News
Mathematical modelling offers new strategies for fighting hospital
infections
7 March 2008
A mathematical model that looks at different strategies for curbing
hospital-acquired infections suggests that antimicrobial cycling and
patient isolation may be effective approaches when patients are
harbouring dual-resistant bacteria.
The model was developed by a team led by Carlos Castillo-Chavez, an
Arizona State University (ASU) Professor and presented at the American
Association for the Advancement of Science annual meeting. It technique
could give new strategies for fighting 'superbugs', such as methicillin-resistant
Staphylococcus aureas (MRSA) and Clostridium dificile (C
dif).
“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,” says Castillo-Chavez, a mathematical epidemiologist in
ASU’s College of Liberal Arts and Sciences.
“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,”
Castillo-Chavez says.
“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.”
He said, “This seems to be the first time that models are used to
deal with the evaluation of two distinct methods of reducing the impact
of dual resistance in hospitals. Models that focus on reducing the
prevalence of pathogens resistant to two types of drugs, excluding the
possibility of dual resistance, have been studied in the past. Models
were used to show that random allocation treatment regimes might be
better than cycling.
“Here, we show that cycling may be useful when dealing with dual
resistance, the most worrisome hospital situation,” he says.
“Our theoretical work shows that cycling is better if the goal is to
reduce dual antimicrobial resistance. We explore the impact of isolating
individuals who have developed dual resistance and found out that
isolation, in fact, dramatically reduces the persistence of dual
resistance. However, we never win the battle against antimicrobial
resistance through the exclusive use of integrated microbial management
approaches that focus entirely on the prescription of antibiotics,” he
says.
“Focusing on reducing dual resistance results in increases in the
levels of individuals experiencing single resistance. In other words, at
the end of the day, drugs provide no silver bullet and only policies
that reward their judicious use have a shot at slowing down what appears
to be a losing battle,” he says.
“If we insist on the exclusive use of antimicrobials to fight
nosocomial infections, then it is only a matter of time before we begin
to run out of effective antibiotics.”
The next step, according to Castillo-Chavez, is to connect these
models more explicitly to specific studies, and to collaborate with
others who are treating patients in hospitals.
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