covidcrosscountry

To use the package, simply run

# install devtools if not installed
install.packages("devtools") 

# install the R package
devtools::install_github("chiyahn/covidcrosscountry")

Fetching the data

covidcrosscountry::fetch_all()

Returns all the fetched data in a single `master' dataframe object. To fetch the daily data only (cases / policy updates), run

covidcrosscountry::fetch_all_daily()

covidcrosscountry::fetch_all_daily()

includes the following data:

fetch_mobility: Google COVID-19 Community Mobility Reports; movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential. Repo: https://www.google.com/covid19/mobility/
fetch_cases: 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE; cross-country data for the number of confirmed/deceased/recovered cases. Repo: https://github.com/CSSEGISandData/COVID-19
fetch_policy: Oxford Covid-19 Government Response Tracker (OxCGRT); systematic information on which governments have taken which measures, and when. Repo: https://github.com/OxCGRT/covid-policy-tracker/

covidcrosscountry::fetch_all_fixed()

includes the following data:

fetch_fixed_pwt: Penn World Table (2015 year as default); cross-country national-accounts data. Supported by an R package pwt9.
fetch_fixed_BCG: National BCG vaccine policy for 57 countries. Data from Akiyama and Ishida (2020). The compiled data can be accessed by calling DF.BCG.POLICY, whose raw data source can be found at system.file("extdata", "bcg-policy.csv", package = "covidcrosscountry").
fetch_fixed_telework: Dingel and Neiman (2020) index for the share of jobs that can be done at home for each country. Repo: https://github.com/jdingel/DingelNeiman-workathome/