SARS-CoV-2 detection in multi-sample pools in a real pandemic scenario: A screening strategy of choice for active surveillance.

BACKGROUND: The current COVID-19 pandemic has overloaded the diagnostic capacity of laboratories by the gold standard method rRT-PCR. This disease has a high spread rate and almost a quarter of infected individuals never develop symptoms. In this scenario, active surveillance is crucial to stop the virus propagation.
METHODS: Between July 2020 and April 2021, 11,580 oropharyngeal swab samples collected in closed and semi-closed institutions were processed for SARS-CoV-2 detection in pools, implementing this strategy for the first time in Córdoba, Argentina. Five-sample pools were constituted before nucleic acid extraction and amplification by rRT-PCR. Comparative analysis of cycle threshold (Ct) values from positive pools and individual samples along with a cost-benefit report of the whole performance of the results was performed.
RESULTS: From 2,314 5-sample pools tested, 158 were classified as positive (6.8%), 2,024 as negative (87.5%), and 132 were categorized as indeterminate (5.7%). The Ct value shift due to sample dilution showed an increase in Ct of 2.6±1.53 cycles for N gene and 2.6±1.78 for ORF1ab gene. Overall, 290 pools were disassembled and 1,450 swabs were analyzed individually. This strategy allowed correctly identifying 99.8% of the samples as positive (7.6%) or negative (92.2%), avoiding the execution of 7,806 rRT-PCR reactions which represents a cost saving of 67.5%.
CONCLUSION: This study demonstrates the feasibility of pooling samples to increase the number of tests performed, helping to maximize molecular diagnostic resources and reducing the work overload of specialized personnel during active surveillance of the COVID-19 pandemic.

Introduction

The emergence of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led humanity to an unprecedented pandemic with severe health consequences for the population worldwide. Diagnostic tests are essential due to their ability to detect and provide answers for pandemic management [1, 2]. However, they may be hampered because of the high demand that overwhelmed the healthcare system and the limited supply of reagents required for the setup of these tests [3]. This aspect has been particularly worse in some geographic regions of the world, in low and middle-income countries as well [4]. Thus, the context of SARS-CoV-2 pandemics motivated the design of alternative diagnostic strategies.

SARS-CoV-2 infection is characterized by the great diversity of signs and symptoms affecting patients. The most frequently associated with COVID-19 are fever, dry cough and generalized weakness, though symptoms such as nausea, diarrhea, loss of smell, pharyngitis and enlarged tonsils have also been reported [5]. However, about a quarter of infected people never develop symptoms (asymptomatic) and about half of the infected individuals do not manifest any symptom at the testing time (presymptomatic) [6, 7]. Both groups are of great concern as they contribute to the spread of the virus because they are not aware that they are infected. These groups are undetectable through passive surveillance but require instead active surveillance strategy based on massive testing methods. Hence, the need to increase testing capacity entails developing alternative strategies to optimize resources, save time and reduce labor demand, thereby enhancing COVID-19 diagnosis which, in turn, is essential for evaluating the disease spread and for tracing the contacts of infected individuals [8, 9]. Testing pooled samples by real-time reverse-transcriptase-polymerase chain reaction (rRT-PCR) could be a plausible way to deal with the huge demand for SARS-CoV-2 detection as long as it demonstrates optimum diagnostic performance. This strategy consists of mixing samples in a pool and then performing a single RNA extraction followed by a rRT-PCR assay. If the result is positive, then it must be identified which of the individual samples that make up the pool are positive by performing the RNA extraction and rRT-PCR test for each one of them. On the other side, if the rRT-PCR test is negative it is assumed that all individual samples composing the pool are also negative. Thus, according to this layout, it is expected that fewer nucleic acid extraction and rRT-PCR tests will be required, saving reagents, time and labor demand compared with analyzing individual samples. This pooling approach was previously developed for the analysis of several infectious diseases, e.g., malaria and HIV [10, 11], and is currently used as a screening method in blood banks prior to transfusion [12, 13]. Pooling nasopharyngeal swab samples for RNA virus detection, such as influenza has already been evaluated [14]. In the case of COVID-19, the method was considered and analyzed as strategy by countries like Germany, Israel and the United States [15-17], after the Food and Drug Administration (FDA) approved the emergency use of Quest SARS-CoV-2 rRT-PCR test for pooled samples on July, 2020 [18].

