# Package overview

The package can either be installed from CRAN, from our r-universe repository, or from GitHub. See the README for details. Once installed load the package using the following,

library(covidregionaldata)

## 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:

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. See the documentation (?get_national_data) for details of optional arguments.

Data is returned with no gaps in the structure of the data by country over time, and NAs fill in where data are not available.

## Sub-national time-series data

### Accessing sub-national data

Access sub-national level data for a specific country over time using get_regional_data(). Use get_available_datasets() to explore the currently supported sub-national datasets and select the data set of interest using the country (selects the country of interest), and level (selects the spatial scale of the data) arguments of get_regional_data.

This function 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. See the documentation (?get_regional_data) for details of optional arguments.

As for national level data any gaps in reported data are filled with NAs.

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

get_regional_data(country = "france")

This data then has the following format:

date region iso_3166_2 cases_new cases_total deaths_new deaths_total recovered_new recovered_total hosp_new hosp_total tested_new tested_total insee_code
2021-07-01 Provence-Alpes-Côte-d’Azur FR-PAC 173 3116575 NA NA NA NA NA NA 30371 54068725 93
2021-07-01 Provence-Alpes-Côte-d’Azur FR-PAC 173 3116748 NA NA NA NA NA NA 30371 54099096 93
2021-07-01 Saint-Barthelemy FR-PM 0 21 NA NA NA NA NA NA 10 1417 05
2021-07-01 Saint-Martin FR-BL 0 955 NA NA NA NA NA NA 126 35053 07
2021-07-01 Saint-Pierre et Miquelon FR-MF 8 2317 NA NA NA NA NA NA 234 42628 08

Alternatively, the same data can be accessed using the underlying class as follows (the France object now contains data at each processing step and the methods used at each step),

france <- France$new(get = TRUE) france$return()

### 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 level = "2" argument. The dataset will still show the corresponding Level 1 region.

An example of a country with Level 2 units is France, where Level 2 units are French departments:

get_regional_data(country = "france", level = "2")

This data again has the following format:

date region iso_3166_2 department ons_region_code cases_new cases_total deaths_new deaths_total recovered_new recovered_total hosp_new hosp_total tested_new tested_total insee_code
2021-07-04 Provence-Alpes-Côte-d’Azur FR-PAC Var FR-83 NA 95133 0 1497 NA NA 2 7927 NA 1712917 93
2021-07-04 Provence-Alpes-Côte-d’Azur FR-PAC Vaucluse FR-84 NA 52894 0 902 NA NA 0 5422 NA 711127 93
2021-07-04 Saint-Barthelemy FR-PM Saint-Barthelemy FR-977 NA 955 NA 0 NA NA NA 0 NA 35053 NA
2021-07-04 Saint-Martin FR-BL Saint-Martin FR-978 NA 2317 NA 0 NA NA NA 0 NA 42628 NA
2021-07-04 Saint-Pierre et Miquelon FR-MF Saint-Pierre et Miquelon FR-975 NA 21 NA 0 NA NA NA 0 NA 1417 NA

### Totals

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

get_regional_data("france", totals = TRUE)

This data now has no date variable and reflects the latest total:

region iso_3166_2 cases_total deaths_total recovered_total hosp_total tested_total
Guadeloupe FR-GP 16970 0 0 0 232070
Martinique FR-MQ 12011 0 0 0 246035
Saint-Pierre et Miquelon FR-MF 2317 0 0 0 42628
Saint-Martin FR-BL 955 0 0 0 35053
Saint-Barthelemy FR-PM 21 0 0 0 1417

## 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 level = "1".

• 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.

#### 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". Total country population estimate in 2019.