U.S. Army Medical Center of Excellence

Graduate School Research and Education Symposium 2025

Events/Announcements:

Graduate School Research and Education Symposium

June 5-6, 2025

The symposium is intended to serve graduate school faculty, researchers, clinicians and healthcare administrators from across the Department of Defense, Department of Veterans Affairs, and partners in the civilian community. The 13th Annual Graduate School Research and Education Symposium is June 5-6, 2025, and will be held in-person at UT Health Science Center, San Antonio, Texas. 

The symposium consists of guest speakers and poster and podium presentations, showcasing student and faculty research across the full spectrum of translational research.

Note: Everyone must fill out the Attendees Registration.

GSRES Attendees Registration: Click Here

Invitations for either podium or poster presentations will be sent out 14-18 APR 2025

Poster submissions and audio submissions are due 14 MAY 2025 @ 2359 CDT

POSTER EXAMPLES

ABSTRACT EXAMPLE: Primary Research

ALGORITHIMIC BIAS IN ADVANCED FOODBORNE DISEASE OUTBREAK SURVEILLANCE; THE NATIONAL OURBREAK REPORTING system, 2009-2019

Joe S. Snuffy (1,2), Jaime B. Smith (3), John J. Jones (2), Joyce K. Jackson (2), Donald D. Duck (2), Michael M. Mouse (2), Peter L. Pan (2)

1.     Army Medical Department Student Detachment, US Army Medical Center of Excellence, Fort Sam Houston, TX

2.     US Army-Baylor University Master’s Program in Nutrition, Fort Sam Houston, USA

3.     US Army Center for Initial Military Training, US Army Training and Doctrine Command, Fort Eustis, VA

Introduction/Background: In deployed and nondeployed military settings, acute gastrointestinal (GI) and diarrheal diseases have been a consistent cause of significant morbidity and mortality. A common, costly and preventable cause of acute GI and diarrheal disease is foodborne illness.

Purpose/Hypothesis: While centralized testing and reporting of foodborne disease outbreaks (FBDO) across the US Department of Defense is lacking, advanced publicly available FBDO surveillance systems offer alternative ways to examine the potential burden of foodborne illness on military readiness and health system resources, and the potential for non-random missingness and consequent algorithmic bias.

Materials/Methods: Using FBDO records from Centers for Disease Control and Prevention’s National Outbreak Reporting System from 2009-2019, we identified the patterns of missingness and quantified the resulting algorithmic bias to inform the development of robust military public health surveillance systems.

Among primary sources of algorithmic bias related to FBDO data collection and reporting (spatial and temporal validation, reporting standards and procedures to define categories), we examined the proportion of missing data in select FBDO characteristics (such as geographic locations; illness, exposure and global duration estimates; and implicated food product categories). We determined patterns of missingness (as completely at random or structural) and quantified their effects on total FBDO caseload using pairwise t-tests with Bonferroni correction and logistic regression models.

Results: Among 9407 records, 9019(96%) and 388(4%) were associated with single and multistate outbreaks, respectively. On average, the caseload of multistate was ~3.3 times more than single state FBDOs (53.1 cases (95%CI:52.4, 53.8) vs. 16.2 cases (16.1, 16.2), respectively, p<0.001). Of records assessed, 25%(2370) were missing a combination of illness and exposure start and end dates, restricting estimation of illness, exposure and global duration to 9116 (97%), 7119 (76%) and 7037 (75%) FBDOs, respectively. For 7111(76%) of FBDOs, data on food products were categorized as missing (5456,58%), undetermined (353,4%), unclassifiable (51,<1%), other (50,<1%) or invalid (5,<1%).

Conclusions: The effect of structural missingness in essential FBDO characteristics, such as location, duration, and causal pathways, on caseload estimates demonstrates the potential algorithmic bias that could jeopardize the reliability of FBDO surveillance. Improvements in data infrastructure are critical to minimize structural missingness, prevent potential algorithmic biases, and strengthen system predictive capacities and food safety policies. Data availability does not translate to usability for national defense purposes, where underestimation of any security threat due to algorithmic bias could lead to inefficient resource utilization, development of ill-informed emergency response and preparedness plans, and implementation of ineffective detection, prevention, and monitoring strategies.

Supports: Disease and Non-Battle Injury Management & Rehabilitation Research, Health & Performance Optimization & Reintegration Research

To submit an abstract to GSRES 2025 for consideration, follow the instructions below:

1. Submit your abstract via a Word document and use the format listed below (also see the example abstract below).  Note there is a 500-word limit for abstract content [this word limit does not include the authors or abstract classification sections]

   Author(s):

   Abstract Classification: (1-primary research, 2-literature review, 3-research proposal/protocol, 4-program evaluation/process improvement, 5-case study/series)

   Title of Abstract:

   Introduction/Background:

   Purpose/Aims:

   Methodology:

   Results/Implications:

   Discussion/Conclusion/Military Relevance:

2. Email your completed abstract to the GSRES abstract committee (medcoe_gsres@army.mil) along with the following information:
1. Since this is a group email, please title your email to indicate the purpose of your email (e.g., "GSRES abstract submission", "GSRES oral presentation submission", "Question regarding abstract submission", etc.)
2. Name and rank (if applicable)
3. Student or Faculty
4. Program with which you are affiliated (ex: MHA/MBA, OTD, LTHET School of Choice, DScPT)
5. Are you available to present in-person or virtually only

**We will acknowledge receipt of your abstract submission via email. If you do not receive an email acknowledging receipt, please reach out to confirm receipt. If we do not receive your submission, your abstract may not be considered for presentation at GSRES 2025**

Contact Us:

Please contact us with any questions or concerns at:

• medcoe_gsres@army.mil