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Alaina 2

Alaina Shreves

Scholar Type:

NIH Oxford Scholar

Entry Year: 2022
Degrees:

B.S. Neuroscience & Public Health,
The College of William and Mary, 2018
M.S. Epidemiology, Harvard T.H. Chan School of Public Health, 2022

Mentors:

Dr. Charles Matthews (NCI), Prof. Aiden Doherty (Oxford),
and Prof. Ruth Travis (Oxford)

Research Interest:

Chronic disease epidemiology, Machine learning, Wearable sensors

Growing up in West Virginia, Alaina witnessed how sociodemographic barriers and lifestyle factors contribute to elevated rates of cancer and chronic disease risk factors. These experiences informed her education at the College of William & Mary, where she majored in Neuroscience and Interdisciplinary Public Health. Through the Amgen Scholars Program, Alaina was introduced to professional public health research and studied the epidemiology of genetic disorders at the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH). Her evolving interest in big data and health disparities led her to conduct a senior undergraduate honors thesis exploring the life course epidemiology of sickle cell disease and the detrimental impact of historically racist health policies.

After William and Mary, Alaina became a postbaccalaureate fellow at the National Cancer Institute (NCI). Under the supervision of Dr. Robert Hoover, her research predominantly focused on reproductive cancers. Additionally, Alaina obtained experience in study management by assisting senior principal investigators with building a new prospective cohort, Connect for Cancer Prevention.

Alaina then completed a Master of Science in Epidemiology at the Harvard T.H. Chan School of Public Health, where she studied modifiable health behaviors among cancer survivors. As a graduate research assistant with Dr. Lorelei Mucci and Dr. Kathryn Penney, she researched prostate cancer survivors' quality of life outcomes in the Health Professionals Follow-up Study. Her thesis examined sleep disturbances among prostate cancer survivors.

As an NIH Oxford Scholar, Alaina will investigate what types of physical activity are associated with lower cancer incidence. She will use machine learning methods to quantify accelerometer-measured activity for cancer risk models with U.K. Biobank data. She will also implement two-sample Mendelian Randomization methods to explore potential causal effects between physical activity and cancer. Alaina hopes this research will inform population-level physical activity guidelines, decreasing the incidence of cancer outcomes and chronic disease risk factors.

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