Objective  To evaluate the impact of swab pooling strategy on the work efficiency, determine the optimum swab pooling size, and provide scientific reference for improving the technical specification of swab pooling detection.

Methods  The principle of binomial distribution, group detection technology, and Python language programming were used to analyze the change rules of sampling workload, the detection workload, and the weighted comprehensive workload of swab pooling detection under different levels of population infection rates with different swab pooling sizes, and to analyze the application conditions and work efficiency of 5 in 1, 10 in 1, and 20 in 1 swab pooling detection.

Results  The higher the population infection rate is, the smaller the optimum swab pooling size is, and the larger the minimum weighted comprehensive workload growth rate (MWCWGR) is (the smaller the absolute value of the negative numbers is), which means that the improvement in work efficiency is less. The larger the weight ratio (K) of the unit workload of sampling to detection is, the larger the optimum swab pooling size is, and the smaller the MWCWGR is (the larger of the absolute value of the negative number is), indicating a greater improvement in work efficiency. When the population infection rate exceeds 6% and the K value is less than 1/2, MWCWGR is a positive number. In this case, the swab pooling detection will increase workload and reduce work efficiency, and should not be used. When the K values are 1/4, 1/3, 1/2, 1, 2, 3, and 4, the 5 in 1, 10 in 1, and 20 in 1 swab pooling detection are most suitable for populations with infection rates between 7‰ to 4%, 2‰ to 9‰, and 5/10 000 to 2‰, respectively. The corresponding MWCWGR ranges from -11.10% to -45.87%, -16.02% to -64.28%, and -18.00% to -72.08%, respectively. As the K value increases, the population infection rates suitable for 5 in 1, 10 in 1, and 20 in 1 swab pooling detection gradually increase, and the magnitude of the weighted comprehensive workload reduction gradually increases separately.

Conclusion  When using swab pooling detection technology, it is necessary to correctly select the optimum swab pooling size based on the population infection rate and the unit workload weight of sampling to detection, in order to maximize the work efficiency. When formulating the technical specification for the swab pooling detection, it is necessary to specify the application conditions for the optimum swab pooling size.

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