Risk-based surveillance

Simple 2-stage risk-based surveillance - calculation of surveillance sensitivity

Relative risk

Population proportion in high risk group

Herd-level design prevalence

Animal-level design prevalence

Test sensitivity

High-risk herds tested

Low-risk herds tested

Animals tested per herd

Prior confidence of freedom

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This page calculates the surveillance sensitivity for simple risk-based surveillance with 2-stage sampling, for instance, a survey in which high risk herds are preferentially targeted for testing, but with representative sampling of animals within selected herds.

This analysis assumes 2-stage sampling to account for clustering of disease (for example at the herd, flock or village level), that all herds have the same number of animals tested 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 herds in the high-risk group being infected, relative to the risk of herds in the low-risk group being infected. For risk-based surveillance, this should usually be greater than 1;
• The population proportion: this is the proportion of herds from the entire population that are in the high-risk group; and
• The numbers of high and low risk herds sampled. This is required to calculate the benefit achieved from targeting high-risk herds.

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. Values must be entered for both herd and animal-level design prevalence;
• The individual animal test sensitivity: this is the sensitivity of the test performed on individual animals;
• The number of herds tested: this is the total number of herds processed by the surveillance system;
• The number of animals tested in each herd: this assumes that the same number of animals is tested in every herd; and
• The prior confidence of freedom, to allow calculation of posterior confidence of freedom after completion of the surveillance.

Outputs 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;
• For comparison, the sensitivity of the system if representative sampling were used;
• The sensitivity ratio (ratio of sensitivities for risk-based and representative sampling). This indicates how much more sensitivity the risk-based approach achieves, relative to a representative approach;
• Posterior confidence of freedom achieved for both risk-based and representative sampling;
• The herd-sensitivity achieved in tested herds; and
• The effective probability of infection (EPI) for high-risk herds. EPI values approaching 100% suggest that, based on the values used for relative risk, population proportions and design prevalence, close to 100% of herds (or animals) in the high-risk group are expected to be infected. If this is unreasonable you may need to review the input values. Values over 100% mean that the model is invalid and processing will be stopped, with an error message. Input values must be changed to ensure EPI values are appropriate.