Calculate least-cost sample sizes for 2-stage surveys for demonstrating disease freedom. This analysis calculates the number of clusters and the number of units within each cluster to be tested to provide a specified system sensitivity (probability of detecting disease) for the given unit and cluster-level design prevalences and test sensitivity. Calculations are based on actual cluster sizes provided (for the entire population) and a list of randomly selected clusters, along with the number of units to sample for each selected cluster is included in the outputs. Test specificity is assumed to be 100% (or follow-up testing of any positive will be undertaken to confirm or exclude disease).
Sample sizes are optimised to minimise overall cost for given cluster and unit-level testing costs. A maximum sample size per cluster can be specified, if desired and calculations can be specified to ensure either a fixed sample size per cluster or a fixed (minimum) cluster sensitivity.
Sample sizes are calculated using the hypergeometric probability approximation (assuming sampling without replacement).
Design prevalence (specified level of disease to be detected) must be specified at both unit and cluster levels. Design prevalence can be specified as either:
Inputs required include:
Outputs from the analysis include:
If it is not possible to achieve the desired system sensitivity by testing all (or the specified maximum number of) units in all of the clusters, a message will be returned, along with a summary of the achieved mean SeH and SSe if all units were tested. In this case a list of all clusters, and the SeH achieved if all or the maximum number of units were tested.