The aim of this work was the implementation of a multi-sample pool strategy during a specific period of the COVID-19 pandemic, to decrease costs and response times, while increasing efficiency and testing capacity, thereby contributing to early patient assistance and control of disease spread.

Methods

Sample pooling

In July 2020, when the background SARS-CoV-2 community prevalence was between 3% and 5% in Córdoba, Argentina [19], oropharyngeal swab samples in viral transport media (Jun Nuo, Chengwu County, Shandong Province, China) obtained by healthcare personnel in testing centers, were processed using a pooling strategy, following the protocol described by Ambrosi et al. with minor modifications [20]. Briefly, from five individual oropharyngeal swab samples, an aliquot of 60 μL of each was taken to create a pool, with a final volume of 300 μL. Each pool of samples was processed for RNA extraction and subsequent rRT-PCR analysis. From August 2020 to April 2021, when the community viral prevalence exceeded 5%, oropharyngeal swab samples were collected in 234 closed and semi-closed institutions. Each group of 5 sequentially obtained samples was pooled, without mixing samples from different institutions. Overall, 2,314 pools were made up, each one containing a mix of 5 individual samples, from initially 11,580 patient samples.

Nucleic acid extraction and SARS-CoV-2 detection

RNA extraction of the pool was performed using Bioer MagaBio plus Virus DNA/RNA Purification Kit in addition to Bioer GenePure Pro fully automatic Nucleic Acid purification System (Bioer, Hangzhou, China) and EasyPure Viral DNA/RNA Kit (TransGene, Beijing, China), according to the manufacturer’s instructions. A multiplex single step real time RT-PCR was carried out for amplification, using DisCoVery SARS-CoV-2 rRT-PCR Detection Kit (TransGen Biotech Co., Ltd, Beijing, China), which is designed to detect two SARS-CoV-2 target genes: Open Reading Frame 1ab (ORF1ab) and nucleocapsid (N), along with the human ribonuclease P (RNAseP) gene as endogenous control (Safecare Biotech Hangzhou, China).

Classification criteria

Considering the cycle threshold (Ct) value for ORF1ab and N genes, the pools were classified as:

Positive: pools with amplification of both genes with Ct≤38.

Negative: those without amplification of both genes, or with fluorescence signal only in one of them with Ct>40.

Suspected positive or indeterminate: pools that showed amplification in only one gene with Ct≤40 and those that amplified both genes with Ct>38.

To validate the previous results, all tests must amplify the endogenous RNAseP control gene.

Data processing

Results obtained by rRT-PCR (sample code and their respective Ct) were organized and converted into comma-delimited files. These data were incorporated into a database based on APACHE, MYSQL and PHPMYADMIN. A web interface was created to monitor the tests, evaluate coherence through PHP scripts, visualize the data pools and their disassembly, and carry out searches.

Statistical analysis

Differences in Ct values, mean, standard deviation and the reduction in the number of tests were calculated using R version 4.0.5, 2021. The delta Ct value (ΔCt) was defined as the absolute change in Ct value when the pooled sample was tested compared to the positive sample that composed the pool, when it was tested individually. Therefore, a positive ΔCt value (i.e., an increase in Ct value of the pooled sample) represents the loss of rRT-PCR sensitivity as a consequence of individual sample dilution within a pool composed of 5 samples [21]. ANOVA tests were done to compare groups, and a P-value of 0.05 or less was considered statistically significant.

Ethics statement

Ethical review, approval and written informed consent from the participants were not required for the study on oropharyngeal swab samples obtained from human participants in accordance with the local legislation and institutional requirements. The Government of the Province of Córdoba waives the ethical review of the SARS-CoV-2 detection in multi-sample pools during 2020 and 2021 under strict confidentiality rules, based on the need for rapid surveillance and availability of methodologies for diagnosis of COVID-19.

