Towards bioinformatics assisted infectious disease control

Vitali Sintchenko*, Blanca Gallego, Grace Chung, Enrico Coiera

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
25 Downloads (Pure)


BACKGROUND: 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. RESULTS: 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. CONCLUSION: 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.

Original languageEnglish
Article numberS10
Pages (from-to)1-11
Number of pages11
JournalBMC Bioinformatics
Issue numberSuppl 1
Publication statusPublished - 2009
Externally publishedYes

Bibliographical note

Copyright the Author(s) 2009. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


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