Gapminder's sources and methodology if well-documented in its dataset at: https://www.gapminder.org/data/
It notes its data sources during three key periods of time:
— 1800 to 1950: Gapminder v7 ( In some cases this is also used for years after 1950, see below.) This was compiled and documented by Mattias Lindgren from many sources, but mainly based on www.mortality.org and the series of books called International Historical Statistics by Brian R Mitchell, which often have historic estimates of Infant mortality rate which were converted to Child mortality through regression. See detailed documentation of v7 below.
— 1950 to 2016: UNIGME, is a data collaboration project between UNICEF, WHO, UN Population Division and the World Bank. They released new estimates of child mortality for countries and a global estimate on October 17, 2017, which is available at www.childmortality.org. In this dataset almost all countries have estimates between 1970 and 2016, while roughly half the countries also reach back to 1950.
— 1950 to 2100: UN WPP, World Population Prospects 2017 provides annual data for Child mortality rate for all countries in the interpolated demographic indicators, called WPP2017_INT_F01_ANNUAL_DEMOGRAPHIC_INDICATORS.xlsx, accessed on September 2, 2017.
Version 12 of the dataset extends back to the year 1800. Version 6 of Gapminder's fertility series includes data for a few countries further than 1800. We have included more historic data from Version 6 for Finland, the United Kingdom and Sweden. All data from 1800 onwards is from Version 12; data from pre-1800 is from Version 6.
There are significant uncertainties in data for many countries pre-1950. To develop full series back to 1800 for all countries, Gapminder combines published estimates within the academic literature and national statistics, with their own guesstimates and extrapolations for countries without published estimates. This series presents the full Gapminder dataset: both those from published estimates and estimates made by Gapminder with high uncertainty. This is provided so users have access to the full dataset.
However, for our main long-term series on child mortality rates at Our World in Data we exclude the highly uncertain data points which are not backed up with published estimates within the literature. Users looking for a series with less uncertainty should refer to that instead.
Kazakhstan | 2100 | 3.8 |
Chad | 2100 | 22.7 |
Cambodia | 2100 | 2.55 |
Honduras | 2100 | 3.69 |
Germany | 2100 | 1.75 |
Bosnia and Herzegovina | 2100 | 2.61 |
Algeria | 2100 | 4.74 |
Bhutan | 2100 | 4.17 |
Indonesia | 2100 | 6.36 |
Democratic Republic of Congo | 2100 | 15.88 |
Albania | 2100 | 2.38 |
Argentina | 2100 | 2.48 |
Bahrain | 2100 | 2.24 |
Latvia | 2100 | 2.7 |
Cape Verde | 2100 | 5.64 |
Belarus | 2100 | 1.56 |
Italy | 2100 | 1.78 |
Austria | 2100 | 1.68 |
Kuwait | 2100 | 2.04 |
Kyrgyzstan | 2100 | 5.58 |
Equatorial Guinea | 2100 | 13.52 |
Guinea | 2100 | 7.71 |
Ethiopia | 2100 | 7.96 |
India | 2100 | 7.54 |
Egypt | 2100 | 8.23 |
Greece | 2100 | 1.71 |
Congo | 2100 | 13.0 |
Central African Republic | 2100 | 16.39 |
Canada | 2100 | 1.77 |
Guyana | 2100 | 10.1 |
Kenya | 2100 | 14.64 |
Djibouti | 2100 | 17.72 |
Channel Islands | 2100 | 2.28 |
Aruba | 2100 | 5.24 |
Dominican Republic | 2100 | 5.39 |
French Guiana | 2100 | 2.24 |
Cote d'Ivoire | 2100 | 20.73 |
Lesotho | 2100 | 13.26 |
Antigua and Barbuda | 2100 | 2.82 |
Bulgaria | 2100 | 3.65 |
France | 2100 | 1.73 |
Bangladesh | 2100 | 4.03 |
Guatemala | 2100 | 4.62 |
Zimbabwe | 2100 | 15.79 |
Ghana | 2100 | 11.05 |
Burkina Faso | 2100 | 12.69 |
Lebanon | 2100 | 2.97 |
Jamaica | 2100 | 4.22 |
Costa Rica | 2100 | 2.84 |
Colombia | 2100 | 2.49 |
Guam | 2100 | 2.32 |
Hungary | 2100 | 2.15 |
Israel | 2100 | 1.7 |
French Polynesia | 2100 | 2.81 |
Angola | 2100 | 22.53 |
Barbados | 2100 | 4.65 |
Guinea-Bissau | 2100 | 11.81 |
Bolivia | 2100 | 4.27 |
Grenada | 2100 | 4.14 |
Cyprus | 2100 | 1.71 |
Botswana | 2100 | 9.59 |
Ecuador | 2100 | 3.67 |
Cuba | 2100 | 1.92 |
China | 2100 | 2.4 |
Estonia | 2100 | 1.99 |
Bahamas | 2100 | 4.64 |
Azerbaijan | 2100 | 7.62 |
Gambia | 2100 | 22.81 |
Armenia | 2100 | 3.24 |
Fiji | 2100 | 6.74 |
Iceland | 2100 | 0.46 |
Croatia | 2100 | 2.65 |
Iraq | 2100 | 6.6 |
Haiti | 2100 | 15.73 |
Belgium | 2100 | 1.57 |
Belize | 2100 | 3.01 |
Jordan | 2100 | 3.23 |
El Salvador | 2100 | 3.6 |
Kiribati | 2100 | 13.63 |
Comoros | 2100 | 20.76 |
Guadeloupe | 2100 | 1.25 |
Eritrea | 2100 | 5.74 |
Iran | 2100 | 2.36 |
Gabon | 2100 | 13.69 |
Laos | 2100 | 9.33 |
Brunei | 2100 | 3.43 |
Ireland | 2100 | 0.48 |
Australia | 2100 | 1.53 |
Burundi | 2100 | 10.03 |
Finland | 2100 | 0.46 |
Cameroon | 2100 | 14.64 |
Georgia | 2100 | 3.79 |
Hong Kong | 2100 | 1.81 |
Benin | 2100 | 29.78 |
Brazil | 2100 | 3.95 |
Curacao | 2100 | 3.58 |
Denmark | 2100 | 1.66 |
Japan | 2100 | 1.5 |
Afghanistan | 2100 | 12.34 |
Chile | 2100 | 2.71 |
Data Published By: Gapminder
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