Dr Thomas Crellen's research focusses on determining risk factors for acquisition of drug resistant bacteria among neonates in a Cambodian hospital. The main organism in both carriage and blood stream infections is Klebsiella pneumoniae; they have sequenced over 300 isolates and aim to use the whole genome data to reconstruct transmission networks within the ward.
Multidrug resistant bacteria are a major problem in Southeast Asia, particularly for infections acquired in hospitals. Patients data and bacteria sequence allow the reconstruction of transmission networks. Using these date, we can also build simulations to investigate the impact of possible interventions, which then inform future clinical trials.
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.
I’m Tom Crellen, I’m a post-doctoral researcher here at the Mahidol Oxford Tropical Medicine Research Unit in Bangkok, working in the Bacterial Resistance Analysis Group which is led by Ben Cooper. The group in general focuses on the transmission of bacterial pathogens, mainly in hospital settings, and looks for interventions to combat the spread of resistant organisms. My research focuses on a carriage study of multidrug resistant bacteria from a children’s hospital in Cambodia. We aim to establish risk factors for the transmission and acquisition of pathogens, and also to model the impact of interventions to reduce the spread of antimicrobial resistance.
The work brings together epidemiological and genomic data, so that’s patient level data collected in the hospital by clinicians and sequence data of the bacteria itself. We aim to use this data to reconstruct transmission networks - who infected whom - and that can lead to questions like: what makes someone more likely to transmit a pathogen, or what makes someone likely to spread it on to multiple people, or do we see evidence of super spreading in these hospital settings for instance. We’ve observed this in major outbreaks, in viral pandemics such as Ebola andSARS (Severe Acute Respiratory Syndrome). We see this pattern but it’s not very well understood in hospital acquired infections whether it’s this pattern that’s driving transmission or not. Certainly an early observation is that patients that stay the longest are the most likely to both acquire infections and pass them on to other people. We also want to explore the effect of a probiotic which was used when children arrive at the hospital to reduce the risk of acquiring infections and we need to quantify exactly how effective that was.
Hospital acquired infections are a major problem, particularly in Southeast Asia where the prevalence of multidrug resistant bacteria is extremely high. In the carriage study that we’re working on, we observe that almost all children become infected with multidrug resistant bacteria during their stay. 60% of people arrive with multidrug resistant organisms and the rest are generally colonised during their stay. It’s very high prevalence and this leads to challenges in control and during clinical episodes it can be difficult to treat because it’s resistant to so many antibiotics. In this region, we face the challenge that people are generally wealthy enough to afford antibiotics but they may not be controlled by prescription, so this leads to very high rates of antibiotic usage which drives resistance in this area.
Being here in Bangkok we have access to a lot of study sites in this region, and these areas are hot spots for antimicrobial resistance in hospitals. It’s a major problem in this area but it’s also understudied and it’s challenging to get really good data from this region. Through the Oxford Tropical Network we have very strong links which aids us in both sample collection and getting good data for analysis. Using data from these studies, we can build simulations or models that allow us to investigate the impact of different interventions. If we can build simulations that effectively reconstruct the conditions of that hospital, we can investigate the impact of interventions in a very low cost way and this can then allow us to decide what we think will be the best interventions to use and that will inform future clinical trials. We relay our results back to the clinicians in the hospitals that carry out these studies, and they can make decisions based on our results and modify their clinical practice accordingly. Antimicrobial resistance is a global problem, and although Southeast Asia is a major hotspot it’s under-represented in terms of data and research. Our results are important in feeding into the global conversation and awareness about drug resistant bacteria globally.