A mathematical model of nosocomial infection and antibiotic resistance: evaluating the efficacy of antimicrobial cycling programs and patient isolation on dual resistance

Hospital-acquired infections caused by antibiotic-resistant bacteria pose a significant threat to public health. Antimicrobial cycling, in which antibiotic classes are alternated over time, has previously been suggested as a strategy for curbing the development of resistance in hospitals. A mixing protocol is a program in which, when given two drug options, half of the physicians will randomly prescribe one drug, and the other half will randomly prescribe the other drug, serving as a reasonable comparison to cycling. A mathematical model of antimicrobial cycling in a hospital setting is developed in order to analyze the efficacy of such a program, with an emphasis on the emergence and significance of dual resistance. Our model also considers the effects of isolating patients harboring dual-resistant bacteria in the hospital. Simulation results compare the effects over time of antimicrobial cycling programs with mixing programs and their ability to reduce antimicrobial resistance. Results show that the optimal antimicrobial drug usage program within a hospital depends upon the type of resistance being treated; a cycling program should be used to curb dual resistance, but if the priority is to first help patients suffering from single-resistant bacterial infections, then a mixing protocol would be best.