Research Symposium

BIO

Aviah Fajerstein is pursuing a Bachelor of Science in Behavioral Neuroscience at Florida State University while completing an Interdepartmental Developmental Disabilities Certificate and the pre-medical track. They are a member of the Honors Medical Scholars Program, the Florida State Honors Program, and a recipient of the Vires Scholarship. Aviah has consistently achieved both the Dean’s and President’s List during their time at Florida State.

Aviah has been actively involved in research across multiple institutions. They co-authored a case report with Dr. Magdalena Anitescu of the University of Chicago Medical Center on spinal cord stimulators, which was presented at the North American Neuromodulation Society Meeting. Additionally, they presented research findings on neurovascular coupling at the Florida International University Student Research Internship Symposium. As part of their interest in preventive medicine and healthcare technology, Aviah is currently working with Dr. Veronica White in the FAMU-FSU College of Engineering Department of Industrial and Manufacturing Engineering to develop a vaccine prediction algorithm intended for future mobile health application integration.

Beyond research and academics, Aviah is involved in several leadership and service positions. They serve as a Hospitality Captain for Dance Marathon, represent Who We Play For as a delegate for their sorority Alpha Omicron Pi, and volunteer with the Alzheimer's Project.

Aviah is a certified medical assistant and completed an internship last semester at Tallahassee Medical Group. Their life mission is to address the injustices in our healthcare system while advancing health equity as a medical doctor and researcher.

Development of Vaccine Eligibility Prediction Algorithm for Potential Mobile Health Application

Abstract

Vaccines are an extremely effective form of preventive healthcare and are known to save lives. However, many populations have vaccination rates below the recommended levels. Limited access to healthcare records and lack of personalized reminders leads to medical non-adherence. Prior research demonstrates patient reminders are associated with higher rates of healthcare compliance, suggesting that a mobile application can improve vaccine schedule adherence and reduce preventable health burdens. Current health tracking apps mainly focus on pill reminders or symptom tracking, and do not offer many options for storing long-term preventive care data. Few digital platforms focus on vaccine predictions and reminders. The development of a vaccination prediction algorithm that can be incorporated into a mobile app can address this gap by tailoring vaccination reminders to each patient.

A synthetic patient dataset accounting for demographics and medical history is developed using Excel to evaluate a vaccine eligibility prediction algorithm based on the Centers for Disease Control and Prevention Clinical Decision Support for Immunization logic. Generated outputs from the algorithm will be compared against established immunization decision-support engines to validate predictive accuracy. Ongoing validation and refinement will support potential integration of the algorithm into a mobile reminder platform to improve long-term vaccination adherence and reduce health disparities.

Keywords: Vaccine, Prediction Algorithm, Preventive Healthcare, Immunization Scheduling, Mobile Health App