2026-27 Project (Knight & Edun & Lindsay)

Antimicrobial resistance: what happens with age and by sex?

SUPERVISORY TEAM

Supervisor

Professor Gwen Knight at LSHTM
Faculty of Epidemiology & Population Health. Department of Infectious Disease Epidemiology and Dynamics
Email: gwen.knight@lshtm.ac.uk

Co-Supervisor

Dr Lanre Edun at LSHTM
Faculty of Epidemiology & Population Health, Department of Infectious Disease Epidemiology and Dynamics
Email: lanre.edun@lshtm.ac.uk

Co-Supervisor

Professor Jodi Lindsay at Royal Veterinary College
Department of Comparative Biomedical Sciences
Email: jlindsay@rvc.ac.uk

PROJECT SUMMARY

Project Summary

Antimicrobial resistance (AMR) is a growing global problem for people of all ages, that requires innovative, cross-disciplinary solutions. However, most AMR research and data presentation ignores variation by age and sex, presenting instead “resistance to drug X in bacteria Y in country Z”. This is despite the huge changes in infection risk, comorbidities, antibiotic and healthcare exposure that happen over the life course. In this project, we will use data analysis paired with mathematical modelling to explore the dynamics of resistance gene accumulation and shuffling. Pairing microbiology data with clinical patterns, we will ask what mechanisms and rates would allow us to explain the patterns we see by age and sex in resistance combinations and hence optimise intervention design.

Project Key Words

Antimicrobial resistance, ageing, mathematical modelling, MRSA

MRC LID Themes

  1. Global Health
  2. Health Data Science
  3. Infectious Disease
  4. Translational and Implementation Research

Skills

MRC Core Skills

  1. Quantitative skills
  2. Interdisciplinary skills

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

  • Awareness of antimicrobial resistance evolution complexity;
  • analytical skills;
  • mathematical modelling;
  • statistical data analysis

Routes

Which route/s are available with this project?

  • 1+4 = Yes
  • +4 = Yes

Possible Master’s programme options identified by supervisory team for 1+4 applicants:

  • LSHTM – MSc Demography & Health
  • LSHTM – MSc Epidemiology
  • LSHTM – MSc Health Data Science

Full-time/Part-time Study

Is this project available for full-time study? Yes
Is this project available for part-time study? Yes

Location & Travel

Students funded through MRC LID are expected to work on site at their primary institution. At a minimum, all students must meet the institutional research degree regulations and expectations about onsite working and under this scheme they may be expected to work onsite (in-person) more frequently. Students may also be required to travel for conferences (up to 3 over the duration of the studentship), and for any required training for research degree study and training. Other travel expectations and opportunities highlighted by the supervisory team are noted below.

Day-to-day work (primary location) for the duration of this research degree project will be at: LSHTM – Bloomsbury, London

Travel requirements for this project: LSHTM / RVC site visits. Potentially collaborative visits to ECDC.

 Eligibility/Requirements

Particular prior educational requirements for a student undertaking this project

  • Minimum standard institutional eligibility criteria for doctoral study at LSHTM
  • Quantitative background (some mathematical training with ideally some experience in use of R)

Other useful information

  • Potential Industrial CASE (iCASE) conversion? = No

PROJECT IN MORE DETAIL

Scientific description of this research project

Antimicrobial resistance (AMR) is a leading cause of morbidity and mortality across the life course of humans. However, most AMR research and data presentation ignores variation by age and sex, presenting national or syndrome based resistant prevalence indices. This is despite the huge changes in infection risk, comorbidities, antibiotic and healthcare exposure that happen over the life course. Our work at a population level shows the stark importance of including age in the analysis of AMR dynamics, with different trends of proportion resistant by bacteria-antibiotic combination.   

This project will be nested within an MRC CDA fellowship that has begun to address these patterns. One initial hypothesis was that resistance would increase with age – we have not found this for many single bacteria-antibiotic combinations. This PhD would test whether there is an accumulation affect with age: those bacteria that cause infections in older individuals that are resistant are resistant to more antibiotics than those in younger individuals.  

Our previous research has also explored rates of resistance gene movement in a key AMR bacteria (Staphylococcus aureus)- pairing this rapid shuffling with the age patterns is a key knowledge gap for AMR.   

The objectives of this project will be to:

  • Quantify the variation in number and type of antibiotic combinations as a patient ages and by sex, to statistically test for age and antibiotic trends
  • Determine the transmission and evolution rates of resistant gene movement that explain multilevel  data (microbiology and ecological patterns)
  • Develop tools to support clinicians to account for age in empiric prescribing decision making and model potential impact on infection burden

The techniques to be used will be:

  • Data analysis and regression techniques
  • Mathematical transmission dynamic modelling to account for potential mechanisms driving the patterns by age and sex
  • Evolutionary mathematical models to explore resistance gene transfer building on laboratory work in S. aureus to account for ecological patterns seen.
  • Clinically co-designed software development

Resources:

  • EARS-NET isolate database with antibiograms, age and sex (3.5million isolates) across Europe for  bloodstream infections
  • Several active hospital collaborations will provide patient level information linked to isolate resistance profiles
  • Mathematical modelling training and support, and computing cluster within the Centre for Mathematical Modelling of Infectious Diseases (CMMID) at LSHTM
  • Ongoing research on MRSA resistance movement and hence data on rates

Potential risks :

  • We have access to the EARS-NET data for the main fellowship but have had to anonymise countries for publication. The risk would be that patterns we find in resistant accumulation can be explained by country-level factors that we may find  difficult to publish. However, we can work with the ECDC to explore publishing options.
  • Existing laboratory data may not provide exactly the data and hence parameters required for this  project. Whilst no laboratory work is proposed in this project, there is the possibility that placement in collaborative labs could be done and the experiments (co-culture transfer of resistant work) with S. aureus are relatively cheap.
  • New supervisory team and hence rhythms of working have not been established. However, GK  and LE work on GK’s fellowship on this topic and have a history of successful collaboration. GK and JL have been long term colleagues. All work in London so in-person meetings and discussion will support PhD supervision.

Further reading

Relevant preprints and/or open access articles:
(DOI = Digital Object Identifier)

Other pre-application materials: None

Additional information from the supervisory team

The supervisory team has provided a recording for prospective applicants who are interested in their project. This recording should be watched before any discussions begin with the supervisory team.

Knight & Edun & Lindsay Recording

MRC LID LINKS

To apply for a studentship: MRC LID How to Apply
Full list of available projects: MRC LID Projects
For more information about the DTP: MRC LID About Us

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