# 19: CoWiz: Interactive Covid-19 Visualization Based on Multilayer Network Analysis

Project ID: 19
Team Members: Aparna Bhat, Kunal Samant, Endrit Memeti, Abhishek Santra, Enamul Karim
Faculty Advisor(s):
Department: Computer Science & Engineering
Project Type: Graduate
Title: CoWiz: Interactive Covid-19 Visualization Based on Multilayer Network Analysis
Abstract: Covid Wizard, or CoWiz, is a Covid-19 visualization dashboard based on Multilayer Network (MLN) analysis underneath1. Online dashboards typically plot/visualize statistical information gleaned from raw data, such as daily cases, deaths, recoveries, tests, etc. However, for a better understanding, we need aggregate analysis (e.g., community, centrality) and its visualization, which is the purpose of CoWiz. As an example, grouping counties across a country/region based on similarity of increase/decrease in cases, deaths, hospitalizations over intervals are not possible without aggregate analysis. This is where CoWiz utilizes community and other concepts over MLNs that are inferred from Covid and other relevant data sets for visualization. This demo presents a flexible, interactive dashboard that is capable of visualizing various aspects of Covid-19 data, including the composition of Covid data with demographics (population density, education level, average earning, vehicle movements, and change in purchase patterns) at the granularity of county for the U.S. This paper elaborates on the types of analysis, underlying model, and how a flexible visualization dashboard has been developed using open-source software and data sets. As new data become available, they can be incorporated into the visualization with no manual intervention.
Poster: View Poster #19 (PDF)
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