Publication Date
Fall 12-16-2022
Abstract
This thesis is an application of epidemiological models for infectious disease transmission and the use of partially observed Markov process (POMP) for model fitting. It focuses on COVID-19 pandemic in the state of New Mexico. The analysis covered March 2020 to June 2021. Daily data of COVID19 cases and deaths and a daily index of eleven statewide government non-pharmaceutical intervention (NPI) policies were collected from six public sources and were validated. These data were integrated through the Susceptible-Exposed-Infected-Removed (SEIR) model. Estimated daily transmission rates between the model compartments quantify the impact of the mitigation policies, and show that transmission rates and reproduction numbers decreased as policy index strengthened.
Degree Name
Statistics
Level of Degree
Masters
Department Name
Mathematics & Statistics
First Committee Member (Chair)
James Degnan
Second Committee Member
Yiliang Zhu
Third Committee Member
Melissa H Roberts
Language
English
Document Type
Thesis
Recommended Citation
Ma, Xingya. "Mitigation impact of statewide non-pharmaceutical policies on COVID-19: An application of infectious disease transmission model and partially observed Markov process to New Mexico." (2022). https://digitalrepository.unm.edu/math_etds/191