Results

The study included 11,570 samples analyzed under 2,314 pools format, containing 5 samples each. The results showed 158 positive (6.8%) and 2,024 negative pools (87.5%); also 132 pools were classified as indeterminate (5.7%). In total, 290 pools were disassembled (158 classified as positive and 132 suspected to be positive) to analyze each one of the 1,450 samples that composed them. As a result, the pooling strategy saved 7,806 tests, that is, 67.5% fewer tests were required for the screening, leading to a two-thirds reduction in costs.

A hundred and five (105) of the positive pools contained a single positive sample, and 53 contained more than one positive sample. Results of Ct variation values comparing each pool and individual samples are shown in

Pools with a single positive.

Scatter plots showing cycle threshold (Ct) values and Ct shifts detected by rRT-PCR in five-samples pools (squares), composed of four negative and one positive sample, with respect to the individual positive samples (circles) for N (top graph) and ORF1ab (bottom graph) genes.

It was observed that 5-sample pools containing one positive and four negative individual swabs samples, yielded higher Ct values than individual sample testing exceeded by 2.6 cycles on average for both, N and ORF1ab genes (2.6±1.53 cycles for N gene and, 2.6±1.78 for ORF1ab gene). The differences between the Ct value of pooled and individual samples (ΔCt) are illustrated in , showing the same mean value and comparable variability for both target genes.

Ct value shift due to sample pooling.

Box plot showing the difference between the Ct values (ΔCt) of five-samples pools (composed of 1 positive and 4 negative samples) and the respective individual positive samples for N and ORF1ab target genes.

For most pools composed of more than one positive individual sample, the Ct values obtained were closer to the average of the individual Ct values, showing a pattern distribution in the middle area of the plot, and decreasing as the number of positive individual swabs increases within the same pool ().

Pools with two or more positives.

Scatter plots showing Ct values detected by rRT-PCR in five-samples pools (squares) and the individual positive samples (circles) from pools containing 2 (Pool # 1–27), 3 (Pool # 28–37), 4 (Pool # 38–47) or 5 (Pool # 39–53) positive samples. The analysis was performed for N (top graph) and ORF1ab (bottom graph) genes.

Regarding the 132 indeterminate pools, 19 contained only one positive sample (), 108 were constituted by all negative individual samples and five contained one suspected positive sample (inconclusive result according to the criteria provided in the user manual of the rRT-PCR kit, so a new sample was requested). Analysis of the Ct values distribution of the indeterminate group, indicates that there are no significant differences (P<0.05) for both, N and ORF1ab genes, regardless of whether any pool contained positive samples ().

Pools classified as indeterminate.

Box plot showing Ct values of N and ORF1ab genes from indeterminate pools which were finally classified as pools constituted by all negative samples (left), pools containing one positive sample (middle) and the individual positive samples after disassembly (right).

Discussion

Given the high transmission rates of SARS-CoV-2 and that almost a quarter of infected people are asymptomatic [6, 7], one of the best strategies to control the virus spread is the early detection of those infected and their subsequent isolation. To achieve early detection of the infection, it is necessary to carry out active surveillance and massive testing. In this sense, different experimental or computational modeling tests have been carried out at the laboratory level to study the sensitivity and accuracy of the SARS-CoV-2 detection strategies using different grouping techniques. However, at present there are very few studies reporting results of some of these strategies applied in a real setting, demonstrating their applicability on a large scale with patient samples.

Strengths of pooling strategy

This study demonstrates that the strategy based on the analysis of samples in the format of pools, consisting of 5 samples each, is a reliable approach for efficient detection of SARS-CoV-2 in a large number of samples in the context of the pandemic. In addition, it contributes to saving molecular diagnosis supplies and labor of the health personnel in areas or institutions with low viral circulation. It can be useful to monitor the infection rate in closed or semi-closed establishments such as residential homes, police and military headquarters, prisons or hospitals, due to these places being populated by those who are generally in close contact and/or at greater risk [20]. The emergence of the Omicron variant, which is more contagious than the previous ones SARS-CoV-2 strains [22], increases the importance of analyzing closed communities through periodic testing. For this, rRT-PCR testing using the pooling strategy has the advantage of being more specific and sensitive than rapid antigen tests, making it possible to detect false-negative and asymptomatic people without increasing costs as much, thus contributing to better management of pandemic in particular time periods.

