Point of Care diagnostics are low-cost methods to diagnose these illnesses, but they are generally only effective when the infection has begun to cause symptoms. Concentrating biological samples has been proven to increase the sensitivity of POC tests and could allow for earlier diagnosis to help monitor the spread of disease. This study reviewed the benefits of freeze concentration over other techniques to process samples in rural areas with limited infrastructure. Additionally, it analyzed the efficiency of thermoelectric devices as the cooling source for freezing. This analysis was conducted reviewing literature on the benefits of concentrating biological samples, software modeling the thermodynamics of a freeze concentrated system, and evaluating a physical model of this process. The software model established trends in altering L/D ratios of sample tubes and thermoelectric temperature. The physical model was successful in increasing the concentration of a red food dye solution through freezing with a thermoelectric device, showing this technique could be beneficial for minimal and efficient concentration devices.

In the following paper, I aim to form relationships between different patient factors and no-show rates. The culmination of these relationships will then be used in a logistic regression model. Data collected from a survey at 26 HonorHealth clinics were analyzed using odds ratios and relative risk methods. Of 310,307 visits collected, 22,280 of them were no shows (7.2%), an 11% decrease from national averages (18.8%). This fueled the study, along with a grant filed by HonorHealth looking at the impact of telehealth on the working poor. A binary logistic regression method was run over the data, and less than 1% of patients' no-shows were predicted correctly. By adding factors, and improving the diversity in the data collected, model accuracy can be improved.