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

Combining serology with case-detection, to allow the easing of restrictions against SARS-CoV-2: a modelling-based study in India

India's lockdown and subsequent restrictions against SARS-CoV-2, if lifted without any other mitigations in place, could risk a second wave of infection. A test-and-isolate strategy, using PCR diagnostic tests, could help to minimise the impact of this second wave. Meanwhile, population-level serological surveillance can provide valuable insights into the level of immunity in the population. Using a mathematical model, consistent with an Indian megacity, we examined how seroprevalence data could guide a test-and-isolate strategy, for fully lifting restrictions. For example, if seroprevalence is 20% of the population, we show that a testing strategy needs to identify symptomatic cases within 5-8 days of symptom onset, in order to prevent a resurgent wave from overwhelming hospital capacity in the city. This estimate is robust to uncertainty in the effectiveness of the lockdown, as well as in immune protection against reinfection. To set these results in their economic context, we estimate that the weekly cost of such a PCR-based testing programme would be less than 2.1% of the weekly economic loss due to the lockdown. Our results illustrate how PCR-based testing and serological surveillance can be combined to design evidence-based policies, for lifting lockdowns in Indian cities and elsewhere.

A discussion on implementing pooling detection tests of novel coronavirus (SARS-CoV-2) for a large population

A pooled sample analysis strategy for novel coronavirus (severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)) is proposed for a large population in this paper. The population to be tested is divided into divisions based on earlier observed detection rate of SARS-CoV-2 first. Samples collected are then grouped in appropriate pooled size. The number of tests per person in that population is expressed as a function of two variables: the observed detection rate and the pooled size or number of samples grouped. The minimum number of tests per person can be further shown to be a function of only one of these two variables, because these two parameters are found to be related at this minimum. A management scheme on grouping the samples is proposed in order to reduce the number of tests, to save time, which is of utmost importance in fighting an epidemic. The proposed testing scheme will be useful for supporting the government in making decisions to handle regular routine detection tests for identifying asymptomatic patients and implementing health code system in large population of millions of citizens. Another important point is to use smaller number of test kits, allowing more resources to speed up the mass screening tests, particularly in places not so rich.

Optimizing the diagnostic capacity for COVID-19 PCR testing for low resource and high demand settings: The development of information-dependent pooling protocol

Aim

To compare different pooling methods in an attempt to improve the COVID-19 PCR diagnostic capacities.

Method

We developed a novel information-dependent pooling protocol (indept), based on transmission of less informative sequential pools on to the next pooling cycle to maximize savings. We then compared it to the halving, generalized halving, splitting and hypercube protocols in a simulation study, across variety of scenarios.

Results

All five methods yielded various amount of test savings, which mostly depended on the virus prevalence in the population. In situations of low prevalence (up to 5%), indept had the best performance, requiring on average 20% of tests needed for singular testing across scenarios that were analyzed. Nevertheless, this comes at the expense of speed, with the worst-case scenario of indept protocol requiring up to twice the time needed to test the same number of samples in comparison to the hypercube protocol. In order to offset this, we developed a faster version of the protocol (indeptSp), which minimizes the number of terminal pools and manages to retain savings compared to other protocols, despite marginally longer processing times.

Conclusion

The increasing demand for more testing globally can benefit from application of pooling, especially in resource-restrained situations of the low- and middle-income countries or situations of high testing demand. Singular testing in situations of low prevalence should be systematically discouraged.

Local polynomial regression for pooled response data

We propose local polynomial estimators for the conditional mean of a continuous response when only pooled response data are collected under different pooling designs. Asymptotic properties of these estimators are investigated and compared. Extensive simulation studies are carried out to compare finite sample performance of the proposed estimators under various model settings and pooling strategies. We apply the proposed local polynomial regression methods to two real-life applications to illustrate practical implementation and performance of the estimators for the mean function.

Pooled testing for COVID-19 diagnosis by real-time RT-PCR: A multi-site comparative evaluation of 5- & 10-sample pooling

BACKGROUND & OBJECTIVES

Public health and diagnostic laboratories are facing huge sample loads for COVID-19 diagnosis by real-time reverse transcription-polymerase chain reaction (RT-PCR). High sensitivity of optimized real-time RT-PCR assays makes pooled testing a potentially efficient strategy for resource utilization when positivity rates for particular regions or groups of individuals are low. We report here a comparative analysis of pooled testing for 5- and 10-sample pools by real-time RT-PCR across 10 COVID-19 testing laboratories in India.

