Epidemic Marketplace: An Information Management System for Epidemiological Data

Mendes, Luís F.; Silva, Fabrício; Couto, Francisco M.; Zamite, João; Ferreira, Hugo Alexandre; Sousa, Carla; Silva, Mário J.

doi:10.1007/978-3-642-15020-3_3

Cited by 8 publications

(6 citation statements)

References 22 publications

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“…A multidisciplinary and multijurisdictional approach is needed to allow adequate data collection, exchange, and evaluation and communication across multiple jurisdictions and wide geographical areas [18,20,21]. Social media programs can allow international networks of food safety, public health, and other professionals to communicate via virtual networks, which can facilitate collaborations and support public health response infrastructure [19-22]. One example is virtual situation rooms using a three-dimensional interface, where public health professionals can collaborate and discuss surveillance data in real-time [20].…”

Section: Resultsmentioning

confidence: 99%

Scoping Review on Search Queries and Social Media for Disease Surveillance: A Chronology of Innovation

Bernardo¹,

Rajić²,

Young³

et al. 2013

J Med Internet Res

153

136

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BackgroundThe threat of a global pandemic posed by outbreaks of influenza H5N1 (1997) and Severe Acute Respiratory Syndrome (SARS, 2002), both diseases of zoonotic origin, provoked interest in improving early warning systems and reinforced the need for combining data from different sources. It led to the use of search query data from search engines such as Google and Yahoo! as an indicator of when and where influenza was occurring. This methodology has subsequently been extended to other diseases and has led to experimentation with new types of social media for disease surveillance.ObjectiveThe objective of this scoping review was to formally assess the current state of knowledge regarding the use of search queries and social media for disease surveillance in order to inform future work on early detection and more effective mitigation of the effects of foodborne illness.MethodsStructured scoping review methods were used to identify, characterize, and evaluate all published primary research, expert review, and commentary articles regarding the use of social media in surveillance of infectious diseases from 2002-2011.ResultsThirty-two primary research articles and 19 reviews and case studies were identified as relevant. Most relevant citations were peer-reviewed journal articles (29/32, 91%) published in 2010-11 (28/32, 88%) and reported use of a Google program for surveillance of influenza. Only four primary research articles investigated social media in the context of foodborne disease or gastroenteritis. Most authors (21/32 articles, 66%) reported that social media-based surveillance had comparable performance when compared to an existing surveillance program. The most commonly reported strengths of social media surveillance programs included their effectiveness (21/32, 66%) and rapid detection of disease (21/32, 66%). The most commonly reported weaknesses were the potential for false positive (16/32, 50%) and false negative (11/32, 34%) results. Most authors (24/32, 75%) recommended that social media programs should primarily be used to support existing surveillance programs.ConclusionsThe use of search queries and social media for disease surveillance are relatively recent phenomena (first reported in 2006). Both the tools themselves and the methodologies for exploiting them are evolving over time. While their accuracy, speed, and cost compare favorably with existing surveillance systems, the primary challenge is to refine the data signal by reducing surrounding noise. Further developments in digital disease surveillance have the potential to improve sensitivity and specificity, passively through advances in machine learning and actively through engagement of users. Adoption, even as supporting systems for existing surveillance, will entail a high level of familiarity with the tools and collaboration across jurisdictions.

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Section: Resultsmentioning

confidence: 99%

Scoping Review on Search Queries and Social Media for Disease Surveillance: A Chronology of Innovation

Bernardo¹,

Rajić²,

Young³

et al. 2013

J Med Internet Res

153

136

View full text Add to dashboard Cite

show abstract

“…Following this vision, a platform for epidemiological resources named Epidemic Marketplace20 21 is being developed at http://www.epimarketplace.net/ under the umbrella of the EPIWORK project,22 a European project sponsored by the Seventh Framework Programme. Its primary goal is to serve as a repository of epidemiologically relevant information, in the form of resources.…”

Section: A Case Studymentioning

confidence: 99%

On the usefulness of ontologies in epidemiology research and practice

Ferreira

Paolotti

Couto

et al. 2012

J Epidemiol Community Health

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“…In fact, the multidisciplinarity of epidemiology has been previously explored and a network of epidemiology-related ontologies has been created, which contains ontologies that represent most of the epidemiology domains mentioned above [33]. The network has been developed within the scope of an European project that developed the Epidemic Marketplace, a repository of epidemiology information [6] that used it to assist users annotate their resources, using ontology concepts as metadata.…”

Section: Resultsmentioning

confidence: 99%

“…Semantic similarity between annotated biomedical resources has been a topic of research since Lord et al [1] applied this technique to annotated proteins, as a search tool within a protein database. With the increase in the amount of biomedical domains being represented in formal ontologies, the desire to use ontologies to annotate biomedical entities increases, which resulted in multiple ontologies being used to that effect: metabolic pathways [2, 3], mathematical models of biological processes [4], functional tissue units [5], epidemiological resources [6], biomedical text and clinical notes [7], chemical toxicity [8] etc . These multidisciplinary entities, along with their multi-ontology annotations, can be regarded as biomedical digital resources that describe complex real-world phenomena.…”

Section: Introductionmentioning

confidence: 99%

Multi-domain semantic similarity in biomedical research

Ferreira

Couto

2019

BMC Bioinformatics

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Background Given the increasing amount of biomedical resources that are being annotated with concepts from more than one ontology and covering multiple domains of knowledge, it is important to devise mechanisms to compare these resources that take into account the various domains of annotation. For example, metabolic pathways are annotated with their enzymes and their metabolites, and thus similarity measures should compare them with respect to both of those domains simultaneously. Results In this paper, we propose two approaches to lift existing single-ontology semantic similarity measures into multi-domain measures. The aggregative approach compares domains independently and averages the various similarity values into a final score. The integrative approach integrates all the relevant ontologies into a single one, calculating similarity in the resulting multi-domain ontology using the single-ontology measure. Conclusions We evaluated the two approaches in a multidisciplinary epidemiology dataset by evaluating the capacity of the similarity measures to predict new annotations based on the existing ones. The results show a promising increase in performance of the multi-domain measures over the single-ontology ones in the vast majority of the cases. These results show that multi-domain measures outperform single-domain ones, and should be considered by the community as a starting point to study more efficient multi-domain semantic similarity measures.

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Epidemic Marketplace: An Information Management System for Epidemiological Data

Cited by 8 publications

References 22 publications

Scoping Review on Search Queries and Social Media for Disease Surveillance: A Chronology of Innovation

Scoping Review on Search Queries and Social Media for Disease Surveillance: A Chronology of Innovation

On the usefulness of ontologies in epidemiology research and practice

Multi-domain semantic similarity in biomedical research

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