A web-based system for near real-time surveillance and space-time cluster analysis of foot-and-mouth disease and other animal diseases.
Considerable attention has been given lately to the need for global systems for animal disease surveillance that support real-time assessment of changing temporal-spatial risks. Until recently, however, prospects for development of such systems have been limited by the lack of informatics tools and an overarching collaboration framework to enable real-time data capturing, sharing, analysis, and related decision-making. In this paper, we present some of the tools of the FMD BioPortal System (www.fmd.ucdavis.edu/bioportal), which is a web-based system that facilitates near real-time information sharing, visualization, and advanced space-time cluster analysis for foot-and-mouth disease (FMD). Using this system, FMD information that is collected and maintained at various data acquisition and management sites around the world can be submitted to a data repository using various mutually agreed upon Extensible Markup Language (XML) formats, including Health Level Seven (HL7). FMD BioPortal makes available a set of advanced space-time cluster analysis techniques, including scan statistic-based methods and machine learning-based clustering methods. These techniques are aimed at identifying local clusters of disease cases in relation to the background risk. Data and analysis results can be displayed using a novel visualization environment, which supports multiple views including GIS, timeline, and periodical patterns. All FMD BioPortal functionalities are accessible through the Web and data confidentiality can be secured through user access control and computer network security techniques such as Secure Sockets Layer (SSL). FMD BioPortal is currently operational with limited data routinely collected by the Office International des Epizooties, the GenBank, the FMD World Reference Laboratory in Pirbright, and by the FMD Laboratory at the University of California in Davis. Here we describe technical attributes and capabilities of FMD BioPortal and illustrate its functionality by analyzing and displaying information from a simulated FMD epidemic in California.
Perez
Andres M
AM
Center for Animal Disease Modeling and Surveillance, Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California in Davis, Davis, CA 95616, USA. amperez@ucdavis.edu
Zeng
Daniel
D
Tseng
Chun-ju
CJ
Chen
Hsinchun
H
Whedbee
Zachary
Z
Paton
David
D
Thurmond
Mark C
MC
D000818:Animals; D002140:California / Q000453:epidemiology; D004196:Disease Outbreaks / Q000662:veterinary*; D005536:Foot-and-Mouth Disease / Q000453:epidemiology* / Q000821:virology; D029544:Foot-and-Mouth Disease Virus / Q000302:isolation & purification*; D040362:Geographic Information Systems; D020407:Internet; D011159:Population Surveillance / Q000379:methods*; D013029:Space-Time Clustering