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PHDL Participates in SMDM Annual Meeting

PHDL-Table-SMDM-Oct2017-image2

The 39th Annual North American Meeting of the Society for Medical Decision Making (SMDM) was held in Pittsburgh, PA, October 22-25, 2017. The focus this year was on “Better Decisions Through Better Data Processes”. The Society for Medical Decision Making has a long history of developing methodologies which take advantage of complex data structures to enhance medical decision making and advance policy formation. The 2017 Annual Meeting explored themes to ensure the credibility and usability of the Society’s efforts and to promote their vision of an integrated approach to health care decision making, through wise use and thoughtful communication of data.

Several Public Health Dynamics Laboratory (PHDL) faculty and postdocs participated in teaching short courses, and oral and poster presentations. The PHDL also participated in an exhibitor’s booth to share information on many of the PHDL software tools, including a demo of FRED (Framework for Reconstructing Epidemiological Dynamics).

 

 David Sinclair SMDM 2017Hawre Jalal SMSM 2017

Click here to see our presentersPHDL Participates in SMDM Annual Meeting

Modeling the Opioid Epidemic Workshop

Modeling the Opioid Epidemic WorkshopThe Public Health Dynamics Laboratory (PHDL) and the Clinical Translational Science Institute (CTSI), both at the University of Pittsburgh, co-sponsored a one-day national workshop on “Modeling the Opioid Epidemic: Insights and Potential Solutions from Computational Science” on October 2, 2017 in Pittsburgh. The workshop, the first in a series, was a great success. Over 140 researchers, clinicians, students and public health officials attended, representing more than a dozen academic institutions, federal agencies, community organizations, and health care systems. This workshop provided investigators and practitioners with a unique opportunity to learn more about the computational work being done at multiple scales in response to the opioid epidemic. Presentations and discussions featured speakers and panelists working at all levels and scales of computational modeling to examine the opioid crisis from the biological, to the individual human, to population-wide levels of science.

Modeling the Opioid Epidemic Workshop

To view recordings of the workshop presentations, click Read More or visit www.ctsi.pitt.edu/opioidmodeling2017.

Read more: Modeling the Opioid Epidemic Workshop

CMU Wins CDC Competition Again

Roni RosenfeldFor three years now, Carnegie Mellon University's Delphi-Stat group, under the leadership of Roni Rosenfeld, PhD, has won the U.S. Centers for Disease Control and Prevention's competition in predicting week-to-week influenza activity levels in 10 regions of the nation, along with national totals. "We're gratified that our forecasting methods continue to perform as well as they do, but it's important to remember that epidemiological forecasting remains in its infancy", said Dr. Rosenfeld. The forecasting effort is expected to help health officials better plan for peak periods of infection, while providing the public with more accurate information to avoid getting the flu. Read more: CMU is the world's best at predicting influenza activity.

Coming Soon: New Release of FRED

New Release!A new version of FRED (A Framework for Reconstructing Epidemiological Dynamics) will soon be ready for release. FRED is a tool for building epidemiological agent-based (individual-based) models and is designed to study how patterns of health conditions in defined populations vary over time. The new FRED will make population modeling easier. It is a unique tool for social science modeling and no computer programming is needed. A systems thinking approach is required to identify conditions of interest, their states, and the rules for changing states. FRED will simplify the workflow environment and manage the data produced by the simulation. To read more about the new FRED platform, click here.

 

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