Article Information

Samiksha Sharma^#, Vaibhav K. Tamrakar^#, Nishant Burnase, Shailendra S. Parihar, Kirti Pagarware and Rekha Barapatre*

Chhattisgarh Institute of Medical Sciences, Bilaspur, Chhattisgarh, India

^#Equeal Contribution

*Corresponding author: Rekha Barapatre. Chhattisgarh Institute of Medical Sciences, Bilaspur, Chhattisgarh, India.

Received: 08 April 2023; Accepted: 17 April 2023; Published: 25 April 2023

Citation: Samiksha Sharma, Vaibhav K. Tamrakar, Nishant Burnase, Shailendra S. Parihar, Kirti Pagarware and Rekha Barapatre. Cost-effective pool Testing qRT-PCR Method for early Detection and mass Screening of SARS-CoV-2 Infection. Fortune Journal of Health Sciences. 6 (2023): 174-177.

Abstract

Keywords

Cost-effective, COVID-19 pandemic, qRT-PCR, Pooling, SARS-CoV-2

Article Details

1. Introduction

The world faces the most crippling pandemic because of an unprecedented outbreak and global spread of COVID-19 after its first detection in Wuhan, China, in December 2019. COVID-19 is a substantial challenge for healthcare systems and their infrastructure and after its worldwide spread, it was declared a pandemic by WHO in March 2020 [1]. The most common symptoms displayed by individual infected with this virus includes fever, cough and sore throat. However, patients having diabetes, cardiovascular disease, chronic respiratory disease, or cancer become seriously ill and require immediate medical attention [2-4]. Testing helps in the detection of viruses in symptomatic as well as in asymptomatic individuals [5]. Many techniques have been used for diagnostic purposes, such as rapid antigen test, True-Nat, Chest CT-scan and qRT-PCR. To differentiate SARS-CoV-2 infection from other respiratory infections WHO has recommended more robust and sensitive tests. qRT-PCR-based diagnosis of COVID-19 is significant in confirming the infection and its containment. qRT-PCR is a susceptible technique as it can detect a single copy of the genome and multiply it into millions of copies resulting in qRT-PCR being considered the gold standard test for detecting SARS CoV-2 infection [6]. Due to its high sensitivity and specificity, qRT-PCR tests are also being performed as confirmatory tests for rapid antigen testing [7, 8]. Mass screening is needed to deal with this pandemic and overcome the load of clinical samples. The high demand for qRT-PCR tests led to a local shortage of resources, so to conserve resources and time, a pool testing strategy can be considered as a viable option. Many studies are available on qRT-PCR is also able to detect several variants of SARS CoV-2 [6]. Sample pooling has been shown as a cost-effective and efficient approach to conserve resources and time for testing a large number of samples [9, 10]. Present study aims to evaluate the feasibility of pool sample testing to enhance the mass screening potential of diagnostic laboratories.

2. Methodology

1389 samples were taken for this study from the upper respiratory tract (Naso- and Oro-pharyngeal swabs) and kept in a viral transport medium (VTM). All these samples have been collected at the COVID-19 sample collection center, CIMS Bilaspur C.G. All procedures were performed according to ICMR guidelines and regulations. Among 1389 samples, 600 were taken to make five pool simulations. Similarly, 789 samples for three pool simulations. For lysis, 140 µL sample was taken from three different VTM and pooled in one vial in case of 3 pool simulations. Then 140µL sample was taken from a pooled vial for RNA extraction. The same process was followed to make five pool simulations. The Viral RNA extraction was performed using the HiPurA viral RNA Purification kit (HIMEDIA, India) as per the manufacturer’s instructions. Once the RNA was extracted, 5μl was added to 20μl of the master mix (Real-Q 2019-nCoV Detection Kit BioSewoom, Korea). Positive control and negative control were used in each batch. qRT-PCR test was performed through BioRad CFX96 thermal cycler followed by thermal conditions 95°C for 15 min and then 40 cycles of 95°C for 15s, 62°C for 45s. Data analysis was done by using two-by-two tables. According to Cohen’s statistical law, the two-by-two table was prepared for three and 5-pool simulations against individual samples.

Cohen’s kappa is a statistical method commonly used to estimate the degree of agreement between two raters. Basically, it compares the probability of agreement between two independent variables.

The Cohen’s kappa degree of agreement between sample pooling tests and individual tests was performed by the following formula:

Cohen’s Kappa results could be interpreted as follows: values ≤ 0 indicates zero agreement, 0.01 – 0.20 represents none to the slight agreement, 0.21 – 0.40 as fair, 0.41–0.60 denotes moderate, 0.61–0.80 as substantial and 0.81–1.00 represents perfect agreement [11].

