Masters Theses

Date of Award


Degree Type


Degree Name

Master of Science


Agricultural and Resource Economics

Major Professor

Sreedhar Upendram, Jada Thompson

Committee Members

Sreedhar Upendram, Jada Thompson, Edward Yu


This thesis is a combination of two distinct chapters. Chapter 1 focuses on human pandemics impacts on global meat trade. An increase in future mass global pandemics is expected as zoonotic diseases, globalization, and trade escalate. These pandemics affect nearly every industrial sector, with animal protein no exception. The COVID-19 pandemic continues to be the largest, most expansive, and unprecedented pandemic in a century. Labor shortages and supply chain defragmentation are only a portion the production process affected. Studies have analyzed species specific disease events’ effects on animal trade, such as those caused by the African Swine Fever amongst Chinese herds. Few studies have identified and analyzed the effects on the animal protein trade in relation to global human pandemics, however. This study uses public trade data and recent pandemics (i.e. MERS-Cov, COVID-19, Ebola, and Zika virus) to estimate the effects to global animal protein trade. The study results will improve preparedness and recognize implications to a potential future pandemic on the meat industry. Chapter 2 focuses on water infrastructure investment methodologies in communities in distress. Many communities in Tennessee face water infrastructure needs. By 2040, these needs are estimated near $15.6 billion. The Tennessee Department of Environment & Conservation (TDEC) Clean Water State Revolving Fund (CWSRF) seeks to ease the burden of these costs on distressed communities through low-interest loans and subsidies. Traditionally, this assistance has been distributed by a single economic metric (e.g., median household income). This study seeks to determine water infrastructure affordability through Ability-to-Pay indices composed of several socioeconomic and financial factors. The ATP indices will more accurately determine community affordability and will be a method able to be replicated for future fund distribution.

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