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Medical Student

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Community/Public Health

Abstract

There have been over 2 million COVID-19 cases within the United States. When considering where infections take place, there appears to be variability between states and even between counties (Gardner 2020). To understand the reasons underlying this phenomenon, we used Texas county data on Covid-19 infection rates and utilized auxiliary data such as age, race, gender, diabetes and obesity rates, temperature, humidity, median household income, metropolitan or rural designation, and poverty rates to see what confers greater risk for higher total infection at a county level. Our study found a positive relationship between diabetes and obesity rates and COVID-19 infection rates, and a negative relationship between the rates of lower educational status and COVID-19 infection rates. Further studies should investigate the underlying mechanisms regarding why those with diabetes, obesity, or a High School Diploma or less are more susceptible to COVID-19 infection as well as the role that population density and different stay-at-home policies affected infection rates in each county.

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Exploration of Potential Risk Factors For Texas County COVID-19 Infection Rates

There have been over 2 million COVID-19 cases within the United States. When considering where infections take place, there appears to be variability between states and even between counties (Gardner 2020). To understand the reasons underlying this phenomenon, we used Texas county data on Covid-19 infection rates and utilized auxiliary data such as age, race, gender, diabetes and obesity rates, temperature, humidity, median household income, metropolitan or rural designation, and poverty rates to see what confers greater risk for higher total infection at a county level. Our study found a positive relationship between diabetes and obesity rates and COVID-19 infection rates, and a negative relationship between the rates of lower educational status and COVID-19 infection rates. Further studies should investigate the underlying mechanisms regarding why those with diabetes, obesity, or a High School Diploma or less are more susceptible to COVID-19 infection as well as the role that population density and different stay-at-home policies affected infection rates in each county.

 

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