ORCID ID
0000-0003-3392-6574
Date Awarded
Summer 2021
Document Type
Thesis
Degree Name
Master of Science (M.Sc.)
Department
Computer Science
Advisor
Evgenia Smirni
Committee Member
Yifan Sun
Committee Member
Adwait Nadkarni
Abstract
We present an individual-centric model for COVID-19 spread in an urban setting. We first analyze patient and route data of infected patients from January 20, 2020 ,to May 31, 2020, collected by the Korean Center for Disease Control & Prevention (KCDC) and illustrate how infection clusters develop as a function of time. This analysis offers a statistical characterization of mobility habits and patterns of individuals. We use this characterization to parameterize agent-based simulations that capture the spread of the disease, we evaluate simulation predictions with ground truth, and we evaluate different what-if counter-measure scenarios. Although the presented agent-based model is not a definitive model of how COVID-19 spreads in a population, its usefulness, limitations, and flexibility are illustrated and validated using hard data.
DOI
http://dx.doi.org/10.21220/s2-m6wv-nh31
Rights
© The Author
Recommended Citation
Schmedding, Anna, "Epidemic Spread Modeling For Covid-19 Using Hard Data" (2021). Dissertations, Theses, and Masters Projects. William & Mary. Paper 1627047844.
http://dx.doi.org/10.21220/s2-m6wv-nh31
