Subnational data for the Covid-19 outbreak

An interface to subnational and national level Covid-19 data. For all countries supported, this includes a daily time-series of cases. Wherever available we also provide data on deaths, hospitalisations, and tests. National level data is also supported using a range of data sources as well as linelist data and links to intervention data sets.

Installation

Install from CRAN:

install.packages("covidregionaldata")

Install the stable development version of the package with:

install.packages("drat")
drat:::add("epiforecasts")
install.packages("covidregionaldata")

Install the unstable development version of the package with:

remotes::install_github("epiforecasts/covidregionaldata")

Quick start

To get worldwide time-series data by country (sourced from the ECDC), use get_national_data():

covidregionaldata::get_national_data()

To get time-series data for subnational regions of a specific country, for example by local authority in the UK, use get_regional_data():

covidregionaldata::get_regional_data(country = "UK", include_level_2_regions = TRUE)

Subnational regions are only available in some countries. See below section 4, "Coverage".

Usage

Worldwide data

Accessing national data

Both the World Health Organisation (WHO) and European Centre for Disease Control (ECDC) provide worldwide national data. Access national level data for any country using:

covidregionaldata::get_national_data()

This returns daily new and cumulative (total) cases, and where available, deaths, hospitalisations, and tests. For a complete list of variables returned, see section 5, "Data glossary" below.

This function takes 3 optional arguments:

• country (optional) - a country name (in any language) for which to return national level data. This argument permits any country in the United Nations and reported by the specified data source (ECDC or WHO). If not specified, all countries will be returned.

• source (optional, default is "ECDC") - the data source for national data. Either "ECDC" or "WHO".

• totals (optional, default is FALSE) - a Boolean (TRUE/FALSE), denoting whether the data returned should be a table of total counts (one row per country) or time series data (one row per country/date combination).

This returns data in the same structure as get_regional_data(). This means there are no gaps in the structure of the data by country over time, and NAs fill in where data are not available.

Accessing national government interventions

A further function for worldwide data extracts non-pharmaceutical interventions by country:

• covidregionaldata::get_interventions_data()

Accessing a patient linelist

Patient linelist data is useful for exploring delays and lags in reporting. An anonymised international patient linelist can be imported and cleaned with:

• covidregionaldata::get_linelist()

Sub-national time-series data

Accessing sub-national data

Access sub-national level data for a specific country over time by using covidregionaldata::get_regional_data().

This returns daily new and cumulative (total) cases, and where available, deaths, hospitalisations, and tests. For a complete list of variables returned, see section 5, "Data glossary" below.

The function takes 3 arguments:

• country - the English name of the country of interest. Not case sensitive
• totals (optional, default is FALSE) - a Boolean (TRUE/FALSE), denoting whether the data returned should be a table of total counts (one row per region) or time series data (one row per region/date combination).
• include_level_2_regions (optional, default is FALSE) - a Boolean (TRUE/FALSE), denoting whether the data returned should be stratified by admin level 1 region (usually the largest subregion available) or admin level 2 region (usually the second largest).

This returns a dataset with one row for each region for each date. For all regions, dates span from the first date until the last date that data are available for any region in the country. This means there are no gaps in the structure of the data, although NAs fill in where data are not available.

For example, data for Belgium Level 1 regions over time can be accessed using:

get_regional_data(country = "Belgium")

This returns a dataset in this format:

Level 1 and Level 2 regions

All countries included in the package (see below,"Coverage") have data for regions at the admin-1 level, the largest administrative unit of the country (e.g. state in the USA). Some countries also have data for smaller areas at the admin-2 level (e.g. county in the USA).

Data for Level 2 units can be returned by using the include_level_2_regions = TRUE argument. The dataset will still show the corresponding Level 1 region.

An example of a country with Level 2 units is Belgium, where Level 2 units are Belgian provinces:

covidregionaldata::get_regional_data("Belgium", include_level_2_regions = TRUE)

This returns a dataset with the format:

Totals

For totalled data up to the most recent date available, use the totals argument.

covidregionaldata::get_regional_data("Belgium", totals = TRUE)

This returns a dataset with one row for each region, in the same format:

Sub-national coverage

We include sub-national data in the following countries. These are the accepted country names when using get_regional_data(country = "").

We are hoping to expand over time (see below "Development").

Data glossary

Subnational data

The data columns that will be returned by get_regional_data() are listed below.

To standardise across countries and regions, the columns returned for each country will always be the same. If the corresponding data was missing from the original source then that data field is filled with NA values (or 0 if accessing totals data).

Note that Date is not included if the totals argument is set to TRUE. Level 2 region/level 2 region code are not included if the include_level_2_regions argument is set to FALSE.

• date: the date that the counts were reported (YYYY-MM-DD).
• level 1 region: the level 1 region name. This column will be named differently for different countries (e.g. state, province).
• level 1 region code: a standard code for the level 1 region. The column name reflects the specific administrative code used. Typically data returns the iso_3166_2 standard, although where not available the column will be named differently to reflect its source.
• level 2 region: the level 2 region name. This column will be named differently for different countries (e.g. city, county).
• level 2 region code: a standard code for the level 2 region. The column will be named differently for different countries (e.g. fips in the USA).
• cases_new: new reported cases for that day
• cases_total: total reported cases up to and including that day
• deaths_new: new reported deaths for that day
• deaths_total: total reported deaths up to and including that day
• recovered_new: new reported recoveries for that day
• recovered_total: total reported recoveries up to and including that day
• hosp_new: new reported hospitalisations for that day
• hosp_total: total reported hospitalisations up to and including that day (note this is cumulative total of new reported, not total currently in hospital)
• tested_new: tests for that day
• tested_total: total tests completed up to and including that day

The exception to this is data for the UK. This is in its raw state, as regions have separate and sometimes incompatible data reporting.

National data

In addition to the above, the following columns are included when using get_national_data().

• un_region: country geographical region defined by the United Nations.
• who_region: only included when source = "WHO". Country geographical region defined by WHO.
• population_2019: only included when source = "ECDC" (the default). Total country population estimate in 2019.

Development

We welcome contributions and new contributors! We particularly appreciate help adding new data sources for countries at sub-national level, or work on priority problems in the issues. Please check and add to the issues, and/or add a pull request. For more detail, please read the System Maintenance Guide.