Publication Date

5-2025

Date of Final Oral Examination (Defense)

3-11-2025

Type of Culminating Activity

Thesis

Degree Title

Master of Science in Mathematics

Department

Mathematics

Supervisory Committee Chair

Juna Goo, Ph.D.

Supervisory Committee Member

Kyungduk Ko, Ph.D.

Supervisory Committee Member

Jens Harlander, Ph.D.

Abstract

At the onset of the COVID-19 pandemic, U.S. states implemented policies that attempted to mitigate the spread and effects of the disease, such as a state of emergency declaration. This study explores the application of functional data analysis (FDA) as a means to investigate the impact of U.S. state-level emergency declarations on weekly confirmed COVID-19 cases per million during the first year of the pandemic. We focus on the duration and extent to which proactive states showed significantly different patterns of COVID-19 spread than those that implemented policies reactively. Additionally, we examine patterns in monthly state-level unemployment rates over the same study period. Utilizing FDA techniques— including data smoothing, functional principal component analysis (FPCA), functional canonical correlation analysis, and functional t- and F-tests— we found that the patterns in cases per million were significantly different between proactive and reactive states from 2 to 10 weeks. Using k-means clustering, states were clustered into high unemployment rate and low unemployment rate groups based on their FPCA scores. We found that cases per million in states with consistently higher unemployment rates during the first year of the pandemic significantly differed from that of states with lower unemployment rates from 2 to 8 weeks and from 27 to 38 weeks. Finally, states were classified into one of four groups based on both their emergency declaration response (proactive or reactive) and unemployment rate (higher or lower). We found that there was an effect of the four classification groups on cases per million curves at 52 weeks.

DOI

10.18122/td.2373.boisestate

Included in

Mathematics Commons

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