Population living in slums 2020
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.
Interactive Map
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 | 73.3 % |
6 | Niger | 70.444 % |
7 | Central African Republic | 68.913 % |
8 | Comoros | 68.6 % |
9 | Benin | 67.933 % |
10 | Madagascar | 67.42 % |
11 | Equatorial Guinea | 64.918 % |
12 | Ethiopia | 64.314 % |
13 | Liberia | 63.885 % |
14 | Angola | 62.6 % |
15 | Guinea-Bissau | 60.81 % |
16 | Myanmar | 58.281 % |
17 | Ecuador | 57.8 % |
18 | Mauritania | 56 % |
19 | Pakistan | 55.974 % |
20 | Mozambique | 54.959 % |
21 | Uganda | 54.012 % |
22 | Côte d'Ivoire | 53.211 % |
23 | Sao Tome and Principe | 52.6 % |
24 | Djibouti | 51.938 % |
25 | Eritrea | 51.938 % |
26 | Mauritius | 51.938 % |
27 | Seychelles | 51.938 % |
28 | Somalia | 51.938 % |
29 | Bangladesh | 51.869 % |
30 | Kenya | 50.813 % |
31 | Sierra Leone | 50.647 % |
32 | Bhutan | 50.426 % |
33 | Iran | 50.426 % |
34 | Sri Lanka | 50.426 % |
35 | Malawi | 49.785 % |
36 | Iraq | 49.339 % |
37 | Guinea | 49.007 % |
38 | Nigeria | 48.982 % |
39 | Haiti | 48.9 % |
40 | Zambia | 48.258 % |
41 | Cabo Verde | 46.675 % |
42 | Bolivia | 46.626 % |
43 | Jordan | 44.4 % |
44 | Gabon | 44.333 % |
45 | Yemen | 44.2 % |
46 | Congo | 44.184 % |
47 | Peru | 43.731 % |
48 | Mali | 41.929 % |
49 | Namibia | 41.4 % |
50 | Tanzania | 40.881 % |
51 | Nepal | 40.282 % |
52 | Cambodia | 39.7 % |
53 | Botswana | 39.6 % |
54 | Gambia | 38.893 % |
55 | Togo | 38.5 % |
56 | Rwanda | 38.349 % |
57 | Guatemala | 37.6 % |
58 | Burundi | 36.8 % |
59 | Philippines | 36.616 % |
60 | Maldives | 34.845 % |
61 | Timor-Leste | 33.9 % |
62 | Ghana | 33.487 % |
63 | Cameroon | 32.672 % |
64 | Senegal | 31.605 % |
65 | Honduras | 29.382 % |
66 | Burkina Faso | 26.55 % |
67 | Venezuela | 25.7 % |
68 | Syrian Arab Republic | 25.575 % |
69 | Lesotho | 25.553 % |
70 | South Africa | 24.2 % |
71 | Libya | 23.681 % |
72 | Papua New Guinea | 22.8 % |
73 | Laos | 21.8 % |
74 | Brunei Darussalam | 21.727 % |
75 | Zimbabwe | 21.568 % |
76 | State of Palestine | 19.5 % |
77 | Indonesia | 19.411 % |
78 | Mongolia | 17.879 % |
79 | Mexico | 17.6 % |
80 | El Salvador | 16.5 % |
81 | Panama | 16.3 % |
82 | Suriname | 15.8 % |
83 | Belize | 15.725 % |
84 | Paraguay | 15.1 % |
85 | Brazil | 14.897 % |
86 | Argentina | 14.5 % |
87 | Turkey | 14.126 % |
88 | Algeria | 13.265 % |
89 | Azerbaijan | 12.519 % |
90 | Guyana | 12.14 % |
91 | Dominican Republic | 11.249 % |
92 | Morocco | 10.851 % |
93 | Eswatini | 10.808 % |
94 | Cuba | 10.542 % |
95 | Colombia | 9.7 % |
96 | Fiji | 9.4 % |
97 | Montenegro | 8.8 % |
98 | Turkmenistan | 8.507 % |
99 | Ireland | 8.5 % |
100 | Armenia | 8.395 % |
101 | Trinidad and Tobago | 8.252 % |
102 | Tunisia | 7.643 % |
103 | Chile | 7.321 % |
104 | Georgia | 7.079 % |
105 | Vietnam | 5.766 % |
106 | Kiribati | 5.6 % |
107 | South Korea | 5.6 % |
108 | Nicaragua | 5.519 % |
109 | India | 5.41 % |
110 | Hungary | 5.04 % |
111 | Cayman Islands | 5.036 % |
112 | Uzbekistan | 4.527 % |
113 | Lebanon | 4.5 % |
114 | Vanuatu | 4.15 % |
115 | Republic of Moldova | 3.89 % |
116 | Poland | 3.7 % |
117 | Costa Rica | 3.546 % |
118 | Albania | 2.8 % |
119 | Russia | 2.75 % |
120 | Antigua and Barbuda | 2.646 % |
121 | Kyrgyzstan | 2.439 % |
122 | Marshall Islands | 2.221 % |
123 | Thailand | 2 % |
124 | Solomon Islands | 1.95 % |
125 | Romania | 1.55 % |
126 | Uruguay | 1.3 % |
127 | Egypt | 0.9 % |
128 | Tuvalu | 0.89 % |
129 | Canada | 0.8 % |
130 | Kazakhstan | 0.794 % |
131 | Latvia | 0.6 % |
132 | Nauru | 0.597 % |
133 | Austria | 0.591 % |
134 | Ukraine | 0.47 % |
135 | Saint Lucia | 0.45 % |
136 | Serbia | 0.35 % |
137 | Tonga | 0.35 % |
138 | Bosnia and Herzegovina | 0.313 % |
139 | Cyprus | 0.3 % |
140 | Palau | 0.3 % |
141 | Bulgaria | 0.25 % |
142 | Croatia | 0.25 % |
143 | Lithuania | 0.25 % |
144 | Samoa | 0.25 % |
145 | United Arab Emirates | 0.227 % |
146 | Malaysia | 0.2 % |
147 | North Macedonia | 0.15 % |
148 | United States | 0.15 % |
149 | British Virgin Islands | 0.136 % |
150 | Bermuda | 0.1 % |
151 | Estonia | 0.1 % |
152 | Sweden | 0.1 % |
153 | United Kingdom | 0.1 % |
154 | Czech Republic | 0.05 % |
155 | Portugal | 0.05 % |
156 | Slovakia | 0.05 % |
157 | Tajikistan | 0.05 % |
158 | Spain | 0.047 % |
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 | Belgium | 0 % |
167 | Denmark | 0 % |
168 | Finland | 0 % |
169 | France | 0 % |
170 | Germany | 0 % |
171 | Iceland | 0 % |
172 | Kuwait | 0 % |
173 | Monaco | 0 % |
174 | Netherlands | 0 % |
175 | New Zealand | 0 % |
176 | Norway | 0 % |
177 | Oman | 0 % |
178 | Qatar | 0 % |
179 | Singapore | 0 % |
180 | Switzerland | 0 % |
181 | Bahrain | 0 % |
182 | Greece | -0.15 % |
↑Top 10 Countries
- #1
South Sudan
- #2
Chad
- #3
