Updated: 20 Jun 2021
Author: Marc Bevand
This project studies the age-stratified infection fatality ratio (IFR) of COVID-19:
The above chart compares the IFR of COVID-19 to the IFR of seasonal influenza. We find that COVID-19 is definitely significantly more fatal than influenza at all ages above 30 years. The source code producing this chart is covid_vs_flu.py.
The vertical indicators represent the difference in fatality between COVID-19 and influenza at various ages, from 30 to 80 years at 10-year intervals. The top/bottom of the indicators are anchored at the geometric means of the COVID-19/influenza IFR estimates.
The COVID-19 IFR curves represent these estimates:
calc_ifr.py
, see this section)The seasonal influenza IFR curves represent data from the US CDC on multiple seasons of flu:
However, these CDC statistics (eg. table 1 in "2018-2019 influenza burden",) only give the estimated number of symptomatic illnesses. We must account for asymptomatic ones as well to calculate the IFR.
Not all influenza infections have symptoms, the infected people may not be aware they are infected. The fraction of cases without symptoms but a confirmation (serologic) of antibodies is called the asymptomatic fraction. The asymptomatic fraction of influenza cases has been studied in recent years in various journal articles. The most recent study was part of UK FluWatch study with results published in the Lancet - showing the asymptomatic fraction was 77%. https://www.thelancet.com/journals/lanres/article/PIIS2213-2600(14)70034-7/fulltext Another study published at : https://journals.lww.com/epidem/Fulltext/2010/09000/Estimating_Pathogen_specific_Asymptomatic_Ratios.28.aspx determines for H1N1 subtype 75%, and H3N2 subtype 65% asymptomatic fraction. Finally a meta study is available here : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586318/ from which a range of 65-85% asymptomatic fraction is determined. We use an estimate of 67% asymptomatic fraction - or 33% symptomatic.
total_illnesses = symptomatic_illnesses / .33
The script apply_ifr.py uses a handful of age-stratified IFR estimates for COVID-19 and the seasonal flu and applies them to countries' population pyramids, to find their expected average IFR. The calculation assumes equal prevalence of the disease among all age groups.
IFR estimates are a subset of the same sources as in covid_vs_flu.py
. The flu
IFR is from the US CDC (last flu season, 2019-2020.)
The real-world overall IFR will, of course, dependent on many factors: varying prevalence among age groups, underlying health conditions, access to healthcare, socioeconomic status, ethnicity, etc.
