Value of syndromic surveillance in monitoring a focal waterborne outbreak due to an unusual Cryptosporidium genotype in Northamptonshire, United Kingdom, June – July 2008

Rabbits as reservoirs: An updated perspective of the zoonotic risk from Cryptosporidium and Giardia

Rabbits are highly abundant in many countries and can serve as reservoirs of diseases for a diversity of pathogens including the enteric protozoan parasites, Cryptosporidium and Giardia. Both parasites shed environmentally robust environmental stages (oo/cysts) and have been responsible for numerous waterborne outbreaks of diseases. Cryptosporidium hominis and C. parvum are responsible for most infections in humans, while Giardia duodenalis assemblages A and B, cause most human cases of giardiasis. Cryptosporidium cuniculus, the dominant species infecting rabbits, is the only spceies other than C. hominis and C. parvum to have caused a waterborne outbreak of gastritis, which occurred in the United Kingdom in 2008. This review examines the prevalence of Cryptosporidium and Giardia species in rabbits to better understand the public health risks of contamination of water sources with Cryptosporidium and Giardia oo/cysts from rabbits. Despite the abundance of C. cuniculus in rabbits, reports in humans are relatively rare, with the exception of the United Kingdom and New Zealand, and reports of C. cuniculus in humans from the United Kingdom have declined substantially since the 2008 outbreak. Subtyping of C. cuniculus has supported the potential for zoonotic transmission. Relatively few studies have been conducted on Giardia, but assemblage B dominates. However, improved typing methods are required to better understand the transmission dynamics of Giardia assemblages in rabbits. Similarly, it is not well understood if pet rabbits or contaminated water are the main source of C. cuniculus infections in humans. Well-planned studies using high-resolution typing tools are required to understand the transmission dynamics better and quantify the public health risk of Cryptosporidium and Giardia from rabbits.

PetBERT: automated ICD-11 syndromic disease coding for outbreak detection in first opinion veterinary electronic health records

Effective public health surveillance requires consistent monitoring of disease signals such that researchers and decision-makers can react dynamically to changes in disease occurrence. However, whilst surveillance initiatives exist in production animal veterinary medicine, comparable frameworks for companion animals are lacking. First-opinion veterinary electronic health records (EHRs) have the potential to reveal disease signals and often represent the initial reporting of clinical syndromes in animals presenting for medical attention, highlighting their possible significance in early disease detection. Yet despite their availability, there are limitations surrounding their free text-based nature, inhibiting the ability for national-level mortality and morbidity statistics to occur. This paper presents PetBERT, a large language model trained on over 500 million words from 5.1 million EHRs across the UK. PetBERT-ICD is the additional training of PetBERT as a multi-label classifier for the automated coding of veterinary clinical EHRs with the International Classification of Disease 11 framework, achieving F1 scores exceeding 83% across 20 disease codings with minimal annotations. PetBERT-ICD effectively identifies disease outbreaks, outperforming current clinician-assigned point-of-care labelling strategies up to 3 weeks earlier. The potential for PetBERT-ICD to enhance disease surveillance in veterinary medicine represents a promising avenue for advancing animal health and improving public health outcomes.

Using topic modelling for unsupervised annotation of electronic health records to identify an outbreak of disease in UK dogs

A key goal of disease surveillance is to identify outbreaks of known or novel diseases in a timely manner. Such an outbreak occurred in the UK associated with acute vomiting in dogs between December 2019 and March 2020. We tracked this outbreak using the clinical free text component of anonymised electronic health records (EHRs) collected from a sentinel network of participating veterinary practices. We sourced the free text (narrative) component of each EHR supplemented with one of 10 practitioner-derived main presenting complaints (MPCs), with the ‘gastroenteric’ MPC identifying cases involved in the disease outbreak. Such clinician-derived annotation systems can suffer from poor compliance requiring retrospective, often manual, coding, thereby limiting real-time usability, especially where an outbreak of a novel disease might not present clinically as a currently recognised syndrome or MPC. Here, we investigate the use of an unsupervised method of EHR annotation using latent Dirichlet allocation topic-modelling to identify topics inherent within the clinical narrative component of EHRs. The model comprised 30 topics which were used to annotate EHRs spanning the natural disease outbreak and investigate whether any given topic might mirror the outbreak time-course. Narratives were annotated using the Gensim Library LdaModel module for the topic best representing the text within them. Counts for narratives labelled with one of the topics significantly matched the disease outbreak based on the practitioner-derived ‘gastroenteric’ MPC (Spearman correlation 0.978); no other topics showed a similar time course. Using artificially injected outbreaks, it was possible to see other topics that would match other MPCs including respiratory disease. The underlying topics were readily evaluated using simple word-cloud representations and using a freely available package (LDAVis) providing rapid insight into the clinical basis of each topic. This work clearly shows that unsupervised record annotation using topic modelling linked to simple text visualisations can provide an easily interrogable method to identify and characterise outbreaks and other anomalies of known and previously un-characterised diseases based on changes in clinical narratives.

