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Contact details: 

Clare Chandler (clare.chandler@lshtm.ac.uk). Co-director of the Antimicrobial Resistance Centre, London School of Hygiene and Tropical Medicine, UK.

Background 

            Antimicrobial use (AMU) has been identified as a key driver of antimicrobial resistance (AMR). However, measuring AMU across different settings is a major challenge given the variety of antibiotics in use, the variety of sources and supply chains for antibiotics, the large size of informal markets and the difficulty of knowing what is prescribed and what is finally used by an individual, and for how long. Even more challenging is how we might meaningfully measure and compare antibiotic use across the human and livestock domains, and in terms of environmental residues. 

       Surveillance about antimicrobial usage in human and animal health sectors is at the core of the World Health Organisation (WHO) Global Action Plan and the World Animal Health Organisation (OIE) plan. Typically, antibiotic surveillance aims to collate national sales figures expressed per human or livestock population as a starting point, although this is currently highly incomplete, especially in most low-income and middle-income countries (LMICs). However, there is even less data available on antibiotic use at the granular level, i.e. on provision by individual provider type and use by individual patients or livestock keepers. Interventions aimed at reducing risk are often aimed at this level; maximising effectiveness will require addressing this gap in rigorous and representative granular data.

Workshop overview

       This workshop aimed to facilitate inter-sectoral and interdisciplinary discussions by bringing together a unique combination of researchers, policy makers and funders from both the human and livestock health sectors, with interest and expertise in antibiotic resistance and the linkages with antibiotic use. The specific objectives of the workshop were1:

  1. Review the methods and metrics for collecting granular data on antibiotic use in LMICs
  2. Identify key data needs for policy making
  3. Identify challenges involved in collecting robust and comparable data both within and across the human and livestock domains, and
  4. Discuss the next steps in developing methods and metrics for widespread, One Health use in LMICs.

       Initially, a literature review about available tools to collect information about AMU was conducted to identify any potential gaps in literature. Subsequently, an intersectoral workshop organised by the London School of Hygiene and Tropical Medicine and supported by the Improving Human Health flagship project of the CGIAR research program on Agriculture for Nutrition and Health (A4NH) was held over two-days (21st and 22nd November 2017). Presentations and roundtables were carried out to motivate discussions.

 

Lessons learned

Several topics emerged from discussions to be considered when developing metrics and techniques for measuring AMU.

  1. The selection of metrics and measurement approaches will depend on the objectives to be met. For example, to understand drivers of antimicrobial resistance and to propose interventions to evaluate AMR, it is necessary to collect information at a granular level disaggregating the volume of antibiotics in use by different provider types, different patient/animal cases, and across different sectors and locations. While ideally such data would be collected using a One Health approach, the methodological challenges of this were recognised.
  2. The heterogeneity of antimicrobial supply systems and products across countries and sectors need to be taken into consideration during data collection and planning.
  3. Solely quantitative metrics are undesirable when gathering data about AMU, with qualitative methods highly valued for both informing the design of quantitative data collection, and interpreting its results. Additionally, insights from experts in policy implementation and research are highly valuable in the data collection processes. Furthermore, a progressive or staged approach that displays a range of data collection options would allow countries to select which is more applicable and pertinent considering the resources available.
  4. Sampling strategies may differ depending on the purpose of the sampling, and the level and supply system to be measured. A One-health approach will likely require more than one sampling strategy.
  5. Volume metrics, especially relative antibiotic volumes by different sectors, areas, providers and case mix, were seen as valuable. An appropriate metric to measure volume is important to collect comparable and scalable information. This metric should be based on the total population at risk. Measuring milligrams of antibiotic per weight (considering 70 kg adult human and the population correction unit for livestock biomass) was proposed to be a promising metric that might be piloted for use across human and livestock populations. 
  6. Volume data collection tools require further development. As well as needing to be relevant for given contexts – case mix, species mix, supply systems – data collection needs to consider the reliability of data sources where different incentives, regulations and levels of black-market activity are prevalent. Volume data should be interpreted alongside actual use at the patient and farmer level. Lessons can be drawn from the malaria world about strategies to measure volumes using a total market approach (i.e. including all types of provider).

 

Next steps

       The workshop confirmed the methodological challenges of assessing antimicrobial use across the human, animal and environmental domains. Although the interest in this topic has increased through the years, data at the granular level are still scarce in LMICs. If such data are to be generated, further work is required to develop generalisable but meaningful protocols for measurement both for human and animal use, and the potential for combining efforts across sectors requires further consideration and piloting. Such data should support the tripartite group formed by WHO, OIE and FAO in their efforts to collate antibiotic use data. The group recommended the following priorities moving forward: 

  1. Creation of a sharing platform and a community of practice, 
  2. Establishment of a working group to develop a progressive pathway for antibiotic use surveillance for countries to position themselves within, 
  3. Increased dialogue between AMR modellers and AMU experts to improve the applicability of use data for analysing the drivers of resistance, and 
  4. Development of small pilot case studies across several different countries and regional sites”1.

 

Research Impact

     The success of interventions to regulate AMU relies on having good, well planned and reliable metrics to assess them. By reviewing metrics to measure antibiotic use at granular and national/state levels, researchers engaged in this project aimed to contribute to the development of methods for objectively and comparatively assessing antibiotic use, highlighting the different challenges faced in the human, animal and environmental domains, and accounting for all potential factors (illegal markets, types of medicines, etc.) that can affect these figures.

 

Researchers

Kevin Queenan5,1, Clare Chandler1, Catherine Goodman1.

 

Institutions involved

  1. Antimicrobial Resistance Centre, London School of Hygiene and Tropical Medicine, UK 
  2. International Livestock Research Institute (ILRI).
  3. Food and Agriculture Organization for the United Nations (FAO).
  4. World Health Organization (WHO).
  5. Royal Veterinary College of London, UK.

 

Research Subject Area(s)

     Human health, Public health, Antimicrobial Use (AMU), Antimicrobial Resistance (AMR)

 

Funding

       This study was funded by the CGIAR Research Program on Agriculture for Nutrition and Health Program (A4NH).

 

More information

  1. Queenan, K., Chandler, C.I.R., and Goodman, C. 2017. Meeting report: Metrics and methods for assessing antibiotic use at the granular level in humans and livestock in LMICs. Available online at: https://amr.lshtm.ac.uk/wp-content/uploads/sites/12/2018/06/LSHTM-ABU-Metrics-and-Methods-Review-Nov17.pdf
  2. AMR-LSHTM. Metrics and Methods for Assessing Antibiotic Use: Roundtable Events, Seminars |21 November 2017. Available online at: https://amr.lshtm.ac.uk/2018/01/08/metrics-methods-assessing-antibiotic/
  3. Queenan, K., Chandler, C.I.R., and Goodman, C. 2017. A review of methods and metrics for studying human and livestock antibiotic use at the granular level. A Pre-read for Roundtable discussion in London, 21&22nd November 2017. Available online at: https://amr.lshtm.ac.uk/wp-content/uploads/sites/12/2018/06/LSHTM-ABU-Metrics-and-Methods-Review-Nov17.pdf

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