Spatiotemporal reasoning about epidemiological data

Objective. In this article, we propose new methods to visualize and reason about spatiotemporal epidemiological data. Background. Efficient computerized reasoning about epidemics is important to public health and national security, but it is a difficult task because epidemiological data are usually spatiotemporal, recursive, and fast changing hence hard to handle in traditional relational databases and geographic information systems. Methodology. We describe the general methods of how to (1) store epidemiological data in constraint databases, (2) handle recursive epidemiological definitions, and (3) efficiently reason about epidemiological data based on recursive and nonrecursive SQL queries. Results. We implement a particular epidemiological system called WeNiVIS that enables the visual tracking of and reasoning about the spread of the West Nile Virus epidemic in Pennsylvania. In the system, users can do many interesting reasonings based on the spatiotemporal dataset and the recursiv...

• Type: Journal
• Year: 2006
• Where: ARTMED
• Authors: Peter Z. Revesz, Shasha Wu
• Keywords: ARTMED 2006, Epidemiological Data, Spatiotemporal Epidemiological Data, West Nile Virus