Population living in slums 2011
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 | 95.603 % |
2 |  Sudan | 86.376 % |
3 |  Chad | 85.384 % |
4 |  Madagascar | 78.227 % |
5 |  Guinea-Bissau | 75.224 % |
6 |  Ethiopia | 75.148 % |
7 |  Congo, Democratic Republic of the | 74.678 % |
8 |  Mozambique | 70.77 % |
9 |  Niger | 70.357 % |
10 |  Central African Republic | 70.334 % |
11 |  Liberia | 70.133 % |
12 |  Benin | 69.703 % |
13 |  Comoros | 67.75 % |
14 |  Mauritania | 66.122 % |
15 |  Uganda | 66.112 % |
16 |  Afghanistan | 66.028 % |
17 |  Djibouti | 63.495 % |
18 |  Eritrea | 63.495 % |
19 |  Mauritius | 63.495 % |
20 |  Seychelles | 63.495 % |
21 |  Somalia | 63.495 % |
22 |  Sierra Leone | 62.966 % |
23 |  Congo | 62.879 % |
24 |  Pakistan | 62.835 % |
25 |  Malawi | 62.084 % |
26 |  Equatorial Guinea | 61.009 % |
27 |  Mali | 60.805 % |
28 |  Nigeria | 60.288 % |
29 |  Côte d'Ivoire | 58.603 % |
30 |  Burundi | 58.274 % |
31 |  Tanzania | 57.911 % |
32 |  Ecuador | 57.8 % |
33 |  Cabo Verde | 57.708 % |
34 |  Sao Tome and Principe | 57.49 % |
35 |  Zambia | 55.245 % |
36 |  Bangladesh | 54.768 % |
37 |  Kenya | 54.679 % |
38 |  Haiti | 54.102 % |
39 |  Cambodia | 53.8 % |
40 |  Bhutan | 53.321 % |
41 |  Iran | 53.321 % |
42 |  Sri Lanka | 53.321 % |
43 |  Rwanda | 52.274 % |
44 |  Burkina Faso | 51.598 % |
45 |  Togo | 51.434 % |
46 |  Nepal | 50.404 % |
47 |  Yemen | 49.394 % |
48 |  Timor-Leste | 48 % |
49 |  Senegal | 47.602 % |
50 |  Cameroon | 47.383 % |
51 |  Gabon | 47.139 % |
52 |  Myanmar | 47.049 % |
53 |  Botswana | 47.018 % |
54 |  Gambia | 47.005 % |
55 |  Bolivia | 46.626 % |
56 |  Guinea | 45.253 % |
57 |  Lesotho | 44.14 % |
58 |  Guatemala | 43.195 % |
59 |  Iraq | 42.389 % |
60 |  Philippines | 42.24 % |
61 |  Peru | 42.126 % |
62 |  Ghana | 41.887 % |
63 |  Namibia | 41.737 % |
64 |  Angola | 41.121 % |
65 |  Maldives | 39.305 % |
66 |  Nicaragua | 37.227 % |
67 |  Mongolia | 35.755 % |
68 |  Laos | 35.55 % |
69 |  Honduras | 35.05 % |
70 |  El Salvador | 31.484 % |
71 |  Algeria | 29.843 % |
72 |  Lebanon | 29.639 % |
73 |  Eswatini | 29.368 % |
74 |  Brunei Darussalam | 27.907 % |
75 |  Azerbaijan | 26.927 % |
76 |  Syrian Arab Republic | 26.216 % |
77 |  Libya | 26.086 % |
78 |  Indonesia | 26.028 % |
79 |  Venezuela | 25.7 % |
80 |  Paraguay | 25.543 % |
81 |  South Africa | 25.515 % |
82 |  Panama | 24.963 % |
83 |  State of Palestine | 24.304 % |
84 |  Zimbabwe | 24.247 % |
85 |  Mexico | 22.73 % |
86 |  Kyrgyzstan | 22.563 % |
87 |  Papua New Guinea | 21.1 % |
88 |  Guyana | 19.553 % |
89 |  Vietnam | 18.126 % |
90 |  Morocco | 17.821 % |
91 |  Dominican Republic | 17.157 % |
92 |  Turkey | 16.914 % |
93 |  Brazil | 16.551 % |
94 |  Argentina | 16.301 % |
