Melanoma is one of the most severe forms of skin cancer and can be life-threatening due to metastasis if not caught early on in its development. Over the past decade, the U.S. Government added a Healthy People 2020 objective to reduce the melanoma skin cancer rate in the U.S. population. Now that the decade has come to a close, this research investigates possible large-scale risk factors that could lead to incidence of melanoma in the population using logistic regression and propensity score matching. Logistic regression results showed that Caucasians are 14.765 times more likely to get melanoma compared to non-Caucasians; however, after adjustment using propensity scoring, this value was adjusted to 11.605 times more likely for Caucasians than non-Caucasians. Cholesterol, Chronic Obstructive Pulmonary Disease, and Hypertension predictors also showed significance in the initial logistic regression. By using the results found in this experiment, the door has been opened for further analysis of larger-scale predictors and gives public health programs the initial information needed to create successful skin safety advocacy plans.

The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.

During the COVID-19 pandemic, increased burdens have been placed on the Arizona healthcare system, and its healthcare providers. Using a survey with a sample of N=308 prescribing providers and nurses in the Arizona healthcare system, the impact of COVID-19 on the wellbeing of healthcare providers was assessed. The survey used measures to evaluate for physical and emotional wellbeing, burnout, stressors associated with COVID-19, and work-life experiences, and found an overall negative impact on the wellbeing of healthcare workers during the COVID-19 pandemic with increased levels of reported stress and tiredness, concern for the health of family and loved ones, concern for the hardships of patients, lack of alignment between organizational priorities and personal values, and low levels of support and appreciation from socially and from leadership at work.

This study compares vaccine hesitancy during the COVID-19 pandemic with previous studies on vaccine hesitancy to evaluate the major driving factors behind COVID-19 vaccine hesitancy among undergraduate students at Arizona State University (ASU). Undergraduate students were surveyed with questions regarding different aspects of vaccines, including personal vaccination history, opinions on the COVID-19 vaccine, knowledge of the COVID-19 vaccine, and reasoning behind vaccination status. The survey was distributed through school listservs within ASU. Close-ended questions underwent statistical analysis on IBM SPSS and open-ended questions were analyzed using content analysis. Results indicated that the main driving factors behind vaccine hesitancy are believing in natural immunity, familial influence, lack of trust behind the technology of the COVID-19 vaccine, and preferring the risk of COVID-19 infection over the risk of COVID-19 vaccination. The main driving factors behind vaccine hesitancy appear to be similar to driving factors in the past, with an increase of mistrust surrounding the vaccine.

The COVID-19 pandemic has renewed interest in the importance of indoor air quality for health. The spread of respiratory aerosols is the primary mechanism for COVID-19 transmission, making it crucial to understand the role of effective ventilation in managing the risk of disease transmission. The concentration of exhaled carbon dioxide (CO2) in indoor spaces can be used as a proxy measure of ventilation efficiency. Poor indoor air quality has been associated with a range of acute and chronic health problems, including respiratory issues, cardiovascular disease, and cancer. Poor air quality may also impair cognitive performance and productivity. Social and economic inequalities exacerbate the impact of indoor air quality issues, making it crucial to address these problems in an equitable manner. Public libraries have been identified as an effective intermediary for providing education and free air quality monitoring technology to communities, with the ultimate goal of promoting awareness and increasing access to tools to promote accountability for maintaining high indoor air quality standards. The primary objectives of this initiative are to: 1) develop a citizen science toolkit for assessing indoor air quality in public spaces and deploy the toolkit to public libraries in Arizona; and 2) to conduct a program evaluation to determine whether this kit can be effectively deployed through public libraries to promote citizen science efforts and engage community members in promoting healthier indoor air quality, identify areas where improvements can be made, and prepare the program to be scaled to a larger audience.