Written in Livemark
(2022-01-18 06:06)

Rolling Immunity

Rolling immunity (in terms of this page) is a collective immunity metric based on factual uses cases (counted using deaths) and vaccination shots timeline and the fact that individual immunity decreases over time. This page is about finding relations with pandemic outbreaks and the rolling immunity concept.

Examples

To showcase the idea of rolling immunity, we use 5 countries having different vaccination timeframes. The Israel use case might be showing that having too fast of a vaccination campaign leads to outbreaks due to low levels of rolling immunity. This USA case might be showing that the vaccination level wasn't enough.

Israel

USA

UK

Germany

Brasil

Locations

Explore charts for other countries and share what you think. Take into account that this methodology is very approximate as the numbers depend on the healthcare and vaccines efficacy in the exact country. This table uses 7 day moving averages for deaths and cases:

Location Immunity Deaths/1M Cases/1M
Afghanistan 0.0 0.029 1.549
Africa 0.11 0.256 25.964
Albania 0.1 1.492 654.731
Algeria 0.0 0.237 13.16
Angola 0.0 0.143 15.4
Argentina 0.45 2.155 2500.079
Armenia 0.06 0.77 86.827
Asia 0.45 0.209 100.381
Australia 0.62 1.856 3878.898
Austria 0.55 1.058 1723.198
Azerbaijan 0.25 1.006 63.189
Bahrain 0.33 0.082 1343.35
Bangladesh 0.2 0.042 24.444
Belarus 0.01 1.694 122.587
Belgium 0.49 1.756 2425.444
Benin 0.0 0.011
Bolivia 0.33 3.079 824.72
Bosnia and Herzegovina 0.08 8.58 661.218
Botswana 0.01 2.205 444.261
Brazil 0.43 0.742 351.416
Bulgaria 0.29 11.911 899.525
Burkina Faso 0.0 0.04 4.074
Burundi 0.0 0.0 13.452
Cambodia 0.45 0.0 1.593
Cameroon 0.0 0.0 0.0
Canada 0.41 3.092 810.709
Central African Republic 0.0 0.203
Chad 0.0 0.0 2.795
Chile 0.56 1.048 387.117
China 0.46 0.0 0.128
Colombia 0.28 2.048 586.024
Congo 0.0 0.025 20.859
Costa Rica 0.02 1.084 801.76
Cote d'Ivoire 0.02 0.121 8.428
Croatia 0.33 8.365 1807.704
Cuba 0.87 -1.944 284.894
Czechia 0.41 3.33 970.39
Democratic Republic of Congo 0.0 0.082 3.071
Denmark 0.6 2.728 4327.194
Djibouti 0.0 0.0 95.077
Dominican Republic 0.17 0.183 554.698
Ecuador 0.41
Egypt 0.01 0.252 10.277
El Salvador 0.13 0.153
Equatorial Guinea 0.0 0.099 61.187
Eritrea 0.0 0.238 23.126
Estonia 0.15 3.018 1662.729
Eswatini 0.03 2.681 61.536
Ethiopia 0.05 0.145 14.464
Europe 0.43 4.07 1534.292
European Union 0.45 3.999 2136.847
Finland 0.07
France 0.49 2.678 4184.605
Gabon 0.0 0.251 62.438
Gambia 0.0 0.23 44.806
Georgia 0.21 9.441 1310.771
Germany 0.53 2.927 908.893
Ghana 0.0 0.05
Greece 0.56 8.375 1988.051
Guatemala 0.27 0.415 113.559
Guinea 0.06 0.085 9.833
Guinea-Bissau 0.0 0.213 22.752
Haiti 0.0 0.0 12.526
High income 0.43 3.235 1640.905
Honduras 0.01 0.17 58.318
Hong Kong 0.27 0.0 1.419
Hungary 0.08 8.304 750.618
India 0.43
Indonesia 0.46 0.02 2.984
Iran 0.04 0.302 26.645
Iraq 0.0 0.139 68.935
Ireland 0.51 3776.169
Israel 0.29
Italy 0.53 5.031 2924.844
Jamaica 0.1 1.682 479.48
Japan 0.16 0.036 149.326
Jordan 0.12 1.544 326.029
Kazakhstan 0.19 0.256 540.617
Kenya 0.06 0.117 13.731
Kosovo 0.24 0.24 316.558
Kuwait 0.01 0.165 1085.021
Kyrgyzstan 0.11 0.302 94.895
Laos 0.04 0.949 112.515
Latvia 0.5 5.586 1273.211