About suspected positive results, almost every indeterminate pool was classified in that way because only the N gene showed amplification, which could be due to the increased sensitivity of this gene, in contrast with the ORF1ab gene [23]. Although in this indeterminate group was found only 19 pools (14.4%) that contained positive samples, the mean and range of the Ct values of both, N and ORF1ab genes, were similar to those found for the remaining indeterminate pools. Hence, it was not possible to establish a more rigorous cut-off Ct value to avoid disassembling groups composed of samples that will ultimately be all negative. Therefore, it was mandatory to disassemble all indeterminate groups to avoid false-negative results. Nevertheless, this approach allowed the correct identification of 99.8% of samples as positive (7.6%) or negative (92.2%), without the necessity to perform 7,806 tests, thus, saving 67.5% of costs and labor.

The pooling approach addresses a variety of difficulties associated with the pandemic context, most notably the limited availability of reagents, supplies, equipment, high labor demand of laboratory workers, as well as the high cost. However, the decision to implement this strategy must consider the total testing capacity and the disease prevalence in a specific geographic area.

The high sensitivity of rRT-PCR assays makes pool testing an efficient system that can be applied for resource optimization when the positivity rate is low (e.g., 5% or lower), improving laboratory testing capacities without additional requirements in terms of equipment availability or qualified personnel [24-26].

Limitations of pooling strategy

It is important to highlight that optimal pool size must be determined according to the prevalence in the area under study [8, 27]. Previous studies have analyzed different pool sizes, from 2- to 64-samples [20, 25], and agreed that the number of samples in the pool is inversely proportional to the test sensitivity [26, 28]. It has been reported that SARS-CoV-2 prevalence is a suitable criterion to define the most efficient pool size, defining 5-sample groups as appropriate when the prevalence rates are about 5% [8, 20]. According to our findings, as well as previous reports, pooling samples entails the loss of sensitivity and an increase of the Ct value of pools compared with the individual specimen due to the sample dilution, especially for samples with low viral loads [26, 28, 29]. The increase in the Ct value observed in this study (2.6 cycles on average) for both target genes was comparable to those described in other reports of SARS-CoV-2 testing in pools constituted by 5 individual samples, where ΔCt ranges were between 2 and 3.4 [20, 28, 30, 31]. This variation results in more tests classified as indeterminate than would be obtained in a single sample approach, mainly in those groups that contained individual positive samples with a Ct value close to 38. In both positive and indeterminate pools, the Ct value distribution for the N and the ORF1ab genes shows the same trend observed in individual samples: lower Ct values were detected for the N gene than for the ORF1ab target sequence.

The limitation of this strategy to test the internal control of each sample, which is required to control the specimen quality, must also be underlined. So, false-negative results may occur if samples are improperly collected, transported or handled. Hence, negative results obtained by pooled sampling do not preclude SARS-CoV-2 infection and should not be used as the only criteria for treatment or for other social management decisions.

Conclusion

The results obtained in this study show that the implementation of the pooling strategy was able to save 67.5% of rRT-PCR reactions in a low viral circulation scenario. Testing in pools was a positive approach that expanded sample processing capabilities, allowing massive testing and early outbreaks detection. This experience could be taken into account as a strategy of active surveillance in hospitals, care homes, schools and other closed and semi-closed institutions. In a new post-pandemic scenario, with an expected decrease of viral circulation due to vaccine programs, the pooling approach could be implemented to carry out periodically large-scale testing to the population.

17 Jan 2022

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Reviewer #1: This is a generally well-written and informative manuscript. I have a few comments.

Abstract should explicitly state that 5 samples were used to create each pool.

Methods should present the sources of the VTM and the swabs. Even if this information is provided in a reference ,the methods section should state whether healthcare personnel obtained swabs or whether self-swabs were pooled, even if this information is provided in a reference.

Someplace the paper should tell us whether the pools represented truly random mixtures of cases, or whether perhaps multiple individuals from a single cluster of people (for example, family members or coworkers) were sometimes combined into a single pooled sample. The fact that 53 of 158 positive pools had more than one positive, while only 153 of 2314 pools contained any positives – a statistically improbable combination, suggests cluster effects or cross-contamination.

