ABSTRACT
BACKGROUND: The proliferation of digital disease-detection systems has led to an increase in earlier warning signals, which subsequently have resulted in swifter responses to emerging threats. Such highly sensitive systems can also produce weak signals needing additional information for action. The delays in the response to a genuine health threat are often due to the time it takes to verify a health event. It was the delay in outbreak verification that was the main impetus for creating EpiCore. OBJECTIVE: This paper describes the potential of crowdsourcing information through EpiCore, a network of voluntary human, animal, and environmental health professionals supporting the verification of early warning signals of potential outbreaks and informing risk assessments by monitoring ongoing threats. METHODS: This paper uses summary statistics to assess whether EpiCore is meeting its goal to accelerate the time to verification of identified potential health events for epidemic and pandemic intelligence purposes from around the world. Data from the EpiCore platform from January 2018 to December 2022 were analyzed to capture request for information response rates and verification rates. Illustrated use cases are provided to describe how EpiCore members provide information to facilitate the verification of early warning signals of potential outbreaks and for the monitoring and risk assessment of ongoing threats through EpiCore and its utilities. RESULTS: Since its launch in 2016, EpiCore network membership grew to over 3300 individuals during the first 2 years, consisting of professionals in human, animal, and environmental health, spanning 161 countries. The overall EpiCore response rate to requests for information increased by year between 2018 and 2022 from 65.4% to 68.8% with an initial response typically received within 24 hours (in 2022, 94% of responded requests received a first contribution within 24 h). Five illustrated use cases highlight the various uses of EpiCore. CONCLUSIONS: As the global demand for data to facilitate disease prevention and control continues to grow, it will be crucial for traditional and nontraditional methods of disease surveillance to work together to ensure health threats are captured earlier. EpiCore is an innovative approach that can support health authorities in decision-making when used complementarily with official early detection and verification systems. EpiCore can shorten the time to verification by confirming early detection signals, informing risk-assessment activities, and monitoring ongoing events.
Subject(s)
Disease Outbreaks , Health Personnel , Animals , Humans , Disease Outbreaks/prevention & control , PandemicsABSTRACT
The Vaccine Safety Net's Web Analytics Project (VSN-WAP) was launched in October 2017 to monitor the behavior of users visiting websites belonging to the VSN, a global network of websites providing science-based information on vaccine safety. Participating websites could provide web metrics in two ways: through a Google Analytics (GA) script, which automatically forwarded metrics to a central account and through manual input (MI) of a reduced subset of metrics (Sessions, Page Views, New Users, Bounce Rate, Views/Session and Average Session Duration), which were pooled with the metrics obtained through GA. Additional metrics were obtained from websites providing data through Google Analytics (Country, Age, Sex, Device). We report results from February 2018 to March 2019. In March 2019, 32 websites were participating in the project (21 through GA, 11 through MI). From February 2018 to March 2019 we recorded 22,471,535 sessions, with 38,307,349 page views. Sessions, New Users and Page views progressively increased, Views/Session, Bounce Rate and Average Session Duration remained stable. Most users were female (68%) and belonged to the 25-34 age range (37%), followed by 35-44 (22%) and 18-24 (19%). Fifty-four percent of users connected from a mobile device, 42% from a desktop and 4% from a tablet. Digital media monitoring techniques can provide insights on the characteristics of users with a specific interest in vaccines. These data can be exploited to improve the performance of websites providing information on vaccines to the general public.
