A web-based system for near real-time surveillance and space-time cluster analysis of foot-and-mouth disease and other animal diseases

Andres M. Perez, Daniel Zeng, Chun ju Tseng, Hsinchun Chen, Zachary Whedbee, David Paton, Mark C. Thurmond

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)39-45
Number of pages7
JournalPreventive Veterinary Medicine
Volume91
Issue number1
DOIs
StatePublished - Sep 1 2009

Bibliographical note

Funding Information:
The project was funded in part by the U.S. National Center for Medical Intelligence (NCMI), the U.S. Department of Homeland Security, the U.S. Department of Agriculture, the University of California, and the Institute for Animal Health in Pirbright, U.K. The Arizona team acknowledges funding support provided by the U.S. National Science Foundation through Grant IIS-0428241 and the U.S. Department of Homeland Security through Grant 2008-ST-061-BS0002.Zeng is also affiliated with the Institute of Automation, Chinese Academy of Sciences, and acknowledges support from the National Natural Science Foundation of China (60621001), the Chinese Academy of Sciences (2F05N01, 2F07C01, and 2F08N03), the Ministry of Health (2009ZX10004-315), and the Ministry of Science and Technology(2006AA010106).

Copyright:
Copyright 2009 Elsevier B.V., All rights reserved.

Keywords

  • Foot-and-mouth disease
  • Infectious disease informatics
  • Spatial analysis
  • Surveillance

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