Reviewer #2: This study by Marcos Castallero et al., is very well-written, concise and timely, presenting a compelling argument for large-scale alternatives in testing strategies to cope with fluctuating test volumes. My only quibble is that the savings are limited to test reagents and laboratory resources and are partially mitigated by increased complexity in other parts of the testing chain, when 5% or less scenarios are transient and geographically variable, especially these days. For how long is pooling actually feasible and how does the lab switch seamlessly from pooling to not pooling? Or pooling for some samples but not for others. Can you make more of an argument about how pooling logistics fit into the overall strategy for surveillance and monitoring in low prevalence populations? Instead of just waiting for pooling to be useless, as it is right now? I realize this may be a bit out of your scope, but could add to your perspective on “the pandemic context”.

Omicron seems to have changed the game entirely. Although outside the timeframe in which your study was conducted, some recognition of how the pooling strategies you recommend are affected by these developments would be welcome. Any predictions about post-Omicrom scenarios – e.g. specific groups of people benefitting from a daily pooled sample prior to accessing a closed facility.

Data processing: I am surprised at all the scripts and databases required to handle two variables (testee identity and Ct values), but I have never worked with such a big sample set! Is there any chance of seeing some of the scripts used, database summaries and visualizations mentioned in this section?

Minor comments:

I think most journals would require a comma thousands separator.

line 95: “waives” is misspelled.

line 112: “Beijing” typo.

line 127-9: To be more concise, I would delete everything from “...exported” to “and interpreted with...”

line 139: Misplaced comma.

line 144: “All together” instead of “Altogether”

line 145-7: “saved” instead of “allowed to save”. Isn’t “67.5% fewer” the same thing as “3 times reduction” (“testing materials and costs were reduced by two thirds.”)?

line 173-4: “regardless of whether any pool contained positive samples.”

line 179: “disassembly” instead of “deconvolution” – stick to one word for testing all samples in a pool.

line 191: just “save” instead of “save costs of”.

line 195: “those” instead of “persons”, “at greater risk” instead of “risk factors”.

line 196: “optimal pool size” instead of “optimum size pool”

line 203: “especially for samples” instead of “affecting especially detection of samples”

line 212: “the increased sensitivity” instead “a more sensitivity”, “in contrast with the” instead of “contrasting with”

line 216: “disassembling” instead of “disarming”

line 219. Just “labor” instead of “decreasing personnel labor demanding”.

line 221: “deals” instead of “allows to deal”, “the pandemic context” instead of “a context of pandemics”

line 236: “expanded”, instead of “allow expanding” – replace period with comma after “capabilities”

Reviewer #3: This paper provides a comprehensive study of a pooled testing approach applied in a practical pandemic scenario. To my knowledge, there is not much data available regarding the trade-off between a potential loss of accuracy and the cost reduction resulting from the reduced number of tests. This paper provides such a comparison, giving an overview of the change of ct-values, the number of correct detections and the savings in terms of test reduction. This information is much needed to design public testing strategies based on pooled PCR tests., especially given the fact that antigen tests do not work well for the omicron variant and that there is still some hesitation with regards to the accuracy of pooled tests. For this reason, I find this study quite timely and recommend publication. The paper is also quite well-written, I do not have any specific suggestions or comments.

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12 Feb 2022

On behalf of my fellow authors, we wish to thank the three reviewers for their insightful, detailed and constructive criticisms of our manuscript.

Responses to comments of reviewer #1

This is a generally well-written and informative manuscript. I have a few comments.

1-Abstract should explicitly state that 5 samples were used to create each pool.

Re.1: The abstract already had this data: On lines 39-40 the abstract states “Five-sample pools were constituted before nucleic acid extraction and amplification by rRT-PCR.”

2-Methods should present the sources of the VTM and the swabs. Even if this information is provided in a reference, the methods section should state whether healthcare personnel obtained swabs or whether self-swabs were pooled, even if this information is provided in a reference.

