Testing of four-sample pools offers resource optimization without compromising diagnostic performance of real time reverse transcriptase-PCR assay for COVID-19

Autor: Bijina J. Mathew, Jogender Yadav, Arti Shrivas, Shashwati Nema, Ranu Tripathi, Anirudh K. Singh, Ritu Pandey, Debasis Biswas, Sarman Singh, Kuldeep Singh, Ashvini Kumar Yadav, Arun Raghuwanshi, Kudsia Ansari, Prem Shankar, Chitra Patankar, Ankur Joshi, Sudheer Gupta, Ram Kumar Nema
Jazyk: angličtina
Rok vydání: 2021
Předmět:
RNA viruses
Viral Diseases
Epidemiology
Coronaviruses
Pooling
Prevalence
Artificial Gene Amplification and Extension
Polymerase Chain Reaction
Turnaround time
Geographical Locations
Medical Conditions
Statistics
Medicine and Health Sciences
Pathology and laboratory medicine
Virus Testing
Multidisciplinary
Medical microbiology
Reverse transcription polymerase chain reaction
Infectious Diseases
COVID-19 Nucleic Acid Testing
Viruses
RNA
Viral

Medicine
SARS CoV 2
Pathogens
Research Article
Asia
SARS coronavirus
Coronavirus disease 2019 (COVID-19)
Concordance
Sample (material)
Science
India
Biology
Real-Time Polymerase Chain Reaction
Research and Analysis Methods
Microbiology
Specimen Handling
Extraction techniques
Diagnostic Medicine
Humans
Molecular Biology Techniques
Molecular Biology
SARS-CoV-2
Organisms
Viral pathogens
COVID-19
Biology and Life Sciences
Covid 19
Reverse Transcriptase-Polymerase Chain Reaction
Gold standard (test)
RNA extraction
Microbial pathogens
People and Places
Zdroj: PLoS ONE, Vol 16, Iss 5, p e0251891 (2021)
PLoS ONE
ISSN: 1932-6203
Popis: Quick identification and isolation of SARS-CoV-2 infected individuals is central to managing the COVID-19 pandemic. Real time reverse transcriptase PCR (rRT-PCR) is the gold standard for COVID-19 diagnosis. However, this resource-intensive and relatively lengthy technique is not ideally suited for mass testing. While pooled testing offers substantial savings in cost and time, the size of the optimum pool that offers complete concordance with results of individualized testing remains elusive. To determine the optimum pool size, we first evaluated the utility of pool testing using simulated 5-sample pools with varying proportions of positive and negative samples. We observed that 5-sample pool testing resulted in false negativity rate of 5% when the pools contained one positive sample. We then examined the diagnostic performance of 4-sample pools in the operational setting of a diagnostic laboratory using 500 consecutive samples in 125 pools. With background prevalence of 2.4%, this 4-sample pool testing showed 100% concordance with individualized testing and resulted in 66% and 59% reduction in resource and turnaround time, respectively. Since the negative predictive value of a diagnostic test varies inversely with prevalence, we re-tested the 4-sample pooling strategy using a fresh batch of 500 samples in 125 pools when the prevalence rose to 12.7% and recorded 100% concordance and reduction in cost and turnaround time by 36% and 30%, respectively. These observations led us to conclude that 4-sample pool testing offers the optimal blend of resource optimization and diagnostic performance across difference disease prevalence settings.
Databáze: OpenAIRE