Using internet intelligence to manage biosecurity risks: a case study for aquatic animal health


Correspondence: Aidan Lyon, Department of Philosophy, University of Maryland, College Park, MD 20742, USA.



Aim is an open-source aquatic biosecurity intelligence gathering and analysis application. The system collects information in much the same way as other similar systems (e.g. HealthMap, BioCaster). However, the information collected undergoes minimal automated analysis, and analysis is largely left to's users. The result is an automated system of intelligence gathering, combined with a manual system of intelligence analysis. This approach relies on a large number of users, and so relies on an open-intelligence analysis method: any user can publish their own analyses for all to see and analyse further. By combining automated data collection and human analysis, will provide fast and accurate forecasts, accompanied with nuanced explanations. These methods can be applied to other areas of biosecurity and disease surveillance.


Canberra, Australia; College Park, Maryland, USA; Melbourne, Australia.


Automated: performs hourly scans of an array of RSS feeds, blogs, social networks and news sites. It analyses this information and removes redundancies and applies taxonomy and geospatial tags. The information is then pushed to the Daily Scan, where users then analyse it further. Manual: Users assess the information for inaccuracies and its importance. They decide whether an article should be a disease alert, which is emailed to all users. Users can change tags, edit reports, add commentary, apply rankings, change search terms and summarize issues in the Emerging Issues blog (formerly a wiki).

Results publishes seven daily reports and 2 weekly disease alerts (on average). Ninety per cent of CEFAS's ( Emerging Disease Updates cite The Australian Sub-Committee for Aquatic Animal Health (SCAAH) uses the system to compile quarterly reports. The Australian Department of Agriculture, Fisheries and Forestry (DAFF) uses to make forecasts—for example, used aquaculture equipment is a high-risk pathway for OsHV.'s users forecasted an increase in emerging marine finfish disease outbreaks in Southeast Asia and are actively watching this issue.

Main conclusions's open-intelligence approach has proven to be an effective and flexible biosecurity forecasting method.