Towards Preventing the next Pandemic: Hybrid Microfluidic Real-time Detection of Airborne Pathogens

Nitin Jayakumar, Michael Caffrey, IGOR PAPROTNY, University of Illinois at Chicago

     Abstract Number: 633
     Working Group: Bioaerosols

Abstract
Airborne pathogens are a reoccurring global health hazard. In December of 2019, a novel coronavirus (CoV) outbreak in the Wuhan region of China became evident, subsequently called SARS-CoV-2 virus, the causative agent of COVID-19. The number of COVID-19 cases quickly surpassed that of the 2003-2004 SARS-CoV outbreak and is the most-deadly pandemic since the 1918 influenza epidemic. In this work, we present the development of an air-microfluidic real-time air-borne pathogen detector, a concept we call "Bioaerium". This talk will address the unique challenges of combining DNA-based pathogen detection with air-microfluidic deposition in a hybrid microfluidic setup, yielding a chip-based detection scheme that has a form-factor of a smoke detector. We will present the Bioaerium technology, and show detection results using a SARS-CoV-2 model, aerozolized deactivated SARS-CoV-2 virus, as well as detection results from a COVID-19 hospital ward. We will address the utility of detecting other pathogens beyond SARS-CoV-2, and touch on our ability to screen for known and unknown mutations using AI. The research is a collaboration between UIC School of Engineering and UIC School of Medicine.