The world's population first reached one billion people in 1803, and reach eight billion in 2023, and will peak at almost 11 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two thirds of the world's population live in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a decade later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

Chart and table of India population from 1950 to 2025. United Nations projections are also included through the year 2100.

This is a hybrid gridded dataset of demographic data for the world, given as 5-year population bands at a 0.5 degree grid resolution. This dataset combines the NASA SEDAC Gridded Population of the World version 4 (GPWv4) with the ISIMIP Histsoc gridded population data and the United Nations World Population Program (WPP) demographic modelling data. Demographic fractions are given for the time period covered by the UN WPP model (1950-2050) while demographic totals are given for the time period covered by the combination of GPWv4 and Histsoc (1950-2020) Method - demographic fractions Demographic breakdown of country population by grid cell is calculated by combining the GPWv4 demographic data given for 2010 with the yearly country breakdowns from the UN WPP. This combines the spatial distribution of demographics from GPWv4 with the temporal trends from the UN WPP. This makes it possible to calculate exposure trends from 1980 to the present day. To combine the UN WPP demographics with the GPWv4 demographics, we calculate for each country the proportional change in fraction of demographic in each age band relative to 2010 as: (\delta_{year,\ country,age}^{\text{wpp}} = f_{year,\ country,age}^{\text{wpp}}/f_{2010,country,age}^{\text{wpp}}) Where: - (\delta_{year,\ country,age}^{\text{wpp}}) is the ratio of change in demographic for a given age and and country from the UN WPP dataset. - (f_{year,\ country,age}^{\text{wpp}}) is the fraction of population in the UN WPP dataset for a given age band, country, and year. - (f_{2010,country,age}^{\text{wpp}}) is the fraction of population in the UN WPP dataset for a given age band, country for the year 2020. The gridded demographic fraction is then calculated relative to the 2010 demographic data given by GPWv4. For each subset of cells corresponding to a given country c, the fraction of population in a given age band is calculated as: (f_{year,c,age}^{\text{gpw}} = \delta_{year,\ country,age}^{\text{wpp}}*f_{2010,c,\text{age}}^{\text{gpw}}) Where: - (f_{year,c,age}^{\text{gpw}}) is the fraction of the population in a given age band for given year, for the grid cell c. - (f_{2010,c,age}^{\text{gpw}}) is the fraction of the population in a given age band for 2010, for the grid cell c. The matching between grid cells and country codes is performed using the GPWv4 gridded country code lookup data and country name lookup table. The final dataset is assembled by combining the cells from all countries into a single gridded time series. This time series covers the whole period from 1950-2050, corresponding to the data available in the UN WPP model. Method - demographic totals Total population data from 1950 to 1999 is drawn from ISIMIP Histsoc, while data from 2000-2020 is drawn from GPWv4. These two gridded time series are simply joined at the cut-over date to give a single dataset covering 1950-2020. The total population per age band per cell is calculated by multiplying the population fractions by the population totals per grid cell. Note that as the total population data only covers until 2020, the time span covered by the demographic population totals data is 1950-2020 (not 1950-2050). Disclaimer This dataset is a hybrid of different datasets with independent methodologies. No guarantees are made about the spatial or temporal consistency across dataset boundaries. The dataset may contain outlier points (e.g single cells with demographic fractions >1). This dataset is produced on a 'best effort' basis and has been found to be broadly consistent with other approaches, but may contain inconsistencies which not been identified. {"references": ["UN. (2019). World Population Prospects 2019: Data Booklet. Retrieved from https://population.un.org/wpp/Publications/Files/WPP2019_DataBooklet.pdf", "NASA SEDAC, & CIESIN. (2016). Gridded Population of the World, Version 4 (GPWv4): Population Count. New York, New York, USA: Columbia University. Retrieved from http://dx.doi.org/10.7927/H4X63JVC", "ISIMIP. (2018). ISIMIP Project Design and Simulation Protocol. Retrieved from https://www.isimip.org/gettingstarted/input-data-bias-correction/details/31/"]}

A flexible model to reconstruct education-specific fertility rates: Sub-saharan Africa case study

The fertility rates are consistent with the United Nation World Population Prospects (UN WPP) 2022 fertility rates.

