Abstract:
The purpose of this paper is to introduce a useful online interactive dashboard
(https://mahdisalehi.shinyapps.io/Covid19Dashboard/) that visualize and follow
confirmed cases of COVID-19 in real-time. The dashboard was made publicly
available on 6 April 2020 to illustrate the counts of confirmed cases, deaths, and
recoveries of COVID-19 at the level of country or continent. This dashboard is intended
as a user-friendly dashboard for researchers as well as the general public to track
the COVID-19 pandemic, and is generated from trusted data sources and built in
open-source R software (Shiny in particular); ensuring a high sense of transparency and
reproducibility. The R Shiny framework serves as a platform for visualization and analysis
of the data, as well as an advance to capitalize on existing data curation to support
and enable open science. Coded analysis here includes logistic and Gompertz growth
models, as two mathematical tools for predicting the future of the COVID-19 pandemic,
as well as the Moran’s index metric, which gives a spatial perspective via heat maps
that may assist in the identification of latent responses and behavioral patterns. This
analysis provides real-time statistical application aiming to make sense to academicand public consumers of the large amount of data that is being accumulated due to the
COVID-19 pandemic.