The effectiveness of syndromic surveillance for the early detection of waterborne outbreaks: a systematic review

Background

Waterborne outbreaks are still a risk in high-income countries, and their early detection is crucial to limit their societal consequences. Although syndromic surveillance is widely used for the purpose of detecting outbreaks days earlier than traditional surveillance systems, evidence of the effectiveness of such systems is lacking. Thus, our objective was to conduct a systematic review of the effectiveness of syndromic surveillance to detect waterborne outbreaks.

Method

We searched the Cochrane Library, Medline/PubMed, EMBASE, Scopus, and Web of Science for relevant published articles using a combination of the keywords ‘drinking water’, ‘surveillance’, and ‘waterborne disease’ for the period of 1990 to 2018. The references lists of the identified articles for full-text record assessment were screened, and searches in Google Scholar using the same key words were conducted. We assessed the risk of bias in the included articles using the ROBINS-I tool and PRECEPT for the cumulative body of evidence.

Results

From the 1959 articles identified, we reviewed 52 articles, of which 18 met the eligibility criteria. Twelve were descriptive/analytical studies, whereas six were simulation studies. There is no clear evidence for syndromic surveillance in terms of the ability to detect waterborne outbreaks (low sensitivity and high specificity). However, one simulation study implied that multiple sources of signals combined with spatial information may increase the timeliness in detecting a waterborne outbreak and reduce false alarms.

Conclusion

This review demonstrates that there is no conclusive evidence on the effectiveness of syndromic surveillance for the detection of waterborne outbreaks, thus suggesting the need to focus on primary prevention measures to reduce the risk of waterborne outbreaks. Future studies should investigate methods for combining health and environmental data with an assessment of needed financial and human resources for implementing such surveillance systems. In addition, a more critical thematic narrative synthesis on the most promising sources of data, and an assessment of the basis for arguments that joint analysis of different data or dimensions of data (e.g. spatial and temporal) might perform better, should be carried out.

Trial registration

PROSPERO: International prospective register of systematic reviews. 2019. CRD42019122332.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06387-y.

Outbreak of Severe Vomiting in Dogs Associated with a Canine Enteric Coronavirus, United Kingdom

The lack of population health surveillance for companion animal populations leaves them vulnerable to the effects of novel diseases without means of early detection. We present evidence on the effectiveness of a system that enabled early detection and rapid response a canine gastroenteritis outbreak in the United Kingdom. In January 2020, prolific vomiting among dogs was sporadically reported in the United Kingdom. Electronic health records from a nationwide sentinel network of veterinary practices confirmed a significant increase in dogs with signs of gastroenteric disease. Male dogs and dogs living with other vomiting dogs were more likely to be affected. Diet and vaccination status were not associated with the disease; however, a canine enteric coronavirus was significantly associated with illness. The system we describe potentially fills a gap in surveillance in neglected populations and could provide a blueprint for other countries.

Adapting Syndromic Surveillance Baselines After Public Health Interventions

BACKGROUND

Public health surveillance requires historical baselines to identify unusual activity. However, these baselines require adjustment after public health interventions. We describe an example of such an adjustment after the introduction of rotavirus vaccine in England in July 2013.

METHODS

We retrospectively measured the magnitude of differences between baselines and observed counts (residuals) before and after the introduction of a public health intervention, the introduction of a rotavirus vaccine in July 2013. We considered gastroenteritis, diarrhea, and vomiting to be indicators for national syndromic surveillance, including telephone calls to a telehealth system, emergency department visits, and unscheduled consultations with general practitioners. The start of the preintervention period varied depending on the availability of surveillance data: June 2005 for telehealth, November 2009 for emergency departments, and July 2010 for general practitioner data. The postintervention period was July 2013 to the second quarter of 2016. We then determined whether baselines incorporating a step-change reduction or a change in seasonality resulted in more accurate models of activity.