Re.2: We agree with the reviewer’s comment. To be clearer now at 'Sample pooling' section of Methods (lines 102-103) the following sentence has been included: "oropharyngeal swab samples in viral transport media (Jun Nuo, Chengwu County, Shandong Province, China), obtained by healthcare personnel in testing centers, were processed…"

3-Someplace the paper should tell us whether the pools represented truly random mixtures of cases, or whether perhaps multiple individuals from a single cluster of people (for example, family members or coworkers) were sometimes combined into a single pooled sample. The fact that 53 of 158 positive pools had more than one positive, while only 153 of 2314 pools contained any positives – a statistically improbable combination, suggests cluster effects or cross-contamination.

Re.3: We agree with the reviewer about this sharp right observation, indeed, it is very likely that there is a cluster effect since, as expressed in lines 107 and 108 of the manuscript ("From August 2020 to April 2021, when the community viral prevalence exceeded 5%, oropharyngeal swab samples were collected in 234 closed and semi-closed institutions."), many pools were formed with individual samples from closed and semi-closed institutions. To clarify on this point, the following sentence has been included: "These oropharyngeal swab samples were pooled together into 5 samples based on the order number, without mixing samples from different institutions." (lines 107-110).

Responses to comments of reviewer #2:

1-This study by Marcos Castallero et al., is very well-written, concisate and timely, presenting a compelling argument for large-scale alternatives in testing strategies to cope with fluctuating test volumes. My only quibble is that the savings are limited to test reagents and laboratory resources and are partially mitigated by increased complexity in other parts of the testing chain, when 5% or less scenarios are transient and geographically variable, especially these days. For how long is pooling actually feasible and how does the lab switch seamlessly from pooling to not pooling? Or pooling for some samples but not for others. Can you make more of an argument about how pooling logistics fit into the overall strategy for surveillance and monitoring in low prevalence populations? Instead of just waiting for pooling to be useless, as it is right now? I realize this may be a bit out of your scope, but could add to your perspective on “the pandemic context”.

Re.1: We are grateful to reviewer for his very interesting analysis and remark.

It is true that the laboratory needs a greater organization that allows the assembly of the pools with perfect traceability. But once the personnel is trained, it does not imply a great extra effort. Regarding when to use the pool strategy and when it does not, it depends on the previous logistics, the epidemiological scenario (the viral prevalence in a given region and moment), and the local health public policy, which is dynamic and varies regarding viral circulation. In other words, an attempt should be made to infer the prevalence percentage of viral infections using recent data from previous tests reported in the area from which the samples come. Another way could be to randomly analyze some individual samples that are representative of the population tested in a given testing center or region. In this way, a percentage of positivity could be estimated and thus decide if the rest of the samples of that population will be analyzed by pooling strategy. Although this could generate a delay in the results.

2-Omicron seems to have changed the game entirely. Although outside the timeframe in which your study was conducted, some recognition of how the pooling strategies you recommend are affected by these developments would be welcome. Any predictions about post-Omicrom scenarios – e.g. specific groups of people benefitting from a daily pooled sample prior to accessing a closed facility.

Re.2: As the reviewer’s stated, the Omicron SARS-CoV-2 variant emerged after the time of this study. However, following your indication, we also add the following paragraph to address your remark at the Discussion section of MS: “The emergence of the Omicron variant, which is more contagious than the previous ones SARS-CoV-2 strains, increases the importance of analyze closed communities through periodic testing. For this, rRT-PCR testing using the pooling strategy has the advantage of being more specific and sensitive than rapid antigen tests, making possible to detect false-negative and asymptomatic people without increasing costs as much, thus contributing to a better management of pandemic in particular time periods.” (line 196-201).

3-Data processing: I am surprised at all the scripts and databases required to handle two variables (testee identity and Ct values), but I have never worked with such a big sample set! Is there any chance of seeing some of the scripts used, database summaries and visualizations mentioned in this section?

Re.3: The following web link: http://covid.ceprocor.com/ , hosts the site created for the storage and management of data related to pools, which is mentioned in the "Data processing" section. This site is in Spanish and in the home page you can access the links: Results (Resultados), Searches (Busquedas), and Database Information (Info de la base de datos). In Results, data are organized by date (in calendar format). Accessing to a specific day between August 2020 and April 2021, it is possible to find out the results of pooled samples and also individual samples, as they are specified. If a specific pool had a result other than negative, it was disassembled to test each individual sample included in the pool. In this situation, the results of the individual samples can be viewed by choosing from the bottom left section of the page for that day, by internal pool code, and clicking on the button: "Choose internal pool code". All results for the pool samples involved will be seen. The Searches and Database Information sections were used for a better follow-up of the daily work.

