R scripts to process/cleanup data from the repo: https://github.com/CSSEGISandData/COVID-19 into tidy datasets[1]
Last updated on 2020-03-19 01:49:54 UTC
Data source commit reference: 9a04578c641092583e4eb93ab92a68fa5bacb5e9
Notes
- For the cases, I’ve used the filename to to get the timestamp, because that is more reliable
- 2020-02-14: the original data source has changed its data structure, the timeseries data is empty as of the commit referred below.
- 2020-02-27: changed code to reflect changes in source data files.
- 2020-03-04: added Continents and ISO-3 country codes, using the
countrycode
R package. - 2020-03-05:
- Latitude and longitude information started appearing in cases files in March, used that to add that information the rest of the cases.
- Added code to tidy the WHO situation report timeseries
- 2020-03-12: source data no longer has the classification “Others” for locations not corresponding to countries (i.e. Cruise Ships), so the code has been modified to account for that change.
Files
covid-19_cases_raw.csv
: CSV with processed cases filecovid-19_cases_raw.RDS
: RDS format version
Data structure:
- continent: Geographical continent
- who_region: WHO region
- country_region: Country (or region)
- iso3c: ISO 3166-1 alpha-3 country code
- province_state: Province/State/Subnational division
- confirmed: Cummulative number of confirmed cases
- dead: Cummulative number of deaths
- recovered: Cummulative number of recovered cases
- lat: Latitude
- lon: Longitude
- update: Entry timestamp update in “YYYY-MM-DD hh:mm:ss” format
- data_update: Data file update date in “YYYY-MM-DD” format
- who_region_code: WHO region code
- who_region: WHO region
- world_bank_income_group: World Bank Income Group
- world_bank_income_group_code: World Bank Income Group code
- world_bank_income_group_gni_reference_year: World Bank Income Group GNI reference year
- world_bank_income_group_release_date: World Bank Income Group release year
Files
covid-19_ts_combined.csv
: CSV with combined timeseries datacovid-19_ts_combined.rds
: RDS version (tsibble
)covid-19_ts_confirmed.csv
: CSV file with confirmed casescovid-19_ts_confirmed.rds
: RDS version (tsibble
)covid-19_ts_deaths.csv
: CSV file with deathscovid-19_ts_deaths.rds
: RDS version (tsibble
)covid-19_ts_recovered.csv
: CSV file with recovered casescovid-19_ts_recovered.rds
: RDS version (tsibble
)
Data structure:
- continent: Geographical continent
- iso3c: ISO 3166-1 alpha-3 country code
- country_region: Country (or region)
- province_state: Province/State/Subnational division
- ts: UTC date in “YYYY-MM-DD” format
- confirmed: number of confirmed cases at ts (in combined and confirmed timeseries)
- deaths: number of deaths at ts (in combined and deaths timeseries)
- recovered: number of recovered cases at ts (in combined and recovered timeseries)
- lat: Latitude
- lon: Longitude
- who_region: WHO region
- who_region_code: WHO region code
- world_bank_income_group: World Bank Income Group
- world_bank_income_group_code: World Bank Income Group code
- world_bank_income_group_gni_reference_year: World Bank Income Group GNI reference year
- world_bank_income_group_release_date: World Bank Income Group release year
Files:
covid-19_who_sitrep_raw.rds
: Lightly cleaned WHO situation report in RDS formatcovid-19_ts_who_sitrep.csv
: Timeseries from WHO situation reportscovid-19_ts_who_sitrep.rds
: RDS version (tsibble
)
Data structure:
- continent: Geographical continent
- iso3c: ISO 3166-1 alpha-3 country code
- country_region: Country (or region)
- province_state: Province/State/Subnational division
- ts: UTC date in “YYYY-MM-DD” format
- cases: number of cases at ts
- who_region: WHO region
- who_region_code: WHO region code
- world_bank_income_group: World Bank Income Group
- world_bank_income_group_code: World Bank Income Group code
- world_bank_income_group_gni_reference_year: World Bank Income Group GNI reference year
- world_bank_income_group_release_date: World Bank Income Group release year
Source: https://apps.who.int/gho/data/node.metadata.COUNTRY?lang=en (CSV Xmart format)
Files:
xmart.csv
: CSV Xmart format (downloaded on 2020-03-09)who_metadata.Rdata
: Rdata format version
Data structure:
- continent: Geographical continent
- who_region: WHO region
- country_region: Country (or region)
- iso3c: ISO 3166-1 alpha-3 country code
- province_state: Province/State/Subnational division
- ts: UTC timestamp in “YYYY-MM-DD hh:mm:ss” format
- cases: Number of cases
- who_region_code: Code for WHO region
- world_bank_income_group: World Bank Income Group
- world_bank_income_group_code: World Bank Income Group code
- world_bank_income_group_gni_reference_year: World Bank Income Group GNI reference year