RESULTS

Residuals in the unadjusted baseline models increased by 42%-198% from preintervention to postintervention. Increases in residuals for vomiting indicators were 19%-44% higher than for diarrhea. Both step-change and seasonality adjustments improved the surveillance models; we found the greatest reduction in residuals in seasonally adjusted models (4%-75%).

CONCLUSION

Our results demonstrated the importance of adjusting surveillance baselines after public health interventions, particularly accounting for changes in seasonality. Adjusted baselines produced more representative expected values than did unadjusted baselines, resulting in fewer false alarms and a greater likelihood of detecting public health threats.

A real-time spatio-temporal syndromic surveillance system with application to small companion animals

Lack of disease surveillance in small companion animals worldwide has contributed to a deficit in our ability to detect and respond to outbreaks. In this paper we describe the first real-time syndromic surveillance system that conducts integrated spatio-temporal analysis of data from a national network of veterinary premises for the early detection of disease outbreaks in small animals. We illustrate the system’s performance using data relating to gastrointestinal disease in dogs and cats. The data consist of approximately one million electronic health records for dogs and cats, collected from 458 UK veterinary premises between March 2014 and 2016. For this illustration, the system predicts the relative reporting rate of gastrointestinal disease amongst all presentations, and updates its predictions as new data accrue. The system was able to detect simulated outbreaks of varying spatial geometry, extent and severity. The system is flexible: it generates outcomes that are easily interpretable; the user can set their own outbreak detection thresholds. The system provides the foundation for prompt detection and control of health threats in companion animals.

Potential added value of the new emergency care dataset to ED-based public health surveillance in England: an initial concept analysis

INTRODUCTION

For the London Olympic and Paralympic Games in 2012, a sentinel ED syndromic surveillance system was established to enhance public health surveillance by obtaining data from a selected network of EDs, focusing on London. In 2017, a new national standard Emergency Care Dataset was introduced, which enabled Public Health England (PHE) to initiate the expansion of their sentinel system to national coverage. Prior to this initiative, we estimated the added value, and potential additional resource use, of an expansion of the sentinel surveillance system.

METHODS

The detection capabilities of the sentinel and national systems were compared using the aberration detection methods currently used by PHE. Different scenarios were used to measure the impact on health at a local, subnational and national level, including improvements to sensitivity and timeliness, along with changes in specificity.

RESULTS

The biggest added value was found to be for detecting local impacts, with an increase in sensitivity of over 80%. There were also improvements found at a national level with outbreaks being detected earlier and smaller impacts being detectable. However, the increased number of local sites will also increase the number of false alarms likely to be generated.

CONCLUSION

We have quantified the added value of national ED syndromic surveillance systems, showing how they will enable detection of more localised events. Furthermore, national systems add value in enabling timelier public health interventions. Finally, we have highlighted areas where extra resource may be required to manage improvements in detection coverage.

Validation of a Natural Language Processing Algorithm for Detecting Infectious Disease Symptoms in Primary Care Electronic Medical Records in Singapore

Background

Free-text clinical records provide a source of information that complements traditional disease surveillance. To electronically harness these records, they need to be transformed into codified fields by natural language processing algorithms.

Objective

The aim of this study was to develop, train, and validate Clinical History Extractor for Syndromic Surveillance (CHESS), an natural language processing algorithm to extract clinical information from free-text primary care records.

Methods

CHESS is a keyword-based natural language processing algorithm to extract 48 signs and symptoms suggesting respiratory infections, gastrointestinal infections, constitutional, as well as other signs and symptoms potentially associated with infectious diseases. The algorithm also captured the assertion status (affirmed, negated, or suspected) and symptom duration.

Electronic medical records from the National Healthcare Group Polyclinics, a major public sector primary care provider in Singapore, were randomly extracted and manually reviewed by 2 human reviewers, with a third reviewer as the adjudicator. The algorithm was evaluated based on 1680 notes against the human-coded result as the reference standard, with half of the data used for training and the other half for validation.