Lebanon 0.23 2.089 959.099
Lesotho 0.01 0.265
Liberia 0.0 0.0 7.446
Libya 0.02 1.17 83.597
Lithuania 0.43 5.63 1399.966
Low income 0.08 0.12 10.669
Lower middle income 0.39 0.29 97.999
Madagascar 0.0 8.674
Malawi 0.03 0.393 18.345
Malaysia 0.52 0.493 95.143
Mali 0.0 0.116 18.796
Mauritania 0.01 0.628 171.185
Mauritius 0.03 0.0
Mexico 0.22
Moldova 0.11 2.556 346.384
Mongolia 0.26 0.644 644.197
Morocco 0.05 0.302 180.266
Mozambique 0.01 0.16 37.305
Myanmar 0.0 0.029 2.81
Namibia 0.02 5.356 94.416
Nepal 0.07 0.082 122.947
Netherlands 0.01 0.582 2014.38
New Zealand 0.56 0.028 11.545
Nicaragua 0.0 0.0 0.789
Niger 0.0 0.068 1.916
Nigeria 0.01 0.017 1.653
North America 0.34 3.355 1309.189
North Macedonia 0.1 5.007 762.829
Norway 0.47 0.836 1895.377
Oceania 0.47 1.236 2326.521
Oman 0.0 0.082 144.324
Pakistan 0.14 0.035 16.713
Palestine 0.08 0.875 93.492
Panama 0.28 1.924 1658.566
Papua New Guinea 0.0 0.078 0.674
Paraguay 0.04 2.988 504.635
Peru 0.62
Philippines 0.25 0.818 313.695
Poland 0.24 9.63 387.4
Portugal 0.34 2.824 3467.951
Qatar 0.16 0.39 1399.603
Romania 0.28 1.718 469.811
Russia 0.36 4.878 162.683
Rwanda 0.02 0.291 41.168
Saudi Arabia 0.33 0.053 151.198
Senegal 0.0 0.083 26.75
Serbia 0.11 3.368 1863.752
Sierra Leone 0.0 0.0 1.579
Singapore 0.42 0.131 173.332
Slovakia 0.07 9.496 544.721
Slovenia 0.36 2.955 3095.032
Somalia 0.0 0.0 0.0
South Africa 0.08 2.191 77.227
South America 0.47 1.341 667.427
South Korea 0.83 0.735 82.473
South Sudan 0.0 0.0 3.515
Spain 0.19 2.619 2955.851
Sri Lanka 0.4 0.558 32.609
Sudan 0.0 0.153 10.965
Sweden 0.03
Switzerland 0.42 2.098 3072.836
Syria 0.0 0.156 1.728
Taiwan 0.47 0.006 2.94
Tajikistan 0.0 0.0 0.0
Tanzania 0.0 0.012 1.93
Thailand 0.39
Timor 0.0 0.0 0.532
Togo 0.0 0.118
Trinidad and Tobago 0.35 12.826 409.421
Tunisia 0.26 1.592 515.198
Turkey 0.37 1.809 803.581
Turkmenistan 0.0
Uganda 0.0 0.203 12.626
Ukraine 0.36 3.747 185.715
United Arab Emirates 0.2 0.3 286.684
United Kingdom 0.49 3.873 1446.841
United States 0.34 5.092 2057.786
Upper middle income 0.44 0.811 198.338
Uruguay 0.27 2.009 2649.731
Uzbekistan 0.26 0.088 22.698
Venezuela 0.0 0.129 46.547
Vietnam 0.6
World 0.38 0.891 358.839
Yemen 0.0 0.023 0.726
Zambia 0.03 0.37 93.835
Zimbabwe 0.13 0.738 32.751
Location Immunity Deaths/1M Cases/1M

Methodology

We use oversimplified rolling immunity formula for a date. We use deaths instead of use cases to overcome the problem of inaccurate use cases reporting. The exact ratio is configurable; we use 1 death for 100 use cases based on known death rate for now around 50 use cases per a death and estimating unreported use cases as 50 use cases per 1 death:

rolling_immunity_for_a_date = (estimated_new_cases + new_vaccinations) / population
estimated_new_cases = new_deaths * 100

We count one case to be equal to one vaccination shot. For the model we use the decreasing ration (180 - days)/180 meaning that you will lose all the immunity you had acquired in 180 days. Again, this parameter is configurable and might be changed in other models.

rolling_immunity_for_a_date = 100%
rolling_immunity_for_a_date_in_180_days = 0%

Please take a look at the full algorithm.

A livemark tracking COVID-19 disease pandemic