- world_bank_income_group_release_date: World Bank Income Group release year
Source: https://databank.worldbank.org/source/population-estimates-and-projections
Files: -
Data_Extract_From_Population_estimates_and_projections.zip
: data and
metadata from World Bank (dowloaded on 2020-03-14) -
wb_population.Rdata
: Rdata format
Data Structure (Rdata file):
- country_name: Country name
- country_code: ISO 3166-1 alpha-3 country code
- series_name: World Bank variable name
- series_code: World Bank variable code
- population_2020: Estimated polution for 2020
Here are couple of quick tables:
continent | iso3c | country_region | province_state | confirmed | deaths | recovered | global_confirmed_pct | global_death_pct | global_recovered_pct | who_region_code | who_region | world_bank_income_group | world_bank_income_group_code | world_bank_income_group_gni_reference_year | world_bank_income_group_release_date |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Asia | CHN | China | Hubei | 67800 | 3122 | 56927 | 31.547 | 35.749 | 68.329 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Guangdong | 1370 | 8 | 1313 | 0.637 | 0.092 | 1.576 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Henan | 1273 | 22 | 1250 | 0.592 | 0.252 | 1.500 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Zhejiang | 1232 | 1 | 1216 | 0.573 | 0.011 | 1.460 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Hunan | 1018 | 4 | 1014 | 0.474 | 0.046 | 1.217 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Anhui | 990 | 6 | 984 | 0.461 | 0.069 | 1.181 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Jiangxi | 935 | 1 | 934 | 0.435 | 0.011 | 1.121 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Shandong | 761 | 7 | 746 | 0.354 | 0.080 | 0.895 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Jiangsu | 631 | 0 | 631 | 0.294 | 0.000 | 0.757 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Chongqing | 576 | 6 | 570 | 0.268 | 0.069 | 0.684 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Sichuan | 540 | 3 | 525 | 0.251 | 0.034 | 0.630 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Heilongjiang | 482 | 13 | 459 | 0.224 | 0.149 | 0.551 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Beijing | 469 | 8 | 378 | 0.218 | 0.092 | 0.454 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Shanghai | 361 | 3 | 326 | 0.168 | 0.034 | 0.391 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Hebei | 318 | 6 | 310 | 0.148 | 0.069 | 0.372 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Fujian | 296 | 1 | 295 | 0.138 | 0.011 | 0.354 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Guangxi | 253 | 2 | 250 | 0.118 | 0.023 | 0.300 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Shaanxi | 246 | 3 | 237 | 0.114 | 0.034 | 0.284 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Hong Kong | 181 | 4 | 92 | 0.084 | 0.046 | 0.110 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Yunnan | 176 | 2 | 172 | 0.082 | 0.023 | 0.206 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Hainan | 168 | 6 | 161 | 0.078 | 0.069 | 0.193 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Guizhou | 146 | 2 | 144 | 0.068 | 0.023 | 0.173 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Tianjin | 136 | 3 | 133 | 0.063 | 0.034 | 0.160 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Shanxi | 133 | 0 | 133 | 0.062 | 0.000 | 0.160 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Gansu | 133 | 2 | 91 | 0.062 | 0.023 | 0.109 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Liaoning | 125 | 1 | 122 | 0.058 | 0.011 | 0.146 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Jilin | 93 | 1 | 92 | 0.043 | 0.011 | 0.110 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Xinjiang | 76 | 3 | 73 | 0.035 | 0.034 | 0.088 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Inner Mongolia | 75 | 1 | 73 | 0.035 | 0.011 | 0.088 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Ningxia | 75 | 0 | 75 | 0.035 | 0.000 | 0.090 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Qinghai | 18 | 0 | 18 | 0.008 | 0.000 | 0.022 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Macau | 15 | 0 | 10 | 0.007 | 0.000 | 0.012 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | CHN | China | Tibet | 1 | 0 | 1 | 0.000 | 0.000 | 0.001 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
