Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


9103.pdf (5.82 MB)

ETD Abstract Container

Abstract Header

Agent-Based Simulation Modeling and Analysis of Infectious Disease Epidemics and Implications for Policy

Kasaie Sharifi, Parasto Alsadat
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1396531551

Abstract Details

2014, PhD, University of Cincinnati, Business: Business Administration.
Infectious diseases are the largest killers of children and young adults in developing countries, and continue to pose a high burden on global health. This dissertation concerns related topics for combating infectious-disease epidemics, and is organized into three main chapters. While each chapter revolves around a specific topic in the general domain of public-health policymaking, the unifying theme of this research is using agent-based simulation methodology for modeling and analysis of infectious-disease epidemics. The first chapter targets the topic of how best to allocate constrained resources to control an epidemic. In this study, we use a collection of computational techniques, including computer simulation and numerical optimization algorithms, to develop a simulation-optimization framework for addressing the resource-allocation problem as applied to an epidemic. The goal is to relax the restrictive assumptions held by traditional analytical approaches, thereby facilitating a more valid model that is necessarily more complex, and to extend the method to support a general class of resource-allocation problems with realistic assumptions about population structure, disease description, and interventions. The second chapter presents a series of studies on transmission dynamics of tuberculosis (TB), and addresses the impact of various control strategies for combating TB epidemics. Using an agent-based simulation model of a TB epidemic in a household-structured population, we estimate the timing of TB transmission among household and community members. Moreover, we consider multiple case-finding strategies, including household contact tracing and a community active approach, and evaluate the population-level impact of each intervention for controlling disease incidence. Finally, the third chapter analyzes estimation bias of the recent-transmission rate in molecular studies of TB. Analysis of population-based DNA data continues to serve as the main method to estimate the proportion of TB incidence due to recent transmission, which in turn has important implications for understanding the dynamics of transmission and policymaking. Previous studies have identified a number of factors affecting the precision of this approach in various settings, but the exact relationship of such factors remains uncertain. In this study, we aim to quantify the role of such factors, and develop a decision tool for adjusting the estimated ratio of infection due to recent transmission. Using an agent-based simulation model of TB as a virtual laboratory, we implement a sequence of statistically controlled experiments with regard to combinations of several factors. The results enable us to compute the estimation bias for various levels of each factor, and can serve as a decision-support tool for adjusting the estimation error in future molecular studies of TB. In summary, this dissertation concerns critical global-health issues in understanding, controlling, and policy-making concerning infectious-disease epidemics, and offers a multidisciplinary approach to such problems using advanced computer-simulation techniques and analytical tools. The agent-based simulation approach is a novel technique that is increasing in popularity across the literature and in several fields. This brings to bear the power and effectiveness of such models in various applications, and their promising contributions for control and policymaking of infectious diseases.
W. David Kelton, Ph.D. (Committee Chair)
Mark Eckman, M.D. (Committee Member)
Craig Froehle, Ph.D. (Committee Member)
299 p.
Operations Research
agent-based simulation; modelling; infectious disease epidemic; tuberculosis; resource allocation; household contact tracing

Recommended Citations

Citations

  • Kasaie Sharifi, P. A. (2014). Agent-Based Simulation Modeling and Analysis of Infectious Disease Epidemics and Implications for Policy [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1396531551

    APA Style (7th edition)

  • Kasaie Sharifi, Parasto Alsadat. Agent-Based Simulation Modeling and Analysis of Infectious Disease Epidemics and Implications for Policy. 2014. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1396531551.

    MLA Style (8th edition)

  • Kasaie Sharifi, Parasto Alsadat. "Agent-Based Simulation Modeling and Analysis of Infectious Disease Epidemics and Implications for Policy." Doctoral dissertation, University of Cincinnati, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1396531551

    Chicago Manual of Style (17th edition)

ucin1396531551
1,189
© 2014, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.