Infectious disease informatics

From LIMSWiki
Revision as of 15:19, 11 June 2014 by Shawndouglas (talk | contribs) (Created stub record. Saving and adding more.)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigationJump to search

Infectious disease informatics (IDI) is a multidisciplinary field of science that focuses on "the development of the science and technologies needed for collecting, sharing, reporting, analyzing, and visualizing infectious disease data and for providing data and decision-making support for infectious disease prevention, detection, and management."[1]

History

In the late 1990s and early 2000s, infectious disease data was increasingly being collected and stored in an electronic format by laboratories of all types at local, state, national, and international levels. As this data format became more common and data transmission requirements to entities like the Centers for Disease Control and Prevention (CDC) became more stringent, custom in-house infectious disease information systems were developed to better access, analyze, and report the associated data. Despite the increase in the number of these systems, some challenges remained for them in the mid-2000s: they required better interoperability among other such systems; improvements in system scalability, user interfaces, model sophistication; a more efficient reporting and alert system across organization boundaries; and a more scrutinous approach to legal issues surrounding data sharing and transmittal to and from those systems.[1] As these challenges were overcome, IDI was clearly becoming more than an application of informatics to disease tracking and reporting. Biomedical research into and biosurveillance of infectious diseases became more sophisticated, requiring equally sophisticated informatics tools to manage, analyze, report, and share the deluge of data. Microbial genome sequence analysis, biomarker discovery, and bacterial computational models and simulations have brought new data-driven approaches to infectious disease research.[2] And the extraction, analysis, and interpretation of biosurveillance data and information from multiple sources requires the development of automated algorithms and improved analytical methodologies.[3]

Application

Infectious disease informatics can help tackle problems and tasks such as the following[2]:

  • the optimization of developed antimicrobials
  • the improvement of vaccines
  • the discovery of biomarkers for transmissibility and clinical outcomes of infectious diseases
  • the development of research into host-pathogen interactions
  • the sequencing and comparative study of the genomes of pathogens
  • the development of computational models for and simulations of bacteria and other microbials
  • the computational analysis and mining of collected disease data
  • the improvement of antibiotic prescribing decisions
  • the automation and facilitation of surveillance data collection and processing

Informatics

External links

References

  1. 1.0 1.1 Chen, Hsinchun; Fuller, Sherrilynne S.; Friedman, Carol; Hersh, William (2006). "Chapter 13: Infectious Disease Informatics and Outbreak Detection". Medical Informatics: Knowledge Management and Data Mining in Biomedicine. Springer. pp. 359–397. ISBN 9780387257396. http://books.google.com/books?id=ku0ubWDKFZgC&pg=PA360. Retrieved 11 June 2014. 
  2. 2.0 2.1 Sintchenko, Vitali (2009). "Chapter 1: Informatics for Infectious Disease Research and Control". Infectious Disease Informatics. Springer. pp. 1–26. ISBN 9781441913272. http://books.google.com/books?id=H794Ej9GPFcC&pg=PA1. Retrieved 11 June 2014. 
  3. Rolka, Henry; O'Connor, Jean (2010). "Chapter 1: Real-Time Public Health Biosurveillance: Systems and Policy Considerations". Infectious Disease Informatics and Biosurveillance. Springer. pp. 3–22. ISBN 9781441968920. http://books.google.com/books?id=SC9nEO_13pEC&pg=PA3. Retrieved 11 June 2014.