continent | iso3c | country_region | province_state | confirmed | deaths | recovered | global_confirmed_pct | global_death_pct | global_recovered_pct | who_region_code | who_region | world_bank_income_group | world_bank_income_group_code | world_bank_income_group_gni_reference_year | world_bank_income_group_release_date |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Europe | ITA | Italy | NA | 35713 | 2978 | 4025 | 16.617 | 34.101 | 4.831 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Asia | IRN | Iran | NA | 17361 | 1135 | 5389 | 8.078 | 12.997 | 6.468 | EMR | Eastern Mediterranean | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | ESP | Spain | NA | 13910 | 623 | 1081 | 6.472 | 7.134 | 1.298 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | DEU | Germany | NA | 12327 | 28 | 105 | 5.736 | 0.321 | 0.126 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | FRA | France | France | 9043 | 148 | 12 | 4.208 | 1.695 | 0.014 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Asia | KOR | Korea, South | NA | 8413 | 84 | 1540 | 3.915 | 0.962 | 1.848 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Europe | CHE | Switzerland | NA | 3028 | 28 | 15 | 1.409 | 0.321 | 0.018 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | GBR | United Kingdom | United Kingdom | 2626 | 71 | 65 | 1.222 | 0.813 | 0.078 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | New York | 2495 | 16 | 0 | 1.161 | 0.183 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Europe | NLD | Netherlands | Netherlands | 2051 | 58 | 2 | 0.954 | 0.664 | 0.002 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | AUT | Austria | NA | 1646 | 4 | 9 | 0.766 | 0.046 | 0.011 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | NOR | Norway | NA | 1550 | 6 | 1 | 0.721 | 0.069 | 0.001 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | BEL | Belgium | NA | 1486 | 14 | 31 | 0.691 | 0.160 | 0.037 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | SWE | Sweden | NA | 1279 | 10 | 1 | 0.595 | 0.115 | 0.001 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | DNK | Denmark | Denmark | 1057 | 4 | 1 | 0.492 | 0.046 | 0.001 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Washington | 1014 | 55 | 0 | 0.472 | 0.630 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | JPN | Japan | NA | 889 | 29 | 144 | 0.414 | 0.332 | 0.173 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Asia | MYS | Malaysia | NA | 790 | 2 | 60 | 0.368 | 0.023 | 0.072 | WPR | Western Pacific | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | USA | US | California | 751 | 13 | 0 | 0.349 | 0.149 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Cruise Ship | Cruise Ship | Cruise Ship | Diamond Princess | 712 | 7 | 325 | 0.331 | 0.080 | 0.390 | NA | NA | NA | NA | NA | NA |
Europe | CZE | Czechia | NA | 464 | 0 | 3 | 0.216 | 0.000 | 0.004 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Asia | QAT | Qatar | NA | 452 | 0 | 4 | 0.210 | 0.000 | 0.005 | EMR | Eastern Mediterranean | High income | WB_HI | 2017 | 2018 |
Europe | PRT | Portugal | NA | 448 | 2 | 3 | 0.208 | 0.023 | 0.004 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Asia | ISR | Israel | NA | 433 | 0 | 11 | 0.201 | 0.000 | 0.013 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | GRC | Greece | NA | 418 | 5 | 8 | 0.194 | 0.057 | 0.010 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | BRA | Brazil | NA | 372 | 3 | 2 | 0.173 | 0.034 | 0.002 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | FIN | Finland | NA | 336 | 0 | 10 | 0.156 | 0.000 | 0.012 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Florida | 314 | 7 | 0 | 0.146 | 0.080 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | SGP | Singapore | NA | 313 | 0 | 114 | 0.146 | 0.000 | 0.137 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Asia | PAK | Pakistan | NA | 299 | 0 | 2 | 0.139 | 0.000 | 0.002 | EMR | Eastern Mediterranean | Lower middle income | WB_LMI | 2017 | 2018 |
Europe | IRL | Ireland | NA | 292 | 2 | 5 | 0.136 | 0.023 | 0.006 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | SVN | Slovenia | NA | 275 | 1 | 0 | 0.128 | 0.011 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Oceania | AUS | Australia | New South Wales | 267 | 5 | 4 | 0.124 | 0.057 | 0.005 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | New Jersey | 267 | 3 | 0 | 0.124 | 0.034 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Europe | ROU | Romania | NA | 260 | 0 | 19 | 0.121 | 0.000 | 0.023 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | EST | Estonia | NA | 258 | 0 | 1 | 0.120 | 0.000 | 0.001 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Louisiana | 257 | 4 | 0 | 0.120 | 0.046 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | BHR | Bahrain | NA | 256 | 1 | 88 | 0.119 | 0.011 | 0.106 | EMR | Eastern Mediterranean | High income | WB_HI | 2017 | 2018 |
