Modeling and study of infectious disease : stochastic modeling for antibiotic resistance and treatment strategies
Name
50336422-MIT.pdf
Description
Full printable version
Size
4.65 MB
Format
Adobe PDF
Checksum (MD5)
6705306a422fec105d8b1e0b67c901e5
Author(s)
Lo, Monique (Monique Chun-Ying), 1978-
Advisor(s)
Eric Klopfer.
Date Issued
2001
Publisher
Massachusetts Institute of Technology
Abstract
Antibiotic-resistant bacteria pose a serious threat to immuno-compromised individuals in Intensive Care Units (ICU). This study examines several cycling treatments (7,14,30,60,120,240-day cycle) and random fraction treatment (50-50,60-40,80-20,100-0) strategies in ICU and finds that no single strategy will outperform all others. Human, hospital and pathogen conditions such as admission/departure rate, transmission rate, drug application rate, and incoming patients' characteristics influence the selection of the optimal treatment strategy. Random fraction treatment is generally favored when admission/departure rate is large. Cycling treatment is generally favored when admission/departure rate is small. When transmission rates are high, longer cycle period are preferred. When transmission rates are low, random fraction treatments are preferred. For cycling treatments, longer cycle periods is associated with lower drug application rates whereas shorter cycle periods are associated with larger drug application rates.Antibiotic-resistant bacteria pose a serious threat to immuno-compromised individuals in Intensive Care Units (ICU). This study examines several cycling treatments (7,14,30,60,120,240-day cycle) and random fraction treatment (50-50,60-40,80-20,100-0) strategies in ICU and finds that no single strategy will outperform all others. Human, hospital and pathogen conditions such as admission/departure rate, transmission rate, drug application rate, and incoming patients' characteristics influence the selection of the optimal treatment strategy. Random fraction treatment is generally favored when admission/departure rate is large. Cycling treatment is generally favored when admission/departure rate is small. When transmission rates are high, longer cycle period are preferred. When transmission rates are low, random fraction treatments are preferred. For cycling treatments, longer cycle periods is associated with lower drug application rates whereas shorter cycle periods are associated with larger drug application rates.
Description
Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2001.
Includes bibliographical references (leaf 46).
Subjects
Urban Studies and Planning.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
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