This is the code repository for our system CovidInsights. The system is online and can be found (along with more details and a demonstration video) here: www.cs.uic.edu/~indexlab/covidinsights/.
In order to confront the Covid-19 (Coronavirus) pandemic, providing insightful information about how the disease is going to evolve in the near future is critical -- both for ordinary citizens as well as policy makers.
Alongside existing exploratory tools and predictive models, in this paper, we propose CovidInsights: the first data exploration system for providing Covid-19 insights by similar examples. Our system works based on the observation that different locations experience different stages of the disease at different times. This time difference enables the opportunity to find similar historical examples that resemble the current state of a given location. This gives the users the benefit to get insights about what they might expect in the near future about the queried location. Moreover, the comparisons between similar locations give the policy makers the opportunity to explore what are the policies that did/did not work in similar situations.
CovidInsights is an opensource project, conducted in the InDeX Lab at UIC.
Team members:- Danyal Saeed, University of Illinois at Chicago
- Hasti Sharifi, University of Illinois at Chicago
- Abolfazl Asudeh, University of Illinois at Chicago
- Gautam Das, University of Texas at Arlington
