Title: Modeling and Analytics to Inform Resource Allocation and Policy Decisions
Date: June 10th, 2024
Time: 09:30 - 11:30 AM EST
Location: Microsoft Teams meeting
Committee
Dr. Pinar Keskinocak, School of Industrial and Systems Engineering, Georgia Institute of Technology (Advisor)
Dr. David Goldsman, School of Industrial and Systems Engineering, Georgia Institute of Technology
Dr. Pelin Pekgun, School of Business, Wake Forest University
Dr. Nicoleta Serban, School of Industrial and Systems Engineering, Georgia Institute of Technology
Dr. Beril Toktay, Scheller College of Business, Georgia Institute of Technology
Abstract
Persistent and emerging health challenges continue to pose significant threats to public well-being. These challenges include infectious disease outbreaks that threaten physical health and a steadily increasing trend of mental illness, particularly among children and adolescents. The increased likelihood of weather-related natural disasters highlights the importance of recycling post-disaster debris to protect environmental health and mitigate subsequent effects on human health. This thesis utilizes modeling and analytical approaches to examine current and potential future health policies that can effectively address these challenges.
In Chapter 2, we investigated the trade-offs and interactions between the efficacy and reach of prophylactic vaccines against infectious diseases. We developed numerous Susceptible-Infectious-Recovered-Death (SIR-D) compartmental models to evaluate the infection attack rate (IAR) under various resource allocation strategies for multiple vaccine types with varying efficacies and reaches. The chapter specifically addressed two key questions: (i) whether resources should be allocated more to a higher-efficacy but resource-intensive vaccine or to a lower-efficacy but less resource-intensive vaccine, and (ii) how the emergence of virus variants that reduce vaccine efficacy influences resource allocation decisions.
In Chapter 3, we examined clinicians’ adherence to clinical practice guidelines and U.S. Food and Drug Administration (FDA) medication labels when prescribing psychotropic medications to Medicaid-insured children with attention deficit hyperactivity disorder (ADHD). We conducted a retrospective analysis using Medicaid claims data from 2016 to 2018 across 46 U.S. states. We identified the chronological diagnoses of ADHD and any other mental health comorbidities, and evaluated whether each prescribed medication was recommended and safe for the recipient’s age and historically assigned diagnoses. We also explored the extent to which prescribed medications misaligned with clinical recommendations.
In Chapter 4, we evaluated the implications of state policies on the management and recycling of post-disaster debris operated by local governments and private-sector recyclers. Natural disasters create substantial amounts of debris, which have been traditionally disposed of via landfilling and incineration. These methods cause environmental damage and subsequently impact human health. Consequently, recycling the debris has been recommended as a more sustainable and healthier disposal method. We employed a three-stage Stackelberg game model, involving three stakeholders with different interests, to analyze how state policies, such as sharing the cost of debris management and mandating a minimum amount of post-disaster debris to be recycled, influence the quantity and quality of recycled debris.