Europe | POL | Poland | NA | 251 | 5 | 13 | 0.117 | 0.057 | 0.016 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | ISL | Iceland | NA | 250 | 1 | 5 | 0.116 | 0.011 | 0.006 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | CHL | Chile | NA | 238 | 0 | 0 | 0.111 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | IDN | Indonesia | NA | 227 | 19 | 11 | 0.106 | 0.218 | 0.013 | SEAR | South-East Asia | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | CAN | Canada | Ontario | 221 | 1 | 5 | 0.103 | 0.011 | 0.006 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Massachusetts | 218 | 0 | 0 | 0.101 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | THA | Thailand | NA | 212 | 1 | 42 | 0.099 | 0.011 | 0.050 | SEAR | South-East Asia | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | LUX | Luxembourg | NA | 203 | 2 | 0 | 0.094 | 0.023 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Asia | PHL | Philippines | NA | 202 | 19 | 5 | 0.094 | 0.218 | 0.006 | WPR | Western Pacific | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | USA | US | Georgia | 199 | 3 | 0 | 0.093 | 0.034 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Africa | EGY | Egypt | NA | 196 | 6 | 32 | 0.091 | 0.069 | 0.038 | EMR | Eastern Mediterranean | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | CAN | Canada | British Columbia | 186 | 7 | 4 | 0.087 | 0.080 | 0.005 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Colorado | 184 | 2 | 0 | 0.086 | 0.023 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Texas | 173 | 3 | 0 | 0.080 | 0.034 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | SAU | Saudi Arabia | NA | 171 | 0 | 6 | 0.080 | 0.000 | 0.007 | EMR | Eastern Mediterranean | High income | WB_HI | 2017 | 2018 |
Asia | IRQ | Iraq | NA | 164 | 12 | 43 | 0.076 | 0.137 | 0.052 | EMR | Eastern Mediterranean | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | USA | US | Illinois | 162 | 1 | 0 | 0.075 | 0.011 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | IND | India | NA | 156 | 3 | 14 | 0.073 | 0.034 | 0.017 | SEAR | South-East Asia | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | USA | US | Pennsylvania | 152 | 0 | 0 | 0.071 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Europe | RUS | Russia | NA | 147 | 0 | 8 | 0.068 | 0.000 | 0.010 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | PER | Peru | NA | 145 | 0 | 1 | 0.067 | 0.000 | 0.001 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | KWT | Kuwait | NA | 142 | 0 | 15 | 0.066 | 0.000 | 0.018 | EMR | Eastern Mediterranean | High income | WB_HI | 2017 | 2018 |
Asia | LBN | Lebanon | NA | 133 | 3 | 3 | 0.062 | 0.034 | 0.004 | EMR | Eastern Mediterranean | Upper middle income | WB_UMI | 2017 | 2018 |
Oceania | AUS | Australia | Victoria | 121 | 0 | 8 | 0.056 | 0.000 | 0.010 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Europe | SMR | San Marino | NA | 119 | 11 | 4 | 0.055 | 0.126 | 0.005 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Africa | ZAF | South Africa | NA | 116 | 0 | 0 | 0.054 | 0.000 | 0.000 | AFR | Africa | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | ARE | United Arab Emirates | NA | 113 | 0 | 26 | 0.053 | 0.000 | 0.031 | EMR | Eastern Mediterranean | High income | WB_HI | 2017 | 2018 |
Americas | ECU | Ecuador | NA | 111 | 2 | 0 | 0.052 | 0.023 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | SVK | Slovakia | NA | 105 | 1 | 0 | 0.049 | 0.011 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Asia | TWN | Taiwan* | NA | 100 | 1 | 22 | 0.047 | 0.011 | 0.026 | NA | NA | NA | NA | NA | NA |
Asia | TUR | Turkey | NA | 98 | 1 | 0 | 0.046 | 0.011 | 0.000 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | CAN | Canada | Alberta | 97 | 0 | 0 | 0.045 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | CAN | Canada | Quebec | 94 | 0 | 0 | 0.044 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Oceania | AUS | Australia | Queensland | 94 | 0 | 8 | 0.044 | 0.000 | 0.010 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Americas | MEX | Mexico | NA | 93 | 0 | 4 | 0.043 | 0.000 | 0.005 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | COL | Colombia | NA | 93 | 0 | 1 | 0.043 | 0.000 | 0.001 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | BGR | Bulgaria | NA | 92 | 2 | 0 | 0.043 | 0.023 | 0.000 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | USA | US | Wisconsin | 92 | 0 | 0 | 0.043 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Ohio | 86 | 0 | 0 | 0.040 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | PAN | Panama | NA | 86 | 1 | 0 | 0.040 | 0.011 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Maryland | 85 | 0 | 0 | 0.040 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | ARM | Armenia | NA | 84 | 0 | 1 | 0.039 | 0.000 | 0.001 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | SRB | Serbia | NA | 83 | 0 | 1 | 0.039 | 0.000 | 0.001 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | USA | US | Michigan | 83 | 0 | 0 | 0.039 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Europe | HRV | Croatia | NA | 81 | 0 | 4 | 0.038 | 0.000 | 0.005 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | ARG | Argentina | NA | 79 | 2 | 3 | 0.037 | 0.023 | 0.004 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Tennessee | 79 | 0 | 0 | 0.037 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Virginia | 77 | 2 | 0 | 0.036 | 0.023 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Minnesota | 77 | 0 | 0 | 0.036 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | VNM | Vietnam | NA | 75 | 0 | 16 | 0.035 | 0.000 | 0.019 | WPR | Western Pacific | Lower middle income | WB_LMI | 2017 | 2018 |
