Towards bioinformatics assisted infectious disease control
2009

Bioinformatics Framework for Infectious Disease Control

Sample size: 816 publication Evidence: moderate

Author Information

Author(s): Sintchenko Vitali, Gallego Blanca, Chung Grace, Coiera Enrico

Primary Institution: Centre for Health Informatics, University of New South Wales

Hypothesis

Can bioinformatics assist in improving infectious disease surveillance and control?

Conclusion

The study demonstrates that microbial profiling and biosurveillance tools can enhance the accuracy and timeliness of outbreak detection.

Supporting Evidence

  • Half of the outbreaks were detected in the first half of their duration.
  • MLVA demonstrated better discrimination power than traditional phage typing.
  • Automated clonal alerts were 100% sensitive in identifying outbreaks.

Takeaway

This study shows that using advanced computer tools can help doctors find and control disease outbreaks faster.

Methodology

The study utilized molecular typing and clustering techniques to analyze Salmonella typhimurium isolates.

Limitations

The study relied on a single database for strain comparisons, which may limit the generalizability of the findings.

Participant Demographics

Patients from New South Wales and Queensland, Australia.

Digital Object Identifier (DOI)

10.1186/1471-2105-10-S2-S10

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