13 - 模拟固定池大小的采样并以不确定的灵敏度和特异性进行测试
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 uncertain test sensitivity and specificity (using Method 5) for
each iteration and calculates the mean prevalence and estimated bias across all iterations. It assumes fixed pool sizes and
that the true values of both sensitivity and specificity are not known exactly and have been estimated in a limited number of
samples. Values for the true sensitivity and specificity that are different to the assumed values 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 Queensland were tested
individually, with 22 positive results (H. Field, pers com). The sensitivity and specificity of the test were assumed to be
0.9 (90%) and 1 (100%) for prevalence estimation, and the true values were assumed to be the same as the assumed values for
prevalence estimation. 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, pooling strategies and results
are summarised in the tables below.
输入 |
值 |
方法 |
不确定的测试Se和Sp |
假定患病率 |
0.14 |
假設靈敏度 |
0.9 |
假設的特異性 |
1 |
灵敏度的样本大小 |
50 |
特异性的样本量 |
10000 |
真正的灵敏度 |
0.9 |
真正的特异性 |
1 |
置信度 |
0.95 |
策略数量 |
6 |
迭代次数 |
1000 |
战略 |
泳池大小 |
池数 |
1 |
2 |
102 |
2 |
3 |
76 |
3 |
4 |
65 |
4 |
5 |
59 |
5 |
10 |
67 |
6 |
15 |
238 |
战略 |
平均患病率 |
最低患病率 |
最大患病率 |
平均偏见 |
平均CI宽度 |
平均标准误差 |
均方误差 |
偏置/AP |
偏置/TP |
偏置/MSE |
比例有效 |
1 |
0.13979 |
0.06765 |
0.2416 |
-0.00021 |
0.10931 |
0.02789 |
0.00079 |
-0.00149 |
-0.00149 |
6e-05 |
0.956 |
2 |
0.14149 |
0.06785 |
0.25397 |
0.00149 |
0.11044 |
0.02817 |
0.00081 |
0.01054 |
0.01065 |
0.00276 |
0.954 |
3 |
0.14229 |
0.05578 |
0.24016 |
0.00229 |
0.11073 |
0.02825 |
0.00082 |
0.01613 |
0.01639 |
0.00644 |
0.961 |
4 |
0.14266 |
0.07427 |
0.26878 |
0.00266 |
0.11168 |
0.02849 |
0.00084 |
0.01861 |
0.01896 |
0.00841 |
0.958 |
5 |
0.14404 |
0.07286 |
0.27866 |
0.00404 |
0.11897 |
0.03035 |
0.00103 |
0.02805 |
0.02886 |
0.01584 |
0.978 |
6 |
0.14229 |
0.10554 |
0.37192 |
0.00229 |
0.12771 |
0.03258 |
0.00642 |
0.01606 |
0.01632 |
0.00081 |
0.998 |
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