Epidemiology Commons^™

Three Dimensional Spatio-Temporal Cluster Analysis Of Sars-Cov-2 Infections, Keith W. Allison

Masters Theses

The COVID-19 pandemic has heightened the need for fine-scale analysis of the clustering of cases of infectious disease in order to better understand and prevent the localized spread of infection. The students living on the University of Massachusetts, Amherst campus provided a unique opportunity to do so, due to frequent mandatory testing during the 2020-2021 academic year, and dense living conditions. The South-West dormitory area is of particular interest due to its extremely high population density, housing around half of students living on campus during normal conditions. Using data gathered by the Public Health Promotion Center (PHPC), we analyzed the …

Evaluating Public Masking Mandates On Covid-19 Growth Rates In U.S. States, Angus K. Wong

Masters Theses

U.S. state governments have implemented numerous policies to help mitigate the spread of COVID-19. While there is strong biological evidence supporting the wearing of face masks or coverings in public spaces, the impact of public masking policies remains unclear. We aimed to evaluate how early versus delayed implementation of state-level public masking orders impacted subsequent COVID-19 growth rates. We defined “early” implementation as having a state-level mandate in place before September 1, 2020, the approximate start of the school-year. We defined COVID-19 growth rates as the relative increase in confirmed cases 7, 14, 21, 30, 45, 60-days after September 1. …

A Comparison Of Techniques For Handling Missing Data In Longitudinal Studies, Alexander R. Bogdan

Masters Theses

Missing data are a common problem in virtually all epidemiological research, especially when conducting longitudinal studies. In these settings, clinicians may collect biological samples to analyze changes in biomarkers, which often do not conform to parametric distributions and may be censored due to limits of detection. Using complete data from the BioCycle Study (2005-2007), which followed 259 premenopausal women over two menstrual cycles, we compared four techniques for handling missing biomarker data with non-Normal distributions. We imposed increasing degrees of missing data on two non-Normally distributed biomarkers under conditions of missing completely at random, missing at random, and missing not …

Sleep Patterns, Urinary Levels Of Melatonin And Subsequent Weight Change In The Women’S Health Initiative Observational Study, Nicole M. Barron

Masters Theses

Results from prospective studies examining associations between sleep duration and weight gain have been mixed. Melatonin has been hypothesized to mediate the association between sleep duration and weight/body composition. In cross-sectional studies, aMT6s has been shown to be inversely associated with weight/body fat percentage. We examined associations between baseline sleep duration, insomnia status, aMT6s levels with weight/body fat percentage through 6 years, utilizing a subset 690 women who participated in a breast cancer case-control study nested within the WHI-OS. Multi-variable and mixed-effects regression was used to calculate beta-coefficients and 95% confidence intervals. Cross-sectional analyses showed urinary aMT6s levels were inversely …

Gpu-Accelerated Influenza Simulations For Operational Modeling, Peter Holvenstot

Masters Theses

Simulations of influenza spread are useful for decision-making during public-health emergencies. Policy-makers use models to predict disease spread and estimate the effects of various intervention strategies. Effective modeling of targeted intervention strategies requires accurate modeling of individual-level behavior and transmission. However, this greatly increases the computational costs of these agent-based models. In addition, if the models are used as an outbreak progresses, some operational decisions must occur rapidly in order to contain the spread of the disease.

Graphics Processing Units (GPUs) are a type of specialized processor used to drive graphical displays. Many recent devices also allow users to write …

Latin Hypercube Sampling And Partial Rank Correlation Coefficient Analysis Applied To An Optimal Control Problem, Boloye Gomero

Masters Theses

Latin Hypercube Sampling/Partial Rank Correlation Coefficient (LHS/PRCC) sensitivity analysis is an efficient tool often employed in uncertainty analysis to explore the entire parameter space of a model. Despite the usefulness of LHS/PRCC sensitivity analysis in studying the sensitivity of a model to the parameter values used in the model, no study has been done that fully integrates Latin Hypercube sampling with optimal control analysis.

In this thesis, we couple the optimal control numerical procedure to the LHS/PRCC procedure and perform a simultaneous examination of the effects of all the LHS parameter on the objective functional value. To test the effectiveness …