Rutgers Urban and Civic Informatics Lab

Rutgers Urban and Civic Informatics Lab

CES-COVID19: Tracking Social and Economic Effects of COVID-19

The RUCI Lab’s project “CES-COVID19” is a cyberinfrastructure that captures real-time or close-to real-time data on social and economic effects of COVID-19, and brings data streams on different sectors together to support decision-making by local and regional governments and private companies in a holistic fashion for a robust recovery.

Much of the analytics related to the pandemic to date has focused on medical research to understand and contain the disease, and public health, as well as non-medical, non-clinical-care research to understand disease spread and to inform activities to deter transmission.

Yet, the current situation poses an unprecedented threat to the economy and society. For example, as of April 23, 2020, over 26 million since the pandemic shut down swaths of the US and brought the economy to a standstill. This level of initial claims for unemployment insurance indicates that the unemployment rate is already about 15%, which is well above the rate at the height of the Great Recession. The disease has also taken an extraordinary toll on older adults and communities of color, with a particularly disproportionate impact on African Americans.

The situation requires urgent action to support decision-making among a wide variety of stakeholders, not only after the crisis is over, but also in the most critical transition phases when states open up from the current lock-down situation.

Most critically, there is a need to bring together heterogeneous streams of data at a fine geographic granularity that are close to real-time, to predict impact on different areas, and to facilitate planning scenarios to facilitate recovery.

CES-COVID19 facilitates analytics to address the economic fallout of the crisis and to understand disparities that are arising using new forms of data. We are particularly focused on transportation, housing, and labor market aspects, as well as on contextual data on socio-demographics, industry sectors and the built environment.

By mining socio-demographic, mobility, jobs/unemployment, real estate, and social media data, we help provide insights into how and when COVID-19 may affect states, communities, and neighborhoods.