Term of Award
Spring 2024
Degree Name
Doctor of Public Health in Epidemiology (Dr.P.H.)
Document Type and Release Option
Dissertation (restricted to Georgia Southern)
Copyright Statement / License for Reuse
This work is licensed under a Creative Commons Attribution 4.0 License.
Department
Department of Biostatistics, Epidemiology, and Environmental Health Sciences
Committee Chair
Isaac Chun-Hai Fung
Committee Member 1
Jing Kersey
Committee Member 2
Kelly Sullivan
Committee Member 3
Gerardo Chowell-Puente (non-voting)
Non-Voting Committee Member
Alicia Kraay, amullis@umich.edu
Abstract
As COVID-19 is becoming endemic with the potential of recurrent epidemics globally, it is a priority to study its transmission dynamics to inform public health decision-making. There are three individual studies conducted to assess COVID-19 disease burden, transmission potential, and to evaluate R packages that are used to estimate a pathogen's transmission potential: 1) estimating the incidence rate ratios of COVID-19 cases among employees of seven District of Columbia government departments, 2) comparing EpiEstim and EpiFilter time-varying reproduction number (Rt) estimation methods using daily reported case count in Hawaii and Guam, 3) comparing the performance of three R packages (EpiEstim, EpiFilter, and EarlyR) that estimate Rt and basic reproduction number (R0) using a discrete-time stochastic S-E-I-R influenza model and a discrete-time stochastic SARS-CoV-2 S-E-P-I-R model simulated epidemic data. The dissertation concludes with a summary and suggestions for future research directions.
OCLC Number
1437797758
Catalog Permalink
https://galileo-georgiasouthern.primo.exlibrisgroup.com/permalink/01GALI_GASOUTH/1r4bu70/alma9916572950402950
Recommended Citation
Hua, Xinyi, "COVID-19 Disease Burden and Transmission Dynamics: Epidemiological, Statistical, and Mathematical Approaches" (2024). Electronic Theses and Dissertations. 2724.
https://digitalcommons.georgiasouthern.edu/etd/2724
Research Data and Supplementary Material
No