Table 1.

Results for number of false positive misclassifications, PPV, and cost per FP identified for alternative scenarios and testing strategies

	10% prevalence			1% prevalence			Malawi 2017a
	Status Quo	With A0	A0, 5% A1 error	Status Quo	With A0	A0, 5% A1 error	Status Quo	With A0	A0, 5% A1 error
Testing Strategy	Two‐test			Three‐test			Two‐test
Algorithm specificity	99.57%			99.91%			99.96%
Verification testing cost	$5			$7			$5
False positive misclassifications per 10,000 HIV negative persons tested
No verificationb	43.2	0.86	2.98	9.3	0.19	0.64	4.18	0.08	2.10
With verificationc	0.64	0.01	0.04	0.03	0.001	0.002	0.04	0.001	0.02
PPV
No verificationb	95.86%	99.91%	99.70%	90.69%	99.80%	99.30%	98.90%	99.98%	99.44%
With verificationc	99.94%	>99.99%	>99.99%	99.97%	>99.99%	>99.99%	99.99%	>99.99%	99.99%
Cost per FP identifiedd	$123	$5,880	$1,708	$75	$3,428	$999	$460	$22,743	$909

FP, false‐positive; PPV, positive predictive value. ^aPrevalence among HIV testing clients was 4% in Malawi in 2017. HIV prevalence among all adults was approximately 10%. ^b“No verification” corresponds to strategy in Figure 1A under “status quo” scenario and Figure 1D for “with A0” scenarios. ^c“With verification” corresponds to Figure 1B under “status quo” scenario’ and Figure 1C under “with A0” scenarios.^dCost per FP identified through verification testing compared to no verification testing. Cost is calculated as the expected number of verification tests conducted (sens × prev + (1 − spec) × (1 − prev)) times the cost per verification test divided by the number of FP cases identified through verification testing.