Calculate the sample size required to achieve a desired level of confidence of population freedom.
Can be applied at the cluster (herd/flock) level
or population level. If applied at the cluster level, sensitivity and design prevalence are unit (animal) level values, whereas if applied
at the population level, sensitivity and design prevalence are cluster level values.
Inputs are:
 the unit or cluster level sensitivity for the sampling;
 prior confidence of freedom (from previous analyses or opinion);
 probability of introduction of disease during the surveillance period;
 the required level of confidence of freedom after the additional surveillance;
 population size (optional); and
 the design prevalence as either a proportion or an integer number of units/clusters.
Enter test sensitivity if the target is a cluster level freedom or clustersensitivity
if the target is a system or population level freedom. If population size is entered the hypergeometric approximation
is used, otherwise the calculation is based on the binomial distribution.
The main outputs are:
 the adjusted prior confidence of freedom (taking into account the probability of introduction
while the surveillance is being undertaken);
 the target cluster or system sensitivity required to achieve the required confidence
of freedom; and
 the sample size required to achieve the target cluster or system sensitivity and resulting confidence of freedom.
A sample size of "n>N" indicates that it is not possible to achieve the desired level of
confidence by testing the entire population. This most commonly occurs with low design prevalence
and poor unit sensitivity of the test in a finite population.
