1-Stage Freedom analysis

Population (or cluster) sensitivity for varying unit sensitivity

Design prevalence

Population size (if known)

Prior confidence of freedom

Paste testing data in the space below. Two columns are required, the first is Unit ID and the second is Sensitivity (test or cluster) for that unit. A header row specifying column names must also be included.
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This utility calculates cluster (herd) or population-level sensitivity when individual unit sensitivity varies. It is useful for example when different units are tested with tests with different sensitivities for some reason, or when cluster-sensitivity varies among clusters when calculating overall population-level sensitivity.

If the population size is not specified the binomial method is used, otherwise the hypergeometric approximation is used.

Inputs are:

• Design prevalence, as either a proportion or as an integer number of units/clusters;
• Population size, if known (Note: Population size MUST be specified if design prevalence is an integer);
• Prior confidence of freedom; and;
• 2 columns of data, including a header row. The first column is an identifier for each unit tested and the second is the sensitivity (test or cluster) for that unit

Outputs are:

• Cluster or population-level sensitivity for the given data; and
• Confidence of freedom of the cluster or population from disease (at the specified design prevalence).