Pooled Prevalence Calculator – Demonstration analyses
Simulate sampling for fixed pool size and assumed perfect test
This program simulates sampling and prevalence estimation for a specified (design) prevalence value and level of confidence. The program runs multiple iterations of sampling, pooling and testing from an infinite population with the specified prevalence, estimates true prevalence assuming a prefect test (using Method 2) for each iteration and calculates the mean prevalence and estimated bias across all iterations. It assumes fixed pool sizes and a test with 100% sensitivity and specificity. Values for the true sensitivity and specificity that are different to the assumed values of 100% can also be entered if desired, to check the importance of the assumption of a perfect test
For this analysis, six alternative pooling strategies were
evaluated for the estimation of prevalence in a population with an assumed true
prevalence of 0.14 (14%). Pool sizes and numbers of pools were previously estimated
to provide 95% confidence of estimating a true prevalence of 0.14 with a
precision of 0.055 (see sample size examples). This is equivalent to the
observed prevalence and precision when 162 samples from little red flying foxes
in
Input 
Value 
Method 
Fixed pool size and known Se &
Sp 
0.14 

1 

1 

1 

1 

0.95 

6 

1000 
Strategy 
Pool size 
Number of pools 
1 
2 
83 
2 
3 
60 
3 
4 
49 
4 
5 
42 
5 
10 
33 
6 
20 
46 
Strategy 

1 
0.14101 
0.06862 
0.23165 
0.00101 
0.11593 
0.02794 
0.00079 
0.00719 
0.00724 
0.0013 
0.968 
2 
0.14017 
0.06528 
0.22434 
0.00017 
0.1161 
0.02787 
0.00079 
0.00124 
0.00124 
4e05 
0.96 
3 
0.14037 
0.06782 
0.25617 
0.00037 
0.11666 
0.02789 
0.00079 
0.0026 
0.00261 
0.00017 
0.967 
4 
0.14123 
0.06508 
0.23506 
0.00123 
0.11878 
0.02826 
0.00081 
0.00872 
0.0088 
0.00187 
0.965 
5 
0.14534 
0.06983 
1 
0.00534 
0.12772 
0.02923 
0.00092 
0.03671 
0.03811 
0.03097 
0.972 
6 
0.23773 
0.08374 
1 
0.09773 
0.22332 
0.02911 
0.01046 
0.41109 
0.69804 
0.91322 
0.974 