Risk-based surveillance

Simple risk-based surveillance - calculation of surveillance sensitivity

Relative risk

Population proportion in high risk group

Design prevalence

Test sensitivity

Number of high-risk units sampled

Number of low-risk units sampled

Prior confidence of freedom

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This page calculates the surveillance sensitivity for simple risk-based surveillance, for instance, a survey in which a high risk population is targeted.

This analysis assumes that there is no clustering of disease (for instance, we are working at the herd level), and that the effective specificity of the surveillance system is equal to one (all positives are followed up to ensure that they are not false positives):

One risk factor is considered, for which the following information is required:

• The relative risk: this measures the risk of animals being infected in the high-risk group, relative to the risk of animals being infected in the low-risk group. For risk-based surveillance, this should be greater than 1. If analysing biased surveillance (for instance abattoir testing), the animals tested may have lower probability of being infected than the rest of the population; and
• The population proportion: this is the proportion of animals from the entire population that are in the high-risk group.

In addition, the following parameters are required:

• The design prevalence: this is the assumed prevalence of disease, if the disease is present in the population. It is used as a standard by which the sensitivity of the surveillance can be evaluated;
• The individual animal test sensitivity: this is the sensitivity of the test performed on individual animals;
• The number of animals tested in each of the high and low risk groups; and;
• The prior confidence of freedom before the surveillance was undertaken. This is combined with system sensitivity to calculate posterior confidence of freedom.

The results include:

• The sensitivity of the surveillance system, or in other words, the probability that the surveillance system would detect at least one infected animal if disease was present at the specified design prevalence;
• The level of confidence that the population is free of disease (at the design prevalence);
• For comparison, the sensitivity of the system and confidence of freedom if representative sampling were used are also shown, along with the sensitivity ratio. This indicates how much more sensitivity the risk-based approach achieves, relative to a representative approach; and
• The effective probability of infection (EPI) for both high and low risk groups.