The stable release of this package is hosted on CRAN. The development version is available at Github.
The only function in the package is covid19()
.
By default, the function downloads worldwide data by country:
x <- covid19()
The argument level
specifies the granularity of the
data:
Download worldwide data by state:
x <- covid19(level = 2)
The argument country
filters the data by country. This
is a vector of country names or ISO
codes (ISO 3166-1 Alpha-2 code, Alpha-3 code, or numeric code).
Download data for Italy and Unites States at county/province level:
The arguments start
and end
specify the
period of interest. The data are subsetted to match this time range.
Download national-level data for United States from 01 October 2021 to 01 November 2021:
x <- covid19("US", start = "2021-10-01", end = "2021-11-01")
The parameter vintage
allows to retrieve the snapshot of
the dataset that was available on the given date. This typically differs
from subsetting the latest data, as most governments are updating the
data retroactively. Available since 14 April, 2020.
Retrieve the data that were available on 15 May, 2020:
x <- covid19(vintage = "2020-05-15")
The argument dir
specifies the folder where the data
files are to be downloaded. By default this is a temporary folder.
Download the files in the folder data
:
dir.create("data")
x <- covid19(dir = "data")
Country-level covariates by World Bank Open Data can be added
via the argument wb
. This is a character vector of
indicator codes to download. The codes can be found by inspecting the
corresponding URL. For example, the code of the indicator “Hospital beds
(per 1,000 people)” available at https://data.worldbank.org/indicator/SH.MED.BEDS.ZS is
SH.MED.BEDS.ZS
. The indicators are typically available at a
yearly frequency. This function returns the latest data available
between the start
and the end
date. See the
table at the bottom of this
page for suggested indicators. Example using GDP and number of
hospital beds:
Mobility data by Google Mobility
Reports can be added via the argument gmr
. This is the
link to the Google “CSV by geographic area” ZIP folder. At the time of
writing, the link is https://www.gstatic.com/covid19/mobility/Region_Mobility_Report_CSVs.zip.
As the link has been stable since the beginning of the pandemic, the
function accepts gmr=TRUE
to automatically use this
link.
x <- covid19(gmr = TRUE)
Mobility data by Apple
Mobility Reports can be added via the argument amr
.
This is the link to the Apple “All CSV data” file. This link is changing
constantly. Consider downloading the data file from the website first,
and then set amr="path/to/file.csv"
. Since v3.0.1 of the
package, if amr=TRUE
is provided, the function tries to
detect the latest URL from this
endpoint.
x <- covid19(amr = TRUE)
We have invested a lot of time and effort in creating COVID-19 Data Hub, please:
The output data files are published under the CC BY license. All other code and assets are published under the GPL-3 license.
Guidotti, E., Ardia, D., (2020), “COVID-19 Data Hub”, Journal of Open Source Software 5(51):2376, doi: 10.21105/joss.02376.
A BibTeX entry for LaTeX users is:
@Article{guidotti2020,
title = {COVID-19 Data Hub},
year = {2020},
doi = {10.21105/joss.02376},
author = {Emanuele Guidotti and David Ardia},
journal = {Journal of Open Source Software},
volume = {5},
number = {51},
pages = {2376}
}
The implementation details and the latest version of the data are described in:
Guidotti, E., (2022), “A worldwide epidemiological database for COVID-19 at fine-grained spatial resolution”, Sci Data 9(1):112, doi: 10.1038/s41597-022-01245-1
A BibTeX entry for LaTeX users is:
Comments