Strategies for tackling drug-resistant bugs put to the test by maths models
To tackle antibiotic resistance, scientists should look at how strains of drug-resistant bugs compete with those susceptible to drugs, according to research from Imperial College London published in eLife.
The team used mathematical modelling to determine what strategies for the timing and dosage of antibiotics work best to prevent drug-resistant strains of bacteria emerging.
The study shows that in order to tackle the spread of bacteria that are resistant to antibiotics, scientists need to analyse how bugs that are drug-resistant are interacting with bacteria that are susceptible to drugs.
The traditional wisdom has been that infections should be treated aggressively with an early, high-dose blast of antibiotics. However some have argued that this strategy accelerates the emergence of resistant mutations and that a moderate strategy may be more effective at preventing the rise of resistance.
Dr Caroline Colijn from Imperial College London and Dr Ted Cohen from Yale University modelled the behaviour of drug-resistant and drug-susceptible bacteria under aggressive and moderate treatment regimes. They several scenarios, such as whether there were ample or scarce resources for the bacteria to use, the growth capabilities of each population, and what the immune response from the host would be.
They found that both treatment strategies could be effective, but that it depended on the ways in which the drug-resistant and susceptible bacteria were interacting with one another.
The researchers modelled conditions both within a host and a whole population of people and found the competition between strains of bacteria to have a similar effect at both levels. However, Dr Colijn says that there is one important difference: “Even when aggressive treatment is best for individuals, it can still drive up levels of resistance in whole populations over time.”
Taken from CRICKNews
Comment from Dr Matthew Buckland, Chair of the PID UK Medical Panel
‘Mathematical modelling is increasing useful in the healthcare sector, it is one tool in the understanding of how our therapies work. There are of course differences in specific infections and antibiotics. Some antibiotics work by their “peak dose” effect, i.e. the drug has to be at a high level but only for a short time to kill bacteria and others work by virtue of being at a good sustained level over time. Some of the differences described in this work may relate to the differences in specific therapies, but the strategy will be helpful in our understanding of resistance and recurrence of infection due to bacterial hibernation.’
Posted July 2016