Written in Livemark
(2022-05-26 06:08)

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 1.284
Africa 0.08 0.025 4.894
Albania 0.01 0.0 12.58
Algeria 0.0 0.0 0.09
Angola 0.0 0.0 1.01
Argentina 0.27
Armenia 0.01 0.048 1.059
Asia 0.21 0.049 35.257
Australia 0.27 1.983 1684.053
Austria 0.02 0.569 278.034
Azerbaijan 0.09 0.014 0.405
Bahrain 0.05 0.409 268.343
Bangladesh 0.17 0.003 0.193
Belarus 0.01 0.0 0.0
Belgium 0.15 0.639 163.031
Benin 0.0 0.0 0.0
Bolivia 0.15 0.024
Bosnia and Herzegovina 0.03 0.131 5.297
Botswana 0.0 0.179
Brazil 0.26 0.699 99.663
Bulgaria 0.08 0.911 28.958
Burkina Faso 0.0 0.0 0.0
Burundi 0.0 0.0 3.742
Cambodia 0.19 0.0 0.0
Cameroon 0.0 0.016 0.876
Canada 0.23 1.516 73.894
Central African Republic 0.0 0.0 0.0
Chad 0.0 0.0 0.017
Chile 0.41 0.602 299.197
China 0.22 0.001 3.138
Colombia 0.09
Congo 0.0 0.0 0.0
Costa Rica 0.01
Cote d'Ivoire 0.0 0.0 0.507
Croatia 0.1 0.98 85.994
Cuba 0.23 0.0 4.065
Czechia 0.11 0.266 24.097
Democratic Republic of Congo 0.0 0.0 0.623
Denmark 0.14 0.86 93.185
Djibouti 0.0 0.0 6.272
Dominican Republic 0.05 0.0 15.755
Ecuador 0.21 0.056 17.633
Egypt 0.0 0.0
El Salvador 0.01 0.022 0.0
Equatorial Guinea 0.0 0.0 0.0
Eritrea 0.0 0.0 0.198
Estonia 0.09 0.0
Eswatini 0.0 0.366 44.598
Ethiopia 0.06 0.001 0.714
Europe 0.14 0.858 189.662
European Union 0.16 1.008 284.367
Finland 0.11
France 0.16 0.864 308.676
Gabon 0.0 0.0 0.878
Gambia 0.0 0.0 0.172
Georgia 0.07 0.0 0.0
Germany 0.2 1.236 425.055
Ghana 0.0 0.0 0.203
Greece 0.22 1.708 350.505
Guatemala 0.06 1.252 30.85
Guinea 0.01 0.0 0.0
Guinea-Bissau 0.0 0.0 1.347
Haiti 0.0 0.0 0.693
High income 0.2 0.949 371.175
Honduras 0.0 0.043 4.486
Hong Kong 0.59 0.132 31.965
Hungary 0.04 0.905 45.671
India 0.17 0.023 1.564
Indonesia 0.15 0.028 0.978
Iran 0.1 0.082 3.038
Iraq 0.0 0.007 2.446
Ireland 0.14 1.72 280.875
Israel 0.07 0.323 200.409
Italy 0.22 1.5 390.359
Jamaica 0.04 1.393 106.273
Japan 0.2 0.278 260.531
Jordan 0.01 0.0
Kazakhstan 0.08 0.0 0.647
Kenya 0.04 0.005 0.803
Kosovo 0.04 0.0 5.451
Kuwait 0.0 0.0
Kyrgyzstan 0.06 0.0 0.0
Laos 0.03 0.039 5.963
Latvia 0.12 0.536 91.288
Lebanon 0.11 0.232 14.076
Lesotho 0.0 0.0 3.507
Liberia 0.0 0.0 0.083
Libya 0.01 0.0 0.677
Lithuania 0.1 45.355
Low income 0.07 0.004 0.488
Lower middle income 0.19 0.017 1.855
Madagascar 0.0 0.0 0.191
Malawi 0.0 0.015 0.327
Malaysia 0.2 0.1 60.658
Mali 0.0 0.0 0.192
Mauritania 0.0 0.0 4.876
Mauritius 0.01 0.0
Mexico 0.12
Moldova 0.04 0.568
Mongolia 0.04 0.0
Morocco 0.0 0.004 3.772
Mozambique 0.0 0.009 0.386
Myanmar 0.0 0.0 0.193
Namibia 0.01 0.221 259.836
Nepal 0.09 0.0 0.303
Netherlands 0.01 0.141 61.566
New Zealand 0.26 2.341 1398.725
Nicaragua 0.0 0.021 0.0
Niger 0.0 0.0 0.0
Nigeria 0.0 0.0 0.056
North America 0.18 0.784 198.577
North Korea 0.0 0.0 0.0
North Macedonia 0.03 0.48 30.593
Norway 0.13 2.091 47.152
Oceania 0.21 1.468 1176.682
Oman 0.0 0.0 0.356
Pakistan 0.07 0.0 0.321
Palestine 0.01 0.027
Panama 0.01 0.815 720.157
Papua New Guinea 0.0 0.0 0.486
Paraguay 0.01 0.079
Peru 0.42 0.278 13.1
Philippines 0.04 0.004 1.746
Poland 0.09 0.227 7.072
Portugal 0.02 3.667 2194.689
Puerto Rico 0.0
Qatar 0.2 0.0 49.43
Romania 0.04 0.209 19.583
Russia 0.09 0.605 31.086
Rwanda 0.0 0.0 0.764
Saudi Arabia 0.1 0.049 14.997
Senegal 0.0 0.0 0.316
Serbia 0.03 0.395 41.974
Sierra Leone 0.0 0.0 0.0
Singapore 0.22 0.288 1101.422
Slovakia 0.04 0.498 43.177
Slovenia 0.08 0.275 168.51
Somalia 0.0 0.0 0.122
South Africa 0.06 0.419 78.576
South America 0.26 0.424 83.39
South Korea 0.26 0.615 408.956
South Sudan 0.0 0.0 0.301
Spain 0.07
Sri Lanka 0.11 0.013 0.439
Sudan 0.0 0.013 0.127
Sweden 0.02 1.125 42.941
Switzerland 0.11 0.066
Syria 0.0 0.0 0.078
Taiwan 0.32 2.264 3456.83
Tajikistan 0.0 0.0 0.0
Tanzania 0.0 0.0 0.0
Thailand 0.25 0.584 83.863
Timor 0.0 0.0 0.744
Togo 0.0 0.0 0.607
Trinidad and Tobago 0.08 1.629 345.29
Tunisia 0.04 0.096 13.716
Turkey 0.09 0.049 13.702
Turkmenistan 0.0
Uganda 0.0 0.006
Ukraine 0.05 0.0 0.0
United Arab Emirates 0.05 0.0 35.16
United Kingdom 0.12 1.244 119.916
United States 0.14 1.044 320.489
Upper middle income 0.21 0.163 24.531
Uruguay 0.22
Uzbekistan 0.01 0.0 0.514
Venezuela 0.0 0.02 1.453
Vietnam 0.16 0.009 15.916
World 0.18 0.206 65.938
Yemen 0.0 0.0 0.0
Zambia 0.02 0.015 4.998
Zimbabwe 0.21 0.095 11.558
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