Fernando Alarid-Escudero

Fernando Alarid-Escudero Headshot

Fernando Alarid-Escudero, PhD

  • Assistant Professor, Health Policy

Encina Commons,
615 Crothers Way Room 100,
Stanford, CA 94305-6006

Biography

Fernando Alarid-Escudero, PhD, is an Assistant Professor of Health Policy at Stanford University School of Medicine. He is a decision scientist specializing in disease simulation, decision-analytic modeling, and cost-effectiveness analysis to inform health policy questions that cannot be readily answered through clinical studies alone. He has also developed novel methods to quantify the value of future research and calibrate simulation models using emulator-based Bayesian methods. Alarid-Escudero is a member of three cancer working groups (colorectal [CRC], bladder, and gastric) in the Cancer Intervention and Surveillance Modeling Network (CISNET) consortium, a group of investigators sponsored by the National Cancer Institute in the United States that uses simulation modeling to evaluate the impact of cancer control interventions (e.g., prevention, screening, and treatment) on population trends in incidence and mortality.

Alarid-Escudero 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 that develop transparent and open-source solutions to implement decision analysis and quantify the value of potential future investigation for health policy analysis.

In The News

2025 Rosenkranz Prize Winners Fernando Alarid-Escudero and Jorge Luis Salinas
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Rosenkranz Prize Honors Innovators Tackling Public Health in Mexico

Two Stanford researchers are working on projects to fight antimicrobial resistance and colorectal cancer in Mexico.
Rosenkranz Prize Honors Innovators Tackling Public Health in Mexico
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.
COVID-19 and End-of-Year Holiday Gatherings in Mexico City
A Simulation of a World COVID-19 Map
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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.
A Story One Year in the Telling: the Stanford COVID Modeling Project