– Executive Summary –
Mitigation strategies to prevent disease transmission during the COVID-19 pandemic included mask mandates, stay-at-home orders, and limitations on social gatherings and events.[1] These strategies were put in place across the country at varying times and to varying degrees, as each state has the authority to institute public health actions independently of other states. Additionally, local governments can opt to instill stricter public health measures than those put in place by the state.
Such mitigation strategies as mask mandates and stay-at-home orders are proven methods to decrease the spread of disease and, therefore, reduce COVID-19 cases, hospitalizations, and mortality.[2] However, their impact is limited by a patchwork approach to mandates in the United States. Inconsistencies in public health mitigation measures across states and metropolitan areas generate confusion and a public health approach that is ripe for political attention and criticism. Moreover, as adherence to public health measures decreased over time, local or state entities were less likely to implement or enforce them.
Many factors contributed to whether an individual accepted and adhered to public health orders, including socioeconomic status, political alliance, personal bias, enforcement, information misconceptions, and perceived risk.[3] Political alliance was a significant contributor, not only in whether individuals adhered to public health orders but also in whether a state or metropolis was likely to enact them.[4] During the COVID-19 pandemic, predominantly conservative states were less likely to adopt public health mandates on a statewide scale while largely liberal states were more likely to adopt and adhere to guidance from federal public health authorities, such as the Centers for Disease Control and Prevention.[5] Adding to the rhetoric, social media was often used as a platform for the expression of individual beliefs surrounding the COVID-19 pandemic, such as doubt about the virus’s severity, political involvement, treatment options, and vaccination.[6]
Initially, public health guidance focused on those who suffered from comorbidities and conditions linked to poor COVID-19 outcomes, such as hospitalization, ventilation, or death. Notably, severe COVID-19, such as conditions requiring hospitalization, intensive care, or ventilation or those that have led to death, has been exacerbated by chronic diseases and conditions. Conditions such as heart disease, diabetes, chronic obstructive pulmonary disease, and obesity are known contributors to severe COVID-19.[7] Additionally, socioeconomic status has played an important role in severe COVID-19, increased cases, and mortality.
The aim of this thesis was to determine whether mitigation strategies, socioeconomic status, political alliance, and behavioral risk factors had an impact on COVID-19 cases and mortality when compared between states. Publicly available data on behavioral risk factors, COVID-19 prevalence and mortality, and socioeconomic status by state were collected in a central database, allowing for an analytical comparison of these factors. The analysis determined that cases of COVID-19 were more prevalent in states that had higher rates of smoking and populations with a higher body mass index, had lower rates of education and income, had conservative governorship, or did not put a mask mandate or stay-at-home order in place. Mortality was greatest in states with lower income and education—these were the only variables that were significantly different among states concerning mortality. This analysis determined that socioeconomic status is a significant indicator of COVID-19 prevalence and mortality. Specifically, those without a high school diploma or with a household income of less than $15,000 annually have an increased risk of COVID-19 infection and death.
Contributing factors in severe COVID-19 or poor outcomes from the disease should be used as a tool to decide whether and when public health mandates should be made and should not be limited to chronic disease comorbidities. Focusing on communities with lower levels of education and income should be prioritized in future pandemic planning. Additional recommendations for future pandemic planning include utilizing existing data on chronic disease and poor health behaviors, adopting a consistent national approach to public health mitigation strategies, promoting earlier public health outreach and intervention for vulnerable populations, and employing adequate and appropriate public health messaging for individuals of lower socioeconomic status.
[1] “How to Protect Yourself and Others,” Centers for Disease Control and Prevention, August 11, 2022, https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-with-medical-conditions.html.
[2] John T. Brooks and Jay C. Butler, “Effectiveness of Mask Wearing to Control Community Spread of SARS-CoV-2,” JAMA 325, no. 10 (March 9, 2021): 998–99, https://doi.org/10.1001/jama.2021.1505; Hien Lau et al., “The Positive Impact of Lockdown in Wuhan on Containing the COVID-19 Outbreak in China,” Journal of Travel Medicine 27, no. 3 (April 2020): taaa037, https://doi.org/10.1093/jtm/taaa037.
[3] Mae K. Fullerton et al., “Evidence against Risk as a Motivating Driver of COVID-19 Preventive Behaviors in the United States,” Journal of Health Psychology (June 2021), https://doi.org/10.1177/13591053211024726.
[4] Gang Wang, Richard A. Devine, and Gonzalo Molina-Sieiro, “Democratic Governors Quicker to Issue Stay-at-Home Orders in Response to COVID-19,” Leadership Quarterly (2021): 101542, https://doi.org/10.1016/j.leaqua.2021.101542.
[5] Wang, Devine, and Molina-Sieiro.
[6] Nicholas Francis Havey, “Partisan Public Health: How Does Political Ideology Influence Support for COVID-19 Related Misinformation?,” Journal of Computational Social Science 3, no. 2 (November 2020): 319–42, https://doi.org/10.1007/s42001-020-00089-2.
[7] “Science Brief: Evidence Used to Update the List of Underlying Medical Conditions Associated with Higher Risk for Severe COVID-19,” Centers for Disease Control and Prevention, June 15, 2022, https://www.cdc.gov/coronavirus/2019-ncov/science/science-briefs/underlying-evidence-table.html.