Africa | DZA | Algeria | NA | 74 | 7 | 12 | 0.034 | 0.080 | 0.014 | AFR | Africa | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | LVA | Latvia | NA | 71 | 0 | 1 | 0.033 | 0.000 | 0.001 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | North Carolina | 70 | 0 | 0 | 0.033 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | BRN | Brunei | NA | 68 | 0 | 0 | 0.032 | 0.000 | 0.000 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Oregon | 68 | 2 | 0 | 0.032 | 0.023 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Connecticut | 68 | 0 | 0 | 0.032 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Europe | ALB | Albania | NA | 59 | 2 | 0 | 0.027 | 0.023 | 0.000 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | HUN | Hungary | NA | 58 | 1 | 2 | 0.027 | 0.011 | 0.002 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | DNK | Denmark | Faroe Islands | 58 | 0 | 0 | 0.027 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Nevada | 55 | 1 | 0 | 0.026 | 0.011 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | JOR | Jordan | NA | 52 | 0 | 1 | 0.024 | 0.000 | 0.001 | EMR | Eastern Mediterranean | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | LKA | Sri Lanka | NA | 51 | 0 | 1 | 0.024 | 0.000 | 0.001 | SEAR | South-East Asia | Lower middle income | WB_LMI | 2017 | 2018 |
Europe | BLR | Belarus | NA | 51 | 0 | 5 | 0.024 | 0.000 | 0.006 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | USA | US | Utah | 51 | 0 | 0 | 0.024 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | CRI | Costa Rica | NA | 50 | 0 | 0 | 0.023 | 0.000 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | URY | Uruguay | NA | 50 | 0 | 0 | 0.023 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Africa | MAR | Morocco | NA | 49 | 2 | 1 | 0.023 | 0.023 | 0.001 | EMR | Eastern Mediterranean | Lower middle income | WB_LMI | 2017 | 2018 |
Asia | CYP | Cyprus | NA | 49 | 0 | 0 | 0.023 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Diamond Princess | 47 | 0 | 0 | 0.022 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | South Carolina | 47 | 1 | 0 | 0.022 | 0.011 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Alabama | 46 | 0 | 0 | 0.021 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Maine | 42 | 0 | 0 | 0.020 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | OMN | Oman | NA | 39 | 0 | 12 | 0.018 | 0.000 | 0.014 | EMR | Eastern Mediterranean | High income | WB_HI | 2017 | 2018 |
Europe | AND | Andorra | NA | 39 | 0 | 1 | 0.018 | 0.000 | 0.001 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Indiana | 39 | 2 | 0 | 0.018 | 0.023 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | GEO | Georgia | NA | 38 | 0 | 1 | 0.018 | 0.000 | 0.001 | EUR | Europe | Lower middle income | WB_LMI | 2017 | 2018 |
Europe | BIH | Bosnia and Herzegovina | NA | 38 | 0 | 2 | 0.018 | 0.000 | 0.002 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | MLT | Malta | NA | 38 | 0 | 2 | 0.018 | 0.000 | 0.002 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Oceania | AUS | Australia | South Australia | 37 | 0 | 3 | 0.017 | 0.000 | 0.004 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Americas | VEN | Venezuela | NA | 36 | 0 | 0 | 0.017 | 0.000 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Oceania | AUS | Australia | Western Australia | 35 | 1 | 0 | 0.016 | 0.011 | 0.000 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Asia | KHM | Cambodia | NA | 35 | 0 | 1 | 0.016 | 0.000 | 0.001 | WPR | Western Pacific | Lower middle income | WB_LMI | 2017 | 2018 |
Europe | MKD | North Macedonia | NA | 35 | 0 | 1 | 0.016 | 0.000 | 0.001 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Asia | KAZ | Kazakhstan | NA | 35 | 0 | 0 | 0.016 | 0.000 | 0.000 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | USA | US | Mississippi | 34 | 0 | 0 | 0.016 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Rhode Island | 33 | 0 | 0 | 0.015 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Arkansas | 33 | 0 | 0 | 0.015 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Africa | SEN | Senegal | NA | 31 | 0 | 2 | 0.014 | 0.000 | 0.002 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Americas | USA | US | District of Columbia | 31 | 0 | 0 | 0.014 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Europe | MDA | Moldova | NA | 30 | 1 | 1 | 0.014 | 0.011 | 0.001 | EUR | Europe | Lower middle income | WB_LMI | 2017 | 2018 |
