Several faculty members, including Rich Tsui, PhD and Greg Cooper, MD, PhD, investigate methods for real-time detection and assessment of disease outbreaks within the Realtime Outbreak and Disease Surveillance (RODS) Laboratory. Founded in part by Michael Wagner, MD, PhD (funded by a R01 grant) and Rich Tsui PhD, and Jeremy Espino, MD, the RODS Laboratory is a biosurveillance research laboratory that is home to three large projects that work with health departments to create surveillance systems: the RODS Open Source Project, Pennsylvania RODS, and the National Retail Data Monitor (NRDM).
These projects benefit the public and also benefit the research by grounding our work in actual public health practice and by collecting surveillance data for algorithm validation and investigations into the value of different types of novel data for outbreak detection. Current research interests of the faculty include algorithm development, assessment of novel types of surveillance data, grid computing, natural language processing, and analyses of detectability. Current funding sources include the Centers for Disease Control, the National Library of Medicine, and the Houston Health Department.
Cooper GF, Villamarín R, Tsui F-C, Millett N, Espino JU, Wagner MM, A method for detecting and characterizing outbreaks of infectious disease from clinical reports, J Biomed Inform. 2014 Aug 30. pii: S1532-0464(14)00192-0. doi: 10.1016/j.jbi.2014.08.011
Ye Y, Tsui F.-C., Wagner M, Espino JU, Li Q, Influenza detection from emergency department reports using natural language processing and Bayesian network classifiers, Journal of American Medical Informatics Association, Jan. 2014, PMID: 24406261
Rexit R, Tsui F.-C., Espino J, et. al., An analytics appliance for identifying (near) optimal over-the-counter medicine products as health indicators for influenza surveillance, Journal Manager of Information Systems, 2014
Liu TY, Sanders JL, Tsui F.-C., Espino JU, Dato VM, and Suyama J, Association of Over-The-Counter pharmaceutical sales with Influenza-Like-Illnesses to patient volume in an urgent care setting, PLOS One, 8(3), Mar. 2013
Wagner MM, Moore A, Aryel R, editors. Handbook of Biosurveillance. New York: Elsevier; 2006.
Hogan WR, Cooper GF, Wallstrom GL, Wagner MM, Depinay JM. The Bayesian aerosol release detector: an algorithm for detecting and characterizing outbreaks caused by an atmospheric release of Bacillus anthracis. Stat Med. 2007 Dec 20;26(29):5225-52. PMID: 17948918
Espino J., Hall K., White P., Washington D., Grant A., Hume A., Antonioletti M., Krause A., Jackson M., Tsui F.-C. and Heinbaugh W. Open-source Collaboration in Practice between RODS, NCPHI Research Lab, University of Edinburgh and Tarrant County Public Health, 2008 PHIN Conference.