Data for the population pyramids comes from the United Nations, specifically the first sheet of Population by Age Groups - Both Sexes. This excel file was converted to CSV format: WPP2019_POP_F07_1_POPULATION_BY_AGE_BOTH_SEXES.csv
The overall expected IFR percentages are summarized in this table (sorted on the ENE-COVID column):
ENE-COVID | COVID: US CDC | COVID: Verity | COVID: Levin | COVID: Brazeau | Flu: US CDC | Region |
---|---|---|---|---|---|---|
1.274 | 2.689 | 1.605 | 2.660 | 1.359 | 0.072 | Japan |
1.065 | 2.251 | 1.382 | 2.177 | 1.140 | 0.061 | Italy |
1.041 | 2.152 | 1.339 | 2.135 | 1.103 | 0.058 | Greece |
0.993 | 2.110 | 1.305 | 1.997 | 1.059 | 0.057 | Germany |
0.984 | 2.196 | 1.320 | 2.027 | 1.059 | 0.059 | Portugal |
0.931 | 2.117 | 1.270 | 1.938 | 1.021 | 0.057 | Martinique |
0.919 | 2.008 | 1.221 | 1.953 | 1.017 | 0.055 | Lithuania |
0.916 | 1.947 | 1.207 | 1.950 | 1.014 | 0.053 | Spain |
0.914 | 2.004 | 1.201 | 1.899 | 1.003 | 0.054 | France |
0.899 | 2.166 | 1.248 | 1.819 | 0.980 | 0.059 | Finland |
0.881 | 2.009 | 1.192 | 1.910 | 0.998 | 0.055 | Latvia |
0.875 | 2.024 | 1.205 | 1.789 | 0.969 | 0.055 | Puerto Rico |
0.868 | 1.967 | 1.171 | 1.773 | 0.939 | 0.054 | Estonia |
0.865 | 2.059 | 1.209 | 1.733 | 0.932 | 0.056 | Croatia |
0.855 | 2.089 | 1.205 | 1.716 | 0.936 | 0.057 | Malta |
0.846 | 1.875 | 1.137 | 1.740 | 0.925 | 0.051 | Belgium |
0.843 | 2.012 | 1.181 | 1.740 | 0.929 | 0.055 | Slovenia |
0.840 | 1.961 | 1.154 | 1.722 | 0.922 | 0.053 | Sweden |
0.836 | 1.881 | 1.149 | 1.709 | 0.919 | 0.051 | Austria |
0.825 | 1.868 | 1.132 | 1.697 | 0.911 | 0.051 | Switzerland |
0.810 | 1.864 | 1.117 | 1.633 | 0.887 | 0.051 | Europe |
0.802 | 1.951 | 1.141 | 1.625 | 0.886 | 0.053 | Netherlands |
0.801 | 2.075 | 1.181 | 1.592 | 0.874 | 0.056 | Bulgaria |
0.798 | 1.884 | 1.113 | 1.637 | 0.893 | 0.051 | Guadeloupe |
0.797 | 1.954 | 1.136 | 1.593 | 0.878 | 0.053 | Denmark |
0.794 | 1.815 | 1.089 | 1.622 | 0.873 | 0.050 | United Kingdom |
0.791 | 1.804 | 1.102 | 1.607 | 0.893 | 0.050 | China, Hong Kong SAR |
0.759 | 1.873 | 1.090 | 1.494 | 0.826 | 0.051 | Romania |
0.753 | 1.952 | 1.101 | 1.534 | 0.841 | 0.053 | Hungary |
0.745 | 1.825 | 1.064 | 1.502 | 0.830 | 0.050 | Poland |
0.739 | 1.763 | 1.059 | 1.538 | 0.819 | 0.048 | Channel Islands |
0.738 | 1.946 | 1.092 | 1.510 | 0.830 | 0.053 | Czechia |
0.734 | 1.775 | 1.047 | 1.505 | 0.829 | 0.049 | Canada |
0.719 | 1.644 | 0.998 | 1.480 | 0.816 | 0.045 | Barbados |
0.713 | 1.753 | 1.038 | 1.403 | 0.789 | 0.048 | Curaçao |
0.709 | 1.714 | 1.007 | 1.447 | 0.797 | 0.047 | Norway |
0.680 | 1.851 | 1.029 | 1.337 | 0.752 | 0.051 | Serbia |
