Biosurveillance Ecosystem

# Biosurveillance Ecosystem **Entity class:** Technology, method, or technical system **Domain:** Austin Research / Programs **Doc Type:** Research entity **Source basis:** Supplied research cluster with linked references; see the [[wiki/Austin Research Evidence Map|evidence map]] for verification scope. The **Biosurveillance Ecosystem (BSVE)** is [[wiki/Defense Threat Reduction Agency|DTRA]]’s cloud-based environment for combining heterogeneous information and analytical tools to support biological-event detection, forecasting, and response analysis. UT’s [[wiki/Surety BioEvent App|BioEvent]] announcement uses the earlier wording **BioSurveillance Virtual Environment**. DTRA’s fact sheet describes an unclassified AWS-based environment with interoperable analytic applications and an SDK. The relevant sources can include diagnostic results and other health and non-health signals. Source quality, timeliness, and context govern what can be inferred from their combination. UT provides two specific bridges: Barber, Meyers, and Ellington’s proposed trust filter, and later [[wiki/Meyers Lab|Meyers Lab]] forecasting methods developed with [[wiki/Texas Advanced Computing Center|TACC]] resources. The lab evaluated more than 600 candidate influenza streams and supplied the resulting methods to BSVE. Those links connect source selection and epidemiological inference to a named defense [[wiki/Biosurveillance|biosurveillance]] environment. The later [[wiki/UT COVID-19 Modeling Consortium|UT COVID-19 Modeling Consortium]] demonstrates the civilian pandemic-response expression of the same research lineage: heterogeneous observations were converted into forecasts, hospital-capacity estimates, staged alerts, and intervention comparisons through a network joining Meyers Lab, TACC, [[wiki/Dell Medical School|Dell Medical School]], [[wiki/Austin Public Health|Austin Public Health]], and the [[wiki/City of Austin|City of Austin]]. ## Connected entries [[wiki/Defense Threat Reduction Agency|Defense Threat Reduction Agency]] · [[wiki/Surety BioEvent App|Surety BioEvent App]] · [[wiki/Lauren Ancel Meyers|Lauren Ancel Meyers]] · [[wiki/Meyers Lab|Meyers Lab]] · [[wiki/UT COVID-19 Modeling Consortium|UT COVID-19 Modeling Consortium]] · [[wiki/Texas Advanced Computing Center|Texas Advanced Computing Center]] · [[wiki/Dell Medical School|Dell Medical School]] · [[wiki/Austin Public Health|Austin Public Health]] · [[wiki/Biosurveillance|Biosurveillance]] · [[wiki/Source Trust Tuple|Source Trust Tuple]] · [[wiki/Detection Before Attribution|Detection Before Attribution]] · [[wiki/Biological Threat Reduction Program|Biological Threat Reduction Program]] ## Sources and corpus context - [[research/The Austin Executable Loop|The Austin Executable Loop — master document]] - [DTRA Biosurveillance Ecosystem — BSVE Fact Sheet](https://www.dtra.mil/Portals/61/Documents/CB/BSVE%20Fact%20Sheet_04282015_PA%20Cleared.pdf) - [Prof. Suzanne Barber Awarded DTRA Grant for Work on Surety BioEvent App](https://ece.utexas.edu/news/prof-suzanne-barber-awarded-dtra-grant-work-surety-bioevent-app) - [Flu Season Forecasts Could Be More Accurate with Access to Health Care Companies’ Data](https://news.utexas.edu/2018/09/19/this-data-source-could-enable-better-flu-forecasts/) **Cluster:** [[wiki/Austin Executable Loop|Austin Executable Loop]] · [[wiki/Austin Research Evidence Map|Austin Research Evidence Map]] ## Relationships  BSVE **received** influenza-forecasting methods from [[wiki/Meyers Lab|Meyers Lab]] after TACC-supported evaluation and **hosted** the earlier [[wiki/Surety BioEvent App|Surety BioEvent]] source-trust concept. The later UT COVID consortium shows the same laboratory’s forecasting family operating through a civilian clinical, public-health, and municipal network.