A team led by scientists at the University of California, Santa Barbara, announced Friday that it has designed a system that uses a smartphone’s camera to perform Covid19 tests, with accuracy that could match lab-based PCR tests.
“As new COVID variants emerge globally, testing and detection remain essential to pandemic control efforts,” said lead author Michael Mahan. “Nearly half the world’s population has a smartphone, and we believe that this holds exciting potential to provide fair and equal access to precision diagnostic medicine.”
The researchers said the kits could deliver test results in 25 minutes and were devised to be more reliable than many of the at-home tests currently on the market, reports NBC.
The process, termed smaRT-LAMP, is simple and straightforward. A small volume of the patient’s saliva is collected and analyzed by the smartphone app using the phone’s camera and the diagnostic kit. No additional specialty materials are required.
LAMP is more sensitive than RT-PCR (Real-time polymerase chain reaction), which requires expensive equipment and takes hours to run.
The collaboration was launched to develop rapid, low-cost diagnostics that can be used by healthcare providers anywhere in the world to diagnose COVID-19. The lab kit can be produced for less than $100, and it requires little more than a smartphone, a hot plate and LED lights. The screening tests can be run for less than $7 each versus $10 to $20 per rapid antigen test and $100 to $150 per PCR test.
The simple lab test can detect and differentiate COVID-19 and the flu, which show very similar respiratory disease symptoms and can lead to misdiagnosis.
“SmaRT-LAMP can detect COVID-19 and can be readily modified to detect novel CoV-2 variants and other pathogens with pandemic potential, including influenza,” said Charles Samuel of UC Santa Barbara.
The free, custom-built app was developed for the Android operating system and can be downloaded and installed from the Google Play Store. Upon opening the app, the user is presented with an option for a step-by-step tutorial prior to running test samples.