This method (Method 5) is for fixed pool sizes and tests with uncertain sensitivity and specificity and produces asymptotic confidence intervals about the estimated prevalence. This method assumes that the true values of both sensitivity and specificity are not known exactly and have been estimated in a limited number of samples. The analysis allows for the additional uncertainty in the prevalence estimate associated with uncertainty about test performance, based on the sample sizes used to estimate sensitivity and specificity values. This method should be used if you are uncertain about the true values of sensitivity and specificity. If the true prevalence is likely to be close to zero, the lower confidence limit could be negative.

For this analysis, it was assumed that samples from 300 individual fruit bats were aggregated into 60 pools of 5 samples each, that 29 pools produced a positive test result and that the test sensitivity was 90% and specificity was 100%. An assumed sensitivity of less than 100% was used to demonstrate the possible effect of dilution on sensitivity of the pooled test. To allow for uncertainty about the true values of test sensitivity and specificity, it was assumed that sample sizes of 50 and 10,000, respectively, were used to estimate these values. Input values and results for this analysis are summarised in the table below.

Method 5 | ||
---|---|---|

Input values: | ||

Number of pools tested | 60 | |

Number of pools positive | 29 | |

Pool size | 5 | |

Sensitivity | 0.9 | |

Specificity | 1.0 | |

Sample size for sensitivity estimate | 50 | |

Sample size for specificity estimate | 10000 | |

Lower CL | 0.025 | |

Upper CL | 0.975 | |

Results: | ||

Estimated Prevalence | 0.1427 | |

2.5 percentile | 0.0876 | |

97.5 percentile | 0.1979 | |

Standard Error | 0.0282 |

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