Table 6. Predictive values and over-treatment ratio for each algorithm, at three different prevalence levels.

Accuracy indicator	Infection prevalence (%)†	Republic of Congo‡	Kiri, Southern Sudan (old algorithm) with QBC (with CTC¶)	Kiri, Southern Sudan (new algorithm‡) with QBC (with CTC¶)	Adjumani, Uganda	Arua-Yumbe, Uganda
Baseline scenario
Positive predictive value (%)	0.1	9.3	48.4 (48.4)	100.0 (100.0)	47.2	47.3
	1.0	50.8	90.5 (90.5)	100.0 (100.0)	90.0	90.0
	10.0	91.9	99.1 (99.1)	100.0 (100.0)	99.0	99.0
Negative predictive value (%)	0.1	100.0	100.0 (100.0)	100.0 (100.0)	100.0	100.0
	1.0	99.9	99.9 (99.9)	99.7 (99.6)	99.9	99.9
	10.0	99.1	99.3 (99.3)	96.4 (96.1)	98.8	98.9
Ratio of false to true cases treated	0.1	9.8	1.1 (1.1)	0.0 (0.0)	1.1	1.1
	1.0	1.0	0.1 (0.1)	0.0 (0.0)	0.1	0.1
	10.0	0.1	0.01 (0.01)	0.0 (0.0)	0.01	0.01
Worst-case scenario
Positive predictive value (%)	0.1	3.7	16.9 (16.7)	37.2 (36.9)	20.0	20.2
	1.0	28.1	67.2 (66.9)	85.7 (85.5)	71.6	71.8
	10.0	81.1	95.8 (95.7)	98.5 (98.5)	96.5	96.6
Negative predictive value (%)	0.1	100.0	100.0 (100.0)	100.0 (100.0)	100.0	100.0
	1.0	99.9	99.8 (99.8)	99.6 (99.6)	99.8	99.8
	10.0	98.4	98.0 (97.8)	95.7 (95.6)	97.3	97.4
Ratio of false to true cases treated	0.1	25.8	4.9 (5.0)	1.7 (1.7)	4.0	4.0
	1.0	2.6	0.5 (0.5)	0.2 (0.2)	0.4	0.4
	10.0	0.2	0.04 (0.05)	0.02 (0.02)	0.04	0.04

†: Assumed stage 1 to stage 2 ratio of two. Note that a ratio of 0.5 would result in almost identical estimates (data not shown), since the differences in sensitivity between stage 1 and 2 are small and have limited influence on the PPV and NPV calculations given the low prevalence of HAT true positives.

‡: Assuming sensitivity and specificity without suspect follow-up, as done in practice.

¶: CTC values in parentheses.