Coronavirus is the word on everyone’s lips, and details of progress in developing an automated animal health surveillance tool, PADI-web, have just been published. PADI-web searches articles from different online information sources to extract epidemiological information from them. This open-access platform for international health surveillance responds to the need of epidemiologists to monitor in real time the emergence and spread of animal infectious diseases. Explanations from Mathieu Roche and Sarah Valentin, a researcher and a doctoral student in Cirad’s TETIS joint research unit, who are developing the tool in collaboration with the ASTRE unit (Cirad – INRAE).
Global animal disease outbreak detection and monitoring rely on official intergovernmental organisations, such as FAO and OIE, as well as unofficial media sources, for which the manual extraction of relevant information is complex and time-consuming. In France, the development of the epidemic intelligence tool PADI-web (Platform for Automated extraction of Disease Information from the web) began in 2016. The International Health Monitoring Unit (VSI), part of the French Animal Health Epidemiological Surveillance Platform (ESA), is already using it to monitor infectious diseases that present risks of introduction into the French territory and harmful effects on animals and production chains..
Supplementing official information with relevant unofficial texts
PADI-web proposes supplementing the official information provided with unofficial sources. Its field of exploration: news articles selected by Google News. And since using robust media articles does not rule out incorrect information, the expertise of epidemiologists is essential to validate their relevance and to supplement the data of the tool’s learning algorithm.
Avian influenza, African swine fever, bluetongue disease, but also coronavirus: based on Google News searches, PADI-web collects, classifies, translates all articles into English, and extracts the epidemiological information. These texts are collected by disease names and animal hosts, but also by symptoms, which may be the only element mentioned in some articles[A1] . The advantage of this is clear: not only does the system provide fresh information, which has not yet been published via the official channels, and identify it according to location and date, but it can also detect the signals of a disease before it is declared. Its multilingual media coverage also considerably enhances its database. To date, it includes more than 200 000 articles, in English, French, Chinese, Spanish and Arabic, among others.
According to the health news, the number of articles on a disease vary from 0 to more than 40 per day in case of a disease emergence or new outbreaks detected.
Two examples: in the week commencing 24 February 2020, PADI-web detected on Google News 25 relevant articles on avian influenza from unofficial sources. And since 31 January 2019[A1] , more than 2 600 articles on coronaviruses have been classified as relevant in PADI-web.
The evolution of international health surveillance
In the circle of existing media monitoring tools, PADI-web is the only one dedicated to the surveillance of infectious animal diseases and the detection of emerging and new diseases, whether diseases transmitted between animals, or between humans and animals. The research team would like to extend this monitoring to include social networks and, after Google, to be able to process data from Baidu, the Chinese search engine. It also hopes to share approaches so that the lessons learned for PADI-web can be applied in other fields, such as plant health.
“We can identify weak signals, now the challenge is to interpret them. International health surveillance could become very effective if PADI-web is combined with other existing tools. This is the goal of the project H2020 MOOD (MOnitoring Outbreak events for Disease surveillance in a data science context) , which began in January, to improve epidemic intelligence tools and services”, says Mathieu Roche. Another challenge will be to identify weak signals from certain data sources and to then take the necessary measures, as some Asian countries are doing.
Learn more
- Contact: Mathieu Roche & Sarah Valentin – padi-web [AT] cirad.fr
- Webite: padi-web.cirad.fr
- Publications :
- Valentin Sarah, Arsevska Elena, Falala Sylvain, De Goër Jocelyn, Lancelot Renaud, Mercier Alizé, Rabatel Julien, Roche Mathieu. (2020). “PADI-web: A multilingual event-based surveillance system for monitoring animal infectious diseases ”. Computers and Electronics in Agriculture , 169, 105163, 5 p. – https://doi.org/10.1016/j.compag.2019.105163
- Arsevska Elena, Valentin Sarah, Rabatel Julien, De Goër de Hervé Jocelyn, Falala Sylvain, Lancelot Renaud, Roche Mathieu. (2018). Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System. PloS One, 13 (8):e0199960, 25 p. – https://doi.org/10.1371/journal.pone.0199960
Jeux de données : https://doi.org/10.18167/DVN1/JZM34U / https://doi.org/10.18167/DVN1/KMTIFG
- Plateforme ESA “Epidémiosurveillance Santé Animale”
- Website of the H2020 MOOD Project – Renaud Lancelot & Elena Arsevska – mood [AT] cirad.fr
The PADI-web pipeline
To facilitate the comparison of official and unofficial data, the EpidNews visualisation tool was created by LIRMM in collaboration with the TETIS and ASTRE research units. It will shortly be fully integrated with the interface. .
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