Evidence map›Paper›PMID 37608098›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Digital PCR: A Partitioning-Based Application for Detection and Surveillance of SARS-CoV-2 from Sewage Samples.

Bhumika Prajapati, Dalipsingh Rathore, Chaitanya Joshi, Madhvi Joshi

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Bhumika PrajapatiGujarat Biotechnology Research Centre (GBRC), Department of Science and Technology, Government of Gujarat, Gandhinagar, India.
Dalipsingh RathoreGujarat Biotechnology Research Centre (GBRC), Department of Science and Technology, Government of Gujarat, Gandhinagar, India.
Chaitanya JoshiGujarat Biotechnology Research Centre (GBRC), Department of Science and Technology, Government of Gujarat, Gandhinagar, India.
Madhvi JoshiGujarat Biotechnology Research Centre (GBRC), Department of Science and Technology, Government of Gujarat, Gandhinagar, India. jd1@gbrc.res.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The wastewater-based surveillance of SARS-CoV-2 has emerged as a potential tool for cost-effective, simple, and long-term monitoring of the pandemic. Since the COVID-19 pandemic, several developed countries have incorporated the national wastewater surveillance program into their national policies related to pandemic management. Various research groups have utilized the approach of real-time quantitative reverse transcription PCR (RT-qPCR) for the quantification of SARS-CoV-2 from environmental samples like sewage water. However, detection and quantification using RT-qPCR relies on standards and is known to have lesser tolerance to inhibitors present in the sample. Unlike RT-qPCR, digital PCR (dPCR) offers an absolute and sensitive quantification without a need reference and offers higher tolerance to inhibitors present in the wastewater samples. Additionally, the accuracy of detection increases with the presence of rare target copies in the sample. The methodology herein presented comprises the detection and quantification of SARS-CoV-2 from sewer shed samples using the dPCR approach. The main features of the process include virus concentration and absolute quantification of the virus surpassing the substantial presence of inhibitors in the sample. This chapter presents the optimized PEG and NaCl-based protocol for virus concentration followed by nucleic acid extraction and quantification using CDC-approved N1 + N2 assay. The protocol uses MS2 bacteriophage as a process recovery or internal control.The methodology herein described highlights the importance of digital PCR technologies for environmental surveillance of important emerging pathogens or pandemics.

Indexed as

COVID-19SARS-CoV-2COVID-19 TestingHumansPandemicsReal-Time Polymerase Chain ReactionSewageWastewaterWastewater-Based Epidemiological MonitoringSewageWastewaterAbsolute quantificationCOVID-19 pandemicDigital PCRSARS-CoV-2Wastewater-based epidemiology

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.