MODELS TO INFORM THE SAFE COLLECTION AND TRANSFUSION OF DONATED BLOOD
A DISSERTATION SUBMITTED TO THE DEPARTMENT OF MANAGEMENT SCIENCE AND ENGINEERING AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
January 2021
Preface
Copywrite
Copywrite 2021 by W. Alton Russell. All Rights Reserved.
Re-distributed by Stanford University under license with the author.
Abstract
Donated blood is a critical component of health systems around the world, but its collection and transfusion involve risk for both donors and recipients. Transfusion-transmitted diseases and non-infectious transfusion-related adverse events pose a risk to transfusion recipients, and repeat blood donation can cause or exacerbate iron deficiency among donors. This dissertation describes four decision-analytic modeling projects that elucidate trade-offs between safety, supply sufficiency, and cost to inform policies designed to protect blood donors and transfusion recipients. The first chapter integrates epidemiological, health-economic, and biovigilance data to estimate the efficacy and cost-effectiveness of a 2016 policy mandating that all blood donations are screened for Zika virus in the U.S. This analysis uses a novel microsimulation of individual transfusion recipients that captured the relationship between disease exposure risk and the number and type of blood components transfused. The second chapter describes the first health-economic assessment of whole blood pathogen inactivation. The analysis is for Ghana and improves on prior blood safety assessments for sub-Saharan Africa by considering the likelihood and timing of clinical detection for chronic viral infections. The third chapter aims to overcome some limitations of traditional cost-effectiveness analyses for blood safety. In this chapter, I develop an optimization-based framework for identifying the optimal portfolio of blood safety interventions across three modalities: deferring high-risk donors, testing for disease markers, and using risk-reducing modifications (e.g., pathogen reduction) which prevent disease transmission. By applying this framework retrospectively to evaluate U.S. policies for Zika and West Nile virus, I show that the optimal policy can vary by geography, season, and year. The final chapter focuses on the inter-donation interval, or how frequently donors are allowed to give blood. Whole blood donors must wait 8 weeks before returning to donate in the U.S., but some donors need longer to replenish iron stores. I developed a machine learning-powered decision model that tailors the inter-donation interval to each donor’s risk of iron-related adverse outcomes. My model aims to help blood collection agencies balance risks to donors against risks to the sufficiency of the blood supply. Together, these model-based analyses provide guidence for efficient and effective use of resources for blood safety.
Acknowledgements
Thank you to my advisor Margaret Brandeau. Her research inspired me to pursue a PhD before we met, and Margaret has been a wonderful mentor in research and teaching. Thank you to Brian Custer, co-advisor in all but name. Brian introduced me to blood safety policy and has shaped each project in this dissertation, along with my research plans for years to come. Margaret and Brian have both given me so much of their time, encouragement, and guidance, and it has been a priviledge to have them as mentors. Thank you to many other mentors and collaborators including Doug Owens and Jeremy Goldhaber-Fiebert, who were kind enough to serve on my reading committee, as well as David Scheinker, Scott Sutherland, David Buckeridge, Mike Busch, Susan Stramer, Jessica Yu, and Eran Bendavid. Thank you to Itai Ashlagi and Josh Saloman for serving on my oral defense committee. Thank you to my MS&E 390 classmates for teaching me so much through your research and providing great feedback on mine over the years.
I have been very fortunate to receive funding throughout my PhD. I thank Vitalant Research Institute for support through an internship and dissertation grant; the Stanford Interdisciplinary Graduate Fellowship program, Mr. Hsieh, and Ms. Liu for providing the Hsieh Family Fellowship; and the Stanford School of Engineering for a Stanford Engineering Fellowship.
Thank you to my parents Barbara and Will and my siblings Lauren and Davis for your love and support, and for the pet pictures in the group chat, which always brighten my day. Thank you to the many friends who have given me so many fond memories of my time in the Bay area.
Fall of 2016 marked the beginning of my PhD and the start of another great adventure. Thank you to my partner Wei-Hsiang, my greatest source of joy and comfort.