To tackle antibiotic resistance, scientists should look at how
strains of drug-resistant bugs compete with those susceptible to
drugs.
That is the conclusion of researchers at Imperial College
London, who have used mathematical modelling to determine what
strategies for the timing and dosage of antibiotics work best to
prevent drug-resistant strains of bacteria emerging.
When an infection occurs in the body, it is usually treated with
antibiotics. However, some of the infecting bacteria may be
resistant to antibiotics and survive the treatment, going on to
proliferate and create more resistant bacteria.
There will also be bacteria present that are susceptible to
antibiotics and can be killed, but these sometimes acquire drug
resistance during the course of infection.
When infections are resistant to drugs, it is known as
antimicrobial resistance. The problem means that diseases that are
relatively minor today could soon become untreatable and fatal. It
is estimated that antimicrobial resistance is already causing an
extra 23,000 deaths per year in the United States, with projections
reaching up to 10 million deaths by 2050.
The new 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. They found that competition
between the two populations plays a key role in determining the
success of antibiotic treatment strategies.
The traditional wisdom has been that infections should be
treated 'aggressively' with an early, high-dose blast of
antibiotics. The idea is that this rapidly reduces the population
of drug-susceptible bacteria from which new, drug-resistant
bacteria could arise.
Recently, some groups have argued that this strategy creates a
greater pressure for the bacteria to change in order to survive -
known as 'selection pressure' - that accelerates the emergence of
resistant mutations from the susceptible bacteria population.
Instead, a moderate strategy may be more effective at preventing
the rise of resistance.
To test these two strategies, Dr Caroline Colijn from the
Department of Mathematics at Imperial College London and her
colleague Dr Ted Cohen from Yale University modelled the behaviour
of drug-resistant and drug-susceptible bacteria under aggressive
and moderate treatment regimes.
They modelled the dynamics under 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.
The researchers 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. For example, if the population of susceptible bacteria is
large and easily acquires resistance, an aggressive treatment
strategy can prevent resistance arising in the first place.
This is because the drug resistant population relies on
susceptible bacteria becoming resistant to strengthen their cause.
An aggressive treatment quickly wipes out susceptible bacteria,
preventing them from becoming resistant.
The team modelled conditions both within a host - one person
with an infection - and within a whole population of people. The
competition between strains of bacteria was found to have a similar
effect at both levels.
However, Dr Colijn says that there is one important difference
when looking at individual hosts and whole populations: "Even when
aggressive treatment is best for individuals, it can still drive up
levels of resistance in whole populations over time."
In other words, even if each individual patient is unlikely to
have resistant strains, once resistance does emerge, aggressive
treatments could pave the way for further spread by reducing the
competition resistant strains of bacteria face for hosts.
"In that situation, there may be a need to choose what is best
for the patient today versus what is best in the long-term for the
whole population," said Dr Colijn.
While it's not yet possible to determine what kind of
interaction is going on in an individual's body or in a population,
these could perhaps be determined in the future with better
observational techniques and better monitoring of the
population.
"These population questions are hard to study in the lab or in
trials as they take a long time to play out, and that's where
mathematical modelling comes in." said Dr Colijn.
"They have been studied for a long time in ecology, but now they
are incredibly important for clinical and public health."
The paper,How competition governs whether moderate or aggressive treatment
minimizes antibiotic resistance, is published ineLife.