apply estimates of the age-stratified infection fatality ratio (IFR) of COVID-19 to countries' population pyramids, to find their expected overall IFR
calculate the age-stratified IFR from the Spanish ENE-COVID serosurvey

Age-stratified IFR applied to countries' population pyramids

The script apply_ifr.py uses a handful of age-stratified IFR estimates and applies them to countries' population pyramids, to find their expected overall IFR assuming equal prevalence of the disease among all age groups.

Of course, the real-world overall IFR will dependent on many factors: varying prevalence among age groups, underlying health conditions, access to healthcare, socioeconomic status, ethnicity, etc.

IFR estimates come from:

ENE-COVID Spanish serosurvey (calculated by calc_ifr.py, see next section)
US CDC (table 1)
Verity et al.: Estimates of the severity of coronavirus disease 2019: a model-based analysis (table 1)
Levin et al.: Assessing the age specificity of infection fatality rates for COVID-19: systematic review, meta-analysis, and public policy implications (table 3)
Humoral Immune Response to SARS-CoV-2 in Iceland, Supplementary Appendix 1 (table S7)

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

Results

The overall expected IFR percentages are summarized in this table:

ENE-COV	US_CDC	Verity	Levin	Iceland	Region
0.074	0.099	0.147	0.121	0.137	Uganda
0.083	0.107	0.158	0.134	0.144	Zambia
0.083	0.104	0.190	0.130	0.124	United Arab Emirates
0.085	0.111	0.164	0.139	0.145	Angola
0.087	0.117	0.169	0.145	0.147	Mali
0.088	0.109	0.169	0.144	0.146	Burundi
0.088	0.118	0.173	0.144	0.145	Burkina Faso
0.088	0.121	0.172	0.146	0.147	Niger
0.090	0.112	0.203	0.141	0.126	Qatar
0.091	0.116	0.170	0.150	0.152	Chad
0.091	0.126	0.177	0.146	0.149	Gambia
0.092	0.118	0.179	0.149	0.149	Equatorial Guinea
0.094	0.130	0.190	0.154	0.145	Nigeria
0.094	0.122	0.186	0.153	0.148	Kenya
0.096	0.128	0.184	0.156	0.151	Afghanistan
0.096	0.129	0.186	0.157	0.152	United Republic of Tanzania
0.097	0.129	0.183	0.157	0.155	Malawi
0.097	0.130	0.192	0.160	0.150	Guinea-Bissau
0.098	0.130	0.189	0.160	0.153	Cameroon
0.100	0.135	0.197	0.165	0.152	Côte d'Ivoire
0.100	0.134	0.194	0.166	0.154	Guinea
0.101	0.133	0.191	0.166	0.156	Central African Republic
0.101	0.137	0.201	0.166	0.152	Congo
0.102	0.139	0.202	0.168	0.152	Togo
0.102	0.135	0.192	0.168	0.158	Somalia
0.103	0.136	0.192	0.168	0.160	Mozambique
0.103	0.165	0.239	0.197	0.135	Kiribati
0.106	0.141	0.203	0.174	0.159	Sierra Leone
0.107	0.139	0.202	0.175	0.160	Yemen
0.110	0.144	0.203	0.182	0.166	Democratic Republic of the Congo
0.111	0.146	0.208	0.184	0.165	Senegal
0.112	0.146	0.216	0.193	0.161	Rwanda
0.112	0.142	0.205	0.188	0.169	Zimbabwe
0.113	0.149	0.220	0.193	0.162	Comoros
0.116	0.146	0.216	0.193	0.166	Madagascar
0.116	0.157	0.230	0.190	0.159	Ghana
0.118	0.160	0.260	0.195	0.143	Western Sahara
