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New Optical Methodology for Detection of COVID-19 Beats RT-PCR in Speed and Sample Size

By LabMedica International staff writers
Posted on 21 Feb 2022
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Image: Researchers working on the project (Photo courtesy of University of Seville)
Image: Researchers working on the project (Photo courtesy of University of Seville)

An optical methodology for the rapid detection of COVID-19 provides an advantage over PCR in terms of the speed of sample processing and the ability to simultaneously analyze a large number of samples.

The new methodology developed by researchers at the University of Seville (Seville, Spain) has obtained a sensitivity of 100% and a specificity of 87.5% in the detection of SARS-CoV-2 in nasopharyngeal exudate (the same samples used in a PCR test) from symptomatic people. It has also been possible to detect the presence of SARS-CoV-2 in fresh saliva of asymptomatic people, as well as to detect, differentiate and quantify two types of synthetic viruses (lentiviruses and synthetic coronaviruses) in two biofluids (saline solution and artificial saliva).

The new methodology allows for the detection of viruses in liquid droplets and dry residues deposited on surfaces, through hyperspectral imaging and data processing based on advanced statistics and artificial intelligence. It allows rapid processing of multiple samples simultaneously, without contact or reagents and with relatively simple equipment, usable by personnel with minimal training. The new technique uses standard optical equipment and has been developed so that it can be implemented in resource-constrained settings.

However, the researchers have warned that these results should still be viewed with caution, as they constitute a 'proof of concept', with relatively small numbers of cases, under partially controlled laboratory conditions. For this reason, they are currently working on validating this new methodology under generic conditions, including new variants of the virus and the effects of vaccines.

Related Links:
University of Seville 

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