Population (or cluster) sensitivity for varying unit sensitivity

Input Values

  

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

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

Outputs from the analysis include:

  • 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.
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.
Download example data


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