Africa | TUN | Tunisia | NA | 29 | 0 | 0 | 0.013 | 0.000 | 0.000 | EMR | Eastern Mediterranean | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | USA | US | Iowa | 29 | 0 | 0 | 0.013 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | AZE | Azerbaijan | NA | 28 | 1 | 6 | 0.013 | 0.011 | 0.007 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Europe | LIE | Liechtenstein | NA | 28 | 0 | 0 | 0.013 | 0.000 | 0.000 | NA | NA | High income | WB_HI | 2017 | 2018 |
Europe | LTU | Lithuania | NA | 27 | 0 | 1 | 0.013 | 0.000 | 0.001 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Arizona | 27 | 0 | 0 | 0.013 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Kentucky | 27 | 1 | 0 | 0.013 | 0.011 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | GLP | Guadeloupe | NA | 27 | 0 | 0 | 0.013 | 0.000 | 0.000 | NA | NA | NA | NA | 2017 | 2018 |
Americas | USA | US | New Hampshire | 26 | 0 | 0 | 0.012 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Nebraska | 24 | 0 | 0 | 0.011 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | New Mexico | 23 | 0 | 0 | 0.011 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | AFG | Afghanistan | NA | 22 | 0 | 1 | 0.010 | 0.000 | 0.001 | EMR | Eastern Mediterranean | Low income | WB_LI | 2017 | 2018 |
Americas | DOM | Dominican Republic | NA | 21 | 1 | 0 | 0.010 | 0.011 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | USA | US | Grand Princess | 21 | 0 | 0 | 0.010 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Oceania | NZL | New Zealand | NA | 20 | 0 | 0 | 0.009 | 0.000 | 0.000 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Africa | BFA | Burkina Faso | NA | 20 | 1 | 0 | 0.009 | 0.011 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Americas | MTQ | Martinique | NA | 19 | 1 | 0 | 0.009 | 0.011 | 0.000 | NA | NA | NA | NA | 2017 | 2018 |
Americas | USA | US | Oklahoma | 19 | 0 | 0 | 0.009 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Delaware | 19 | 0 | 0 | 0.009 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Kansas | 18 | 1 | 0 | 0.008 | 0.011 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Missouri | 18 | 0 | 0 | 0.008 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Vermont | 18 | 0 | 0 | 0.008 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | CAN | Canada | Manitoba | 15 | 0 | 0 | 0.007 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Wyoming | 15 | 0 | 0 | 0.007 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | UZB | Uzbekistan | NA | 15 | 0 | 0 | 0.007 | 0.000 | 0.000 | EUR | Europe | Lower middle income | WB_LMI | 2017 | 2018 |
Europe | UKR | Ukraine | NA | 14 | 2 | 0 | 0.007 | 0.023 | 0.000 | EUR | Europe | Lower middle income | WB_LMI | 2017 | 2018 |
Asia | BGD | Bangladesh | NA | 14 | 1 | 3 | 0.007 | 0.011 | 0.004 | SEAR | South-East Asia | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | USA | US | Hawaii | 14 | 0 | 0 | 0.007 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | MDV | Maldives | NA | 13 | 0 | 0 | 0.006 | 0.000 | 0.000 | SEAR | South-East Asia | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | JAM | Jamaica | NA | 13 | 0 | 2 | 0.006 | 0.000 | 0.002 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | CAN | Canada | Nova Scotia | 12 | 0 | 0 | 0.006 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | BOL | Bolivia | NA | 12 | 0 | 0 | 0.006 | 0.000 | 0.000 | AMR | Americas | Lower middle income | WB_LMI | 2017 | 2018 |
Africa | REU | Reunion | NA | 12 | 0 | 0 | 0.006 | 0.000 | 0.000 | NA | NA | NA | NA | 2017 | 2018 |
Americas | CAN | Canada | New Brunswick | 11 | 0 | 0 | 0.005 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | PRY | Paraguay | NA | 11 | 0 | 0 | 0.005 | 0.000 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | USA | US | Montana | 11 | 0 | 0 | 0.005 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | South Dakota | 11 | 1 | 0 | 0.005 | 0.011 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | GUF | French Guiana | NA | 11 | 0 | 0 | 0.005 | 0.000 | 0.000 | NA | NA | NA | NA | 2017 | 2018 |
