Introduction & Overview
As a result of persecution, conflict, violence, human rights violations or other events seriously disturbing public order, 79.5 million people were forcibly displaced worldwide at the end of 2019.
This includes 26.0 million refugees, 45.7 million internally displaced people, and 4.2 million asylum-seekers.
The global refugee crisis is a salient, ongoing problem that deserves more attention. This data project aims to convert these immense statistics into digestible and clear visualizations in order to illustrate the refugee crisis.
Key question: What is the current status of the refugee crisis and resettlement countries?
As a board member of Penn for Refugee Empowerment, working to help educate and resettle refugees and immigrants is a personal passion of mine. I hope this project helps others realize the exigence of this crisis.
First, I conducted an analysis to evaluate how the number of refugees has changed by year. I utilized the ggplot function in R and a dataset extracted from the United Nations High Commissioner for Refugees (UNHCR)’s Refugee Data Finder to illustrate the change in the number of refugees by year.
The rough spike in the number of refugees in 2011–2012 can be attributed to the advent of the Syrian war, as a result of the 2011 Arab Spring protests. It is evident that the number of refugees has peaked in 2020, and is expected to continue rising, shown by the blue trend line.
I conducted a similar analysis on the global number of internationally displaced persons, or IDPs.
The distinction between refugees and IDPs is due to the UNHCR’s legal bind by international law to protect and assist refugees: Refugees are migrants who must have crossed an international frontier because of a well-founded fear of persecution. IDPs are those who have involuntarily been uprooted and displaced but still remain in their own countries. UNHCR still cares for IDPs, but without a legal bind.
From the plot, the blue trend line illustrates a clear exponential increase in the global number of IDPs. Cross comparing the two graphs draws attention to the difference in scale of the y-axes — there are significantly more IDPs than refugees in the world.
I used the plotly package and API in R to generate an interactive visualization of the number of refugees by year by different origin countries from 2010 to 2019. After mousing over the highest points in the graph (denoted in green and yellow), the effects of the Syrian war are again illustrated. Although there was a slight decrease in the number of Syrian refugees from 2018 to 2019, the number of Syrian refugees remains larger than 6.6 million.
Origin countries that averaged 2.5–3 million, shown by the blue color gradient, include Afghanistan from 2010 to 2019 and South Sudan from 2017 to 2019. More than two thirds of all refugees under UNHCR’s mandate come from just five countries, including Syria, Afghanistan, and South Sudan.
I again used the ggplot function to plot heatmaps of the number of refugees from origin countries. I chose to analyze these countries on a more granular basis, by year and month. I segmented my analysis to the years 2013 through 2016, to best visualize the spike in the number of refugees that was illustrated in the first line graph.
I selected Iraq as a country of analysis due to the staggering number of refugees from the Iraq conflict: 3 million have been forced to flee since 2014 and approximately 250,000 people have sought refuge in neighboring countries.
As indicated by the light blue, there was a spike in the number of Iraqi refugees in September through November 2015. This trend illustrates the new wave of migrants fleeing Iraq for Europe in 2015. Iraqis who did not leave during previous crises left on the next great wave of emigration, an exodus threatened by the Islamic State.
I performed a similar heatmap analysis for Syria. There was a similar wave of refugees in September through November 2015, but at a much larger rate than Iraq. Again, this can be attributed to the worsening of the Syrian crisis and the mass exodus to Europe in 2015.
Next, I evaluated the countries that provided the most resettlement aid, to visualize where refugees reside after fleeing their origin countries.
From this treemap, I found that the top countries where refugees resettle are the United States, Canada, the U.K., Australia, Sweden, Germany, and France. This analysis was surprising to me: I would have assumed that countries closer to war-torn regions would have higher rates of resettlement.
However, this illustrates the important point of asylum vs resettlement. Asylum is a form of protection which allows an individual to remain in the United States instead of being deported back to a potentially dangerous origin country. Resettlement is the transfer of refugees from an asylum country to another country that has agreed to admit and ultimately grant them permanent residence.
Thus, I would conjecture that the top asylum countries are closer to regions like Syria, Iraq, and Afghanistan.
Finally, I created a Sankey diagram to show the flow of refugees from their origin countries (pictured on the left) to their resettlement countries (pictured on the right) from 2016 to 2019. The four largest number of refugees from origin countries are Afghanistan, the Congo, Somalia, and Syria. Again, the country that accepts the largest number of refugees for resettlement is the U.S.
It is interesting to view the flow of refugees over time in this way, and clearly illustrates the proportion of refugees that resettle in distinct countries. Norable data trends include the wide variety of countries Syrian refugees resettle in, whereas nearly all refugees from Afghanistan resettle in America. It is also surprising to view such a large percentage of Congolese refugees settling in America as opposed to other common resettlement countries.
Conclusion and Future Steps
Overall, the refugee crisis is staggering in terms of number of people displaced, number of countries in crisis, and number of resettlement countries necessary. Before this analysis, I had no idea about the sheer depth and breadth of this pressing issue.
For future steps, I would more closely analyze asylum countries and attempt to find data from novel sources, since the UNHCR typically provides the most up-to-date and accurate data. Although it was difficult to find new and reputable sources, I would sharpen my scope to a US or even a Philadelphia basis to conduct further analysis.
I am a sophomore at the University of Pennsylvania studying Business Analytics, Finance, and Math who is enrolled in OIDD 245 with Professor Prasanna Tambe. You can read more about my work with refugees here and here.