Results

The symptoms most commonly present within the 1680 clinical records at the episode level were those typically present in respiratory infections such as cough (744/7703, 9.66%), sore throat (591/7703, 7.67%), rhinorrhea (552/7703, 7.17%), and fever (928/7703, 12.04%). At the episode level, CHESS had an overall performance of 96.7% precision and 97.6% recall on the training dataset and 96.0% precision and 93.1% recall on the validation dataset. Symptoms suggesting respiratory and gastrointestinal infections were all detected with more than 90% precision and recall. CHESS correctly assigned the assertion status in 97.3%, 97.9%, and 89.8% of affirmed, negated, and suspected signs and symptoms, respectively (97.6% overall accuracy). Symptom episode duration was correctly identified in 81.2% of records with known duration status.

Conclusions

We have developed an natural language processing algorithm dubbed CHESS that achieves good performance in extracting signs and symptoms from primary care free-text clinical records. In addition to the presence of symptoms, our algorithm can also accurately distinguish affirmed, negated, and suspected assertion statuses and extract symptom durations.

Early outbreak detection by linking health advice line calls to water distribution areas retrospectively demonstrated in a large waterborne outbreak of cryptosporidiosis in Sweden

Background

In the winter and spring of 2011 a large outbreak of cryptosporidiosis occurred in Skellefteå municipality, Sweden. This study summarizes the outbreak investigation in terms of outbreak size, duration, clinical characteristics, possible source(s) and the potential for earlier detection using calls to a health advice line.

Methods

The investigation included two epidemiological questionnaires and microbial analysis of samples from patients, water and other environmental sources. In addition, a retrospective study based on phone calls to a health advice line was performed by comparing patterns of phone calls between different water distribution areas.

Results

Our analyses showed that approximately 18,500 individuals were affected by a waterborne outbreak of cryptosporidiosis in Skellefteå in 2011. This makes it the second largest outbreak of cryptosporidiosis in Europe to date. Cryptosporidium hominis oocysts of subtype IbA10G2 were found in patient and sewage samples, but not in raw water or in drinking water, and the initial contamination source could not be determined. The outbreak went unnoticed to authorities for several months. The analysis of the calls to the health advice line provides strong indications early in the outbreak that it was linked to a particular water treatment plant.

Conclusions

We conclude that an earlier detection of the outbreak by linking calls to a health advice line to water distribution areas could have limited the outbreak substantially.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-017-4233-8) contains supplementary material, which is available to authorized users.

Safe drinking water and waterborne outbreaks

The present work compiles a review on drinking waterborne outbreaks, with the perspective of production and distribution of microbiologically safe water, during 2000-2014. The outbreaks are categorised in raw water contamination, treatment deficiencies and distribution network failure. The main causes for contamination were: for groundwater, intrusion of animal faeces or wastewater due to heavy rain; in surface water, discharge of wastewater into the water source and increased turbidity and colour; at treatment plants, malfunctioning of the disinfection equipment; and for distribution systems, cross-connections, pipe breaks and wastewater intrusion into the network. Pathogens causing the largest number of affected consumers were Cryptosporidium, norovirus, Giardia, Campylobacter, and rotavirus. The largest number of different pathogens was found for the treatment works and the distribution network. The largest number of affected consumers with gastrointestinal illness was for contamination events from a surface water source, while the largest number of individual events occurred for the distribution network.

Limiting swimming pool outbreaks of cryptosporidiosis - the roles of regulations, staff, patrons and research

Cryptosporidium is the leading cause of swimming pool outbreaks of gastroenteritis. Transmission occurs through the ingestion of oocysts that are passed in the faeces of an infected person or animal when an accidental faecal release event occurs. Cryptosporidium parasites present specific challenges for infection control as oocysts are highly resistant to chlorine levels used for pool disinfection, infected individuals can shed large numbers of oocysts, there is a long incubation period and shedding of oocysts occurs even after symptom resolution. The purposes of this review are to identify key barriers to limiting swimming pool-associated outbreaks of cryptosporidiosis and to outline needs for research and collaboration to advance co-ordinated management practices. We reviewed swimming pool-associated cryptosporidiosis outbreaks, disinfection teachniques, current regulations and the role of staff and patrons. Key barriers to limiting swimming pool-associated outbreaks of cryptosporidiosis are a lack of uniform national and international standards, poor adherence and understanding of regulations governing staff and patron behaviour, and low levels of public knowledge and awareness.