0.676 | 1.476 | 0.904 | 1.407 | 0.760 | 0.041 | Uruguay |
0.675 | 1.647 | 0.967 | 1.379 | 0.768 | 0.045 | Northern America |
0.671 | 1.588 | 0.944 | 1.374 | 0.754 | 0.044 | Australia |
0.671 | 1.669 | 0.983 | 1.271 | 0.736 | 0.046 | Ukraine |
0.669 | 1.632 | 0.958 | 1.365 | 0.761 | 0.045 | United States of America |
0.659 | 1.768 | 1.011 | 1.243 | 0.736 | 0.049 | Bosnia and Herzegovina |
0.654 | 1.606 | 0.945 | 1.323 | 0.738 | 0.044 | New Zealand |
0.644 | 1.588 | 0.941 | 1.314 | 0.740 | 0.044 | Cuba |
0.641 | 1.976 | 1.059 | 1.308 | 0.728 | 0.054 | United States Virgin Islands |
0.633 | 1.587 | 0.963 | 1.259 | 0.722 | 0.044 | Republic of Korea |
0.628 | 1.584 | 0.938 | 1.280 | 0.730 | 0.044 | China, Taiwan Province of China |
0.624 | 1.537 | 0.916 | 1.191 | 0.693 | 0.043 | Russian Federation |
0.624 | 1.552 | 0.921 | 1.252 | 0.707 | 0.043 | Belarus |
0.615 | 1.426 | 0.881 | 1.261 | 0.698 | 0.040 | Luxembourg |
0.607 | 1.510 | 0.896 | 1.155 | 0.667 | 0.042 | Georgia |
0.605 | 1.512 | 0.888 | 1.236 | 0.688 | 0.042 | Iceland |
0.604 | 1.642 | 0.935 | 1.222 | 0.695 | 0.045 | Slovakia |
0.582 | 1.556 | 0.891 | 1.138 | 0.654 | 0.043 | Montenegro |
0.563 | 1.437 | 0.838 | 1.126 | 0.641 | 0.040 | Ireland |
0.561 | 1.421 | 0.839 | 1.106 | 0.632 | 0.040 | Cyprus |
0.548 | 1.467 | 0.857 | 1.079 | 0.623 | 0.041 | Albania |
0.531 | 1.493 | 0.874 | 1.049 | 0.608 | 0.042 | Aruba |
0.518 | 1.265 | 0.754 | 1.052 | 0.593 | 0.036 | Oceania |
0.510 | 1.319 | 0.795 | 1.017 | 0.600 | 0.037 | Thailand |
0.500 | 1.284 | 0.763 | 1.020 | 0.585 | 0.036 | Réunion |
0.499 | 1.218 | 0.710 | 1.021 | 0.570 | 0.034 | Israel |
0.497 | 1.195 | 0.748 | 0.915 | 0.552 | 0.034 | Armenia |
0.497 | 1.443 | 0.816 | 0.968 | 0.578 | 0.040 | North Macedonia |
0.493 | 1.230 | 0.736 | 1.001 | 0.576 | 0.035 | Chile |
0.479 | 1.367 | 0.796 | 0.952 | 0.588 | 0.039 | Singapore |
0.454 | 1.130 | 0.671 | 0.917 | 0.521 | 0.032 | Argentina |
0.449 | 1.241 | 0.738 | 0.887 | 0.556 | 0.035 | China, Macao SAR |
0.447 | 1.273 | 0.732 | 0.885 | 0.539 | 0.036 | Mauritius |
0.435 | 1.263 | 0.721 | 0.876 | 0.527 | 0.036 | Republic of Moldova |
0.415 | 1.168 | 0.681 | 0.820 | 0.502 | 0.033 | Trinidad and Tobago |
0.413 | 1.048 | 0.638 | 0.823 | 0.490 | 0.030 | Costa Rica |
0.413 | 1.018 | 0.626 | 0.818 | 0.498 | 0.030 | Saint Lucia |
0.409 | 1.226 | 0.695 | 0.806 | 0.502 | 0.035 | China |
0.394 | 1.042 | 0.648 | 0.822 | 0.463 | 0.030 | Antigua and Barbuda |
0.387 | 1.136 | 0.651 | 0.762 | 0.469 | 0.032 | Sri Lanka |
0.377 | 0.984 | 0.635 | 0.706 | 0.447 | 0.029 | Dem. People's Republic of Korea |
0.376 | 0.984 | 0.594 | 0.743 | 0.451 | 0.029 | Brazil |