3. Result

Three pool and five pool simulations were prepared through 1389 swab samples. 128 pools of 600 specimens including five pool simulation were made, out of which 115 pools were found positive. After that, these pool simulations were tested individually, resulting in 128 positive samples. Individual testing was performed to obtain the number of truly positive samples. Sometimes, pool may found more than one positive sample. Cohen's kappa statistic for the 5-pool sample testing method was 0.932. Out of 600 samples, 13 samples were found discordant. The Ct value of these 13 samples is nearly 35-37. Similarly, 789 specimens were collected and merged into 263 pools to make 3-pool simulations. In this, 263 pools were reported as positive and while tested individually, all samples were found to have 100% concordance results. Cohen's kappa statistic for 3-Pool sample testing was 1.000. For the detection of COVID-19 infection in both, symptomatic and asymptomatic individuals 3-pool approach was found more suitable, sensitive and accurate than the 5-pool.[11] Positive and negative agreements between 3-pooled versus individual and 5-pooled versus individual testing were 100% and 93.8%, respectively (Table I and Table II).

Table I: Comparison of pool testing and individual testing of SARS-Cov-2 clinical specimen through qRT- PCR for 3-pool testing strategy

Table II: Comparison of pool testing and individual testing of SARS-Cov-2 clinical specimen through qRT-PCR for 5-pool testing strategy

4. Discussion

During the COVID-19 pandemic, the deficit of laboratory consumables, lack of trained human resources and shortage of kits for RNA extraction as well as for qRT-PCR has become an issue of concern [12, 13]. A pooling strategy could be used to overcome all these issues. This study evaluates the cost-effectiveness and diagnostic sensitivity of sample pooling through qRT-PCR in COVID-19 diagnosis. It was observed that both 3-sample and 5-sample pooling are almost equally accurate and had a perfect agreement with individual sample testing. However, 3-sample pooling showed low false negativity and had high concordance rates with individual sample testing. The majority of people remain asymptomatic even after the infection of SARS-CoV-2 [14]. Mass screening using pooled sample strategy may be implemented to find out positive cases to restrict the community transmission of SARS-CoV-2 [15]. Moreover, in previous studies, pooled sample testing is an effective strategy to save resources and increase the capacity of diagnostic laboratories for COVID-19 surveillance, especially in low-resource settings [16]. The present study found that batched testing of pooled samples significantly reduced the cost of testing. Similar findings had been observed in previous studies with those of current work, which releveled that pooling helps to manage the global scarcity of testing resources, thus increasing the cost-effectiveness without much hampering the accuracy and sensitivity of qRT-PCR in detecting SARS-CoV-2 [17, 18]. In this study, only two pool groups were evaluated regarding their sensitivity and cost-effectiveness. The marginal discordance of 5-sample pooling with single-sample testing focuses on the inadequacy of pooled sample testing in detecting the specimens with low positivity. In future research studies, sample pooling should be optimized by considering the range of Ct (cycle of threshold) value of samples to avoid false negativity in the low positive specimens [19] Moreover, Costa et al [20] investigated and found that qRT-PCR pool testing methods is a helpful surveillance technique to find new SARS-CoV-2 variants and assess the duration of immunogenicity and overall immunity from vaccinations the general population. The pooling technique is an intriguing tactic for the health crisis brought on by the COVID-19 pandemic, optimizes the number of tests carried out and decreases the delivery time of results. We can screen COVID-19 samples through pool testing to save material and labour resources (public health and medical laboratory personnel). With the pandemic's constantly rising case count, pool testing has a clear advantage in resource conservation [21, 22].

5. Conclusion

Based on this study, it can be concluded that all the strategies regarding SARS-CoV-2 pooling are worth to develop so the mass testing can be more cost-effective. Moreover, pooling strategies could also speed up patient screening during the infectious disease outbreak by maximizing the current testing capacity of detection in both community and healthcare workers. Based on the prevalence rate of COVID-19 in particular regions, laboratories must work on their pool validation studies for RNA extraction and amplification kits. Overall, pooling is a cost-effective approach to increase the mass screening capacity of laboratories for clinical samples through qRT-PCR. The number of tests to be performed in the mass screening of samples decreases significantly by implementing sample pooling, thus, generating less laboratory waste.

Data Availability

The authors confirm that the data supporting the findings of this study are available within the article.

Ethical Approval

This study was approved by the Institutional Ethical Committee, Chhattisgarh Institute of Medical Sciences, Bilaspur, Chhattisgarh, India (Ref. No. 211/I.E.C./CIMS/2022).

Conflict Of Interest

The authors declare no conflict of interest.

Acknowledgement

The authors are thankful to the Dean, and all virology staff, at Chhattisgarh Institute of Medical Sciences, Bilaspur, Chhattisgarh, India, for their support. We also thank Chhattisgarh Medical Services Corporation (CGMSC), South Eastern Coal India Ltd. (SECL) and Azim Premji Foundation for providing essential equipment and chemicals.

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