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Low-Cost, Easy to Use COVID-19 Saliva Test Provides Accurate Results within 30 Minutes

By LabMedica International staff writers
Posted on 08 Dec 2020
An at-home, COVID-19 saliva test that is designed to cost USD 5 or less uses no electricity and provides accurate results within 30 minutes.

The low-cost, fast saliva test for COVID-19 that will be the focus of a study at Stanford University School of Medicine (Stanford, CA, USA) involves little more than boiling some water, reading some instructions and spitting into a funnel. The test takes no more than 10 minutes to self-administer and is designed to detect the presence or absence of SARS-CoV-2 in saliva within 30 minutes, with an accuracy rate similar to that of the clinical tests performed in hospitals. A color display will appear yellow if there is a coronavirus infection or pink if there is no infection. The researchers estimate the kit’s retail cost, if the test is approved, to be as low as USD 5 and perhaps closer to USD 1. The test is also designed for easy, large-scale manufacture, which is crucial in the current pandemic.

Image: Manu Prakash, PhD, associate professor of bioengineering and the inventor of the test (Photo courtesy of Stanford Medicine)
Image: Manu Prakash, PhD, associate professor of bioengineering and the inventor of the test (Photo courtesy of Stanford Medicine)

“The world needs rapid-screening kits now, and at a very large scale,” said Manu Prakash, PhD, associate professor of bioengineering and the inventor of the test. “If the study is successful, our goal will be to manufacture tens of millions of them per day. We’re already building industrial partnerships to generate that capacity.”

“Our hope is to prove this works in the real world and then scale to hundreds of millions of tests to help open schools, universities and businesses as we wait for the vaccines now in development to come online,” said Euan Ashley, MB ChB, DPhil, associate dean in the School of Medicine and professor of cardiovascular medicine, of genetics and of biomedical data science.

Related Links:
Stanford Medicine


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