Oceania | AUS | Australia | Tasmania | 10 | 0 | 0 | 0.005 | 0.000 | 0.000 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Africa | CMR | Cameroon | NA | 10 | 0 | 0 | 0.005 | 0.000 | 0.000 | AFR | Africa | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | CAN | Canada | Grand Princess | 9 | 0 | 0 | 0.004 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Idaho | 9 | 0 | 0 | 0.004 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | HND | Honduras | NA | 9 | 0 | 0 | 0.004 | 0.000 | 0.000 | AMR | Americas | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | CAN | Canada | Saskatchewan | 8 | 0 | 0 | 0.004 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Africa | NGA | Nigeria | NA | 8 | 0 | 1 | 0.004 | 0.000 | 0.001 | AFR | Africa | Lower middle income | WB_LMI | 2017 | 2018 |
Europe | GBR | United Kingdom | Gibraltar | 8 | 0 | 2 | 0.004 | 0.000 | 0.002 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Africa | RWA | Rwanda | NA | 8 | 0 | 0 | 0.004 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Europe | MCO | Monaco | NA | 7 | 0 | 0 | 0.003 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Americas | CUB | Cuba | NA | 7 | 1 | 0 | 0.003 | 0.011 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | GUY | Guyana | NA | 7 | 1 | 0 | 0.003 | 0.011 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Africa | GHA | Ghana | NA | 7 | 0 | 0 | 0.003 | 0.000 | 0.000 | AFR | Africa | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | TTO | Trinidad and Tobago | NA | 7 | 0 | 0 | 0.003 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Alaska | 6 | 0 | 0 | 0.003 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | North Dakota | 6 | 0 | 0 | 0.003 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Asia | MNG | Mongolia | NA | 6 | 0 | 0 | 0.003 | 0.000 | 0.000 | WPR | Western Pacific | Lower middle income | WB_LMI | 2017 | 2018 |
Europe | GBR | United Kingdom | Channel Islands | 6 | 0 | 0 | 0.003 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Africa | CIV | Cote d’Ivoire | NA | 6 | 0 | 1 | 0.003 | 0.000 | 0.001 | AFR | Africa | Lower middle income | WB_LMI | 2017 | 2018 |
Africa | ETH | Ethiopia | NA | 6 | 0 | 0 | 0.003 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Americas | GTM | Guatemala | NA | 6 | 1 | 0 | 0.003 | 0.011 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | USA | US | Puerto Rico | 5 | 0 | 0 | 0.002 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | Guam | 5 | 0 | 0 | 0.002 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Africa | COD | Congo (Kinshasa) | NA | 4 | 0 | 0 | 0.002 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Americas | ABW | Aruba | NA | 4 | 0 | 0 | 0.002 | 0.000 | 0.000 | NA | NA | High income | WB_HI | 2017 | 2018 |
Africa | SYC | Seychelles | NA | 4 | 0 | 0 | 0.002 | 0.000 | 0.000 | AFR | Africa | High income | WB_HI | 2017 | 2018 |
Africa | GNQ | Equatorial Guinea | NA | 4 | 0 | 0 | 0.002 | 0.000 | 0.000 | AFR | Africa | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | CAN | Canada | Newfoundland and Labrador | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Oceania | AUS | Australia | Australian Capital Territory | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Europe | FRA | France | St Martin | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | FRA | France | Saint Barthelemy | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | FRA | France | French Polynesia | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Africa | KEN | Kenya | NA | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | AFR | Africa | Lower middle income | WB_LMI | 2017 | 2018 |
Europe | NLD | Netherlands | Curacao | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Africa | TZA | Tanzania | NA | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Asia | KGZ | Kyrgyzstan | NA | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | EUR | Europe | Lower middle income | WB_LMI | 2017 | 2018 |
Africa | MUS | Mauritius | NA | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | AFR | Africa | Upper middle income | WB_UMI | 2017 | 2018 |
Africa | MYT | Mayotte | NA | 3 | 0 | 0 | 0.001 | 0.000 | 0.000 | NA | NA | NA | NA | 2017 | 2018 |
Americas | USA | US | Virgin Islands | 2 | 0 | 0 | 0.001 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | United States Virgin Islands | 2 | 0 | 0 | 0.001 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Africa | SDN | Sudan | NA | 2 | 1 | 0 | 0.001 | 0.011 | 0.000 | EMR | Eastern Mediterranean | Lower middle income | WB_LMI | 2017 | 2018 |
Africa | NAM | Namibia | NA | 2 | 0 | 0 | 0.001 | 0.000 | 0.000 | AFR | Africa | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | LCA | Saint Lucia | NA | 2 | 0 | 0 | 0.001 | 0.000 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Kosovo | Kosovo | Kosovo | NA | 2 | 0 | 0 | 0.001 | 0.000 | 0.000 | NA | NA | NA | NA | NA | NA |