The potential impact of media reporting in syndromic surveillance: an example using a possible Cryptosporidium exposure in North West England, August to September 2015

During August 2015, a boil water notice (BWN) was issued across parts of North West England following the detection of Cryptosporidium oocysts in the public water supply. Using prospective syndromic surveillance, we detected statistically significant increases in the presentation of cases of gastroenteritis and diarrhoea to general practitioner services and related calls to the national health telephone advice service in those areas affected by the BWN. In the affected areas, average in-hours general practitioner consultations for gastroenteritis increased by 24.8% (from 13.49 to 16.84) during the BWN period; average diarrhoea consultations increased by 28.5% (from 8.33 to 10.71). Local public health investigations revealed no laboratory reported cases confirmed as being associated with the water supply. These findings suggest that the increases reported by syndromic surveillance of cases of gastroenteritis and diarrhoea likely resulted from changes in healthcare seeking behaviour driven by the intense local and national media coverage of the potential health risks during the event. This study has further highlighted the potential for media-driven bias in syndromic surveillance, and the challenges in disentangling true increases in community infection from those driven by media reporting.

Monitoring the effect of air pollution episodes on health care consultations and ambulance call-outs in England during March/April 2014: A retrospective observational analysis

There is an increasing body of evidence illustrating the negative health effects of air pollution including increased risk of respiratory, cardiac and other morbid conditions. During March and April 2014 there were two air pollution episodes in England that occurred in close succession. We used national real-time syndromic surveillance systems, including general practitioner (GP) consultations, emergency department attendances, telehealth calls and ambulance dispatch calls to further understand the impact of these short term acute air pollution periods on the health seeking behaviour of the general public. Each air pollution period was comparable with respect to particulate matter concentrations (PM10 and PM2.5), however, the second period was longer in duration (6 days vs 3 days) and meteorologically driven 'Sahara dust' contributed to the pollution. Health surveillance data revealed a greater impact during the second period, with GP consultations, emergency department attendances and telehealth (NHS 111) calls increasing for asthma, wheeze and difficulty breathing indicators, particularly in patients aged 15-64 years. Across regions of England there was good agreement between air quality levels and health care seeking behaviour. The results further demonstrate the acute impact of short term air pollution episodes on public health and also illustrate the potential role of mass media reporting in escalating health care seeking behaviour.

Human cryptosporidiosis in Europe

Cryptosporidium has emerged as a significant cause of diarrhoeal disease worldwide, with severe health consequences for very young, malnourished children living in endemic areas and for individuals with highly impaired T-cell functions. In Europe, as elsewhere, the burden of disease has been difficult to measure as a result of the lack of appropriate, standardized surveillance and monitoring systems. The recent occurrence of large water- and foodborne outbreaks in several EU countries, as well as the results of many surveys of human and animal cryptosporidiosis, indicate that this parasite is widespread. Specific subtypes of the zoonotic Cryptosporidium parvum and the anthroponotic C. hominis are responsible for the majority of human cases in Europe. No treatment is currently available to clear the infection, but recent progress in genetic engineering of the parasite, coupled with advances in genomics, have opened important avenues for future research. Here we explore the possible reasons for underascertainment of cryptosporidiosis and the importance of accurate diagnosis in clinical management, the epidemiology of human cryptosporidiosis and key messages from recent outbreaks to highlight important interventions and emerging public health issues.

What is the utility of using syndromic surveillance systems during large subnational infectious gastrointestinal disease outbreaks? An observational study using case studies from the past 5 years in England

Syndromic surveillance systems in England have demonstrated utility in the early identification of seasonal gastrointestinal illness (GI) tracking its spatio-temporal distribution and enabling early public health action. There would be additional public health utility if syndromic surveillance systems could detect or track subnational infectious disease outbreaks. To investigate using syndromic surveillance for this purpose we retrospectively identified eight large GI outbreaks between 2009 and 2014 (four randomly and four purposively sampled). We then examined syndromic surveillance information prospectively collected by the Real-time Syndromic Surveillance team within Public Health England for evidence of possible outbreak-related changes. None of the outbreaks were identified contemporaneously and no alerts were made to relevant public health teams. Retrospectively, two of the outbreaks - which happened at similar times and in proximal geographical locations - demonstrated changes in the local trends of relevant syndromic indicators and exhibited a clustering of statistical alarms, but did not warrant alerting local health protection teams. Our suite of syndromic surveillance systems may be more suited to their original purposes than as means of detecting or monitoring localized, subnational GI outbreaks. This should, however, be considered in the context of this study's limitations; further prospective work is needed to fully explore the use of syndromic surveillance for this purpose. Provided geographical coverage is sufficient, syndromic surveillance systems could be able to provide reassurance of no or minor excess healthcare systems usage during localized GI incidents.

