Population living in slums 2021
This statistic measures the percentage of a country's population living in slums, highlighting urban poverty and living conditions. Understanding slum populations is crucial for addressing housing challenges and improving the quality of life.
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Complete Data Rankings
Rank | ||
|---|---|---|
1 | South Sudan | 94.2 % |
2 | Chad | 82 % |
3 | Congo, Democratic Republic of the | 78.362 % |
4 | Sudan | 73.7 % |
5 | Afghanistan | 72.445 % |
6 | Niger | 70.444 % |
7 | Central African Republic | 68.913 % |
8 | Sao Tome and Principe | 67.497 % |
9 | Mali | 67.213 % |
10 | Madagascar | 66.569 % |
11 | Benin | 65.972 % |
12 | Equatorial Guinea | 64.803 % |
13 | Ethiopia | 64.314 % |
14 | Angola | 62.65 % |
15 | Liberia | 62.181 % |
16 | Guinea-Bissau | 59.905 % |
17 | Congo | 59.763 % |
18 | Comoros | 58.551 % |
19 | Myanmar | 58.281 % |
20 | Ecuador | 57.8 % |
21 | Mauritania | 57.28 % |
22 | Burkina Faso | 57.216 % |
23 | Pakistan | 55.974 % |
24 | Tanzania | 55.483 % |
25 | Mozambique | 54.959 % |
26 | Uganda | 53.347 % |
27 | Bangladesh | 51.689 % |
28 | Côte d'Ivoire | 50.736 % |
29 | Djibouti | 50.312 % |
30 | Eritrea | 50.312 % |
31 | Mauritius | 50.312 % |
32 | Seychelles | 50.312 % |
33 | Somalia | 50.312 % |
34 | Haiti | 49.98 % |
35 | Sierra Leone | 49.963 % |
36 | Jordan | 49.65 % |
37 | Iraq | 49.339 % |
38 | Nigeria | 48.74 % |
39 | Zambia | 48.258 % |
40 | Bhutan | 47.558 % |
41 | Iran | 47.558 % |
42 | Sri Lanka | 47.558 % |
43 | Bolivia | 46.626 % |
44 | Cabo Verde | 46.543 % |
45 | Guinea | 46.482 % |
46 | Kenya | 45.655 % |
47 | Peru | 44.395 % |
48 | Yemen | 44.2 % |
49 | Malawi | 43.879 % |
50 | Gabon | 41.553 % |
51 | Namibia | 41.4 % |
52 | Cambodia | 40.985 % |
53 | Nepal | 40.169 % |
54 | Botswana | 39.6 % |
55 | Senegal | 39.008 % |
56 | Togo | 38.48 % |
57 | Rwanda | 38.349 % |
58 | Laos | 38.32 % |
59 | Zimbabwe | 38.225 % |
60 | Gambia | 37.987 % |
61 | Guatemala | 37.6 % |
62 | Burundi | 36.776 % |
63 | Philippines | 36.245 % |
64 | Maldives | 34.845 % |
65 | Timor-Leste | 33.91 % |
66 | Ghana | 33.487 % |
67 | Syrian Arab Republic | 33.35 % |
68 | Cameroon | 32.672 % |
69 | Honduras | 28.791 % |
70 | Tuvalu | 25.895 % |
71 | Venezuela | 25.7 % |
72 | Lesotho | 25.553 % |
73 | South Africa | 24.2 % |
74 | Papua New Guinea | 22.534 % |
75 | Brunei Darussalam | 21.662 % |
76 | Libya | 20.131 % |
77 | Indonesia | 19.411 % |
78 | Vietnam | 19.133 % |
79 | State of Palestine | 18.255 % |
80 | Mongolia | 17.879 % |
81 | Mexico | 17.6 % |
82 | Samoa | 17.418 % |
83 | El Salvador | 16.489 % |
84 | Panama | 16.3 % |
85 | Suriname | 15.8 % |
86 | Belize | 15.725 % |
87 | Paraguay | 15.1 % |
88 | Brazil | 14.897 % |
89 | Argentina | 14.5 % |
90 | Turkey | 14.126 % |
91 | Eswatini | 13.907 % |
92 | Algeria | 13.256 % |
93 | Guyana | 11.722 % |
94 | Dominican Republic | 11.249 % |
95 | Azerbaijan | 11.018 % |
96 | Morocco | 10.851 % |
97 | Cuba | 10.792 % |
98 | Colombia | 9.7 % |
99 | Fiji | 9.4 % |
100 | Montenegro | 8.785 % |
101 | Ireland | 8.5 % |
102 | Turkmenistan | 8.444 % |
103 | Trinidad and Tobago | 8.439 % |
104 | Armenia | 8.395 % |
105 | Tunisia | 7.643 % |
106 | Chile | 7.322 % |
107 | Georgia | 7.079 % |
108 | Uzbekistan | 5.814 % |
109 | Kiribati | 5.767 % |
110 | India | 5.41 % |
111 | Cayman Islands | 5.258 % |
112 | South Korea | 5.05 % |
113 | Nicaragua | 4.954 % |
114 | Hungary | 4.625 % |
115 | Lebanon | 4.515 % |
116 | Poland | 3.959 % |
117 | Vanuatu | 3.607 % |
118 | Costa Rica | 3.546 % |
119 | Republic of Moldova | 3.165 % |
120 | Albania | 2.75 % |
121 | Russia | 2.684 % |
122 | Antigua and Barbuda | 2.646 % |
123 | Kyrgyzstan | 2.439 % |
124 | Egypt | 2.37 % |
125 | Marshall Islands | 2.298 % |
126 | Romania | 2.035 % |
127 | Thailand | 2 % |
128 | Solomon Islands | 1.95 % |
129 | Uruguay | 1.3 % |
130 | Canada | 0.948 % |
131 | Serbia | 0.883 % |
132 | Kazakhstan | 0.794 % |
133 | Nauru | 0.597 % |
134 | Latvia | 0.597 % |
135 | Palau | 0.459 % |
136 | Saint Lucia | 0.445 % |
137 | Croatia | 0.389 % |
138 | Lithuania | 0.379 % |
139 | Tonga | 0.329 % |
140 | Austria | 0.319 % |
141 | Bosnia and Herzegovina | 0.313 % |
142 | Ukraine | 0.295 % |
143 | Cyprus | 0.286 % |
144 | Bulgaria | 0.223 % |
145 | Estonia | 0.223 % |
146 | Sweden | 0.218 % |
147 | North Macedonia | 0.214 % |
148 | Malaysia | 0.2 % |
149 | United Arab Emirates | 0.17 % |
150 | British Virgin Islands | 0.136 % |
151 | United Kingdom | 0.131 % |
152 | United States | 0.122 % |
153 | Bermuda | 0.089 % |
154 | Slovakia | 0.058 % |
155 | Portugal | 0.054 % |
156 | Tajikistan | 0.05 % |
157 | Spain | 0.047 % |
158 | Czech Republic | 0.039 % |
159 | Malta | 0.038 % |
160 | Australia | 0.035 % |
161 | Italy | 0.02 % |
162 | Luxembourg | 0.017 % |
163 | Belarus | 0.004 % |
164 | Andorra | 0 % |
