Date of Graduation
5-2019
Document Type
Thesis
Degree Name
Bachelor of Science in Industrial Engineering
Degree Level
Undergraduate
Department
Industrial Engineering
Advisor/Mentor
Rossetti, Manuel D.
Committee Member/Reader
Pohl, Edward A.
Abstract
Tuberculosis is the deadliest infectious disease in the world; it is especially rampant in underdeveloped countries because they do not have the infrastructure, technology, or funding to properly combat the infection. However, the development of portable point-of-care diagnosis machines can reverse this epidemic as they far surpass conventional laboratory identification. The question now is where to place these machines, which is a difficult decision with a lack of data. Therefore, a flexible simulation model is created to test the implementation of these machines with different countries and configurations. The simulation tests the baseline model and three proposed implementations of the machines. Initial analysis indicates these machines can reduce the average diagnosis period of patients by a factor of one-hundred. Furthermore, a fractional factorial design was conducted to test the sensitivity of each variable to determine which data needs to be collected before making any decisions. The model is built to be accessible and flexible allowing for the model to be expanded upon in future research.
Keywords
Simulation; Modeling; Arena; Flexible; Africa; POC
Citation
Turner, L. (2019). Simulating Alternative Tuberculosis Diagnosis Methods in Underdeveloped Countries. Industrial Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/ineguht/61
Included in
Diagnosis Commons, Industrial Engineering Commons, Operational Research Commons, Respiratory Tract Diseases Commons, Systems Engineering Commons