The Bayesian model developed to reconstruct the fertility rates using Demographic and Health Surveys and the UN WPP is published in a working paper.

Abstract

The future world population growth and size will be largely determined by the pace of fertility decline in sub-Saharan Africa. Correct estimates of education-specific fertility rates are crucial for projecting the future population. Yet, consistent cross-country comparable estimates of education-specific fertility for sub-Saharan African countries are still lacking. We propose a flexible Bayesian hierarchical model to reconstruct education-specific fertility rates by using the patchy Demographic and Health Surveys (DHS) data and the United Nations’ (UN) reliable estimates of total fertility rates (TFR). Our model produces estimates that match the UN TFR to different extents (in other words, estimates of varying levels of consistency with the UN). We present three model specifications: consistent but not identical with the UN, fully-consistent (nearly identical) with the UN, and consistent with the DHS. Further, we provide a full time series of education-specific TFR estimates covering five-year periods between 1980 and 2014 for 36 sub-Saharan African countries. The results show that the DHS-consistent estimates are usually higher than the UN-fully-consistent ones. The differences between the three model estimates vary substantially in size across countries, yielding 1980-2014 fertility trends that differ from each other mostly in level only but in some cases also in direction.

Funding

The data set are part of the BayesEdu Project at Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna) funded from the “Innovation Fund Research, Science and Society” by the Austrian Academy of Sciences (ÖAW).

We provide education-specific total fertility rates (ESTFR) from three model specifications: (1) estimated TFR consistent but not identical with the TFR estimated by the UN (“Main model (UN-consistent)”; (2) estimated TFR fully consistent (nearly identical) with the TFR estimated by the UN ( “UN-fully -consistent”, and (3) estimated TFR consistent only with the TFR estimated by the DHS ( “DHS-consistent”).

For education- and age-specific fertility rates that are UN-fully consistent, please see https://doi.org/10.5281/zenodo.8182960

Variables

Country: Country names

Education: Four education levels, No Education, Primary Education, Secondary Education and Higher Education.

Year: Five-year periods between 1980 and 2015.

ESTFR: Median education-specific total fertility rate estimate

sd: Standard deviation

Upp50: 50% Upper Credible Interval

Lwr50: 50% Lower Credible Interval

Upp80: 80% Upper Credible Interval

Lwr80: 80% Lower Credible Interval

Model: Three model specifications as explained above and in the working paper. DHS-consistent, Main model (UN-consistent) and UN-fully consistent.

List of countries:

Angola, Benin, Burkina Faso, Burundi, Cote D'Ivoire, Cameroon, Central African Republic, Chad, Comoros, Congo, Democratic Republic of Congo, Eswatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mozambique, Namibia, Niger, Nigeria, Rwanda, Senegal, Sierra Leone, South Africa, Tanzania, Togo, Uganda, Zambia, Zimbabwe

In 1800, the population of Ethiopia was 2.95 million. Like most other Sub-Saharan countries, Ethiopia experienced slow but steady growth for much of the 18th century, and growth which would increase exponentially as the country entered the 20th century. Ethiopia’s population grew more rapidly as the 20th century progressed, however, this growth was offset in the late 1970s, with the beginning of the Ethiopian Civil War and the coinciding Qey Shibir (Red Terror) campaign. However, despite experiencing a significant famine from 1983 to 1985, which would result in approximately one million deaths, Ethiopia’s population would begin to grow rapidly once more, from 35 million in 1980 to 66 million by the beginning of the 21st century. By 2020, Ethiopia is estimated to have a population of almost 115 million, with some experts predicting that Ethiopia may become one of the most populous countries in the world by 2100.

