Load and Analyze Live Data from the COVID-19 Pandemic

Load and analyze updated time series worldwide data of reported cases for the Novel Coronavirus Disease (COVID-19) from different sources, including the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) data repository <>, "Our World in Data" <> among several others. The datasets reporting the COVID-19 cases are available in two main modalities, as a time series sequences and aggregated data for the last day with greater spatial resolution. Several analysis, visualization and modelling functions are available in the package that will allow the user to compute and visualize total number of cases, total number of changes and growth rate globally or for an specific geographical location, while at the same time generating models using these trends; generate interactive visualizations and generate Susceptible-Infected-Recovered (SIR) model for the disease spread.

Imports: readxl, ape, rentrez, curl, plotly, htmlwidgets, deSolve, gplots, pheatmap, shiny, shinydashboard, shinycssloaders, DT, dplyr, collapsibleTree
Suggests: knitr, devtools, roxygen2, markdown, rmarkdown, testthat
Published: 2023-10-15
DOI: 10.32614/
Author: Marcelo Ponce [aut, cre], Amit Sandhel [ctb]
Maintainer: Marcelo Ponce <m.ponce at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: citation info
Materials: README NEWS
In views: Epidemiology
CRAN checks: results


Reference manual:
Vignettes: covid19 Package


Package source: covid19.analytics_2.1.3.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): covid19.analytics_2.1.3.3.tgz, r-oldrel (arm64): covid19.analytics_2.1.3.3.tgz, r-release (x86_64): covid19.analytics_2.1.3.3.tgz, r-oldrel (x86_64): covid19.analytics_2.1.3.3.tgz
Old sources: archive


Please use the canonical form to link to this page.