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Technology and tuberculosis control: the OUT-TB Web experience. | LitMetric

AI Article Synopsis

Article Abstract

Objective: Develop a tool to disseminate integrated laboratory, clinical, and demographic case data necessary for improved contact tracing and outbreak detection of tuberculosis (TB).

Methods: In 2007, the Public Health Ontario Laboratories implemented a universal genotyping program to monitor the spread of TB strains within Ontario. Ontario Universal Typing of TB (OUT-TB) Web utilizes geographic information system (GIS) technology with a relational database platform, allowing TB control staff to visualize genotyping matches and microbiological data within the context of relevant epidemiological and demographic data.

Results: OUT-TB Web is currently available to the 8 health units responsible for >85% of Ontario's TB cases and is a valuable tool for TB case investigation. Users identified key features to implement for application enhancements, including an e-mail alert function, customizable heat maps for visualizing TB and drug-resistant cases, socioeconomic map layers, a dashboard providing TB surveillance metrics, and a feature for animating the geographic spread of strains over time.

Conclusion: OUT-TB Web has proven to be an award-winning application and a useful tool. Developed and enhanced using regular user feedback, future versions will include additional data sources, enhanced map and line-list filter capabilities, and development of a mobile app.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7651931PMC
http://dx.doi.org/10.1093/jamia/ocw130DOI Listing

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Objective: Develop a tool to disseminate integrated laboratory, clinical, and demographic case data necessary for improved contact tracing and outbreak detection of tuberculosis (TB).

Methods: In 2007, the Public Health Ontario Laboratories implemented a universal genotyping program to monitor the spread of TB strains within Ontario. Ontario Universal Typing of TB (OUT-TB) Web utilizes geographic information system (GIS) technology with a relational database platform, allowing TB control staff to visualize genotyping matches and microbiological data within the context of relevant epidemiological and demographic data.

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