Antibiotic-resistant bacteria(ARB) is causing increased health risk and cost to society. Mathematical models have been developed to study the transmission of resistant bacteria and the efficacy of preventive measures to slow its spread within a hospital setting. The majority of these models have assumed a constant total hospital population with the admission and discharge rates being equal throughout the duration. But a typical hospital population varies from day to day and season to season. In this thesis, we apply variable admission and discharge daily rates to existing deterministic and stochastic models which examine the transmission of single and dual resistant bacteria. We perform stability and equilibrium analyses as well as a sensitivity analysis on the resulting model..
Identifer | oai:union.ndltd.org:ETSU/oai:dc.etsu.edu:etd-2308 |
Date | 01 May 2013 |
Creators | Snyder, Edward H |
Publisher | Digital Commons @ East Tennessee State University |
Source Sets | East Tennessee State University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations |
Rights | Copyright by the authors. |
Page generated in 0.0024 seconds