Dataset from Detection and Automatic Privacy-Protected Contact Tracing System Designed for COVID-19

Background: The goal of the study was to develop a pipeline for automatic detection and tracing of active SARS-CoV-2 infection in a cost-effective, highly accurate, real-time, portable, and super-encrypted manner.

Materials/Methods: This integrated approach first captured viral particles from patient samples to activate fluorescence reporters, followed by signal detection using a smartphone fluorimeter, along with blockchain-based data processing and tracing. Designer DNA net nanostructures were deployed that matched the spatial pattern of trimeric spike glycoprotein clusters on the viral outer surface for specific and rapid SARS-CoV-2 virion detection, smartphone-based point-of-care device for portable signal reading, and blockchain encryption for privacy protection during result recording and track tracing,

Outcome/Impact: This detection and tracing model allowed a direct, automatic, and cost-effective detection, a highly flexible result acquisition process, and a super-encrypted data transition and tracing system.