Linear regression analysis revealed that N1, N2, and E were all highly correlated, with N1 and N2 showing similar concentrations that were somewhat higher than concentrations of E (Figure 1). In total, of 1,451 samples were analyzed, of which 431 (30%) samples were removed from analysis because none of the three markers tested were positive for SARS-CoV-2. Of the remaining 1,020 samples, N1 and N2 had comparable ability to detect SARS-CoV-2, which was nearly always better than the ability of E (Table 1). Individually, N1 or N2 was able to account for 85% of the SARS-CoV-2 detections without the use of another marker (Table 1). When duplexed together, these markers (N1 and N2) had the highest ability to detect SARS-CoV-2 compared to the other possible duplex combinations (Table 1), accounting for 98% of the SARS-CoV-2-positive samples.
Close modal
Table 1
Frequency of positive samples as well as the percent of samples under the minimum detection limit (MDL) at each sample location
| Location (n) | N1 | N2 | E | N1 or N2 | N1 or E | N2 or E | < MDL (n = 431) |
|---|---|---|---|---|---|---|---|
| A (435) | 92% (89–95) | 85% (81–88) | 73% (68–77) | 98% (96–99) | 96% (94–98) | 90% (87–93) | 14% |
| B (546) | 79% (74–83) | 87% (82–90) | 57% (52–63) | 98% (95–99) | 83% (78–87) | 92% (88–94) | 45% |
| C (4) | 100% (43–100) | 100% (43–100) | 100% (43–100) | 100% (43–100) | 100% (43–100) | 100% (43–100) | 50% |
| D (237) | 75% (68–81) | 77% (70–83) | 47% (39–55) | 94% (89–97) | 79% (72–85) | 83% (77–88) | 32% |
| E (48) | 98% (88–100) | 91% (79–97) | 87% (74–94) | 98% (88–100) | 100% (91–101) | 96% (85–100) | 4% |
| F (181) | 85% (78–90) | 89% (82–93) | 67% (59–74) | 99% (95–100) | 91% (85–95) | 93% (87–96) | 22% |
| Total (1,451) | 85% (83–88) | 85% (83–88) | 64% (62–67) | 98% (97–99) | 90% (88–91) | 91% (89–93) | 29% |
| Location (n) | N1 | N2 | E | N1 or N2 | N1 or E | N2 or E | < MDL (n = 431) |
|---|---|---|---|---|---|---|---|
| A (435) | 92% (89–95) | 85% (81–88) | 73% (68–77) | 98% (96–99) | 96% (94–98) | 90% (87–93) | 14% |
| B (546) | 79% (74–83) | 87% (82–90) | 57% (52–63) | 98% (95–99) | 83% (78–87) | 92% (88–94) | 45% |
| C (4) | 100% (43–100) | 100% (43–100) | 100% (43–100) | 100% (43–100) | 100% (43–100) | 100% (43–100) | 50% |
| D (237) | 75% (68–81) | 77% (70–83) | 47% (39–55) | 94% (89–97) | 79% (72–85) | 83% (77–88) | 32% |
| E (48) | 98% (88–100) | 91% (79–97) | 87% (74–94) | 98% (88–100) | 100% (91–101) | 96% (85–100) | 4% |
| F (181) | 85% (78–90) | 89% (82–93) | 67% (59–74) | 99% (95–100) | 91% (85–95) | 93% (87–96) | 22% |
| Total (1,451) | 85% (83–88) | 85% (83–88) | 64% (62–67) | 98% (97–99) | 90% (88–91) | 91% (89–93) | 29% |
95% confidence intervals are shown in parentheses.
Figure 1
General trends of virus expression for all combinations of markers tested, fitted with a linear regression model. The plots represent all three pair-wise relationships, with the left plot involving N2 and N1, the center plot E and N1, and the right plot E and N2.
Figure 1
General trends of virus expression for all combinations of markers tested, fitted with a linear regression model. The plots represent all three pair-wise relationships, with the left plot involving N2 and N1, the center plot E and N1, and the right plot E and N2.