Estimation of the Relative Sensitivity of qPCR Analysis Using Pooled Samples

Abstract

The high sensitivity of qPCR makes it a desirable diagnostic method in epidemiological surveillance programs. However, due to high costs, the use of pooling has been suggested. In this paper, an algorithm based on the Montecarlo method has been designed and implemented. The algorithm had been tested in many different situations, and finally it was validated with a real dataset. Moreover, based on the results obtained and depending on pooling conditions, a drastic decrease of sensitivity is observed.

Simulation of pooled-sample analysis strategies for COVID-19 mass testing

“…Computer simulations are common tools for the assessment of the cost-effectiveness of PCR pooled samples screening [23,24,25,26]. Owing to the wide range of uncertain parameters in the current COVID-19 pandemic, we applied Monte Carlo simulation techniques to enable the comparison of the effect of the two mass testing strategies on the required number of tests [27,28].…”

To pool or not to pool? Guidelines for pooling samples for use in surveillance testing of infectious diseases in aquatic animals

“…In 2013, Hall et al described an ED50 method (‘the number of infected individuals corresponding to a 50% chance of a pool testing positive’) for calculating PSe and PSp for ISAV; but in 2014, they described limitations with this approach and introduced a potential statistical approach (see their Figure ) for reliability of PSe and PSp using simulated data for SAV and discuss limitations with this approach as well. A recent study by Muniesa et al () used a Monte Carlo‐based algorithm and simulated data for porcine respiratory and reproductive syndrome virus to estimate relative sensitivity of qPCR when using pools versus individuals for qPCR analysis and demonstrated the strong effect of both analyte concentration and prevalence on the relative PSe with different pool sizes (pools of 2, 3, 5 or 10). In low prevalence situations, larger pool sizes will decrease the concentration of the target analyte, sometimes resulting in substantial decreases in the relative sensitivity of qPCR when using pools, particularly at low microbe concentrations (Muniesa et al, ).…”

“…A recent study by Muniesa et al () used a Monte Carlo‐based algorithm and simulated data for porcine respiratory and reproductive syndrome virus to estimate relative sensitivity of qPCR when using pools versus individuals for qPCR analysis and demonstrated the strong effect of both analyte concentration and prevalence on the relative PSe with different pool sizes (pools of 2, 3, 5 or 10). In low prevalence situations, larger pool sizes will decrease the concentration of the target analyte, sometimes resulting in substantial decreases in the relative sensitivity of qPCR when using pools, particularly at low microbe concentrations (Muniesa et al, ). They reported that ‘ the theoretical probability of including at least 1 infected individual in a pool…is increased when the pool size…is bigger and the prevalence is higher’ .…”

“…In 2013, Hall et al described an ED50 method ('the number of infected individuals corresponding to a 50% chance of a pool testing positive') for calculating PSe and PSp for ISAV; but in 2014, they described limitations with this approach and introduced a potential statistical approach (see their with different pool sizes (pools of 2, 3, 5 or 10). In low prevalence situations, larger pool sizes will decrease the concentration of the target analyte, sometimes resulting in substantial decreases in the relative sensitivity of qPCR when using pools, particularly at low microbe concentrations (Muniesa et al, 2014). They reported that 'the theoretical probability of including at least 1 infected individual in a pool…is increased when the pool size…is bigger and the prevalence is higher'.…”

Limited evidence for white spot syndrome virus susceptibility associated with expression of PmVRP15 in local population of giant tiger shrimp (Penaeus monodon)

“…However, since the inferences of this study are needed for estimation in population, we assume that pooled sampling of hemocytes would be more representative to compare baseline expression and inducible expression within population. Number of individuals in pooling strategy should be examined carefully to consider population characteristics in expressing genes (Muniesa et al, 2014;Peng et al, 2003;Taylor et al, 2010).…”