A Study of Failure Events in Drinking Water Systems As a Basis for Comparison and Evaluation of the Efficacy of Potable Reuse Schemes

Potable reuse is implemented in several countries around the world to augment strained water supplies. This article presents a public health perspective on potable reuse by comparing the critical infrastructure and institutional capacity characteristics of two well-established potable reuse schemes with conventional drinking water schemes in developed nations that have experienced waterborne outbreaks. Analysis of failure events in conventional water systems between 2003 and 2013 showed that despite advances in water treatment technologies, drinking water outbreaks caused by microbial contamination were still frequent in developed countries and can be attributed to failures in infrastructure or institutional practices. Numerous institutional failures linked to ineffective treatment protocols, poor operational practices, and negligence were detected. In contrast, potable reuse schemes that use multiple barriers, online instrumentation, and operational measures were found to address the events that have resulted in waterborne outbreaks in conventional systems in the past decade. Syndromic surveillance has emerged as a tool in outbreak detection and was useful in detecting some outbreaks; increases in emergency department visits and GP consultations being the most common data source, suggesting potential for an increasing role in public health surveillance of waterborne outbreaks. These results highlight desirable characteristics of potable reuse schemes from a public health perspective with potential for guiding policy on surveillance activities.

An early warning system based on syndromic surveillance to detect potential health emergencies among migrants: results of a two-year experience in Italy

Profound geopolitical changes have impacted the southern and eastern Mediterranean since 2010 and defined a context of instability that is still affecting several countries today. Insecurity combined with the reduction of border controls has led to major population movements in the region and to migration surges from affected countries to southern Europe, especially to Italy. To respond to the humanitarian emergency triggered by this migration surge, Italy implemented a syndromic surveillance system in order to rapidly detect potential public health emergencies in immigrant reception centres. This system was discontinued after two years. This paper presents the results of this experience detailing its strengths and weaknesses in order to document the applicability and usefulness of syndromic surveillance in this specific context.

Approaches to the detection of very small, common, and easily missed outbreaks that together contribute substantially to human Cryptosporidium infection

Water supply-associated cryptosporidiosis outbreaks have decreased in England since the application of risk reduction measures to public water supplies. We hypothesized that smaller outbreaks were occurring which could be better detected by enhanced surveillance. Rolling analysis of detailed questionnaire data was applied prospectively in a population of 2·2 million in the south of England in 2009 and 2010. Detection of spatiotemporal clusters using SaTScan was later undertaken retrospectively. Together these approaches identified eight outbreaks, compared to an expectation of less than one based on national surveillance data. These outbreaks were small and associated with swimming pool use or, less commonly, direct (e.g. petting-farm) contact with animals. These findings suggest that frequent small-scale transmission in swimming pools is an important contributor to disease burden. Identification of swimming pool-level risk factors may inform preventative measures. These findings and the approaches described may be applicable to many other populations and to some other diseases.

Syndromic surveillance for local outbreak detection and awareness: evaluating outbreak signals of acute gastroenteritis in telephone triage, web-based queries and over-the-counter pharmacy sales

For the purpose of developing a national system for outbreak surveillance, local outbreak signals were compared in three sources of syndromic data--telephone triage of acute gastroenteritis, web queries about symptoms of gastrointestinal illness, and over-the-counter (OTC) pharmacy sales of antidiarrhoeal medication. The data sources were compared against nine known waterborne and foodborne outbreaks in Sweden in 2007-2011. Outbreak signals were identified for the four largest outbreaks in the telephone triage data and the two largest outbreaks in the data on OTC sales of antidiarrhoeal medication. No signals could be identified in the data on web queries. The signal magnitude for the fourth largest outbreak indicated a tenfold larger outbreak than officially reported, supporting the use of telephone triage data for situational awareness. For the two largest outbreaks, telephone triage data on adult diarrhoea provided outbreak signals at an early stage, weeks and months in advance, respectively, potentially serving the purpose of early event detection. In conclusion, telephone triage data provided the most promising source for surveillance of point-source outbreaks.

