Simple risk-based surveillance - calculation of minimum detectable prevalence
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;
- The population proportion: this is the proportion of animals from the entire population that are in the high-risk group; and
- The surveillance proportion: this is the proportion of animals from the surveillance that are in the high-risk group.
In addition, the following parameters are required:
- The individual animal test sensitivity: this is the sensitivity of the test performed on individual animals;
- The required surveillance sensitivity: this is the target value for population sensitivity (confidence of detection) for the given sample size and test sensitivity; and
- The number of animals tested: this is the total number of animals processed by the surveillance system.
The results indicate the mimimun detectable prevalence, or in other words, the design prevalence that would be required for the surveillance system to achieve the specified target population sensitivity.