Table 1.
Details of Coronavirus Disease 2019 Data, IFITM3 rs12252 Genotype Prevalence, and Correlation Analysis
| Country | SARS-CoV-2–Infected Cases per Million Population | SARS-CoV-2–Related Deaths per Million Population | No. of Reports Considered for Prevalence of Genotype Investigation | Total No. of Healthy Controls | C/C Genotype, No. | C/T Genotype, No. | T/T Genotype, No. | C Allele, No. | T Allele, No. | Frequency of Allele C, % | References | No. of Doctors/10 000 Population | No. of Nurses/10 000 Population | Expenditure of % of GDP on Health Sector | Spearman Rank Correlation |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Nigeria | 48 | 3 | 3 | 266 | 18 | 89 | 159 | 125 | 407 | 23.49 | Jiménez et al 2017; Kim et al 2017 | 3.81 | 11.79 | 3.7 | Allele C frequency (%) vs SARS-CoV-2 cases/million (r = –0.632, P = .002, n = 21); Allele C frequency (%) vs deaths/million (r = –0.715, P = .0008, n = 18) |
| Kenya | 491 | 8 | 1 | 99 | 8 | 43 | 48 | 59 | 139 | 29.79 | Jiménez et al 2017 | 1.57 | 11.66 | 5.7 | |
| The Gambia | 510 | 9 | 1 | 113 | 8 | 33 | 72 | 49 | 177 | 21.68 | Jiménez et al 2017 | 1.02 | 15.45 | 7.3 | |
| Sierra Leone | 240 | 9 | 1 | 85 | 5 | 32 | 48 | 42 | 128 | 24.70 | Jiménez et al 2017 | .25 | 2.24 | 11.1 | |
| China | 59 | 3 | 9 | 1383 | 351 | 687 | 345 | 1389 | 1377 | 50.21 | Wang et al 2013; Zhang et al 2013; Lee et al 2017; Zhang et al 2013; Lee et al 2017; Pan et al 2017; Zhang et al 2013; Zhang et al 2015 | 19.8 | 26.62 | 5.5 | |
| India | 1603 | 32 | 2 | 205 | 5 | 45 | 155 | 55 | 355 | 13.41 | Jiménez et al 2017 | 8.57 | 17.27 | 4.7 | |
| South Korea | 285 | 6 | 2 | 858 | 294 | 434 | 130 | 1022 | 694 | 59.55 | Kim et al 2017; Seo et al 2010 | 23.61 | 73.01 | 7.4 | |
| Japan | 370 | 8 | 1 | 89 | 39 | 35 | 15 | 113 | 65 | 63.48 | Kim et al 2017 | 24.12 | 121.5 | 10.2 | |
| Spain | 7730 | 610 | 3 | 599 | 0 | 41 | 558 | 41 | 1157 | 3.42 | Rodríguez et al 2016; Jiménez et al 2017 | 38.72 | 57.3 | 9 | |
| Finland | 1369 | 60 | 1 | 99 | 0 | 16 | 83 | 16 | 182 | 8.08 | Jiménez et al 2017 | 38.12 | 147.4 | 9.7 | |
| Italy | 4145 | 582 | 1 | 107 | 0 | 7 | 100 | 7 | 207 | 3.27 | Jiménez et al 2017 | 39.77 | 57.4 | 9.2 | |
| Portugal | 5167 | 172 | 3 | 1086 | 2 | 132 | 952 | 136 | 2036 | 6.26 | Gaio et al 2016; David et al 2017 | 51.24 | 69.75 | 9.5 | |
| UK | 4576 | 686 | 3 | 3072 | 5 | 228 | 2839 | 238 | 5906 | 3.87 | Mills et al 2013; Everitt et al 2013; Kim et al 2017 | 28.12 | 81.72 | 9.1 | |
| Mexico | 3721 | 405 | 5 | 820 | 24 | 248 | 548 | 296 | 1344 | 18.04 | Jiménez et al 2017 | 23.83 | 23.96 | 6.3 | |
| US | 15 698 | 500 | 5 | 10 642 | 10 | 701 | 9931 | 721 | 20 563 | 3.38 | Carter et al 2017; Randolph et al 2017; Jiménez et al 2017 | 26.12 | 145.5 | 17.1 | |
| Barbados | 249 | 24 | 1 | 96 | 4 | 35 | 57 | 43 | 149 | 22.39 | Jiménez et al 2017 | 24.84 | 30.6 | 7.5 | |
| Colombia | 7607 | 252 | 1 | 94 | 0 | 14 | 80 | 14 | 174 | 7.44 | Jiménez et al 2017 | 21.85 | 13.31 | 7.2 | |
| Peru | 14 477 | 638 | 1 | 85 | 9 | 40 | 36 | 58 | 112 | 34.11 | Jiménez et al 2017 | 24.4 | 13.05 | 5.5 | |
| Bangladesh | 1562 | 21 | 1 | 86 | 3 | 22 | 61 | 28 | 144 | 16.27 | Jiménez et al 2017 | 5.81 | 4.12 | 2.8 | |
| Pakistan | 1286 | 28 | 1 | 96 | 5 | 24 | 67 | 34 | 158 | 17.70 | Jiménez et al 2017 | 9.8 | 6.68 | 2.68 | |
| Sri Lanka | 133 | .5 | 1 | 102 | 2 | 23 | 77 | 27 | 177 | 13.23 | Jiménez et al 2017 | 10.04 | 21.8 | 3.5 |
Data on SARS-CoV-2–infected cases, related death, and recovery rate were obtained from https://www.worldometers.info/coronavirus/ (accessed 10 August 2020). Correlation analysis was performed by Spearman rank correlation coefficient in GraphPad Prism 8.3.0 software.
Abbreviations: GDP, gross domestic product; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; UK, United Kingdom; US, United States.