0.118	0.138	0.222	0.195	0.165	Oman
0.118	0.178	0.278	0.228	0.136	Micronesia (Fed. States of)
0.119	0.150	0.219	0.173	0.170	Sao Tome and Principe
0.120	0.157	0.222	0.196	0.171	State of Palestine
0.120	0.155	0.224	0.199	0.170	Mauritania
0.121	0.157	0.222	0.203	0.173	Benin
0.121	0.157	0.226	0.203	0.171	Liberia
0.122	0.165	0.247	0.204	0.160	Papua New Guinea
0.123	0.168	0.244	0.196	0.163	Vanuatu
0.124	0.163	0.225	0.204	0.176	South Sudan
0.125	0.150	0.253	0.199	0.156	Bahrain
0.125	0.157	0.229	0.212	0.176	Iraq
0.127	0.165	0.236	0.212	0.176	Africa
0.128	0.158	0.245	0.207	0.169	Tajikistan
0.130	0.174	0.242	0.224	0.179	Solomon Islands
0.130	0.167	0.231	0.216	0.183	Ethiopia
0.133	0.173	0.245	0.221	0.182	Gabon
0.134	0.173	0.244	0.224	0.183	Sudan
0.135	0.176	0.302	0.222	0.145	Kuwait
0.139	0.173	0.248	0.234	0.188	Namibia
0.145	0.187	0.254	0.239	0.199	Eswatini
0.146	0.180	0.282	0.248	0.177	Saudi Arabia
0.152	0.209	0.279	0.253	0.197	Timor-Leste
0.154	0.199	0.287	0.257	0.191	Lao People's Democratic Republic
0.155	0.203	0.289	0.263	0.193	Botswana
0.156	0.199	0.279	0.260	0.199	Jordan
0.157	0.194	0.268	0.281	0.212	Mayotte
0.157	0.183	0.277	0.252	0.203	Maldives
0.158	0.204	0.273	0.268	0.208	Eritrea
0.164	0.210	0.292	0.274	0.206	Pakistan
0.168	0.221	0.314	0.288	0.199	Cambodia
0.170	0.238	0.325	0.271	0.197	Samoa
0.170	0.225	0.317	0.287	0.205	Djibouti
0.173	0.216	0.320	0.294	0.201	Mongolia
0.181	0.229	0.319	0.308	0.221	Lesotho
0.182	0.226	0.324	0.307	0.216	Libya
0.185	0.224	0.323	0.317	0.222	Syrian Arab Republic
0.187	0.219	0.340	0.317	0.212	Uzbekistan
0.188	0.245	0.353	0.344	0.216	French Guiana
0.188	0.220	0.335	0.310	0.217	Kyrgyzstan
0.192	0.262	0.376	0.318	0.206	Fiji
0.192	0.247	0.343	0.321	0.224	Egypt
0.193	0.222	0.339	0.316	0.220	Turkmenistan
0.193	0.251	0.355	0.325	0.220	South Africa
0.194	0.237	0.331	0.330	0.233	Haiti
0.197	0.249	0.381	0.331	0.210	Brunei Darussalam
0.202	0.267	0.360	0.344	0.232	Nepal
0.204	0.255	0.360	0.342	0.232	Philippines
0.204	0.233	0.323	0.349	0.253	Guatemala
0.206	0.235	0.331	0.353	0.249	Honduras
0.208	0.235	0.334	0.351	0.244	Belize
0.215	0.277	0.401	0.366	0.228	Myanmar
0.217	0.284	0.375	0.310	0.247	Tonga
0.221	0.232	0.349	0.374	0.260	Cabo Verde
0.221	0.269	0.368	0.374	0.255	Bangladesh
0.228	0.259	0.373	0.393	0.262	Nicaragua
0.229	0.293	0.416	0.387	0.244	Indonesia
0.234	0.293	0.414	0.398	0.253	India
0.246	0.301	0.431	0.418	0.263	Iran (Islamic Republic of)
0.251	0.297	0.403	0.423	0.288	Bhutan
0.257	0.307	0.418	0.436	0.287	Paraguay
0.260	0.305	0.426	0.446	0.289	Algeria
0.263	0.325	0.453	0.442	0.279	Malaysia
0.269	0.358	0.495	0.460	0.272	Bahamas
0.272	0.337	0.474	0.462	0.284	Morocco
0.273	0.313	0.474	0.452	0.279	Azerbaijan
0.280	0.335	0.463	0.469	0.298	Suriname
0.282	0.326	0.456	0.456	0.298	Guyana
0.287	0.384	0.527	0.513	0.286	French Polynesia
0.293	0.400	0.542	0.477	0.284	Seychelles
0.295	0.346	0.482	0.501	0.317	Lebanon
