Reza Yaesoubi

Dr. Reza Yaesoubi’s research focuses on medial decision making and model-based evaluation of health policies. His work incorporates mathematical and computer simulation models, machine learning methods, and optimization techniques to guide resource allocation and decision making in public health and health delivery systems. He has applied these methods in estimating the impact of different strategies to reduce the prevalence of alcohol-exposed pregnancies, conducting cost-effectiveness analyses of colorectal cancer screening strategies, estimating societal willingness-to-pay for health, and characterizing performance-based payment systems for preventive care systems. His current work mainly focuses on optimizing public health responses to control the spread of infectious diseases including COVID-19, influenza, meningitis, and drug-resistant tuberculosis and gonorrhea. He is also interested in theoretical and methodological issues in medical decision-making and health care resource allocation.

What do you do with data science?

My main interest and work in data science are focused on developing and applying analytical methods to inform data-driven and cost-effective decisions when the evidence base and data are shifting too quickly for any static decision to suffice (e.g., during outbreaks of novel pathogens). Through incorporating mathematical and computer simulation models, statistical and machine learning methods, and optimization techniques, my proposed methods provide mechanisms to combine data and evidence from various sources to inform cost-effective decisions in real-time. I have focused on several areas of application: designing adaptive policies to mitigate outbreaks of viral pathogens (e.g., SARS-CoV-2 and influenza), optimizing strategies to survey and interrupt the spread of antimicrobial-resistant bacteria such as N. gonorrhea and M. tuberculosis, developing methods for real-time data assembly and calibration of transmission models of infectious diseases, guiding the use of intensified tuberculosis interventions in high burden settings, and informing meningococcal vaccination strategies in Sub-Saharan Africa.