As of July 2024, Nigeria's population was estimated at around 229.5 million. Between 1965 and 2024, the number of people living in Nigeria increased at an average rate of over two percent. In 2024, the population grew by 2.42 percent compared to the previous year. Nigeria is the most populous country in Africa. By extension, the African continent records the highest growth rate in the world. Africa's most populous country Nigeria was the most populous country in Africa as of 2023. As of 2022, Lagos held the distinction of being Nigeria's biggest urban center, a status it also retained as the largest city across all of sub-Saharan Africa. The city boasted an excess of 17.5 million residents. Notably, Lagos assumed the pivotal roles of the nation's primary financial hub, cultural epicenter, and educational nucleus. Furthermore, Lagos was one of the largest urban agglomerations in the world. Nigeria's youthful population In Nigeria, a significant 50 percent of the populace is under the age of 19. The most prominent age bracket is constituted by those up to four years old: comprising 8.3 percent of men and eight percent of women as of 2021. Nigeria boasts one of the world's most youthful populations. On a broader scale, both within Africa and internationally, Niger maintains the lowest median age record. Nigeria secures the 20th position in global rankings. Furthermore, the life expectancy in Nigeria is an average of 62 years old. However, this is different between men and women. The main causes of death have been neonatal disorders, malaria, and diarrheal diseases.

Chart and table of Ghana population from 1950 to 2025. United Nations projections are also included through the year 2100.

Chart and table of Pakistan population from 1950 to 2025. United Nations projections are also included through the year 2100.

In 1800, the population of modern day area of South Africa was approximately 1.44 million. Like most of the continent, the population of South Africa increased gradually through most of the 19th century, reaching 4.71 million by the start of the 20th century. Beginning in the 20th century however, the population would begin to rise exponentially as industrialization, advances in medicine and health, and the spread of vaccinations allowed for lower child mortality rates and increased life expectancy among adults. The population of South Africa would continue to rise exponentially for almost a century, going from just under 5 million at the start of the 1900s to almost 45 million by 2000. However, since the early 2000s, South Africa’s population growth has slowed, the result of a significant decrease in fertility rates in the country in recent years. In 2020, South Africa is estimated to have a population of 59.31 million.

In 2021, about 37.7 percent of the U.S. population who were aged 25 and above had graduated from college or another higher education institution, a slight decline from 37.9 the previous year. However, this is a significant increase from 1960, when only 7.7 percent of the U.S. population had graduated from college.

Demographics

Educational attainment varies by gender, location, race, and age throughout the United States. Asian-American and Pacific Islanders had the highest level of education, on average, while Massachusetts and the District of Colombia are areas home to the highest rates of residents with a bachelor’s degree or higher. However, education levels are correlated with wealth. While public education is free up until the 12th grade, the cost of university is out of reach for many Americans, making social mobility increasingly difficult.

Earnings

White Americans with a professional degree earned the most money on average, compared to other educational levels and races. However, regardless of educational attainment, males typically earned far more on average compared to females. Despite the decreasing wage gap over the years in the country, it remains an issue to this day. Not only is there a large wage gap between males and females, but there is also a large income gap linked to race as well.

In 1800, the population of the region that makes up today's Republic of Uganda was just over two million people. Throughout the 19th century, the population of Uganda would see only modest growth, as increased exposure to the outside world would lead to a series of epidemics afflicting the population, including a devastating outbreak of rinderpest in 1891 killing off much of the region’s cattle, and several outbreaks of smallpox. Uganda’s population would begin to grow more rapidly in the years following the First World War, in part the result of economic growth from wartime agricultural production (unlike neighboring Tanzania, Uganda was spared much of the conflict in East Africa, and as a result saw a significant expansion of cash crop production).

The population of Uganda would continue to grow throughout the remainder of the 20th century, particularly so following the country’s independence from the British Empire in 1962. However, this growth would slow through the 1970s under Idi Amin’s Second Republic of Uganda, which saw real wage and salaries decrease by 90% in less than a decade, and mass expulsions and terror campaigns resulting in a significant number of deaths and refugees throughout the country. Following Idi Amin’s ousting from power in the 1979 Ugandan-Tanzanian War, Uganda’s population has continued to rise exponentially, and in 2020, Uganda is estimated to have a population of approximately 45.7 million.