Europe | NLD | Netherlands | Aruba | 2 | 0 | 0 | 0.001 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Africa | BEN | Benin | NA | 2 | 0 | 0 | 0.001 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Africa | LBR | Liberia | NA | 2 | 0 | 0 | 0.001 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Americas | BRB | Barbados | NA | 2 | 0 | 0 | 0.001 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Africa | ZMB | Zambia | NA | 2 | 0 | 0 | 0.001 | 0.000 | 0.000 | AFR | Africa | Lower middle income | WB_LMI | 2017 | 2018 |
Asia | NPL | Nepal | NA | 1 | 0 | 1 | 0.000 | 0.000 | 0.001 | SEAR | South-East Asia | Low income | WB_LI | 2017 | 2018 |
Americas | CAN | Canada | Prince Edward Island | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Oceania | AUS | Australia | Northern Territory | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Asia | BTN | Bhutan | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | SEAR | South-East Asia | Lower middle income | WB_LMI | 2017 | 2018 |
Africa | TGO | Togo | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Americas | USA | US | West Virginia | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Americas | USA | US | US | 1 | 0 | 106 | 0.000 | 0.000 | 0.127 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Europe | VAT | Holy See | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | NA | NA | NA | NA | NA | NA |
Europe | GBR | United Kingdom | Cayman Islands | 1 | 1 | 0 | 0.000 | 0.011 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | GBR | United Kingdom | Montserrat | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Africa | GIN | Guinea | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Americas | ATG | Antigua and Barbuda | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Africa | SWZ | Eswatini | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AFR | Africa | Lower middle income | WB_LMI | 2017 | 2018 |
Africa | GAB | Gabon | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AFR | Africa | Upper middle income | WB_UMI | 2017 | 2018 |
Africa | MRT | Mauritania | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AFR | Africa | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | VCT | Saint Vincent and the Grenadines | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Americas | SUR | Suriname | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AMR | Americas | Upper middle income | WB_UMI | 2017 | 2018 |
Africa | CAF | Central African Republic | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Africa | COG | Congo (Brazzaville) | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AFR | Africa | Lower middle income | WB_LMI | 2017 | 2018 |
Americas | GRL | Greenland | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | NA | NA | High income | WB_HI | 2017 | 2018 |
Africa | SOM | Somalia | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | EMR | Eastern Mediterranean | Low income | WB_LI | 2017 | 2018 |
Americas | BHS | The Bahamas | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AMR | Americas | High income | WB_HI | 2017 | 2018 |
Europe | MNE | Montenegro | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | EUR | Europe | Upper middle income | WB_UMI | 2017 | 2018 |
Africa | DJI | Djibouti | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | EMR | Eastern Mediterranean | Lower middle income | WB_LMI | 2017 | 2018 |
Africa | GMB | Gambia, The | NA | 1 | 0 | 0 | 0.000 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Oceania | AUS | Australia | From Diamond Princess | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | WPR | Western Pacific | High income | WB_HI | 2017 | 2018 |
Europe | FRA | France | French Guiana | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | FRA | France | Mayotte | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | FRA | France | Guadeloupe | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | FRA | France | Reunion | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | EUR | Europe | High income | WB_HI | 2017 | 2018 |
Europe | JEY | Jersey | NA | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | NA | NA | NA | NA | NA | NA |
Europe | GGY | Guernsey | NA | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | NA | NA | NA | NA | NA | NA |
Africa | GMB | The Gambia | NA | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | AFR | Africa | Low income | WB_LI | 2017 | 2018 |
Oceania | GUM | Guam | NA | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | NA | NA | High income | WB_HI | 2017 | 2018 |
Americas | PRI | Puerto Rico | NA | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | NA | NA | High income | WB_HI | 2017 | 2018 |
Africa | COG | Republic of the Congo | NA | 0 | 0 | 0 | 0.000 | 0.000 | 0.000 | AFR | Africa | Lower middle income | WB_LMI | 2017 | 2018 |
[1] “Tidy Data” H. Wickham, https://www.jstatsoft.org/article/view/v059i10