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New Mathematical Model may Help to Combat Hospital-acquired Infections
February 18, 2008 at 11:57 AM
General Health News
This model has suggested that antimicrobial cycling and patient isolation may be effective approaches when patients are harbouring dual-resistant bacteria.
In the time of superbugs such as methicillin-resistant Staphylococcus aureas (MRSA), and with increasing public awareness and concern over bacterial infections, this type of modelling, if used to develop policies and treatment protocols, may reduce dual drug-resistant infections in hospitals.
The research was presented by Castillo-Chavez, a mathematical epidemiologist in Arizona State Universitys College of Liberal Arts and Sciences, at the American Association for the Advancement of Science annual meeting. The research was an extension of an undergraduate honors thesis by Karen C. Chow, now a graduate student at ASU, in collaboration with his postdoctoral research associate Xiaohong Wang.
We deal primarily with the issue of finding ways of slowing down the growing levels of dual resistance to antimicrobials that are the result of their intense use in the treatment of nosocomial (hospital-acquired) infections. Model simulations were used to compare the effects of antimicrobial cycling, in which antibiotic classes are alternated over time, with mixing programs (random allocation of treatment drugs) in a setting where the goal is that of reducing the prevalence of dual resistance, said Castillo-Chavez.
He added: Resistance to multiple drugs cannot be ignored and cycling programs appear more useful in reducing dual resistance than the random mixing regime, he says. The early diagnosis and isolation of colonized patients with dual-resistant bacteria turns out to be quite effective at maintaining lower levels of dual resistance in hospitals.
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