Monitoring online media reports for the early detection of unknown diseases: insights from a retrospective study of COVID-19 emergence

Event-based surveillance (EBS) systems monitor a broad range of information sources to detect early signals of disease emergence, including new and unknown diseases. Following the emergence of a newly identified coronavirus –so-called COVID-19, in humans in December 2019 in Wuhan, China, we conducted a retrospective analysis of the capacity of three Event-Based Systems (EBS) systems (ProMED, HealthMap and PADI-web) to detect early signals of this emergence. We evaluated the changes in the online news vocabulary coinciding with the period before / after the identification of COVID-19, as well as the assessment of 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 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 the three EBS systems are complementary regarding data sources, and all need improvements regarding timeliness. EBS methods should be adapted to the different stages of disease emergence to improve the early detection of future emergence of unknown pathogens.