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Data Science Blog > R Shiny > 5 Things You Should Know About The Future of Population

5 Things You Should Know About The Future of Population

Colleen Tapen
Posted on Jul 29, 2018

The skills the authors demonstrated here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

Motivation

About a decade ago, I stumbled upon a TED Talk by a Swedish global health professor named Hans Rosling.  During the video I learned more about global macro-trends (infant mortality, GDP, etc.), opening my eyes to some misconceptions and piquing my interest.  Dr. Roslingโ€™s moving bubble plots enraptured me and his broader audience. See here:

I decided to analyze similar data for myself, to see what I could confirm or uncover about the future of population.  

Methods

I used R to transform data from the UN World Population Prospects 2017 and Gapminder (Dr. Roslingโ€™s organization) into a suitable format for my analysis.  After leveraging dplyr to summarize my data sets, I plotted the data using ggplot2 and googleVis.  Lastly, I built an R Shiny app to showcase my findings and to enable the user to interact with the plots, say by selecting the population category or by toggling by time period.  

Findings

Finding #1. The worldโ€™s population will grow by ~50% to 11b by 2100, driven by African population growth.

Africa made up 16% of the worldโ€™s population in 2015, yet it is projected to rise to 40% of the worldโ€™s population by 2100.  Therefore, Africa and Asia together will make up roughly 80% of the worldโ€™s population, likely moving the locus of the worldโ€™s economy further southeast.  In that same timespan, the UN expects Asia's population to continue to grow until it plateaus and starts declining circa 2055.

Potential implications for this growth include insufficient food and water supply, breakdowns in security, and increases in migration.

Finding #2. Two factors contributing to African population projections include improvements in life expectancy and higher birth rates.

While the explicit drivers of the UN model are unspecified, two likely contributors include life expectancy and birth rate per woman.  First, life expectancy is projected to continue to rise in Africa and in fact has already risen beyond the 2007 figures from Gapminder.  Second, birth rates will continue to come down, but have lagged significantly in many African nations, contributing to the continentโ€™s population boom.  By contrast, birth rates in much of the rest of the world have dropped to around or below replacement rate (roughly 2.1). The UN data for 2020 show Nigerโ€™s birth rate at 6.8 (highest), versus Portugalโ€™s at 1.3 (one of the lowest).  You can see the discrepant birth rates in the coloring of the below map.

(Certainly, I would be remiss if I did not acknowledge other interrelated features like womenโ€™s education, access to contraceptives, and improved economic opportunity.  The UNโ€™s projections must account for a multitude of features while not double-counting their shared impact, but I do not know the precise modeling techniques employed).

Finding #3. An interesting case example is Nigeria: There will be more babies born in a year in Nigeria than born in all of Europe.

Nigeria will experience tremendous population growth and will overtake the U.S. as the third largest country in the world.  More babies will be born in a year (over the coming 2-5 years) in Nigeria than will be born in all of Europe.  Note that Europe is about 11x the size of Nigeria, so Nigerian population density will be quite high.  Nigeriaโ€™s population growth is staggering and little-known.

Finding #4. 80% of the worldโ€™s youth (under 25) lives in Africa and Asia.

Per 2020 UN projections, over half of the worldโ€™s youth live in Asia and a quarter in Africa.  By 2100 this will shift to nearly half in Africa and a third in Asia, leaving only about 10% on the remaining continents.  Significant potential implications include youth unemployment, brain drain, and insufficient capacity of education systems.

Finding #5. The worldโ€™s population will age considerably, and the aging will be more widespread across continents than anticipated.

The aging of the worldโ€™s population will become more pronounced, not only in the usual suspects of Europe and North America, but also in places like Latin America and Asia.  The below rose plot shows total population of each continent from 1990 to 2100, colored by age grouping. The increase of the dark-blue illustrates the aging of the population as a percent of the total.

Why Should We Care?

Regardless of what sector youโ€™re in, implications abound.  In the private sector, there will be approximately two billion new middle class consumers, mostly out of Asia.  As it is, this example speaks volumes: Alibabaโ€™s Singles Day brings in $25 billion in revenue, compared to Amazon Prime Dayโ€™s $1 billion.  In the public sector, we will contend with how to pay out social security and pensions, how to bend the healthcare cost curve given the graying of America, and how to sustain economic growth in areas with population declines.  Finally, in the social sector, we will need to work to improve the prospects for water supply, for tertiary education access in Africa, and in job retraining in the US and Europe, amongst many other implications.

Additional Materials

Explore the app yourself here: ShinyApp.io (free account, so may expire at some point)

View the code: github repo

Browse the presentation pdf: slides

About Author

Colleen Tapen

Colleen Tapen studied at Georgetown University and Harvard Business School, working in analytics at healthcare startup Evolent in between. She loves solving problems and finding data-driven insights. Colleen also enjoys playing soccer, baking, traveling, and volunteering.
View all posts by Colleen Tapen >

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