1.3 Sampling and validity

Why is it important to describe and identify these sampling parameters?

Here, we need to think about the ‘validity’ of sampling: how well a measurement represents the true situation. If you have already completed the Fundamentals of data for AMR module, you may recall that the concepts of external validity and internal validity were introduced. These concepts are defined in terms of the relationship between the study sample and the target population.

Described image
Figure 2 External and internal validity.

Epidemiological principles of sampling in animal populations are the same as the principles applied to sampling in human populations. In human health, it is similarly necessary to define the target population, the source population, the study sample and the sampling unit. In human health, individuals are the most common lowest-level sampling unit. Compared to human health, it is somewhat more common to choose a flock, herd or other group as the lowest-level sampling unit in animal health: this is because in a herd, all the animals are in the same physical area and exposed to identical risk factors. There are well-established AMR sampling protocols that use farms or slaughterhouses as the lowest level sampling unit.

Activity 3 has an example of this.

Activity 3: Extracting useful sampling information

Timing: Allow about 15 minutes

Read the following abstract from a study describing surveillance of AMR in poultry (Nguyen et al., 2015). Use the space below to identify the target population, source population, study sample and sampling unit.

Objectives: To describe the prevalence of AMR among commensal Escherichia coli isolates on household and small-scale chicken farms, common in southern Vietnam, and to investigate the association of AMR with farming practices and antimicrobial use (AMU).

Methods: We collected data on farming and AMU from 208 chicken farms. E. coli was isolated from boot swabs and cultured on selective media. E. coli isolates were tested for their susceptibility to 11 antimicrobials. Risk factor analyses were carried out at both the bacterial population and farm levels.

Results: E. coli resistant to gentamicin, ciprofloxacin and third-generation cephalosporins (3GCs) was detected on 201 (96.6%), 191 (91.8%) and 77 (37.0%) of the farms, respectively. Of the 895 E. coli isolates included in the analysis, resistance to gentamicin, ciprofloxacin and 3GCs was detected in 178 (19.9%), 291 (32.5%) and 29 (3.2%) of the isolates, respectively. Ciprofloxacin resistance was significantly associated with quinolone usage and tetracycline usage.

Conclusions: Household and small farms showed frequent AMU associated with a high prevalence of resistance to the most commonly used antimicrobials. Given the weak biocontainment, the high prevalence of resistant E. coli could represent a risk to the environment and to humans.

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Discussion

How did you find this exercise? Was there enough information available in the abstract to complete this activity?

The target population is household and small-scale chicken farms in Vietnam.

The source population is not described in this abstract. If you read the full study, it reports that the source population is three districts in the province of Tien Giang.

The study sample is 208 chicken farms.

The sampling unit is a single chicken farm. How do we know this? It is not clearly described in the abstract, but there’s an important clue in the description of the data collection method. ‘Boot swab samples’ were collected from farm workers, which represent the bacteria present on the entire farm. Similar to sediment sampling in fish, if certain types of bacteria are present in the environment in a farm, they are almost certainly present in the majority of the flock. If you are looking for prevalence of particular bacteria in a flock it is therefore often much more efficient to sample the environment (through the boot swab technique) rather than individual animals.

1.2 Sampling terminology

2 Sampling frames