
Calculate herd sensitivity (SeH) and herd specificity (SpH) for a specified
test sensitivity, test specificity, cutpoint number of reactors and design
prevalence for a list of herd sizes and corresponding sample sizes.
A metasimulation is also run, using the calculated SeH and SpH for each
herd size, to calculate the number of herds required to be tested to achieve a
specfied target system sensitivity (SSe). SSe achieved and the number of animals to be
tested from a specified number of herds selected at random from the population
are also calculated.
Inputs include:
 Test sensitivity and specificity;
 Animallevel and herdlevel design prevalence values;
 Desired cutpoint number of reactors to declare a herd positive;
 Target number of herds to be tested from population;
 Target system sensitivity (SSe) for population testing scheme;
 Number of iterations per simulation and number of simulations for
metasimulation of population testing;
 The desired precision of results (number of digits to be displayed after the decimal point); and
 Pasted data comprising columns for herd size and corresponding sample size and
counts or relative frequency of each herd size in the population. Include a row
of column headings in the data.
Note: Large numbers of metasimulations generally provide only minimal
additional benefit and may result in a system crash if used in combination with large
numbers of iterations. A maximum of 100 metasimulations is usually ample.
Results are calculated using the HerdPlus method (Greiner 2006?) and include:
 Table of SeH and SpH values for each specified herd and sample size;
 Plot of SeH and SpH values against herd size.
 Summary table of metasimulation results including median and 5th/95th
percentiles of the numbers of herds required to achieve the target SSe and the
achieved SSe and number of animals tested under the optimised scheme for the specified
number of herds tested; and
 Detailed results of metasimulations.
Acknowledgement:Developed by Matthias Greiner and Evan Sergeant
