Sampling techniques and surveillance

Sampling techniques and surveillance

Sampling: definition

«The process of selecting elements (sample units) from a population (animal species) in order to construct a subset (sample) to be used for making inferences about the population »

Sampling: objectives for animal health

• Estimation of an epidemiological parameter

• Disease detection and definition of herd status

• Investigation of the relationship between potential risk factors and disease

• Many other purposes

Sampling: reasons for sampling

• Population to large to collect information from all animals

• Main advantages: reduction of the investigation cost and to save time in obtaining. This with possibility to control systematic error (deviation from real prevalence, sampling size accuracy)

• Risk to produce different types of errors and to produce wrong data

Sampling population groups

Reference population

Target population

Study population

Study sample

Sampling frames and sampling units

Recent lists of:

Regions or localities to be sampled (sampling unit = region)

Herds to be sampled in a region (sampling unit = herd)

Individuals to be sampled within a herd (sampling unit = animal)

Probability sampling methods

• Simple random sampling

• Systematic random sampling

• Stratified random sampling

• Cluster sampling

Sample random sampling

Assumption

The obtained results from sample should be representative of the real situation in the whole population

Simple random sampling

Select three random numbers of cows between 1 and 10

Simple random sampling: fundamental conditions

Two conditions:

The individuals in population must have the same probability of being included in the sample

The selection of an individual should not affect the probability of selecting another (selections must be mutually exclusive

Stratified random sampling

Animals are stratified by breed and a random sample within each breed is taken

Non-probability sampling methods

Convenience sampling (most accessible samples)

Purposive sampling (most desired samples)

Hazard sampling (no special scheme or method)

“Non-probability sampling will produce biased population estimates, and the extent of

that bias cannot be quantified”

Simple random sampling: sample size calculation

Detecting disease or infected animals in herd (Qualitative approach, minimum sample size to be able to detect at least one infected/diseased cases if existing in the population with a given level of confidence, use statistical tables )

Estimation of prevalence (or sero prevalence) of a given disease (Quantitative approach, appropriate sample size to carry out the estimate, use appropriate formula)

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