Abstract
This article contains data on country-specific variability in Covid-19 prevalence, incidence, and case fatality rate among the 238 countries globally. We used the World Health Organization worldwide Covid-19 tracking site to determine the number of confirmed Covid-19 cases, the number of fatalities attributed to Covid-19, and the case fatality rate for each of 238 countries. Using data from the United Nations Department of Economic and Social Affairs, we extracted key country-specific metrics with potential associations with Covid-19 including total population, land area, population density, percentage of residents living in urban areas, and median age. We extracted country-specific economic indicators from The World Bank Group Open Data database. All data were extracted on August 15, 2020. We developed consolidated data sets and calculated the country-specific point prevalence and incidence of Covid-19 and associated deaths. These data are associated with the article “Spatial Analysis of Global Variability in Covid-19 Burden”. Data are stored in a comma separated value format and can be downloaded from the Data in Brief website.
Keywords: Coronavirus, Covid-19, Global, Incidence, Prevalence
Specifications Table
| Subject | Public Health and Health Policy |
| Specific subject area | Infectious disease |
| Type of data | Tables, figures, raw data |
| How data were acquired | Using the CDC worldwide Covid-19 tracking site [1], we extracted the number of confirmed Covid-19 cases, the number of fatalities attributed to Covid-19, and the case fatality rate for each of 238 countries. Using 2020 data available from the United Nations Department of Economic and Social Affairs [2], we extracted key country-specific metrics with potential associations with Covid-19 including total population, land area, population density, percentage of residents living in urban areas, and median age. We extracted country-specific economic indicators from The World Bank Group Open Data database [3]. All data were extracted on August 15, 2020. |
| Data format | Raw, analyzed |
| Parameters for data collection | Countries included in this dataset were listed within the CDC worldwide Covid-19 tracking site, the United Nations Department of Economic and Social Affairs, or The World Bank Group Open Data database. |
| Description of data collection | We developed consolidated data sets and calculated the country-specific point prevalence and incidence of Covid-19 and associated deaths. Non-normally distributed data were log-transformed, descriptive and correlational analyses were performed by a biostatistician (LM). |
| Data source location | 238 countries. |
| Data accessibility | Unpublished summary data are available with this article and raw data are available as a supplemental file. |
| Related research article | Miller LE, Bhattacharyya R, Miller AL. Spatial Analysis of Global Variability in Covid-19 Burden. Risk Management and Healthcare Policy 13:519-522, 2020. doi: 10.2147/RMHP.S255793 |
Value of the Data
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Media headlines place great emphasis on the prevalence of Covid-19 among countries. This dataset combines global data from three sources to provide unique information related to country-specific Covid-19 prevalence, incidence, case fatality rate, and potential modifiers of these rates.
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This dataset can be used by public health officials to serve as a model by which Covid-19 incidence, which accounts for population variability among countries, might also be calculated and reported.
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These data may raise awareness of the high Covid-19 infection burden reported in less populated countries, inform and influence public health policy, and facilitate allocation of economic, social, and health resources to the most impacted regions.
1. Data Description
The data in this article consist of previously unpublished tables and figures derived from a global analysis of Covid-19 prevalence, incidence, and case fatality rate. The association of the relative Covid-19 burden with key country indicators is displayed in Fig. 1. Table 1 lists the top 10 countries with the highest total and relative Covid-19 infection and fatality burden. Key Covid-19 statistics are provided for the top 10 countries with the largest population (Table 2), highest population density (Table 3), largest land area (Table 4), highest GDP per capita (Table 5), highest median age (Table 6), and largest percentage of population living in urban areas (Table 7). Raw data from this analysis are available as a .csv file in the Data Supplement at www.journals.elsevier.com/data-in-brief.
Fig. 1.
Association of relative Covid-19 burden with key country indicators. Countries with less than 30,000 population were excluded from the urban density analysis due to poor estimate precision. Data current as of August 15, 2020.
Table 1.
Top 10 countries with highest total and relative Covid-19 infection and fatality burden.
| Country | Covid-19 cases | Country | Covid-19 cases per million |
|---|---|---|---|
| United States | 5,203,206 | Qatar | 39,754 |
| Brazil | 3,224,876 | French Guyana | 28,622 |
| India | 2,526,192 | Bahrain | 27,064 |
| Russia | 917,884 | San Marino | 21,190 |
| South Africa | 579,140 | Chile | 19,989 |
| Peru | 507,996 | Panama | 18,181 |
| Mexico | 505,751 | Kuwait | 17,605 |
| Colombia | 433,805 | Oman | 16,203 |
| Chile | 382,111 | United States | 15,720 |
| Spain | 348,285 | Peru | 15,407 |
| Country | Fatal Covid-19 cases | Country | Fatal Covid-19 cases per million |
|---|---|---|---|
| United States | 165,995 | San Marino | 1,238 |
| Brazil | 105,463 | Belgium | 857 |
| Mexico | 55,293 | Peru | 778 |
| India | 49,036 | Andorra | 686 |
| United Kingdom | 41,358 | Spain | 613 |
| Italy | 35,234 | United Kingdom | 609 |
| France | 30,275 | Italy | 583 |
| Spain | 28,640 | Sweden | 573 |
| Peru | 25,648 | Chile | 541 |
| Iran | 19,331 | United States | 502 |
Table 2.