METHODS

Ten virus research and diagnostic laboratories (VRDLs) testing for COVID-19 by real-time RT-PCR participated in this evaluation. At each laboratory, 100 nasopharyngeal swab samples including 10 positive samples were used to create 5- and 10-sample pools with one positive sample in each pool. RNA extraction and real-time RT-PCR for SARS-CoV-2-specific E gene target were performed for individual positive samples as well as pooled samples. Concordance between individual sample testing and testing in the 5- or 10-sample pools was calculated, and the variation across sites and by sample cycle threshold (Ct) values was analyzed.

RESULTS

A total of 110 each of 5- and 10-sample pools were evaluated. Concordance between the 5-sample pool and individual sample testing was 100 per cent in the Ct value ≤30 cycles and 95.5 per cent for Ctvalues ≤33 cycles. Overall concordance between the 5-sample pooled and individual sample testing was 88 per cent while that between 10-sample pool and individual sample testing was 66 per cent. Although the concordance rates for both the 5- and 10-sample pooled testing varied across laboratories, yet for samples with Ct values ≤33 cycles, the concordance was ≥90 per cent across all laboratories for the 5-sample pools.

INTERPRETATION & CONCLUSIONS

Results from this multi-site assessment suggest that pooling five samples for SARS-CoV-2 detection by real-time RT-PCR may be an acceptable strategy without much loss of sensitivity even for low viral loads, while with 10-sample pools, there may be considerably higher numbers of false negatives. However, testing laboratories should perform validations with the specific RNA extraction and RT-PCR kits in use at their centres before initiating pooled testing.

Wastewater surveillance for population-wide Covid-19: The present and future

The Covid-19 pandemic (Coronavirus disease 2019) continues to expose countless unanticipated problems at all levels of the world's complex, interconnected society - global domino effects involving public health and safety, accessible health care, food security, stability of economies and financial institutions, and even the viability of democracies. These problems pose immense challenges that can voraciously consume human and capital resources. Tracking the initiation, spread, and changing trends of Covid-19 at population-wide scales is one of the most daunting challenges, especially the urgent need to map the distribution and magnitude of Covid-19 in near real-time. Other than pre-exposure prophylaxis or therapeutic treatments, the most important tool is the ability to quickly identify infected individuals. The mainstay approach for epidemics has long involved the large-scale application of diagnostic testing at the individual case level. However, this approach faces overwhelming challenges in providing fast surveys of large populations. An epidemiological tool developed and refined by environmental scientists over the last 20 years (Wastewater-Based Epidemiology - WBE) holds the potential as a key tool in containing and mitigating Covid-19 outbreaks while also minimizing domino effects such as unnecessarily long stay-at-home policies that stress humans and economies alike. WBE measures chemical signatures in sewage, such as fragment biomarkers from the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), simply by applying the type of clinical diagnostic testing (designed for individuals) to the collective signature of entire communities. As such, it could rapidly establish the presence of Covid-19 infections across an entire community. Surprisingly, this tool has not been widely embraced by epidemiologists or public health officials. Presented is an overview of why and how governments should exercise prudence and begin evaluating WBE and coordinating development of a standardized WBE methodology - one that could be deployed within nationalized monitoring networks to provide intercomparable data across nations.

Sample pooling for SARS-CoV-2 RT-PCR screening

Objective

To evaluate the efficacy of sample pooling compared to the individual analysis for the diagnosis of coronavirus disease 2019 (COVID-19) by using different commercial platforms for nucleic acid extraction and amplification.

Methods

A total of 3519 nasopharyngeal samples received at nine Spanish clinical microbiology laboratories were processed individually and in pools (342 pools of ten samples and 11 pools of nine samples) according to the existing methodology in place at each centre.

Results

We found that 253 pools (2519 samples) were negative and 99 pools (990 samples) were positive; with 241 positive samples (6.85%), our pooling strategy would have saved 2167 PCR tests. For 29 pools (made out of 290 samples), we found discordant results when compared to their correspondent individual samples, as follows: in 22 of 29 pools (28 samples), minor discordances were found; for seven pools (7 samples), we found major discordances. Sensitivity, specificity and positive and negative predictive values for pooling were 97.10% (95% confidence interval (CI), 94.11–98.82), 100%, 100% and 99.79% (95% CI, 99.56–99.90) respectively; accuracy was 99.80% (95% CI, 99.59–99.92), and the kappa concordant coefficient was 0.984. The dilution of samples in our pooling strategy resulted in a median loss of 2.87 (95% CI, 2.46–3.28) cycle threshold (C_t) for E gene, 3.36 (95% CI, 2.89–3.85) C_t for the RdRP gene and 2.99 (95% CI, 2.56–3.43) C_t for the N gene.

