TABLE 2.
Recommended approach to pooling algorithm selectiona
| Factor(s) | Area(s) affected |
|---|---|
| Laboratory setting | |
| Training, quality assurance, quality control | Feasibility of pooling for NAAT |
| Availability of robotics | MAPS; acceptable algorithm complexity |
| No. of personnel | Possible frequency of NAAT runs (turnaround time) |
| Economic resources (assay budget, per assay cost) | Minimal acceptable efficiency (maximum allowable test usage) |
| Available assay sensitivity | MAPS; algorithm performance (efficiency, PPV) |
| Available assay specificity | Algorithm performance |
| End-user requirements | |
| Required turnaround time | MAPS; maximum no. of pooling stages |
| Required accuracy for NAAT screen | Minimum acceptable PAS; minimum acceptable positive predictive value |
| Testing population | |
| Anticipated throughput (rate of specimen arrival) | MAPS |
| No. of AHI anticipated; AHI prevalence | Algorithm performance |
a
Summary of important factors to be discussed in the planning process. Most of the factors listed serve to limit the available range of strategies a program can consider. Information on the characteristics of the NAAT assay to be utilized and anticipated AHI prevalence can then be used to find relevant estimates of performance for remaining candidate algorithms from Table 1 and Tables S1, S2, and S3 in the supplemental material. The ultimate algorithm choice will reflect a balance of program needs and capacity.