About

In December 2019, a novel respiratory infectious disease called Coronavirus (COVID-19) was reported in Wuhan, Hubei Province, China. As a severe infectious with high risk but was not been identified in humans, we observed a rapid outbreak of this tragic epidemic. Over the past two and a half years, COVID-19 has evolved into a global concern and affected all aspects of society, including daily commutes, college admissions, stocks, economics, people's work style, and even elections.

Existing Resources

With a common goal to fight this pandemic, scientific researchers from various fields and organizations have been actively collaborating and paying extensive efforts in the form of data repositories and visualization systems. Although the existing data resources have proven to be valuable, we found that they are insufficient to support multi-scale and multifaceted modeling of computational disease understanding and simulation. In actuality, the spread of infectious diseases, human movement and behavior, and social and civil infrastructures are closely intertwined. In addition, the hidden mechanism that drives their co-evolution and the resulting phenomena are usually dramatically distinctive at different observation scales. Understanding their interplay from a multi-scale perspective is critical for designing public policies and control measures. An easy interpretation for this would be the fact that policies are usually issued at multiple scales, such as national policy or school policy, which directly affects the populations at that corresponding scale and brings varying degrees of effects. For this reason, we believe it is problematic to ignore the differences of scales and model everything together.

Our Work

To this end, we offer an interactive visualization dashboard and a multi-scale geospatial dataset by taking into account the geographical and social properties of locations and their connections, and the populations within.