0.365 | 1.033 | 0.611 | 0.703 | 0.425 | 0.030 | Guam |
0.364 | 0.929 | 0.569 | 0.725 | 0.431 | 0.027 | Jamaica |
0.361 | 1.018 | 0.605 | 0.764 | 0.435 | 0.029 | Saint Vincent and the Grenadines |
0.359 | 0.874 | 0.540 | 0.724 | 0.428 | 0.026 | Panama |
0.358 | 0.953 | 0.566 | 0.709 | 0.428 | 0.028 | WORLD |
0.356 | 0.918 | 0.555 | 0.710 | 0.426 | 0.027 | Latin America and the Caribbean |
0.355 | 0.930 | 0.560 | 0.707 | 0.427 | 0.027 | Colombia |
0.354 | 0.987 | 0.595 | 0.740 | 0.421 | 0.029 | Grenada |
0.347 | 0.877 | 0.528 | 0.687 | 0.401 | 0.026 | El Salvador |
0.343 | 0.828 | 0.528 | 0.701 | 0.422 | 0.025 | Viet Nam |
0.342 | 0.920 | 0.552 | 0.675 | 0.408 | 0.027 | Turkey |
0.339 | 0.893 | 0.537 | 0.671 | 0.404 | 0.026 | Peru |
0.336 | 0.919 | 0.553 | 0.664 | 0.407 | 0.027 | Tunisia |
0.327 | 0.974 | 0.573 | 0.616 | 0.396 | 0.028 | New Caledonia |
0.325 | 0.916 | 0.541 | 0.640 | 0.399 | 0.027 | Asia |
0.310 | 0.761 | 0.463 | 0.622 | 0.365 | 0.023 | Bolivia (Plurinational State of) |
0.309 | 0.779 | 0.480 | 0.616 | 0.374 | 0.023 | Dominican Republic |
0.307 | 0.826 | 0.503 | 0.574 | 0.368 | 0.024 | Kazakhstan |
0.306 | 0.791 | 0.485 | 0.615 | 0.376 | 0.023 | Mexico |
0.305 | 0.829 | 0.502 | 0.604 | 0.377 | 0.024 | Venezuela (Bolivarian Republic of) |
0.303 | 0.782 | 0.474 | 0.607 | 0.368 | 0.023 | Ecuador |
0.295 | 0.788 | 0.482 | 0.576 | 0.356 | 0.023 | Lebanon |
0.293 | 0.886 | 0.542 | 0.527 | 0.368 | 0.026 | Seychelles |
0.287 | 0.897 | 0.527 | 0.579 | 0.370 | 0.026 | French Polynesia |
0.282 | 0.737 | 0.456 | 0.521 | 0.343 | 0.022 | Guyana |
0.280 | 0.740 | 0.463 | 0.536 | 0.344 | 0.022 | Suriname |
0.273 | 0.737 | 0.474 | 0.515 | 0.343 | 0.022 | Azerbaijan |
0.272 | 0.795 | 0.474 | 0.522 | 0.337 | 0.024 | Morocco |
0.269 | 0.814 | 0.495 | 0.517 | 0.345 | 0.024 | Bahamas |
0.263 | 0.754 | 0.453 | 0.504 | 0.329 | 0.023 | Malaysia |
0.260 | 0.702 | 0.426 | 0.512 | 0.319 | 0.021 | Algeria |
0.257 | 0.703 | 0.418 | 0.500 | 0.313 | 0.021 | Paraguay |
0.251 | 0.650 | 0.403 | 0.486 | 0.302 | 0.020 | Bhutan |
0.246 | 0.699 | 0.431 | 0.476 | 0.312 | 0.021 | Iran (Islamic Republic of) |
0.234 | 0.694 | 0.414 | 0.452 | 0.300 | 0.021 | India |
0.229 | 0.675 | 0.416 | 0.437 | 0.299 | 0.021 | Indonesia |
0.228 | 0.599 | 0.373 | 0.452 | 0.286 | 0.018 | Nicaragua |
0.221 | 0.567 | 0.368 | 0.428 | 0.279 | 0.018 | Bangladesh |
0.221 | 0.530 | 0.349 | 0.432 | 0.276 | 0.017 | Cabo Verde |
0.217 | 0.610 | 0.375 | 0.342 | 0.253 | 0.019 | Tonga |
0.215 | 0.670 | 0.401 | 0.412 | 0.285 | 0.020 | Myanmar |
0.208 | 0.521 | 0.334 | 0.406 | 0.267 | 0.016 | Belize |
0.206 | 0.529 | 0.331 | 0.407 | 0.258 | 0.017 | Honduras |