All data, for the purposes of this publication, was extracted from the database, accessed directly via MySQL."

4-Minor comments:

4.1 I think most journals would require a comma thousands separator.

Re.4.1: Right, in this revised version all numbers are with comma thousands separator format.

4.2 line 95: “waives” is misspelled.

Re.4.2: This mistake was fixed, now at line 96 says: “The Government of the Province of Córdoba waives the ethical review…”

4.3 line 112: “Beijing” typo.

Re.4.3: This mistake was fixed, now at line 115 says: “TransGene, Beijing, China…”

4.4 line 127-9: To be more concise, I would delete everything from “...exported” to “and interpreted with...”

Re.4.4: We agree, this part was deleted according to the reviewer’s observation, and the paragraph at lines 130-131 now says: “Results obtained by Real Time PCR (sample code and their respective Ct) were organized and converted into comma delimited files.”

4.5 line 139: Misplaced comma.

Re.4.5: This mistake was fixed

4.6 line 144: “All together” instead of “Altogether”

Re.4.6: Now at line 145 says: “In total, 290 pools were disassembled”

4.7 line 145-7: “saved” instead of “allowed to save”. Isn’t “67.5% fewer” the same thing as “3 times reduction” (“testing materials and costs were reduced by two thirds.”)?

Re.4.7: We acknowledge for this observation, now at lines 146-148 says: “As a result, the pooling strategy saved 7,806 tests, that is, 67.5% fewer tests were required for the screening, leading to a two-thirds reduction in costs.”

4.8 line 173-4: “regardless of whether any pool contained positive samples.”

Re.4.8: We agree, now the sentence “regardless of whether any pool contained positive samples” is at lines 174-175.

4.9 line 179: “disassembly” instead of “deconvolution” – stick to one word for testing all samples in a pool.

Re.4.9: We agree, now the caption of fig 4. at line 180 says “…and the individual positive samples after disassembly…”

4.10 line 191: just “save” instead of “save costs of”.

Re.4.10: Done, now at line 191 says “In addition, it contributes to saving molecular diagnosis…”

4.11 line 195: “those” instead of “persons”, “at greater risk” instead of “risk factors”.

Re.4.11: Done, now at line 195-196 says “…being populated by those who are generally in close contact and/or at greater risk”

4.12 line 196: “optimal pool size” instead of “optimum size pool”

Re.4.12: Done, now at line 202 says “It is important to highlight that optimal pool size must be determined…”

4.13 line 203: “especially for samples” instead of “affecting especially detection of samples”

Re.4.13: Done, now at line 209 says “especially for samples with low viral loads”

4.14 line 212: “the increased sensitivity” instead “a more sensitivity”, “in contrast with the” instead of “contrasting with”

Re.4.14: This change has been done, now at lines 218-219 says: “which could be due to the increased sensitivity of this gene, in contrast with the ORF1ab gene”

4.15 line 216: “disassembling” instead of “disarming”

Re.4.15: This change has been included, now at line 222 says “…to avoid disassembling groups composed of…”

4.16 line 219. Just “labor” instead of “decreasing personnel labor demanding”.

Re.4.16: This change has been done, now at line 225 says “thus, saving 67.5% of costs and labor”

4.17 line 221: “deals” instead of “allows to deal”, “the pandemic context” instead of “a context of pandemics”

Re.4.17: Done, now at line 226 says “The pooling approach addresses a variety of difficulties associated the pandemic context, most notably …”

4.18 line 236: “expanded”, instead of “allow expanding” – replace period with comma after “capabilities”

Re.4.18: Agree, now at lines 239-240 says “The approach of testing in pools was a positive experience that expanded sample processing capabilities, allowing massive testing and early outbreak detections.”

