Modeling and Study of Infectious Disease: Stochastic Modeling for Antibiotic Resistance and Treatment Strategies

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.