Simulating Alternative Tuberculosis Diagnosis Methods in Underdeveloped Countries

Author

Luke TurnerFollow

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

Committee Member/Reader

Pohl, Ed

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