1.3 AMR surveillance data

1.3.1 Types of AMR surveillance data and their uses

AMR surveillance can involve collecting various types of data. Table 1 shows the different types of data that can be obtained in animal production systems (previously introduced in the course Antimicrobial resistance in animals). The different types of data provide different information about how to address AMR and consequently have different uses.

Table 1 Types of AMR data in relation to the point of data collection, source and information uses.
Type of data Point of data collection Sources Information uses
Resistant bacteria and antimicrobial resistant genes (ARGs) data Farms Diseased animals Clinical samples: animal faeces, milk, fish, etc. Control animal diseases
Healthy animals Pooled samples of faeces, bulk milk, fish, pond water Understand transmission dynamics of AMR emergence, sources of AMR, trends, transmission
Feed mill Feed Investigate contamination of feed with bacteria, e.g. Salmonella spp.
Food chain, post-harvest: abattoir, markets, retail Products: meat carcasses and products, bulk milk, eggs, fish Understand dynamics of pathogenic and commensal AMR bacteria, transmission; risk to public health
Environment: manure tank, water sources, pond Water, soil, manure Understand dynamics of AMR transmission
AMU data Farm Records: AMU Assess AMU and understand its effect on AMR
AMC data Industry, customs Records of sales and imports data Proxy for AMU data
Antimicrobial residues data Farm Animal products, such as milk Compliance with withdrawal periods
Food chain Animal products: carcasses, milk, eggs, fish Compliance with export requirements
Environment Water, manure, sediment, soil Understand dynamics of AMR transmission

The types of data described in Table 1 are useful in themselves, but can also be combined to provide information that is more valuable. For example, data on the prevalence of resistant bacteria present on a farm could be analysed alongside AMU records to look at the impact of AMU on AMR. Another approach would be to compare data from different sample types, such as manure from poultry farms and pond water, and sediments from fish farms, to explore possible transmission of resistant bacteria.

1.2 Types of surveillance

1.3.2 Metrics of AMU