0.303	0.347	0.474	0.525	0.329	Ecuador
0.305	0.365	0.502	0.526	0.317	Venezuela (Bolivarian Republic of)
0.306	0.352	0.485	0.532	0.327	Mexico
0.307	0.348	0.503	0.505	0.319	Kazakhstan
0.309	0.348	0.480	0.532	0.333	Dominican Republic
0.310	0.350	0.463	0.535	0.346	Bolivia (Plurinational State of)
0.325	0.394	0.541	0.559	0.331	Asia
0.327	0.432	0.573	0.547	0.328	New Caledonia
0.336	0.394	0.553	0.579	0.344	Tunisia
0.339	0.397	0.537	0.583	0.358	Peru
0.342	0.408	0.552	0.588	0.356	Turkey
0.343	0.363	0.528	0.602	0.355	Viet Nam
0.347	0.399	0.528	0.595	0.377	El Salvador
0.354	0.438	0.595	0.642	0.368	Grenada
0.355	0.412	0.560	0.613	0.367	Colombia
0.356	0.410	0.555	0.614	0.371	Latin America and the Caribbean
0.358	0.418	0.566	0.615	0.370	WORLD
0.359	0.399	0.540	0.623	0.380	Panama
0.361	0.454	0.605	0.663	0.375	Saint Vincent and the Grenadines
0.364	0.425	0.569	0.627	0.381	Jamaica
0.365	0.464	0.611	0.618	0.373	Guam
0.376	0.437	0.594	0.645	0.382	Brazil
0.377	0.487	0.635	0.622	0.373	Dem. People's Republic of Korea
0.387	0.495	0.651	0.668	0.377	Sri Lanka
0.394	0.497	0.648	0.712	0.409	Antigua and Barbuda
0.409	0.507	0.695	0.707	0.385	China
0.413	0.468	0.626	0.704	0.413	Saint Lucia
0.413	0.475	0.638	0.712	0.417	Costa Rica
0.415	0.511	0.681	0.717	0.402	Trinidad and Tobago
0.435	0.501	0.721	0.766	0.413	Republic of Moldova
0.447	0.544	0.732	0.772	0.425	Mauritius
0.449	0.514	0.738	0.770	0.412	China, Macao SAR
0.454	0.515	0.671	0.790	0.471	Argentina
0.479	0.550	0.796	0.829	0.433	Singapore
0.493	0.550	0.736	0.861	0.492	Chile
0.497	0.616	0.816	0.851	0.474	North Macedonia
0.497	0.522	0.748	0.794	0.491	Armenia
0.499	0.545	0.710	0.872	0.516	Israel
0.500	0.569	0.763	0.880	0.493	Réunion
0.510	0.588	0.795	0.881	0.491	Thailand
0.518	0.580	0.754	0.902	0.526	Oceania
0.531	0.652	0.874	0.920	0.508	Aruba
0.548	0.659	0.857	0.941	0.533	Albania
0.561	0.649	0.839	0.957	0.559	Cyprus
0.563	0.653	0.838	0.972	0.559	Ireland
0.582	0.667	0.891	0.989	0.567	Montenegro
0.604	0.709	0.935	1.059	0.580	Slovakia
0.605	0.683	0.888	1.061	0.599	Iceland
0.607	0.670	0.896	1.002	0.598	Georgia
0.615	0.668	0.881	1.078	0.616	Luxembourg
0.624	0.657	0.921	1.082	0.606	Belarus
0.624	0.663	0.916	1.030	0.606	Russian Federation
0.628	0.686	0.938	1.100	0.599	China, Taiwan Province of China
0.633	0.725	0.963	1.090	0.606	Republic of Korea
0.641	0.877	1.059	1.152	0.608	United States Virgin Islands
0.644	0.735	0.941	1.131	0.630	Cuba
0.654	0.742	0.945	1.137	0.645	New Zealand
0.659	0.757	1.011	1.088	0.620	Bosnia and Herzegovina
0.669	0.738	0.958	1.169	0.654	United States of America
0.671	0.733	0.983	1.103	0.651	Ukraine
0.671	0.736	0.944	1.174	0.670	Australia
0.675	0.745	0.967	1.181	0.660	Northern America
0.676	0.694	0.904	1.193	0.686	Uruguay
0.680	0.800	1.029	1.160	0.659	Serbia
0.709	0.802	1.007	1.239	0.699	Norway
0.713	0.808	1.038	1.210	0.694	Curaçao
0.719	0.756	0.998	1.259	0.705	Barbados