Key Covid-19 statistics for top 10 countries with largest population.
| Country | Population (millions) | Covid-19 cases | Fatal Covid-19 cases | Per capita rate, per million | Per capita fatality rate, per million | Case fatality rate |
|---|---|---|---|---|---|---|
| China | 1,439 | 89,695 | 4,708 | 62 | 3 | 5.2% |
| India | 1,380 | 2,526,192 | 49,036 | 1,831 | 36 | 1.9% |
| United States | 331 | 5,203,206 | 165,995 | 15,720 | 502 | 3.2% |
| Indonesia | 274 | 135,123 | 6,021 | 494 | 22 | 4.5% |
| Pakistan | 221 | 288,047 | 6,162 | 1,304 | 28 | 2.1% |
| Brazil | 213 | 3,224,876 | 105,463 | 15,172 | 496 | 3.3% |
| Nigeria | 206 | 48,445 | 973 | 235 | 5 | 2.0% |
| Bangladesh | 165 | 271,881 | 3,591 | 1,651 | 22 | 1.3% |
| Russia | 146 | 917,884 | 15,617 | 6,290 | 107 | 1.7% |
| Mexico | 129 | 505,751 | 55,293 | 3,923 | 429 | 10.9% |
Table 3.
Key Covid-19 statistics for top 10 countries with highest population density.
| Country | Population density (per km2 land area) | Covid-19 cases | Fatal Covid-19 cases | Per capita rate, per million | Per capita fatality rate, per million | Case fatality rate |
|---|---|---|---|---|---|---|
| Monaco | 26,337 | 143 | 1 | 3644 | 26 | 0.7% |
| Macao | 21,645 | 19 | 0 | 18 | 0 | 0.0% |
| Singapore | 8358 | 55,580 | 27 | 9500 | 5 | 2.6% |
| Hong Kong | 7140 | 51,256 | 23 | 9419 | 4 | 2.5% |
| Gibraltar | 3369 | 205 | 0 | 6085 | 0 | 0.0% |
| Bahrain | 2239 | 46,052 | 168 | 27,064 | 99 | 0.4% |
| Holy See | 2003 | 12 | 0 | 14,981 | 0 | 0.0% |
| Maldives | 5572 | 22 | 10,308 | 41 | 6 | 0.9% |
| Malta | 1380 | 1175 | 9 | 2661 | 20 | 0.8% |
| Bangladesh | 1265 | 271,881 | 3,591 | 1651 | 22 | 1.3% |
Table 4.
Key Covid-19 statistics for top 10 countries with largest land area.
| Country | Land Area (million/km2) | Covid-19 cases | Fatal Covid-19 cases | Per capita rate, per million | Per capita fatality rate, per million | Case fatality rate |
|---|---|---|---|---|---|---|
| Russia | 16.4 | 917,884 | 15,617 | 6290 | 107 | 1.7% |
| China | 9.4 | 89,695 | 4708 | 62 | 3 | 5.2% |
| United States | 9.1 | 5,203,206 | 165,995 | 15,720 | 502 | 3.2% |
| Canada | 9.1 | 121,234 | 9015 | 3212 | 239 | 7.4% |
| Brazil | 8.4 | 3,224,876 | 105,463 | 15,172 | 496 | 3.3% |
| Australia | 7.7 | 22,743 | 375 | 892 | 15 | 1.6% |
| India | 3.0 | 2,526,192 | 49,036 | 1831 | 36 | 1.9% |
| Argentina | 2.7 | 276,072 | 5428 | 6108 | 120 | 2.0% |
| Kazakhstan | 2.7 | 119,781 | 1433 | 6379 | 76 | 1.2% |
| Algeria | 2.4 | 37,664 | 1351 | 859 | 31 | 3.6% |
Table 5.
