Our April speaker for the monthly lunch series "CEND It!" featured an engaging and timely discussion with Reza Yaesoubi, Associate Professor at UCSF Institute for Health Policy Studies and the UCSF Department of Epidemiology and Biostatistics. His talk explored how analytical methods can support real-time health decision-making in contexts where scientific evidence is rapidly evolving.
Dr. Yaesoubi highlighted the growing need for flexible, data-driven approaches in public health and clinical care, especially during infectious disease outbreaks. Drawing on his work, he illustrated how modeling and predictive analytics can help decision-makers act with greater confidence even amid uncertainty. The discussion also delved into applications of these methods across a range of challenges, from optimizing responses to emerging infectious threats to improving predictions of clinical outcomes. A key focus was the potential to personalize treatment strategies for drug-resistant infections such as tuberculosis and gonorrhea, where timely and tailored interventions can significantly impact patient outcomes.