Validation of Saliva as the Clinical Specimen Type for a University-Wide COVID-19 Surveillance Program.

At the beginning of the COVID-19 pandemic, the Georgia Institute of Technology made the decision to keep the university doors open for on-campus attendance. To manage COVID-19 infection rates, internal resources were applied to develop and implement a mass asymptomatic surveillance program. The objective was to identify infections early for proper follow-on verification testing, contact tracing, and quarantine/isolation as needed.

Surveillance-to-Diagnostic Testing Program for Asymptomatic SARS-CoV-2 Infections on a Large, Urban Campus in Fall 2020.

Background: Six months into the COVID-19 pandemic, college campuses faced uncertainty regarding the likely prevalence and spread of disease, necessitating large-scale testing to help guide policy following re-entry.

Methods: A SARS-CoV-2 testing program combining pooled saliva sample surveillance leading to diagnosis and intervention surveyed over 112,000 samples from 18,029 students, staff and faculty, as part of integrative efforts to mitigate transmission at the Georgia Institute of Technology in Fall 2020.

Results: Cumulatively, we confirmed 1,508 individuals diagnostically, 62% of these through the surveillance program and the remainder through diagnostic tests of symptomatic individuals administered on or off campus.

Performance limits of ICA-based heart rate identification techniques in imaging photoplethysmography.

Imaging photoplethysmography is a relatively new technique for extracting biometric information from video images of faces. This is useful in non-invasive monitoring of patients including neonates or the aged, with respect to sudden infant death syndrome, sleep apnoea, pulmonary disease, physical or mental stress and other cardio-vascular conditions. In this paper, we investigate the limits of detection of the heart rate (HR) while reducing the video quality.

Signal recovery in imaging photoplethysmography.

Imaging photoplethysmography is an emerging technique for the extraction of biometric information from people using video recordings. The focus is on extracting the cardiac heart rate of the subject by analysing the luminance of the colour video signal and identifying periodic components. Advanced signal processing is needed to recover the information required.