Fernando Alarid-Escudero

Fernando Alarid-Escudero Headshot

Fernando Alarid-Escudero, PhD

  • Assistant Professor, Health Policy

Encina Commons,
615 Crothers Way Room 117,
Stanford, CA 94305-6006

Biography

Fernando Alarid-Escudero, Ph.D., is an Assistant Professor of Health Policy at Stanford University School of Medicine. He obtained his Ph.D. in Health Decision Sciences from the University of Minnesota School of Public Health, and was an Assistant Professor at the Center for Research and Teaching in Economics (CIDE) Región Centro, Aguascalientes, Mexico, from 2018 to 2022, prior to coming to Stanford. His research focuses on developing statistical and decision-analytic models to identify optimal prevention, control, and treatment policies to address a wide range of public health problems and develops novel methods to quantify the value of future research. Dr. Alarid-Escudero is part of the Cancer Intervention and Surveillance Modeling Network (CISNET), a 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 co-founded the Stanford-CIDE Coronavirus Simulation Modeling (SC-COSMO) workgroup. He also co-founded 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. He received a BSc in Biomedical Engineering from the Metropolitan Autonomous University in Iztapalapa (UAM-I), and a Master’s in Economics from CIDE, both in Mexico.

In The News

Christmas decorations in Mexico City
News

COVID-19 and End-of-Year Holiday Gatherings in Mexico City

Mexico City was hit hard by COVID-19 at the end of 2020, which may have been due in part to big holiday gatherings and public festivals. The SHP modeling team is warning that the sprawling metropolitan area could face another winter surge — by offering evidence of how the numbers spiked after the holidays and into the new year.
cover link COVID-19 and End-of-Year Holiday Gatherings in Mexico City
A Simulation of a World COVID-19 Map
News

A Story One Year in the Telling: the Stanford COVID Modeling Project

The Stanford-CIDE Coronavirus Simulation Model was established in the frightening days when the world was realizing a deadly virus in China would become a pandemic. A look at its accomplishments and projects one year later.
cover link A Story One Year in the Telling: the Stanford COVID Modeling Project