Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System
Open accessAbstract
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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Social media has an opportune disease surveillance area, improving its capability to detect disease outbreaks.
“The platform has an opportune disease surveillance area, improving its capability to detect disease outbreaks.”
From Social Media Role and Its Impact on Public Health: A Narrative Review (2023) · cites this paper as [18]
The Introduction identifies social networks as a possible source for detecting emerging animal diseases. The Discussion reports that PADI-web detected outbreak signals, sometimes ahead of official notification, but PADI-web monitors online news; the paper does not show that social media improved its outbreak-detection capability. (LLM, conf=0.84)
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- Authors
- Arsevska, E., Valentin, S., Rabatel, J., de Goër de Hervé, J., Falala, S., Lancelot, R., & Roche, M.
- Affiliations
- Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR)
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Arsevska, Elena
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2018-08-03
- Volume
- 13
- Issue
- 8
- Pages
- e0199960
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC6075742
- OpenAlex
- W2886506786
- Cited by
- 64
- References
- 37
- Citations by year
- 2026: 3 · 2025: 10 · 2024: 5 · 2023: 7 · 2022: 8 · 2021: 8 · 2020: 14 · 2019: 7 · 2018: 2
- FWCI
- 6.05
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by)
- Agritrop (Cirad) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- French General Directorate for Food (DGAL)
- French Agricultural Research Centre for International Development (CIRAD)
- SONGES Project (FEDER and Languedoc-Roussillon)
- LabEx NUMEV project funded by the “Investissements d’Avenir” French Government program, managed by the French National Research Agency (ANR) (ANR-10-LABX-20)
- Topics
- Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Animal Disease Management and Epidemiology
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Zoonotic diseases and public health
- Keywords
- epidemic intelligence, automatic information extraction, Google News, early warning, African swine fever, avian influenza, bluetongue, foot-and-mouth disease, notifiable diseases, OIE, outbreak detection, rule-based extraction
- MeSH terms
- Animals, France, Mass Media, Pattern Recognition, Automated, Time Factors, Internet, Communicable Diseases, Emerging, Data Mining, Epidemiological Monitoring
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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