Analyse cluster-testing data for 2-stage surveys for demonstrating disease freedom.
This analysis calculates the overall system sensitivity for the survey and the
resulting probability of population freedom from disease. It assumes that a random sample of clusters (or all clusters) has been selected for testing
from the population and that a random sample of units (or all units) has been
tested within each selected clusters. It also assumes that the test system has a specificity
of 100% (any positive results are further investigated to exclude false positives)
and that no positive results were recorded. The analysis adjusts for imperfect sensitivity
of the test used.
The analysis calculates both cluster and system (population) level sensitivity estimates using three
different methods depending on the available data:
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:
Paste cluster testing data in the space below. Data columns can be
in any order but must include a column for number tested (labeled "Tested"). Columns for cluster id,
and cluster size (labeled "ClusterSize") are optional. A header row specifying column
names must also be included.
Download example data
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with funding from a range of sources.It provides a range of epidemiological tools for the use of researchers and epidemiologists, particularly in animal health. Please send
any comments, questions or suggestions to Evan Sergeant
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