0.734	0.810	1.047	1.288	0.714	Canada
0.738	0.878	1.092	1.302	0.717	Czechia
0.739	0.828	1.059	1.315	0.737	Channel Islands
0.745	0.800	1.064	1.285	0.724	Poland
0.753	0.854	1.101	1.323	0.732	Hungary
0.759	0.830	1.090	1.285	0.745	Romania
0.791	0.811	1.102	1.367	0.761	China, Hong Kong SAR
0.794	0.868	1.089	1.384	0.794	United Kingdom
0.797	0.935	1.136	1.370	0.782	Denmark
0.798	0.864	1.113	1.399	0.779	Guadeloupe
0.801	0.949	1.181	1.377	0.779	Bulgaria
0.802	0.909	1.141	1.394	0.785	Netherlands
0.810	0.861	1.117	1.396	0.802	Europe
0.825	0.897	1.132	1.447	0.819	Switzerland
0.836	0.910	1.149	1.462	0.830	Austria
0.840	0.943	1.154	1.471	0.838	Sweden
0.843	0.905	1.181	1.489	0.829	Slovenia
0.846	0.881	1.137	1.478	0.847	Belgium
0.855	0.965	1.205	1.471	0.835	Malta
0.865	0.932	1.209	1.487	0.855	Croatia
0.868	0.892	1.171	1.516	0.870	Estonia
0.875	0.957	1.205	1.528	0.857	Puerto Rico
0.881	0.919	1.192	1.624	0.870	Latvia
0.899	1.008	1.248	1.556	0.883	Finland
0.914	0.941	1.201	1.606	0.913	France
0.916	0.942	1.207	1.648	0.921	Spain
0.919	0.933	1.221	1.658	0.918	Lithuania
0.931	0.985	1.270	1.648	0.918	Martinique
0.984	1.045	1.320	1.726	0.986	Portugal
0.993	1.012	1.305	1.702	0.994	Germany
1.041	1.043	1.339	1.806	1.057	Greece
1.065	1.092	1.382	1.847	1.068	Italy
1.274	1.311	1.605	2.247	1.283	Japan
-------	------	------	-----	-------	------
ENE-COV	US_CDC	Verity	Levin	Iceland	Region

Note that in addition to countries, there are rows for each continent and for the world.

Findings

The overall IFR estimates, with the exception of Levin et al., are relatively consistent with each other, usually within 30-40%.

The country with the oldest population is expected to have the highest overall IFR: Japan at 1.3-1.6% (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 IFR=0.127% for Africa, and IFR=0.810% in Europe, a 6-fold difference.

Calculating the age-stratified IFR of COVID-19 from the Spanish ENE-COVID study

The largest serological prevalence survey 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 Spanish serological study remains the largest published study available to this day. The age-stratified IFR was calculated from three sources:

Detailed prevalence data for age brackets, from the serosurvey (table 1)
Total deaths and deaths per age bracket from the Ministry of Health's daily report for 29 May (table 2 and table 3)
Population pyramid for Spain, from worldpopulationreview.com

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:

100% claimed by the manufacturer (serosurvey, page 3)
100% measured by the Ministry of Health (serosurvey, page 3)
99.2% measured by a third-party

However the sensitivity is more uncertain:

97% claimed by the manufacturer (serosurvey, page 3)
79% measured by the Ministry of Health (serosurvey, page 3)
93.1% measured by a third-party

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.