CDS Prof. Ye and ECSE Prof. Loparo received NSF RAPID Award to develop AI technologies for real-time COVID-19 risk assessment

\MyWeb\Website_20200425\files\fanny_3.jpgDr. Yanfang (Fanny) Ye, Theodore L. and Dana J. Schroeder Associate Professor in the department of computer and data sciences at Case Western Reserve University (CWRU), and her collaborator Dr. Kenneth Loparo, Arthur L. Parker Professor in the department of electrical, computer and systems engineering at CWRU, have been awarded a RAPID grant from the National Science Foundation in support of their work to develop novel artificial intelligence (AI) techniques for real-time COVID-19 risk assessment. The award comes with $84,000 dollars in funding over a one-year period.

According to the Centers for Disease Control and Prevention (CDC), before a vaccine or drug becomes widely available, community mitigation, which is a set of actions that persons and communities can take to help slow the spread of respiratory virus infections, is the most readily available intervention to help slow transmission of the virus in communities. “A growing number of areas are reporting community transmission of the virus, which would represent a significant turn for the worse in the battle against the novel coronavirus,” said Ye. “This points to an urgent need for expanded surveillance so we can better understand the spread of COVID-19 and better respond with actionable strategies for community mitigation.” By advancing capabilities of AI and leveraging the large-scale and real-time data generated from heterogeneous sources, Profs. Ye and Loparo will focus their efforts on the development of new AI technologies to provide real-time hierarchical community-level risk assessment to help combat the COVID-19 pandemic.

After the team launched the prototype system, named alpha-Satellite, for public testing on April 20, it had attracted 42,546 users in the first week. The large number of its users indicate the high demand from the public for effective computational tools to assist people with actionable strategies for protection while minimizing disruptions to daily life. The system also provides an analysis board for COVID-19 comparisons and trend analysis for user’s selected counties and states. The developed alpha-Satellite has gotten a lot of good feedback from the media and users on the ease of use of the system as well as the utility of the relative risk estimation. 

Motivated by the high demand and generous feedback from the public, as more and more places are preparing or devising strategies for reopening, the team will continue their efforts to improve the system by advancing AI-driven techniques to facilitate not only individuals but also organizations for decision making for the reopening. The public can access the AI-driven system here: https://covid-19.yes-lab.org/