Podcast: Meet our Researchers

Ben Cooper

Mathematical Modelling

Professor Ben Cooper from MORU in Thailand uses mathematical modelling and statistical techniques to help understand the dynamics of infectious disease and evaluate potential control measures.
The major focus of this work is on antibiotic-resistant bacteria that cause common infections (e.g. urinary tract infections, pneumonia, bloodstream infections) in resource-limited hospital settings.

Modelling bacterial drug resistance

Antibiotic resistance is one of today's major global health problems. Mathematical models help us answer what if questions and evaluate the impact of specific interventions such as hands hygiene on the spread of bacterial drug resistance. Effective solutions are then translated into policy changes or changes in practice at national or international level.

Translational Medicine

From Bench to Bedside

Ultimately, medical research must translate into improved treatments for patients. At the Nuffield Department of Medicine, our researchers collaborate to develop better health care, improved quality of life, and enhanced preventative measures for all patients. Our findings in the laboratory are translated into changes in clinical practice, from bench to bedside.

Ben Cooper: Modelling bacterial drug resistance

Ben Cooper: Drug resistance in bacteria is one of the major global health problems that we’re facing now. Increasingly, bacteria that cause serious infections are becoming resistant to the antibiotics that we use. And this is particularly a problem in South East and South Asia, particularly in lower and middle income countries. In some cases we are already seeing infections which can’t be treated with the antibiotics available in those countries. The risk is that resistance will continue to spread more and more and that we’ll see more commonly infections which we don’t have antibiotics to treat them with.

The great thing when you have a mathematical model is that you can start to ask what if questions: What if we increase hands hygiene by  20%? What impact would that have on how the bacterial infections spread? How many infections will the patients get? As we get better and more reliable mathematical models - so we need to fit these models to data - we can increasingly ask what would be the impact of changing the way we use antibiotics on how much resistance we see.

We recently published a paper that analysed data from all the highest quality hands hygiene intervention studies and found good evidence that this intervention can significantly improve hands hygiene, and that appears to be associated with reductions in infections with certain drug-resistant bacteria. We have also used mathematical models to show how increases in hands hygiene can be associated with substantial reductions in certain resistant infections, and recently how this can be a very cost effective intervention. This kind of work feeds into policy decisions made by governments to invest in hands hygiene campaigns. That has happened already in previous work in Europe and we’re hoping it’s going to happen increasingly in lower and middle income countries.

Similarly, I have done some work on pandemic influenza, and using mathematical models to look at how movement restrictions – whether shutting down airports, stopping people traveling – would impact on the spread of pandemic flu. And we found, surprisingly, that it would have very little impact. And that also fed into international recommendations on how to respond to a pandemic.

Q: What important lines of research have emerged in the past few years?

BC: One of the biggest changes in the last few years is the emergence of very cheap sequencing technology. It used to be incredibly expensive and hugely time consuming to look at the DNA sequence of a particular bacteria. It costs now about $100 to get the whole genome sequence of a bacteria. This means we can get very detailed information on the DNA of a bacteria, which we can use as a kind of bar code, and we can use that bar code to identify how these bacteria are spreading between patients. This has potentially a huge impact on how we can understand how bacteria are spreading between individuals.

Q: Why does your research matter?

BC: The research into antibiotic resistance bacteria matters because antibiotics are incredibly useful. They have had a major impact on human health since they were introduced. The threat of antibiotic resistance risks putting us back into the pre-antibiotic era. We’re already seeing that in some cases when patients have infections  antibiotics  are not available to treat them. The risk is that this can happen more and more. So we really need to find strategies to combat the spread of resistance.

Q: What is the impact of your research on patients? How does it fit into translational medicine within the Department?

BC: The first aspect of our work is to understand what is going on, how bacteria are spreading. The second aspect is to find what interventions work to stop this resistance spreading and to improve patient outcomes. The third aspect, when we have found effective solutions, is to try and translate them into changes in policy or changes in practice at a national or international level.

One aspect of our work that I think helps a lot is when we combine analyses with cost effectiveness, because we can show not only if a certain intervention works and is likely to improve patient outcomes, we also show it is worth governments investing in- it is actually something they should be doing.