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What factors drive antimicrobial resistance in the UK vs Japan? - NU/LSHTM project

Supervisors

LSHTM

Nagasaki University

Project

The risk of antimicrobial resistance (AMR) across many bacteria and antibiotic combinations varies across by age and sex, as do other factors such as antibiotic usage, contact patterns, healthcare utilisation and the immune system. Understanding how AMR and the potential influencing factors vary by age and sex and between countries such as between the UK and Japan can give us further power to understand the drivers for the development of drug-resistant infections. In particular, it can help to determine who is most at risk of drug-resistant infections leading to improved patient care. 

This PhD aims to work towards understanding these questions, with the potential to work on a diverse range of data available both in the UK and Japan. Key methods will be the use of statistical and mathematical models, as well as epidemiology. The following focus areas could be considered:

National level

  • How does the level of AMR vary by age and sex across Japan? How does this compare to the UK?
  • What are the comparative age and sex trends of antibiotic usage in Japan and UK?
  • What is the relationship between antimicrobial consumption and the prevalence of antibiotic resistance and does this relationship vary between the UK and Japan? 

Hospital level (working with reference hospitals in Japan and the UK)

  • Does antibiotic usage in hospital increase a patient’s risk of a subsequent resistant infection?
  • What other factors predict the development of drug-resistant Infections (DRI)?
  • Using longitudinal samples from the same patient, can we untangle whether transmission of or selection for resistance is the dominant pathway to DRI? 

Working across different hospitals will give further power to answer these questions.

The PhD will initially involve exploring a range of bacteria and antibiotic combinations to map the AMR landscape. Detailed investigations will then focus on one or two specific bacteria-antibiotic combinations based on the epidemiology or clinical problem and data availability. 

Datasources that could be used include: 

Japan

  • Nationwide claims databases including the National Database of Health Insurance Claims and Specific Health Checkups (NDB), NDB Open Data and JMDC Claims Database.
  • Japan Surveillance for Infection Prevention and Healthcare Epidemiology (J-SIPHE), a national surveillance database system for AMR measures.
  • Infection and resistance data from Nagasaki University.

UK

  • Prescriptions of antibiotics from General Practices in England from 2015, made available by NHS Business service authority.
  • AMR indicator data that is produced by the UK Health Security Agency (UKHSA) and published through the “Fingertips” service. Blood stream infection and resistance rates, linked to within-hospital prescription data from a local London Hospital.

Relevant references: 

  • Waterlow NR, Cooper BS, Robotham JV, Knight GM (2024) Antimicrobial resistance prevalence in bloodstream infection in 29 European countries by age and sex: An observational study. PLoS Med 21(3): e1004301. https://doi.org/10.1371/journal.pmed.1004301
  • Antibiotic prescribing patterns by age and sex in England: why we need to take this variation into account to evaluate antibiotic stewardship and AMR selection. Naomi R Waterlow, Tom Ashfield, Gwenan M Knight. medRxiv 2024.09.10.24313389; doi: https://doi.org/10.1101/2024.09.10.24313389 
  • Leclerc Q, Clements A, Dunn H, Hatcher J, Lindsay JA, Grandjean L, Knight GM. Quantifying patient- and hospital-level antimicrobial resistance dynamics in Staphylococcus aureus from routinely collected data. J Med Microbiol. 2023 Jul;72(7). doi: 10.1099/jmm.0.001724. PMID: 37431889.
  • Tsuzuki S, Koizumi R, Matsunaga N, Ohmagari N. Decline in Antimicrobial Consumption and Stagnation in Reducing Disease Burden due to Antimicrobial Resistance in Japan. Infect Dis Ther. 2023 Jul;12(7):1823-1834. doi: 10.1007/s40121-023-00829-7.
  • Aliabadi S, Anyanwu P, Beech E, Jauneikaite E, Wilson P, Hope R, Majeed A, Muller-Pebody B, Costelloe C. Effect of antibiotic stewardship interventions in primary care on antimicrobial resistance of Escherichia coli bacteraemia in England (2013-18): a quasi-experimental, ecological, data linkage study. Lancet Inf Dis 2021 Dec;21(12):1689-1700. doi: 10.1016/S1473-3099(21)00069-4. 

The role of LSHTM and NU in this collaborative project

The student will meet with the supervisory team on a regular basis over videoconference. When working with data from specific hospitals (in the UK or designated reference hospitals in Japan) the student will need to reside in the relevant country, in order to access data and work with local teams to ensure appropriate understanding of the data.

Particular prior educational requirements for a student undertaking this project

The student should either have:

  • a clinical/biological background with strong quantitative skills and the desire to develop their skills in statistics, modelling and programming,   

OR 

  • A strong mathematical/statistical background with a proven interest and knowledge of clinical settings or epidemiology.

In addition the student should have strong motivation to work in both countries with keen interest in comparing antibiotic prescribing practices and a desire to learn a range of mathematical and statistical techniques.

Skills we expect a student to develop/acquire whilst pursuing this project

  • Statistical inference
  • Statistical modelling
  • Advanced epidemiology
  • Dynamic modelling
  • Clinical practices of infectious diseases (if the candidate is medically qualified).