung Cancer

ObjectiveUncertainty exists regarding the optimal surveillance imaging schedule following definitive chemoradiation (CRT) for locally advanced non–small-cell lung cancer (LA-NSCLC) with regards to both frequency and modality. We sought to document the clinical impact of frequent (at least every 4 months) surveillance imaging. Materials and MethodsThe records of all patients treated with CRT for stage IIIA/IIIB NSCLC between August 1999 and April 2014 were reviewed. Patients were included if they underwent frequent (at least every 4 months) chest computed tomography or positron emission tomography for routine surveillance following CRT for at least 1 year or until progression or death. Radiographic findings and clinical interventions within the first year were identified. ResultsWe identified 145 patients with LA-NSCLC treated with CRT, 63 with eligible imaging. Median age was 63.6 years (range, 41.0-86.9 years). Asymptomatic recurrence was radiographically detected in 38 (60.3%). Twenty-one (33.3%) initiated systemic therapy. Two (3.2%) underwent definitive-intent treatment for isolated disease, including lobectomy for a histologically distinct primary NSCLC and stereotactic radiotherapy for an isolated recurrence, both of whom subsequently progressed. Eleven patients (17.5%) received no further therapy. Five patients (7.9%) underwent additional diagnostic procedures for false-positive findings. ConclusionsFrequent surveillance within the first year following CRT for LA-NSCLC lung cancer detects asymptomatic recurrence in a high proportion of patients. However, definitive-intent interventions were infrequent. The predominant benefit of frequent surveillance appears to be expedient initiation of palliative systemic therapy. Evidence-based algorithms for surveillance are needed, and should account for expected patient tolerance of and willingness to undergo additional cancer-directed therapies.

Early-Term Birth in Single-Ventricle Congenital Heart Disease After the Fontan Procedure: Neurodevelopmental and Psychiatric Outcomes

To investigate the long-term impact of early-term birth (37-38 weeks' gestation) relative to full-term birth (≥39 weeks' gestation) on neurodevelopmental and psychiatric outcomes in adolescents with single-ventricle congenital heart disease (CHD). This cross-sectional cohort study analyzed retrospective medical records from full term adolescents with single-ventricle CHD who underwent the Fontan procedure. Participants underwent neurodevelopmental and psychiatric evaluations, as well as structural brain magnetic resonance imaging. Early-term born adolescents were compared with full-term born adolescents using regression models with adjustments for family social status, birth weight, and genetic abnormality status. Medical and demographic risk factors were examined as well. Compared with the full-term group (n = 100), adolescents born early term (n = 33) scored significantly worse on daily-life executive functions, as measured by the Behavior Rating Inventory of Executive Function parent-report (mean scores: early term, 62.0 ± 10.9; full-term, 55.6 ± 12.2; P = .009) and self-report (P = .02) composites. Adolescents born early term were more likely than those born full term to have a lifetime attention-deficit/hyperactivity disorder (ADHD) diagnosis (early term, 55%; full term, 26%; P = .001). The early-term group also displayed greater psychiatric symptom severity, as indicated by the clinician-reported Brief Psychiatric Rating Scale (mean score: early term, 16.1 ± 8.6; full-term, 12.5 ± 8.2; P = .007). Early-term birth is associated with greater prevalence of executive dysfunction, ADHD diagnosis, and psychiatric problems in adolescents with single-ventricle CHD. Early-term birth should be included as a potential risk factor in the algorithm for closer developmental surveillance in CHD.

Observability transition in real networks.

We consider the observability model in networks with arbitrary topologies. We introduce a system of coupled nonlinear equations, valid under the locally treelike ansatz, to describe the size of the largest observable cluster as a function of the fraction of directly observable nodes present in the network. We perform a systematic analysis on 95 real-world graphs and compare our theoretical predictions with numerical simulations of the observability model. Our method provides almost perfect predictions in the majority of the cases, even for networks with very large values of the clustering coefficient. Potential applications of our theory include the development of efficient and scalable algorithms for real-time surveillance of social networks, and monitoring of technological networks.

Electronic surveillance and using administrative data to identify healthcare associated infections.

Traditional surveillance of healthcare associated infections (HCAI) is time consuming and error-prone. We have analysed literature of the past year to look at new developments in this field. It is divided into three parts: new algorithms for electronic surveillance, the use of administrative data for surveillance of HCAI, and the definition of new endpoints of surveillance, in accordance with an automatic surveillance approach. Most studies investigating electronic surveillance of HCAI have concentrated on bloodstream infection or surgical site infection. However, the lack of important parameters in hospital databases can lead to misleading results. The accuracy of administrative coding data was poor at identifying HCAI. New endpoints should be defined for automatic detection, with the most crucial step being to win clinicians' acceptance. Electronic surveillance with conventional endpoints is a successful method when hospital information systems implemented key changes and enhancements. One requirement is the access to systems for hospital administration and clinical databases.Although the primary source of data for HCAI surveillance is not administrative coding data, these are important components of a hospital-wide programme of automated surveillance. The implementation of new endpoints for surveillance is an approach which needs to be discussed further.

Hepatocellular carcinoma recurrence pattern following liver transplantation and a suggested surveillance algorithm

PurposeThis study aims to evaluate the recurrence pattern of hepatocellular carcinoma (HCC) following liver transplantation. Materials and methodsA total of 54 patients underwent liver transplantation for HCC; 9 patients developed biopsy-proven recurrent HCC (16.6%). The site of HCC recurrence along with other factors was analyzed. ResultsSeven patients were diagnosed with HCC prior to liver transplantation and 2 patients had incidental HCC in the explanted liver. Two patients had locoregional recurrence, 4 patients had distant metastasis, and 3 patients had synchronous locoregional recurrence and distant metastasis. ConclusionA significant proportion of HCC recurrence following liver transplantation is extrahepatic.

Hepatitis E virus: Assessment of the epidemiological situation in humans in Europe, 2014/15

BackgroundHepatitis E virus (HEV) is endemic in EU/EEA countries, but the understanding of the burden of the infection in humans is inconsistent as the disease is not under EU surveillance but subject to national policies. StudyCountries were asked to nominate experts and to complete a standardised questionnaire about the epidemiological situation and surveillance of HEV in their respective EU/EEA country. This study reviewed surveillance systems for human cases of HEV in EU/EEA countries and nominated experts assessed the epidemiology in particular examining the recent increase in the number of autochthonous cases. ResultsSurveillance systems and case definitions across EU/EEA countries were shown to be highly variable and testing algorithms were unreliable. Large increases of autochthonous cases were reported from Western EU/EEA countries with lower case numbers seen in Northern and Southern European countries. Lack of clinical awareness and variability in testing strategies might account for the observed differences in hepatitis E incidence across EU/EEA countries. Infections were predominantly caused by HEV genotype 3, the most prevalent virus type in the animal reservoirs. ConclusionDiscussions from the expert group supported joint working across countries to better monitor the epidemiology and possible changes in risk of virus acquisition at a European level. There was agreement to share surveillance strategies and algorithms but also importantly the collation of HEV data from human and animal populations. These data collected at a European level would serve the ‘One Health’ approach to better informing on human exposure to HEV.