0.204 | 0.526 | 0.323 | 0.403 | 0.250 | 0.016 | Guatemala |
0.204 | 0.590 | 0.360 | 0.388 | 0.262 | 0.018 | Philippines |
0.202 | 0.614 | 0.360 | 0.388 | 0.258 | 0.019 | Nepal |
0.197 | 0.595 | 0.381 | 0.373 | 0.269 | 0.019 | Brunei Darussalam |
0.194 | 0.547 | 0.331 | 0.376 | 0.245 | 0.017 | Haiti |
0.193 | 0.589 | 0.355 | 0.366 | 0.253 | 0.018 | South Africa |
0.193 | 0.529 | 0.339 | 0.360 | 0.250 | 0.017 | Turkmenistan |
0.192 | 0.567 | 0.343 | 0.363 | 0.247 | 0.018 | Egypt |
0.192 | 0.621 | 0.376 | 0.354 | 0.258 | 0.019 | Fiji |
0.188 | 0.525 | 0.335 | 0.353 | 0.245 | 0.017 | Kyrgyzstan |
0.188 | 0.579 | 0.353 | 0.392 | 0.253 | 0.018 | French Guiana |
0.187 | 0.532 | 0.340 | 0.359 | 0.250 | 0.017 | Uzbekistan |
0.185 | 0.524 | 0.323 | 0.361 | 0.240 | 0.017 | Syrian Arab Republic |
0.182 | 0.502 | 0.324 | 0.349 | 0.242 | 0.016 | Libya |
0.181 | 0.529 | 0.319 | 0.350 | 0.231 | 0.017 | Lesotho |
0.173 | 0.490 | 0.320 | 0.333 | 0.236 | 0.016 | Mongolia |
0.170 | 0.509 | 0.317 | 0.324 | 0.225 | 0.016 | Djibouti |
0.170 | 0.540 | 0.325 | 0.299 | 0.223 | 0.017 | Samoa |
0.168 | 0.527 | 0.314 | 0.325 | 0.227 | 0.017 | Cambodia |
0.164 | 0.470 | 0.292 | 0.310 | 0.212 | 0.015 | Pakistan |
0.158 | 0.468 | 0.273 | 0.303 | 0.200 | 0.015 | Eritrea |
0.157 | 0.401 | 0.277 | 0.285 | 0.204 | 0.014 | Maldives |
0.157 | 0.433 | 0.268 | 0.324 | 0.199 | 0.014 | Mayotte |
0.156 | 0.437 | 0.279 | 0.294 | 0.206 | 0.014 | Jordan |
0.155 | 0.482 | 0.289 | 0.296 | 0.209 | 0.015 | Botswana |
0.154 | 0.467 | 0.287 | 0.289 | 0.207 | 0.015 | Lao People's Democratic Republic |
0.152 | 0.458 | 0.279 | 0.285 | 0.196 | 0.015 | Timor-Leste |
0.146 | 0.413 | 0.282 | 0.281 | 0.214 | 0.014 | Saudi Arabia |
0.145 | 0.425 | 0.254 | 0.271 | 0.182 | 0.014 | Eswatini |
0.139 | 0.394 | 0.248 | 0.265 | 0.183 | 0.013 | Namibia |
0.135 | 0.400 | 0.302 | 0.246 | 0.219 | 0.014 | Kuwait |
0.134 | 0.400 | 0.244 | 0.254 | 0.178 | 0.013 | Sudan |
0.133 | 0.391 | 0.245 | 0.248 | 0.177 | 0.013 | Gabon |
0.130 | 0.381 | 0.231 | 0.244 | 0.170 | 0.013 | Ethiopia |
0.130 | 0.397 | 0.242 | 0.252 | 0.175 | 0.013 | Solomon Islands |
0.128 | 0.369 | 0.245 | 0.233 | 0.177 | 0.012 | Tajikistan |
0.127 | 0.384 | 0.236 | 0.239 | 0.171 | 0.013 | Africa |
0.125 | 0.378 | 0.229 | 0.240 | 0.171 | 0.013 | Iraq |
0.125 | 0.336 | 0.253 | 0.224 | 0.190 | 0.012 | Bahrain |
0.124 | 0.366 | 0.225 | 0.230 | 0.164 | 0.012 | South Sudan |
0.123 | 0.398 | 0.244 | 0.216 | 0.170 | 0.013 | Vanuatu |
0.122 | 0.401 | 0.247 | 0.227 | 0.176 | 0.013 | Papua New Guinea |
0.121 | 0.366 | 0.226 | 0.228 | 0.164 | 0.012 | Liberia |
0.121 | 0.360 | 0.222 | 0.229 | 0.162 | 0.012 | Benin |