Conclusions

We found a high efficiency of pooling strategies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA testing across different RNA extraction and amplification platforms, with excellent performance in terms of sensitivity, specificity and positive and negative predictive values.

Large-scale implementation of pooled RNA extraction and RT-PCR for SARS-CoV-2 detection

INTRODUCTION

Testing for active SARS-CoV-2 infection is a fundamental tool in the public health measures taken to control the COVID-19 pandemic. Because of the overwhelming use of SARS-CoV-2 reverse transcription (RT)-PCR tests worldwide, the availability of test kits has become a major bottleneck and the need to increase testing throughput is rising. We aim to overcome these challenges by pooling samples together, and performing RNA extraction and RT-PCR in pools.

METHODS

We tested the efficiency and sensitivity of pooling strategies for RNA extraction and RT-PCR detection of SARS-CoV-2. We tested 184 samples both individually and in pools to estimate the effects of pooling. We further implemented Dorfman pooling with a pool size of eight samples in large-scale clinical tests.

RESULTS

We demonstrated pooling strategies that increase testing throughput while maintaining high sensitivity. A comparison of 184 samples tested individually and in pools of eight samples showed that test results were not significantly affected. Implementing the eight-sample Dorfman pooling to test 26 576 samples from asymptomatic individuals, we identified 31 (0.12%) SARS-CoV-2 positive samples, achieving a 7.3-fold increase in throughput.

DISCUSSION

Pooling approaches for SARS-CoV-2 testing allow a drastic increase in throughput while maintaining clinical sensitivity. We report the successful large-scale pooled screening of asymptomatic populations.

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

OBJECTIVE

To evaluate two pooled-sample analysis strategies (a routine high-throughput approach and a novel context-sensitive approach) for mass testing during the coronavirus disease 2019 (COVID-19) pandemic, with an emphasis on the number of tests required to screen a population.

METHODS

We used Monte Carlo simulations to compare the two testing strategies for different infection prevalences and pooled group sizes. With the routine high-throughput approach, heterogeneous sample pools are formed randomly for polymerase chain reaction (PCR) analysis. With the novel context-sensitive approach, PCR analysis is performed on pooled samples from homogeneous groups of similar people that have been purposively formed in the field. In both approaches, all samples contributing to pools that tested positive are subsequently analysed individually.

FINDINGS

Both pooled-sample strategies would save substantial resources compared to individual analysis during surge testing and enhanced epidemic surveillance. The context-sensitive approach offers the greatest savings: for instance, 58-89% fewer tests would be required for a pooled group size of 3 to 25 samples in a population of 150 000 with an infection prevalence of 1% or 5%. Correspondingly, the routine high-throughput strategy would require 24-80% fewer tests than individual testing.

CONCLUSION

Pooled-sample PCR screening could save resources during COVID-19 mass testing. In particular, the novel context-sensitive approach, which uses pooled samples from homogeneous population groups, could substantially reduce the number of tests required to screen a population. Pooled-sample approaches could help countries sustain population screening over extended periods of time and thereby help contain foreseeable second-wave outbreaks.

Implementation of Antibody Rapid Diagnostic Testing versus Real-Time Reverse Transcription-PCR Sample Pooling in the Screening of COVID-19: a Case of Different Testing Strategies in Africa

Coronavirus disease 2019 (COVID-19) has wreaked havoc across the globe; although the number of cases in Africa remains lower than in other regions, it is on a gradual upward trajectory. To date, COVID-19 cases have been reported in 54 out of 55 African countries. However, due to limited severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) real-time reverse transcription-PCR (rRT-PCR) testing capacity and scarcity of testing reagents, it is probable that the total number of cases could far exceed published statistics. In this viewpoint, using Ghana, Malawi, South Africa, and Zimbabwe as examples of countries that have implemented different testing strategies, we argue that the implementation of sample pooling for rRT-PCR over antibody rapid diagnostic testing could have a greater impact in assessing disease burden. Sample pooling offers huge advantages compared to single test rRT-PCR, as it reduces diagnostic costs, personnel time, burnout, and analytical run times. Africa is already strained in terms of testing resources for COVID-19; hence, cheaper alternative ways need to be implemented to conserve resources, maximize mass testing, and reduce transmission in the wider population.