Simultaneous detection of viral and bacterial enteric pathogens using the Seeplex® Diarrhea ACE detection system

A panel of 223 faecal samples was analysed to determine the clinical utility of the Seeplex® Diarrhea ACE Detection multiplex PCR system (Seeplex system; Seegene, Korea), a qualitative multiplexing PCR technology that enables simultaneous multi-pathogen detection of four viruses and/or ten bacteria associated with acute gastroenteritis. Conventional diagnostic methods and a norovirus-specific multiplex real-time RT–PCR detected 98 pathogens in 96 samples. The Seeplex system detected 81 pathogens in 75 samples. All samples positive for adenovirus, norovirus, Campylobacter spp., Escherichia coli O157, Shigella spp. or Vibrio spp. were detected by the Seeplex system. Rotavirus, Clostridium difficile toxin B, and Salmonella spp. were not detected in 12.5%, 50% and 15.8% of samples, respectively. Additional multiple infections were detected in 19 samples by the Seeplex system. The Seeplex system provides significant additional diagnostic capability for the syndromic diagnosis of acute gastroenteritis with increased sensitivity for the majority of pathogens.

The use of syndromic surveillance for decision-making during the H1N1 pandemic: a qualitative study

Background

Although an increasing number of studies are documenting uses of syndromic surveillance by front line public health, few detail the value added from linking syndromic data to public health decision-making. This study seeks to understand how syndromic data informed specific public health actions during the 2009 H1N1 pandemic.

Methods

Semi-structured telephone interviews were conducted with participants from Ontario’s public health departments, the provincial ministry of health and federal public health agency to gather information about syndromic surveillance systems used and the role of syndromic data in informing specific public health actions taken during the pandemic. Responses were compared with how the same decisions were made by non-syndromic surveillance users.

Results

Findings from 56 interviews (82% response) show that syndromic data were most used for monitoring virus activity, measuring impact on the health care system and informing the opening of influenza assessment centres in several jurisdictions, and supporting communications and messaging, rather than its intended purpose of early outbreak detection. Syndromic data had limited impact on decisions that involved the operation of immunization clinics, school closures, sending information letters home with school children or providing recommendations to health care providers. Both syndromic surveillance users and non-users reported that guidance from the provincial ministry of health, communications with stakeholders and vaccine availability were driving factors in these public health decisions.

Conclusions

Syndromic surveillance had limited use in decision-making during the 2009 H1N1 pandemic in Ontario. This study provides insights into the reasons why this occurred. Despite this, syndromic data were valued for providing situational awareness and confidence to support public communications and recommendations. Developing an understanding of how syndromic data are utilized during public health events provides valuable evidence to support future investments in public health surveillance.

Perceived usefulness of syndromic surveillance in Ontario during the H1N1 pandemic

BACKGROUND

Despite the growing popularity of syndromic surveillance, little is known about if or how these systems are accepted, utilized and valued by end users. This study seeks to describe the use of syndromic surveillance systems in Ontario and users' perceptions of the value of these systems within the context of other surveillance systems.

METHODS

Ontario's 36 public health units, the provincial ministry of health and federal public health agency completed a web survey to identify traditional and syndromic surveillance systems used routinely and during the pandemic and to describe system attributes and utility in monitoring pandemic activity and informing decision-making.

RESULTS

Syndromic surveillance systems are used by 20/38 (53%) organizations. For routine surveillance, laboratory, integrated Public Health Information System and school absenteeism data are the most frequently used sources. Laboratory data received the highest ratings for reliability, timeliness and accuracy ('very acceptable' by 92, 51 and 89%). Hospital/clinic screening data were rated as the most reliable and timely syndromic data source (50 and 43%) and ED visit data the most accurate (48%). During the pandemic, laboratory data were considered the most useful for monitoring the epidemiology and informing decision-making while ED screening and visit data were considered the most useful syndromic sources.

CONCLUSIONS

End user perceptions are valuable for identifying opportunities for improvement and guiding further investments in public health surveillance.