0.120 | 0.357 | 0.224 | 0.224 | 0.163 | 0.012 | Mauritania |
0.120 | 0.355 | 0.222 | 0.220 | 0.162 | 0.012 | State of Palestine |
0.119 | 0.351 | 0.219 | 0.191 | 0.153 | 0.012 | Sao Tome and Principe |
0.118 | 0.488 | 0.278 | 0.250 | 0.193 | 0.016 | Micronesia (Fed. States of) |
0.118 | 0.306 | 0.222 | 0.222 | 0.173 | 0.011 | Oman |
0.118 | 0.398 | 0.260 | 0.214 | 0.184 | 0.013 | Western Sahara |
0.116 | 0.360 | 0.230 | 0.212 | 0.165 | 0.012 | Ghana |
0.116 | 0.346 | 0.216 | 0.218 | 0.159 | 0.012 | Madagascar |
0.113 | 0.349 | 0.220 | 0.217 | 0.159 | 0.012 | Comoros |
0.112 | 0.331 | 0.205 | 0.211 | 0.151 | 0.011 | Zimbabwe |
0.112 | 0.349 | 0.216 | 0.218 | 0.158 | 0.012 | Rwanda |
0.111 | 0.342 | 0.208 | 0.206 | 0.151 | 0.011 | Senegal |
0.110 | 0.331 | 0.203 | 0.205 | 0.148 | 0.011 | Democratic Republic of the Congo |
0.107 | 0.326 | 0.202 | 0.196 | 0.147 | 0.011 | Yemen |
0.106 | 0.326 | 0.203 | 0.195 | 0.147 | 0.011 | Sierra Leone |
0.103 | 0.394 | 0.239 | 0.217 | 0.170 | 0.013 | Kiribati |
0.103 | 0.315 | 0.192 | 0.189 | 0.139 | 0.011 | Mozambique |
0.102 | 0.319 | 0.192 | 0.189 | 0.139 | 0.011 | Somalia |
0.102 | 0.328 | 0.202 | 0.187 | 0.146 | 0.011 | Togo |
0.101 | 0.316 | 0.201 | 0.185 | 0.145 | 0.011 | Congo |
0.101 | 0.312 | 0.191 | 0.186 | 0.139 | 0.011 | Central African Republic |
0.100 | 0.325 | 0.194 | 0.185 | 0.139 | 0.011 | Guinea |
0.100 | 0.323 | 0.197 | 0.184 | 0.142 | 0.011 | Côte d'Ivoire |
0.098 | 0.305 | 0.189 | 0.178 | 0.137 | 0.011 | Cameroon |
0.097 | 0.321 | 0.192 | 0.178 | 0.137 | 0.011 | Guinea-Bissau |
0.097 | 0.295 | 0.183 | 0.176 | 0.133 | 0.010 | Malawi |
0.096 | 0.298 | 0.186 | 0.175 | 0.135 | 0.010 | United Republic of Tanzania |
0.096 | 0.298 | 0.184 | 0.175 | 0.134 | 0.010 | Afghanistan |
0.094 | 0.291 | 0.186 | 0.172 | 0.137 | 0.010 | Kenya |
0.094 | 0.309 | 0.190 | 0.171 | 0.136 | 0.011 | Nigeria |
0.092 | 0.279 | 0.179 | 0.167 | 0.131 | 0.010 | Equatorial Guinea |
0.091 | 0.286 | 0.177 | 0.162 | 0.127 | 0.010 | Gambia |
0.091 | 0.278 | 0.170 | 0.168 | 0.125 | 0.010 | Chad |
0.090 | 0.254 | 0.203 | 0.158 | 0.157 | 0.010 | Qatar |
0.088 | 0.288 | 0.172 | 0.162 | 0.124 | 0.010 | Niger |
0.088 | 0.275 | 0.173 | 0.160 | 0.126 | 0.010 | Burkina Faso |
0.088 | 0.270 | 0.169 | 0.161 | 0.124 | 0.010 | Burundi |
0.087 | 0.277 | 0.169 | 0.162 | 0.123 | 0.010 | Mali |
0.085 | 0.253 | 0.164 | 0.155 | 0.121 | 0.009 | Angola |
0.083 | 0.210 | 0.190 | 0.146 | 0.147 | 0.009 | United Arab Emirates |
0.083 | 0.246 | 0.158 | 0.150 | 0.118 | 0.009 | Zambia |
0.074 | 0.231 | 0.147 | 0.136 | 0.109 | 0.009 | Uganda |
Note that in addition to countries, there are rows for each continent and for the world.
