This method assumes a fixed pool size but unknown (or uncertain) test sensitivity
and specificity. Uncertainty associated with the point estimates of test sensitivity and specificity
is incorporated through the inclusion of additional variance associated with the sample size used to
determine the values used for these parameters. The smaller the sample size, the greater the uncertainty
about the true values for sensitivity and/or specificity and hence the greater the uncertainty about the
resulting prevalence estimate. Asymptotic confidence
limits are based on a normal approximation and may be <0 for low prevalence values. See
the User Guide or
Cowling et al. (1999) (Method 6) for more details. See demonstration analysis
Required inputs for these methods are pool size, number of pools tested, number of pools
positive, test sensitivity and specificity and desired upper and lower confidence limits for
the estimate. The sample size used for estimating test sensitivity and specificity must also be entered.
Pool size, number of pools, number of pools positive and sample sizes for sensitivity and specificity
estimates must all be positive integers and the number of positive pools must be less than the number
of pools tested. Sensitivity, specificity and upper and lower confidence limits must be between zero
Outputs for these methods are a point estimate, upper and lower confidence limits
(asymptotic) and the standard error for the estimated prevalence as specified. A graph and
text file listing of estimates and confidence limits for all possible results are also
created for downloading if desired, by clicking on the appropriate icon.
Estimates are only valid if the proportion of positive pools is greater than the false positive
rate (1 - Specificity) and less than or equal to the true positive rate (Sensitivity). Invalid
results are indicated by NA in the results table.