Congo, Democratic Republic of the
- #4
Sudan
- #5
Afghanistan
- #6
Niger
- #7
Central African Republic
- #8
Comoros
- #9
Benin
- #10
Madagascar
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
↓Bottom 10 Countries
- #182
Greece
- #181
Bahrain
- #180
Switzerland
- #179
Singapore
- #178
Qatar
- #177
Oman
- #176
Norway
- #175
New Zealand
- #174
Netherlands
- #173
Monaco
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
The statistic of the "Population living in slums" for the year 2020 provides a critical insight into urban poverty and housing conditions across the globe. This metric measures the percentage of individuals residing in slum areas within various countries, underscoring significant inequalities in living standards and highlighting the need for targeted housing policies. Understanding these dynamics is essential for governments and organizations aiming to improve global living conditions.
Global Overview of Slum Populations in 2020
In 2020, the global average percentage of populations living in slums stood at 23.45%, with data available from 160 countries. This year showcased stark contrasts between nations, with some countries recording negligible slum populations while others revealed alarmingly high percentages. For instance, South Sudan had the highest rate, with 94.2% of its urban population living in slum conditions, reflecting ongoing challenges related to conflict, governance, and economic development. In stark contrast, countries such as Germany, Switzerland, and Singapore reported a 0% slum population, indicating effective urban planning and robust economic frameworks.
Regional Contrasts and Their Implications
Examining regional contrasts reveals insightful data patterns. African countries dominate the list of the highest percentages of populations living in slums, highlighting the continent's ongoing struggle with urban poverty and inadequate infrastructure. Countries such as Chad (82%), the Democratic Republic of the Congo (78.36%), and Sudan (73.7%) are notable examples where economic instability and rapid urbanization without adequate planning have exacerbated slum proliferation. Conversely, European countries generally exhibit minimal slum populations, attributing this to more developed economies and stronger governance structures.
Economic Factors and Urban Planning
The economic conditions and urban planning policies of a country significantly influence its slum population. In 2020, nations with stable economies and effective governance were better equipped to provide their citizens with adequate housing and infrastructure, thereby reducing slum populations. Countries like Germany and Switzerland are prime examples of how economic prosperity and comprehensive urban policies can lead to zero slum habitation. On the other hand, ongoing conflicts, political instability, and poor economic management in countries like South Sudan and Afghanistan contribute to high slum population percentages, as these factors hinder effective urban development and housing reforms.
Impacts on Health and Society
The widespread existence of slums has profound implications for health and social well-being. Slum areas often lack essential services such as clean water, sanitation, and adequate waste management, leading to heightened health risks. In 2020, the COVID-19 pandemic further underscored the vulnerabilities of slum populations, who faced increased transmission risks due to overcrowded living conditions and limited access to healthcare. Addressing these challenges is crucial for improving public health outcomes and enhancing the quality of life for millions living in these conditions.
Policy Initiatives and Future Outlook
As of 2020, several countries were prioritizing slum upgrades and housing policies to address the challenges of urban poverty. Initiatives such as providing affordable housing, improving infrastructure, and implementing inclusive urban planning are critical steps towards reducing slum populations. Additionally, international cooperation and funding can support these efforts, especially in low-income countries where national resources are limited. Looking ahead, the global community must continue to advocate for sustainable urban development to ensure that all individuals have access to safe and decent living conditions.
The year 2020 highlighted the ongoing challenge of slum populations across the world, emphasizing the need for concerted efforts in policy-making, economic development, and urban planning. By addressing these issues, countries can make significant strides in reducing urban poverty and improving the living standards of their populations.
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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