Key Covid-19 statistics for top 10 countries with highest GDP per capita.
| Country | GDP per capita (USD) | Covid-19 cases | Fatal Covid-19 cases | Per capita rate, per million | Per capita fatality rate, per million | Case fatality rate |
|---|---|---|---|---|---|---|
| Monaco | 164,823 | 143 | 1 | 3644 | 26 | 0.7% |
| Liechtenstein | 162,444 | 91 | 1 | 2387 | 26 | 1.1% |
| Luxembourg | 117,725 | 7405 | 122 | 11,829 | 195 | 1.6% |
| Bermuda | 98,387 | 159 | 9 | 2553 | 145 | 5.7% |
| Macao | 95,726 | 149 | 8 | 2458 | 144 | 5.6% |
| Switzerland | 85,585 | 37,580 | 1,714 | 4342 | 198 | 4.6% |
| Ireland | 82,058 | 26,995 | 1,774 | 5467 | 359 | 6.6% |
| Norway | 80,908 | 9850 | 261 | 1817 | 48 | 2.6% |
| Iceland | 78,598 | 1983 | 10 | 5811 | 29 | 0.5% |
| Qatar | 70,810 | 114,532 | 190 | 39,754 | 66 | 0.2% |
Table 6.
Key Covid-19 statistics for top 10 countries with highest median age.
| Country | Median age | Covid-19 cases | Fatal Covid-19 cases | Per capita rate, per million | Per capita fatality rate, per million | Case fatality rate |
|---|---|---|---|---|---|---|
| Japan | 48 | 53,577 | 1085 | 424 | 9 | 2.0% |
| Italy | 47 | 252,809 | 35,234 | 4,181 | 583 | 13.9% |
| Martinique | 47 | 336 | 16 | 895 | 43 | 4.8% |
| Germany | 46 | 222,828 | 9231 | 2,660 | 110 | 4.1% |
| Portugal | 46 | 53,783 | 1772 | 5,275 | 174 | 3.3% |
| Greece | 46 | 6632 | 223 | 636 | 21 | 3.4% |
| Hong Kong | 45 | 4512 | 70 | 478 | 62 | 2.5% |
| Spain | 45 | 348,285 | 28,640 | 7,449 | 613 | 8.2% |
| Slovenia | 45 | 2369 | 124 | 1,140 | 60 | 5.2% |
| Lithuania | 45 | 2352 | 81 | 864 | 30 | 3.4% |
Table 7.
Key Covid-19 statistics for top 10 countries with largest population living in urban areas.
| Country | Percentage of urban population* | Covid-19 cases | Fatal Covid-19 cases | Per capita rate, per million | Per capita fatality rate, per million | Case fatality rate |
|---|---|---|---|---|---|---|
| Réunion | 100% | 776 | 5 | 867 | 6 | 0.6% |
| Belgium | 98% | 78,417 | 9936 | 6766 | 857 | 12.7% |
| Bermuda | 97% | 159 | 9 | 2553 | 145 | 5.7% |
| Cayman Islands | 97% | 203 | 1 | 3089 | 15 | 0.5% |
| San Marino | 97% | 719 | 42 | 21,190 | 1,238 | 5.8% |
| U.S. Virgin Islands | 96% | 704 | 9 | 6742 | 86 | 1.3% |
| Uruguay | 96% | 1409 | 37 | 406 | 11 | 2.6% |
| Qatar | 96% | 114,532 | 190 | 39,754 | 66 | 0.2% |
| Sint Maarten | 96% | 263 | 17 | 6134 | 397 | 6.5% |
| Guam | 95% | 494 | 5 | 2927 | 30 | 1.0% |
Minimum 30,000 population.
2. Experimental design, materials, and methods
Using the CDC worldwide Covid-19 tracking site [1], we extracted the number of confirmed Covid-19 cases, the number of fatalities attributed to Covid-19, and the case fatality rate (death rate among those diagnosed with Covid-19) for each of 238 countries. Using 2020 data available from the United Nations Department of Economic and Social Affairs [2], we extracted key country-specific metrics with potential associations with Covid-19 including total population, land area, population density, percentage of residents living in urban areas, and median age. We extracted country-specific economic indicators from The World Bank Group Open Data database [3]. All data were extracted on August 15, 2020. We developed consolidated data sets and calculated the country-specific point prevalence (total cases at a point in time) and incidence (total cases per capita at a point in time) of Covid-19 and associated deaths. Non-normally distributed data were log-transformed, descriptive and correlational analyses were performed by a biostatistician. The data utilized in the related research article were extracted on March 19, 2020. Due to the rapidly evolving nature of Covid-19, here we provide updated data current as of August 15, 2020.
Funding
No funding was provided for this study.
Declaration of Competing Interest
None.
Acknowledgments
The authors thank César Carvajal (Kannon & Saga Solutions, Maracaibo, Venezuela) for graphical assistance.
Footnotes
Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.dib.2020.106276.
Appendix. Supplementary materials
References
- 1.Coronavirus Disease 2019 (COVID-19): Global Map . 2020. https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/world-map.html [Google Scholar]
- 2.World Population Prospects: The 2019 Revision . 2020. https://www.worldometers.info/world-population/population-by-country/ [Google Scholar]
- 3.World Bank Open Data . 2020. https://data.worldbank.org/ [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.