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This article is part of the supplement: Selected Proceedings of the First Summit on Translational Bioinformatics 2008

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Towards bioinformatics assisted infectious disease control

Vitali Sintchenko12*, Blanca Gallego1, Grace Chung1 and Enrico Coiera1

Author Affiliations

1 Centre for Health Informatics, University of New South Wales, Sydney, New South Wales, Australia

2 Centre for Infectious Diseases and Microbiology, Western Clinical School, The University of Sydney, Sydney, New South Wales, Australia

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BMC Bioinformatics 2009, 10(Suppl 2):S10  doi:10.1186/1471-2105-10-S2-S10

Published: 5 February 2009



This paper proposes a novel framework for bioinformatics assisted biosurveillance and early warning to address the inefficiencies in traditional surveillance as well as the need for more timely and comprehensive infection monitoring and control. It leverages on breakthroughs in rapid, high-throughput molecular profiling of microorganisms and text mining.


This framework combines the genetic and geographic data of a pathogen to reconstruct its history and to identify the migration routes through which the strains spread regionally and internationally. A pilot study of Salmonella typhimurium genotype clustering and temporospatial outbreak analysis demonstrated better discrimination power than traditional phage typing. Half of the outbreaks were detected in the first half of their duration.


The microbial profiling and biosurveillance focused text mining tools can enable integrated infectious disease outbreak detection and response environments based upon bioinformatics knowledge models and measured by outcomes including the accuracy and timeliness of outbreak detection.