2025-26 Project (Knight & Moore & Waterlow)

Antimicrobial resistance: what happens with age and by sex?

SUPERVISORY TEAM

Supervisor

Dr Gwen Knight at LSHTM
Email: gwen.knight@lshtm.ac.uk

Co-Supervisor

Dr Catrin Moore at City St George’s
Email: camoore@sgul.ac.uk

Co-Supervisor

Dr Naomi Waterlow at LSHTM
Email: Naomi.Waterlow1@lshtm.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 and by sex.   

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, sex

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; microbiology

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, meeting – at the minimum – the institutional research degree regulations and expectations. 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). Other travel expectations and opportunities highlighted by the supervisory team are noted below.

Primary location for duration of this research degree: LSHTM, London

Travel requirements for this project: We would expect the student to work between Keppel Street (LSHTM) and CSG with other members of the Knight Group based across both institutions.

Eligibility/Requirements

Particular prior educational requirements for a student undertaking this project

  • Minimum LSHTM institutional eligibility criteria for doctoral study.
  • Quantitative background (some statistical /  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, open access data and reports ignore 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 and that differ by sex. 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 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  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 in SGUL could be done and the (co-culture transfer of resistant work) with S. aureus are relatively cheap. 

Further reading

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

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-Moore-Waterlow recording

MRC LID LINKS

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