Comments of reviewer #3:

1-This paper provides a comprehensive study of a pooled testing approach applied in a practical pandemic scenario. To my knowledge, there is not much data available regarding the trade-off between a potential loss of accuracy and the cost reduction resulting from the reduced number of tests. This paper provides such a comparison, giving an overview of the change of ct-values, the number of correct detections and the savings in terms of test reduction. This information is much needed to design public testing strategies based on pooled PCR tests., especially given the fact that antigen tests do not work well for the omicron variant and that there is still some hesitation with regards to the accuracy of pooled tests. For this reason, I find this study quite timely and recommend publication. The paper is also quite well-written, I do not have any specific suggestions or comments.

Re.1: We are grateful to the reviewer for his/her positive comments, recommending the publication of our work.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

6 Mar 2022

15 Mar 2022

All the authors and I wish to take this opportunity to acknowledge the editor and the reviewers for their constructive comments and valuable recommendations. We have revised the manuscript on our R1 version according to the concerns, and have resubmitted it online. Our responses are listed below.

ACADEMIC EDITOR

1. Check the first paragraph of the introduction as there is no references. Is it your own sentences?

Re. 1- This paragraph was written based on our own experience and the situation that many countries in the world went through. The corresponding citations supporting these sayings have been added.

2. Replace “in order to” with “to” throughout the text

Re. 2- In line 90 of manuscript, “in order to” was replaced by “to”.

3. Check spaces and punctuation throughout the text

Re. 3- Following the editor's comment, spaces and punctuation were checked through the manuscript.

4. P letter for statistical value should be uppercase-italic face

Re. 4- Now, the P letter for statistical value now have the indicated format.

5. Figs captions should not be incorporated in the text. They should be at the bottom of the corresponding one.

Re. 5- At the editor’s request, figure captions were moved from the body text to the bottom of the manuscript.

6. Avoid using “we, our”. Use impersonal phrasing throughout the text

Re. 6- As suggested, most of the personal phrases in the manuscript were changed to impersonal phrases.

7. Study strengths and limitations should be in a separate section, headed as addressed. It should be ahead of the conclusion. Start with the strength of the study, followed by limitations.

Re. 7- The discussion section has been reordered according to the editor’s suggestion. Now, the first part exposes the strengths of the pooling strategy followed by the limitations, both under the corresponding subtitle.

8. The conclusion should be in a separate section. What are the clinical relevance and future perspective? Add this to the conclusion section.

Re. 8- Now the conclusion is in a separate section after the discussion.

9. Proofread the text for grammar and syntax errors

Re. 9- Based on the editor’s comment, English, grammar, and syntax were checked throughout the manuscript.

Reviewer #1:

10. According to the reviewer’s comment: Line 108 currently states: "These oropharyngeal swab samples were pooled together into 5 samples based on the order number, without mixing samples from different institutions."

This would be more clearly written as "Each group of 5 sequentially obtained samples was pooled, without mixing samples from different institutions."

Re. 10- We thank the reviewer’s advice and following it, the paragraph was changed according to the suggestion (line 102).

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

21 Mar 2022

SARS-CoV-2 detection in multi-sample pools in a real pandemic scenario: a screening strategy of choice for active surveillance

PONE-D-21-40099R2

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PLOS ONE

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Reviewer #1: All comments have been addressed

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25 Mar 2022

PONE-D-21-40099R2

SARS-CoV-2 detection in multi-sample pools in a real pandemic scenario: a screening strategy of choice for active surveillance

Dear Dr. Castellaro:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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Table 1

Ct values of positive individual samples from 19 indeterminate pools.

N gene		ORF1ab gene
Pooled (Ct)	Individual Sample (Ct)	Pooled (Ct)	Individual Sample (Ct)
37.4	33.7	NA	36.1
35.7	34.6	NA	36.6
NA	37.9	38.3	36.7
32.9	29.6	39.9	31.7
35.2	33.0	41.0	35.0
37.0	33.5	NA	36.6
38.9	34.4	NA	36.5
36.3	32.7	NA	34.7
35.5	31.2	NA	36.2
37.3	32.1	NA	36.0
36.9	34.7	NA	37.7
34.6	31.1	38.4	32.9
NA	36.0	39.5	37.8
37.2	35.4	NA	37.5
39.9	36.4	NA	37.0
38.0	31.9	NA	34.4
35.8	32.7	NA	35.3
38.6	31.0	NA	33.5
NA	36.5	39.5	35.3

NA: no amplification.