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Diana Prieto

Assistant Professor

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Diana Prieto is an Assistant Professor of Practice at the Johns Hopkins Carey School Business. She holds an MA in Statistics and a PhD in Industrial Engineering from the University of South Florida. In her research, she analyzes complex systems in public health where customer prioritization is needed to manage resource scarcity. Examples of those systems include: 1) Influenza speicmens waiting to be tested for virus confirmation, and 2) patients waiting for healthcare services. She has also served as a consultant in projects for education, transportation, and manufacturing.

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Papers

Paul R, Han D, DeDoncker E, Prieto D. (2022). Dynamic downscaling and daily nowcasting from influenza surveillance data. Statistics in medicine

Martinez DA, Klein EY, Parent C, Prieto D, Bigelow BF, Saxton RE, Page KR. (2021). Latino Household Transmission of SARS-CoV-2. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America

Gu Y, DeDoncker E, VanEnk R, Paul R, Peters S, Stoltman G, Prieto D. (2021). Accuracy of State-Level Surveillance during Emerging Outbreaks of Respiratory Viruses: A Model-Based Assessment. Medical decision making : an international journal of the Society for Medical Decision Making

Barzan Shekh ; Elise de Doncker ; Diana Prieto. (2015). Hybrid multi-threaded simulation of agent-based pandemic modeling using multiple GPUs. 2015 IEEE International Conference on Bioinformatics and Biomedicine

Prieto D, Das TK. (2016). An operational epidemiological model for calibrating agent-based simulations of pandemic influenza outbreaks. Health care management science, 19(1)

Soto-Ferrari M, Holvenstot P, Prieto D, Dedoncker E, Kapenga J.. (2013). Parallel Programming Approaches for an Agent-based Simulation of Concurrent Pandemic and Seasonal Influenza Outbreaks. Procedia Computer Science, (18)

Prieto DM, Das TK, Savachkin AA, Uribe A, Izurieta R, Malavade S. (2012). A systematic review to identify areas of enhancements of pandemic simulation models for operational use at provincial and local levels. BMC public health, (12)

Uribe-Sánchez A, Savachkin A, Santana A, Prieto-Santa D, Das TK. (2011). A Predictive Decision-Aid Methodology for Dynamic Mitigation of Influenza Pandemics. OR spectrum : quantitative approaches in management, 33(3)

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