Best antibacterial treatment strategies

A mathematical model has been used to explore different approaches to minimising antibiotic resistance.
12 November 2015

Interview with 

Caroline Colijn, Imperial College London


The UK's chief medical officer Dame Sally Davies has ranked the threat posed by antibiotic resistance as on par with terrorism. A number of strategies have been put forward to combat the problem, but one area being debated is whether to hit bugs really hard in one fell swoop, or to take a more gentle approach. Now a mathematical model developed by Imperial College scientist Caroline Colijn suggests that both strategies have their place, but you need to use them under the right circumstances, as she explained to Graihagh Jackson...

Caroline - So it's long been thought that hard and fast approach to treating with strong antibiotics will be best at preventing the emergence of drug resistance within individuals, and there's also an opposing or competing view to that that of course when you treat very strongly, you also very efficiently select for any resistant organisms that might be present initially or that might arise during that treatment.  So there have been two recent bodies of literature, one arguing for a hit hard and fast, treat really strongly with a strong dose of antibiotics, and the other arguing for a more moderate approach to using the least possible amount of antibiotics that will cure the infection.

Graihagh - And your paper is looking at these two strategies and seeing which is best within a mathematical model.  How did you go about that?

Caroline - So we used two models.  We used a model for the bacterial infection inside one individual and we studied how two strains, a resistant strain and a sensitive strain might interact and how that might play out under different strengths of treatment. Then we did the same thing at a community level where you imagine a drug sensitive strain and a drug resistance strain circulating amongst individuals and we look at whether really strong treatment or more moderate treatment, which one of those will drive more increases in resistance.

Graihagh - What did your model show?

Caroline - So we found that both of these two opposing views can really be right under very sensible assumptions in models.  So it can be the case that it's really best to do the hard and fast treatment, but it can equally well be the case that it's really best, in terms of minimising resistance to take a more moderate approach to how much treatment to give.  We found that the key factor that determines which of those is right, is how effectively the two strains are actually competing with each other.

Graihagh -   Competing, what do you mean?

Caroline - So, two strains would be competing if suppressing one of them paves the way for, provides additional resources for, or in some way helps the other one.  If the strains are just spreading independently and they are not related to each other in terms of how many you have of one and how many you have of other, then that's a very different scenario in terms of whether treatment drives resistance than if the two strains are depending on the same resources and are really in strong, active competition with each other.

Graihagh -   So competition is the key thing here?

Caroline - That's right.  We found that when the resistant strain was a fit and strong competitor to the sensitive strain, in order to minimise resistance, it's best to do a more moderate approach to treatment.  Whereas when that resistant strain can be assumed not to be a very fit competitor either because it just doesn't grow very well or because it faces a really strong immune system that's really effective at suppressing it, then the more aggressive approach is great because it more rapidly supresses the sensitive bugs and they are most of the problem and they don't have a fit competitor.

Graihagh - This is all in a mathematical model, so I wonder what the limitations of this might be.  Is this something that you have seen within the real world in vivo?

Caroline - Well I think we have certainly seen rising resistance at population levels, so you can track the emergence of resistance with a short leg behind the introduction of new antibiotics.  So we know that using antibiotics is driving resistance on long terms at the population level and those are regimes where it's actually very hard to empirically experiment.  So I think there's a real role for mathematical models to play in uncovering fundamental mechanisms and looking at what's important in driving these effects in a way that maybe help us to guide empirical studies to understand these interactions.

Graihagh -   I suppose in an ideal world you would be able to test this sort of competition within individuals to determine what sort of treatment might be best, but I suppose that's not something that's already on the cards just yet?

Caroline -   Right, I think it would be really important to get much better understanding of the kinds of strain diversities that we have in human infections in lots of different pathogens and also not just a picture of that diversity as a single snapshot, but to really develop an understanding of how strains are interacting within hosts and also in communities of individuals, and I think there are some real challenges to that.  I think there is a growing awareness that resistant strains are increasing in fitness and we need to start thinking about these possible competitive interactions between resistant and sensitive strains.


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