165 | Aruba | 0 % |
166 | Bahrain | 0 % |
167 | Belgium | 0 % |
168 | Denmark | 0 % |
169 | Finland | 0 % |
170 | France | 0 % |
171 | Germany | 0 % |
172 | Iceland | 0 % |
173 | Kuwait | 0 % |
174 | Monaco | 0 % |
175 | Netherlands | 0 % |
176 | New Zealand | 0 % |
177 | Norway | 0 % |
178 | Oman | 0 % |
179 | Qatar | 0 % |
180 | Singapore | 0 % |
181 | Switzerland | 0 % |
182 | Greece | -0.175 % |
- #1
South Sudan
- #2
Chad
- #3
Congo, Democratic Republic of the
- #4
Sudan
- #5
Afghanistan
- #6
Niger
- #7
Central African Republic
- #8
Sao Tome and Principe
- #9
Mali
- #10
Madagascar
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
- #182
Greece
- #181
Switzerland
- #180
Singapore
- #179
Qatar
- #178
Oman
- #177
Norway
- #176
New Zealand
- #175
Netherlands
- #174
Monaco
- #173
Kuwait
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
In 2021, South Sudan recorded the highest Population living in slums at 94.2%, while Greece had the lowest at -0.18%, showcasing the global range of urban poverty and living conditions. The global average for this metric stood at 23.04%, highlighting significant disparities in urban housing across different regions.
Economic and Political Drivers of Slum Populations
The prevalence of slum populations is often closely tied to economic and political factors within a country. In nations like South Sudan and the Democratic Republic of the Congo, with slum populations of 94.2% and 78.36% respectively, ongoing conflicts and political instability have severely hindered economic development and infrastructure investment. These conditions exacerbate urban poverty, forcing large segments of the population to reside in informal settlements lacking basic services.
Conversely, countries with stable economies and robust urban planning, such as Singapore and Kuwait, report a 0% slum population. These nations have implemented effective housing policies and economic strategies that prevent the proliferation of slums and promote sustainable urban development.
Geographic and Demographic Influences
Geographic and demographic factors also play a crucial role in the distribution of slum populations. In Mali and Niger, with slum populations of 67.21% and 70.44% respectively, rapid urbanization outpaces the development of infrastructure and housing. These countries face challenges in managing population growth and urban sprawl, which often leads to the expansion of slums.
In contrast, countries like Monaco and Andorra, with 0% of their populations living in slums, benefit from smaller, more manageable urban populations and geographic constraints that limit uncontrolled expansion. These factors enable more effective urban planning and resource allocation.
Trends in Year-over-Year Changes
Analyzing year-over-year changes reveals significant shifts in slum populations in certain countries. Burkina Faso experienced the largest increase, with a 30.67% rise, indicating rapid urban growth and possibly inadequate urban planning mechanisms. Similarly, Mali saw a 25.28% increase, reflecting similar challenges in accommodating burgeoning urban populations.
Conversely, some countries have managed to reduce their slum populations significantly. Comoros leads with a -10.05% decrease, suggesting successful interventions in housing policy and urban management. Malawi and Kenya also show decreases of -5.91% and -5.16% respectively, indicating positive trends in addressing urban poverty.
Implications for Policy and Planning
The stark contrast in slum populations across countries emphasizes the need for targeted policy interventions. For nations like Chad and Sudan, with slum populations of 82% and 73.7% respectively, investment in infrastructure and housing is critical. International cooperation and aid could play a vital role in supporting these efforts, facilitating sustainable urban development.
Moreover, countries showing positive trends, such as Comoros and Kenya, provide valuable case studies for effective policy implementation. Their success stories can guide other nations in formulating strategies to reduce slum populations and improve living conditions. Ultimately, addressing the challenges of slum populations requires a multifaceted approach, integrating economic, demographic, and policy-driven solutions.
Data Source
UN Habitat
The Data and Analytics Section (DAS) is the specialized statistics unit within UN-Habitat. The data section is responsible for overall data oversight across all urban monitoring domains within UN-Habitat, methodological developments, supporting member states in their monitoring efforts around global agenda such as the SDGs, implementing direct data collection and compilation, providing data to UN-Habitat global reports, and publicly and openly disseminating urban data through its urban indicators programme.
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