Monitoring online media reports for early detection of unknown diseases: Insight from a retrospective study of COVID‐19 emergence
2021
Valentin, Sarah | Mercier, Alizé | Lancelot, Renaud | Roche, Mathieu | Arsevska, Elena | Animal, Santé, Territoires, Risques et Ecosystèmes (UMR ASTRE) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Département Systèmes Biologiques (Cirad-BIOS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) | Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Département Environnements et Sociétés (Cirad-ES) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) | the French Agricultural Research Centre for International Development (CIRAD); the French General Directorate for Food (DGAL); French National Research Agency under the Investments for the Future Program, Grant/Award Number: ANR-16-CONV-0004; H2020 "Monitoring outbreak events for disease surveillance in a data science context" (MOOD), Grant/Award Number: 874850; SONGES Project FEDER and Occitanie | ANR-16-CONV-0004,DIGITAG,Institut Convergences en Agriculture Numérique(2016) | European Project: 874850,H2020-SC1-2019-Single-Stage-RTD,MOOD(2020)
International audience
Afficher plus [+] Moins [-]anglais. Event-based surveillance (EBS) systems monitor a broad range of information sources to detect early signals of disease emergence, including new and unknown diseases. In December 2019, a newly identified coronavirus emerged in Wuhan (China), causing a global coronavirus disease (COVID-19) pandemic. A retrospective study was conducted to evaluate the capacity of three event-based surveillance (EBS) systems (ProMED, HealthMap and PADI-web) to detect early COVID-19 emergence signals. We focused on changes in online news vocabulary over the period before/after the identification of COVID-19, while also assessing its contagiousness and pandemic potential. ProMED was the timeliest EBS, detecting signals one day before the official notification. At this early stage, the specific vocabulary used was related to 'pneumonia symptoms' and 'mystery illness'. Once COVID-19 was identified, the vocabulary changed to virus family and specific COVID-19 acronyms. Our results suggest that the three EBS systems are complementary regarding data sources, and all require timeliness improvements. EBS methods should be adapted to the different stages of disease emergence to enhance early detection of future unknown disease outbreaks.
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