5 - 固定池大小的汇总流行率和具有已知灵敏度和特异性的测试

These methods use frequentist approaches to estimate prevalence and confidence limits, assuming a fixed pool size and a test with known values for sensitivity and specificity, as described below.

方法3

这种方法（方法4来自Cowling等人。（1999年） assumes a fixed pool size and that test sensitivity and specificity are known exactly (no uncertainty about their values). Confidence limits are based on a normal approximation and may be <0 for low prevalence values.

流行率估计为:

和标准误差（SE（p））:

哪里:

• p =患病率;
• k =池大小;
• m =测试的池数;
• x =正池的数量;
• Se =测试的灵敏度;和
• Sp =测试的特异性;

使用正态近似计算渐近置信限:

哪里 是对应于所需置信限的标准化正态变量.

此方法所需的输入是:

• 游泳池大小;
• 测试的池数;
• 池数正面;
• 假定测试的敏感性;
• 假设测试的特异性;和
• 期望的上限和下限置信度.

Pool size, number of pools and number of pools positive must be positive integers and the number of positive pools must be less than the number of pools tested. Sensitivity and specificity must be >0 and <=1 and upper and lower confidence limits must be >0 and <1.

产出包括:

• 估计动物水平的流行率;
• 上下渐近置信限;
• 估计的标准误差;和
• 所有可能结果的估计和置信度的图形和文本文件（通过单击相应的图标下载）.

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.

方法4

这种方法（方法5来自Cowling等人。（1999年）) 假设一个固定的池大小，并且确切地知道测试的灵敏度和特异性（没有关于它们的值的不确定性）。 确切的置信限度基于二项式理论，因此置信限度永远不会<0或> 1.

流行率和方差估计如下方法3:

和:

哪里:

• p =患病率;
• k =池大小;
• m =测试的池数;
• x =正池的数量;
• Se =测试的灵敏度;和
• Sp =测试的特异性.

Exact confidence limits are estimated by calculating the corresponding binomial confidence limits for the proportion of positive pools and then transforming these back to individual-level prevalence values using the equation for estimating prevalence from 方法3.

此方法所需的输入是:

• 游泳池大小;
• 测试的池数;
• 池数正面;
• 假定测试的敏感性.
• 假设测试的特异性;和
• 期望的上限和下限置信度.

Pool size, number of pools and number of pools positive must be positive integers and the number of positive pools must be less than the number of pools tested. Sensitivity and specificity must be >0 and <=1 and upper and lower confidence limits must be >0 and <1.

产出包括:

• 估计动物水平的流行率;
• 上下精确（二项式）置信限;
• 估计的标准误差;和
• 所有可能结果的估计和置信度的图形和文本文件（通过单击相应的图标下载）.

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.