The overall IFR estimates of COVID-19, with the exception of Levin et al., are relatively consistent with each other, usually within 30-40%. Levin et al. is often up to 2-fold higher than the others, depending on the country.
The country with the oldest population is expected to have the highest overall IFR: Japan at 1.274-1.605% (excluding Levin et al.)
The country with the youngest population is expected to have the lowest overall IFR: Uganda at 0.074-0.147%.
The overall IFR varies dramatically by more than 10-fold between countries with a young population and those with an old population.
In fact, the young age of the population in Africa is a major factor explaining the relatively small number of deaths on this continent. We find (ENE-COVID) IFR=0.127% for Africa, and IFR=0.810% in Europe, a 6-fold difference.
The overall IFR of COVID-19 is, for each world region and the world:
Our code, with the ENE-COVID Spanish serosurvey data from June 2020, accurately predicted an overall IFR of 0.669% in the United States, which is very close to overall US CDC estimate of 0.65% published in July 2020.
The IFR of COVID-19 is one order of magnitude (10×) higher than the seasonal flu for all regions. For example, in the US the average flu IFR is 0.078%, compared to 0.669-1.169% for COVID-19.
One of the largest serological prevalence surveys of COVID-19 was conducted by Spain during the second round of the ENE-COVID study that analyzed 63 564 samples between 18 May 2020 and 01 June 2020. We used its provisional results published on 03 June to calculate the overall and age-stratified IFR of COVID-19 with the Python script calc_ifr.py:
$ ./calc_ifr.py
Ages 0 to 9: 115013 infected, 4 deaths, 0.003% IFR
Ages 10 to 19: 177929 infected, 7 deaths, 0.004% IFR
Ages 20 to 29: 212099 infected, 32 deaths, 0.015% IFR
Ages 30 to 39: 281290 infected, 86 deaths, 0.030% IFR
Ages 40 to 49: 447942 infected, 287 deaths, 0.064% IFR
Ages 50 to 59: 410213 infected, 874 deaths, 0.213% IFR
Ages 60 to 69: 334709 infected, 2404 deaths, 0.718% IFR
Ages 70 to 79: 270572 infected, 6451 deaths, 2.384% IFR
Ages 80 to 89: 131703 infected, 11150 deaths, 8.466% IFR
Ages 90 to 199: 46631 infected, 5827 deaths, 12.497% IFR
Ages 0 to 199: 2428102 infected, 27121 deaths, 1.117% IFR
The average IFR for Spain is 1.117%. However the true IFR may be higher due to right-censoring, under-reporting of deaths, or low specificity of the serological test; or the true IFR may be lower due to low sensitivity of the serological test.
The age-stratified IFR was calculated from three sources:
In order to minimize right-censoring (deaths lagging infections,) the parameters total deaths and deaths per age bracket should be obtained from a point in time as close as possible to when the serosurvey was conducted (18 May to 01 June, preferably closer to the mid-point 25 May.) This is because the seroconversion time is roughly the same as the time between infection and death. We found only two Ministry of Health reports in this time period that document deaths per age bracket: 18 May, 29 May. However the Ministry of Health has made significant corrections to deaths statistics on 25 May by subtracting approximately 2 000 deaths. Therefore we trusted the statistics from 29 May over those of 18 May. Furthermore, 29 May is closer to the mid-point.
Important detail to note: there were 27 121 total deaths, however age information was only available for 20 585 deaths, and was missing for 6 536 deaths. We assume that these 6 536 deaths were distributed proportionally—not equally—among age brackets, which seems to be a reasonable assumption.
Regarding the specificity of the commercial test used (COVID-19 IgG Rapid Test Cassette by Zhejiang Orient Gene Biotech Co Ltd) we found various claims, all 100% or close, so no significant false positives are expected:
However the sensitivity is more uncertain:
So a false negative rate anywhere from 3% to 21% could be possible, and we think it is premature to adjust IFR calculations given the exact sensitivity is not known.