A Markov Decision Process Approach to Control of Networks and Analysis of North Carolina COVID-19 Spread by a New Compartmental Model

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  • December 11, 2020
Creator
  • Whitehead, Thomas
    • Affiliation: College of Arts and Sciences, Department of Statistics and Operations Research
Abstract
  • Networks play an important role in modelling the interactions of people, and how this can lead to the spread of ideas, influence, products, and disease. For my first semester of research, I focus on modelling social networks as Finite Horizon Markov Decision Processes, so that I can find the optimal set of activations using Backwards Iteration. In particular, I focus on Linear Threshold social networks and Independent Cascade social networks. For the second semester of research, I focus on working with a compartmental model created by Housni et al., to model the spread of Covid-19 in North Carolina [3]. I make three major adjustments to the model: including a parameter that accounts for the possibility of False Negative tests, and eliminating the effects of contact tracing. The former adjustment does not result in any significant changes in outcome, while the latter results in a highly unrealistic predictions.
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  • In Copyright
Advisor
  • Ziya, Serhan
    • Affiliation: College of Arts and Sciences, Department of Statistics and Operations Research
Degree
  • Bachelor of Science
Graduation year
  • 2020
Language
  • English

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