Disease Watch is a web application that ingests real-time open source data to identify and characterize global disease outbreaks or pre-cursor events (natural disasters, civil unrest) that may increase the likelihood of an outbreak.
About Disease Watch
With support from the Paul G. Allen Ebola program, Disease Watch leverages research methods FPDI originally developed for global food system disruptions and applies those methods to infectious disease surveillance. While valuable data exists to detect emerging disease outbreaks, analyzing and monitoring this data is made difficult both by the sheer amount of information and differences in data structure across systems. FPDI developed a prototype technology utilizing an innovative approach to address these challenges and improve infectious disease surveillance and situational awareness.
Disease Watch currently collects data from many different sources, including public health, disaster and events, global news media and reports from government agencies. The application performs natural language processing and machine review of data to classify data as either “true” (related to a disease or pre-cursor event) or “false” (not related to a disease or pre-cursor event). Disease Watch also facilitates comprehensive coding of articles using an ontology developed by FPDI. The ontology codes each article according to more than 30 concepts referred to as classes and subclasses. Data related to the same outbreak or pre-cursor event are then grouped together into a “case.” FPDI is using the technology to develop a library of past cases. As the library will utilize a robust coding scheme that is consistently applied across all records, it has the potential to support data mining and pattern recognition of future emerging outbreaks.
Users of Disease Watch have the ability to:
- Visualize and monitor active outbreaks and pre-cursor events
- Layer real-time information with reference data
- Browse a library of past outbreaks and events
- Sign up for email alerts that may be customized according to region(s) and/or disease(s) of interest
Contact us at email@example.com for more information