Fernando Alarid-Escudero is an Assistant Professor in the Division of Public Administration, a member of the Drug Policy Program (PPD) and the head of the [Project of Decision Analysis in Uncertain Contexts](PADeCI; https://padeci.org) at the Center for Research and Teaching in Economics (CIDE) Region Centro in Aguascalientes, Mexico. He obtained his PhD in Health Decision Sciences from the University of Minnesota School of Public Health. His research focuses on developing statistical and decision-analytic models to identify optimal prevention, control and treatment strategies of different diseases, and on developing novel methods to quantify the value of future research.

Dr. Alarid-Escudero is part of the Cancer Intervention and Surveillance Modeling Network (CISNET), consortium of NCI-sponsored investigators that includes modeling to improve our understanding of the impact of cancer control interventions (e.g., prevention, screening, and treatment) on population trends in incidence and mortality. Dr. Alarid-Escudero is a co-founding member of the Stanford-CIDE Coronavirus Simulation Modeling (SC-COSMO) workgroup (https://www.sc-cosmo.org). He is also a co-founding member of the Decision Analysis in R for Technologies in Health (DARTH) workgroup and the Collaborative Network on Value of Information (ConVOI), international and multi-institutional collaborative efforts where we develop transparent and open-source solutions to implement decision analysis and quantify the value of potential future investigation for health policy analysis.