Grant: Project Grant

Viral respiratory tract infections (VRTI) like the flu and COVID-19 are among the most common human illnesses, impacting billions globally. There is an unmet need to identify novel ways to detect, treat and prevent their spread. A new technology harnessing wearable biosensors (wearables) worn by people could address this need. We will assess the potential of wearables to detect small changes in vital sign patterns (e.g., breathing, heart rate variability, oxygen saturation, skin temperature, sweat level, blood pressure) and activity levels that can accompany VRTIs. METHODS: A clinical study of 60 healthy adults aged 18-59 years. Participants' vital signs and activity levels will be monitored continuously using wearable biosensors for 7-days prior to and 7-days following receipt of live attenuated influenza virus (FluMist vaccine), along with symptom tracking and blood tests to measure immune responses. Artificial intelligence (AI) and machine learning (ML) algorithms will be used to analyze the data and develop a detection model for low grade influenza infection. EXPECTED OUTCOMES: This multidisciplinary study will assess a new indication for wearable biosensor technologies. AI and ML will identify subtle changes in vital signs and activity levels from the immune response to respiratory viruses. These data will help design future studies to address important public health questions related to respiratory virus detection, containment and management.