2. Enter parameters Parameter Input value Notes Pooling Algorithm Sensitivity (PAS) The PAS depends on dilution effects in the master pool only, the length of the sensitivity window (w, which in turn depends on both the sensitivity/ lower limit of detection of the NAAT assay and the ELISA assay in use), and exponential rate of HIV viral load increase early in acute infection (R). Typically, PAS will be determined a priori and MAPS will be determined from PAS, by equation (ii) in Westreich et al. (not included in this calculator). PAS must be 0 < PAS <= 1 Maximum Acceptable Pooling Size (MAPS) Typically determined from PAS (see above, and equation (ii) in Westreich et al.) MAPS must be an integer greater than 1. NAAT assay specificity NAAT assay specificity is the probabilty an individual specimen is correctly categorized as negative when tested individually by NAAT. Specificity must be 0 < specificity <= 1. Prevalence of acute HIV (p) p, the prevalence of acute HIV among ELISA-negative individuals in the population being pooled. Prevalence must be 0 < p < 1. 3. Click this button to calculate optimally efficient master pool size, and efficiency and positive predictive value for that master pool size: 4. Results: Algorithm Optimal master pool size Efficiency* Positive predictive value* D2 D3 A2m * For a given algorithm/row, efficiency and positive predictive value are both calculated for the master pool size listed in column 2. Efficiency is measured in NAAT test kits per specimen; individual testing has an efficiency of 1; an efficiency < 1 is better than individual testing.
3. Click this button to calculate optimally efficient master pool size, and efficiency and positive predictive value for that master pool size:
4. Results: Algorithm Optimal master pool size Efficiency* Positive predictive value* D2 D3 A2m * For a given algorithm/row, efficiency and positive predictive value are both calculated for the master pool size listed in column 2. Efficiency is measured in NAAT test kits per specimen; individual testing has an efficiency of 1; an efficiency < 1 is better than individual testing.