95 |  Belize | 15.743 % |
96 |  Montenegro | 14.25 % |
97 |  Uzbekistan | 14.233 % |
98 |  Albania | 14.15 % |
99 |  Colombia | 13.782 % |
100 |  Suriname | 12.034 % |
101 |  Fiji | 11.95 % |
102 |  Egypt | 11.92 % |
103 |  Kiribati | 11.2 % |
104 |  Republic of Moldova | 10.85 % |
105 |  Uruguay | 10.636 % |
106 |  Georgia | 10.53 % |
107 |  Armenia | 10.106 % |
108 |  Tunisia | 9.894 % |
109 |  Turkmenistan | 9.632 % |
110 |  Kazakhstan | 9.146 % |
111 |  Hungary | 8.5 % |
112 |  Trinidad and Tobago | 8.33 % |
113 |  South Korea | 8.15 % |
114 |  Costa Rica | 7.663 % |
115 |  Ireland | 7.6 % |
116 |  Chile | 7.305 % |
117 |  Cuba | 5.824 % |
118 |  Solomon Islands | 5.325 % |
119 |  Bosnia and Herzegovina | 4.4 % |
120 |  Vanuatu | 4.2 % |
121 |  Cayman Islands | 4.15 % |
122 |  Russia | 3.175 % |
123 |  Austria | 3.04 % |
124 |  Romania | 2.8 % |
125 |  Antigua and Barbuda | 2.646 % |
126 |  Saint Lucia | 2.475 % |
127 |  Samoa | 2.2 % |
128 |  Ukraine | 2.15 % |
129 |  British Virgin Islands | 1.813 % |
130 |  Lithuania | 1.775 % |
131 |  Latvia | 1.45 % |
132 |  Oman | 1.325 % |
133 |  Marshall Islands | 1.175 % |
134 |  Tonga | 1.175 % |
135 |  Nauru | 1.125 % |
136 |  Palau | 0.95 % |
137 |  Tuvalu | 0.9 % |
138 |  North Macedonia | 0.725 % |
139 |  United Arab Emirates | 0.575 % |
140 |  Canada | 0.525 % |
141 |  Serbia | 0.5 % |
142 |  Poland | 0.4 % |
143 |  Portugal | 0.325 % |
144 |  Croatia | 0.325 % |
145 |  Cyprus | 0.25 % |
146 |  United States | 0.2 % |
147 |  Bulgaria | 0.15 % |
148 |  Sweden | 0.15 % |
149 |  Bermuda | 0.1 % |
150 |  Estonia | 0.1 % |
151 |  United Kingdom | 0.1 % |
152 |  Australia | 0.075 % |
153 |  Greece | 0.075 % |
154 |  Czech Republic | 0.05 % |
155 |  Slovakia | 0.05 % |
156 |  Malta | 0.038 % |
157 |  Italy | 0.02 % |
158 |  Luxembourg | 0.01 % |
159 |  Belarus | 0.004 % |
160 |  Andorra | 0 % |
161 |  Aruba | 0 % |
162 |  Belgium | 0 % |
163 |  Denmark | 0 % |
164 |  Finland | 0 % |
165 |  France | 0 % |
166 |  Germany | 0 % |
167 |  Iceland | 0 % |
168 |  Kuwait | 0 % |
169 |  Monaco | 0 % |
170 |  Netherlands | 0 % |
171 |  New Zealand | 0 % |
172 |  Norway | 0 % |
173 |  Singapore | 0 % |
174 |  Switzerland | 0 % |
- #1South Sudan
- #2Sudan
- #3Chad
- #4Madagascar
- #5Guinea-Bissau
- #6Ethiopia
- #7Congo, Democratic Republic of the
- #8Mozambique
- #9Niger
- #10Central African Republic
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
- #174Switzerland
- #173Singapore
- #172Norway
- #171New Zealand
- #170Netherlands
- #169Monaco
- #168Kuwait
- #167Iceland
- #166Germany
- #165France
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
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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