Using AquaticHealth.net to Detect Emerging Trends in Aquatic Animal Health

Lyon, Aidan; Mooney, Allan; Grossel, Geoff

doi:10.3390/agriculture3020299

Cited by 8 publications

(3 citation statements)

References 3 publications

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“…Similarly to other biosurveillance systems [ 11 – 13 ], PADI-web collects online news directly from structured data services, i.e. Really Simple Syndication (RSS) feeds.…”

Section: Methodsmentioning

confidence: 99%

Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System

et al. 2018

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Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively.

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“…Similarly to other biosurveillance systems [ 11 – 13 ], PADI-web collects online news directly from structured data services, i.e. Really Simple Syndication (RSS) feeds.…”

Section: Methodsmentioning

confidence: 99%

Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System

et al. 2018

View full text Add to dashboard Cite

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“…To detect articles on the web (e.g., Google News), the International Biosurveillance System (IBIS) uses the knowledge of registered users of the system that propose the search terms themselves. Registered users can edit the search terms and add or edit the tags in the articles that are relevant to the search terms (Lyon et al, 2013).…”

Section: Related Workmentioning

confidence: 99%

Identification of Associations between Clinical Signs and Hosts to Monitor the Web for Detection of Animal Disease Outbreaks

Arsevska

Roche

Hendrikx

et al. 2016

International Journal of Agricultural and Environmental Information Systems

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In a context of intensification of international trade and travels, the transboundary spread of emerging human or animal pathogens represents a growing concern. One of the missions of the national veterinary services is to implement international epidemiological intelligence for a timely and accurate detection of emerging animal infectious diseases (EAID) worldwide, and take early actions to prevent their introduction on the national territory. For this purpose, an efficient use of the information published on the web is essential. The authors present a comprehensive method for identification of relevant associations between terms describing clinical signs and hosts to build queries to monitor the web for early detection of EAID. Using text and web mining approaches, they present statistical measures for automatic selection of relevant associations between terms. In addition, expert elicitation is used to highlight the most relevant terms and associations among those automatically selected. The authors assessed the performance of the combination of the automatic approach and expert elicitation to monitor the web for a list of selected animal pathogens.

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“…The definitions and concepts from both ECDC and WHO were elaborated for public health. However, they have been successfully transferred to other domains, such as plant health [ 7 ] and both terrestrial and aquatic animal health [ [8] , [9] , [10] ]. Both EBS and IBS can be formally represented as consecutive steps, corresponding to the flow of epidemiological information from its detection to its communication to the relevant authorities [ 4 , 11 , 12 ] (see Fig.…”

Section: Introductionmentioning

confidence: 99%

PADI-web 3.0: A new framework for extracting and disseminating fine-grained information from the news for animal disease surveillance

et al. 2021

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PADI-web (Platform for Automated extraction of animal Disease Information from the web) is a biosurveillance system dedicated to monitoring online news sources for the detection of emerging animal infectious diseases. PADI-web has collected more than 380,000 news articles since 2016. Compared to other existing biosurveillance tools, PADI-web focuses specifically on animal health and has a fully automated pipeline based on machine-learning methods. This paper presents the new functionalities of PADI-web based on the integration of: (i) a new fine-grained classification system, (ii) automatic methods to extract terms and named entities with text-mining approaches, (iii) semantic resources for indexing keywords and (iv) a notification system for end-users. Compared to other biosurveillance tools, PADI-web, which is integrated in the French Platform for Animal Health Surveillance (ESA Platform), offers strong coverage of the animal sector, a multilingual approach, an automated information extraction module and a notification tool configurable according to end-user needs.

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Using AquaticHealth.net to Detect Emerging Trends in Aquatic Animal Health

Cited by 8 publications

References 3 publications

Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System

Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System

Identification of Associations between Clinical Signs and Hosts to Monitor the Web for Detection of Animal Disease Outbreaks

PADI-web 3.0: A new framework for extracting and disseminating fine-grained information from the news for animal disease surveillance

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