Population living in slums 2019
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 | 78.132 % |
4 | Sudan | 73.7 % |
5 | Afghanistan | 73.3 % |
6 | Niger | 70.444 % |
7 | Central African Republic | 68.913 % |
8 | Madagascar | 68.621 % |
9 | Comoros | 68.6 % |
10 | Benin | 68.13 % |
11 | Equatorial Guinea | 64.796 % |
12 | Ethiopia | 64.314 % |
13 | Liberia | 63.885 % |
14 | Guinea-Bissau | 62.615 % |
15 | Angola | 62.591 % |
16 | Myanmar | 58.281 % |
17 | Ecuador | 57.8 % |
18 | Pakistan | 56.736 % |
19 | Mozambique | 56.716 % |
20 | Mauritania | 56 % |
21 | Uganda | 55.357 % |
22 | Côte d'Ivoire | 53.211 % |
23 | Djibouti | 52.655 % |
24 | Eritrea | 52.655 % |
25 | Mauritius | 52.655 % |
26 | Seychelles | 52.655 % |
27 | Somalia | 52.655 % |
28 | Sao Tome and Principe | 52.6 % |
29 | Bangladesh | 52.191 % |
30 | Sierra Leone | 52.015 % |
31 | Kenya | 50.813 % |
32 | Bhutan | 50.546 % |
33 | Iran | 50.546 % |
34 | Sri Lanka | 50.546 % |
35 | Nigeria | 50.238 % |
36 | Malawi | 49.785 % |
37 | Haiti | 49.216 % |
38 | Zambia | 49.034 % |
39 | Guinea | 48.59 % |
40 | Iraq | 48.567 % |
41 | Cabo Verde | 47.938 % |
42 | Bolivia | 46.626 % |
43 | Gabon | 44.333 % |
44 | Yemen | 44.2 % |
45 | Congo | 44.184 % |
46 | Mali | 44.026 % |
47 | Peru | 43.974 % |
48 | Tanzania | 41.945 % |
49 | Namibia | 41.4 % |
50 | Nepal | 40.282 % |
51 | Gambia | 39.794 % |
52 | Cambodia | 39.7 % |
53 | Botswana | 39.594 % |
54 | Togo | 39.291 % |
55 | Rwanda | 39.22 % |
56 | Jordan | 39.15 % |
57 | Burundi | 38.153 % |
58 | Guatemala | 37.6 % |
59 | Philippines | 36.967 % |
60 | Maldives | 35.124 % |
61 | Cameroon | 34.306 % |
62 | Timor-Leste | 33.9 % |
63 | Ghana | 33.487 % |
64 | Senegal | 33.382 % |
65 | Honduras | 29.973 % |
66 | Burkina Faso | 29.333 % |
67 | Lesotho | 27.618 % |
68 | Venezuela | 25.7 % |
69 | Syrian Arab Republic | 25.378 % |
70 | South Africa | 24.191 % |
71 | Laos | 22.7 % |
72 | Papua New Guinea | 22.6 % |
73 | Brunei Darussalam | 22.082 % |
74 | Zimbabwe | 21.866 % |
75 | Libya | 20.032 % |
76 | Mongolia | 19.865 % |
77 | Indonesia | 19.824 % |
78 | State of Palestine | 19.5 % |
79 | Mexico | 17.6 % |
80 | El Salvador | 16.5 % |
81 | Panama | 16.3 % |
82 | Belize | 15.727 % |
83 | Suriname | 15.382 % |
84 | Algeria | 15.218 % |
85 | Paraguay | 15.076 % |
86 | Brazil | 14.897 % |
87 | Argentina | 14.5 % |
88 | Turkey | 14.126 % |
89 | Azerbaijan | 14.02 % |
90 | Guyana | 12.964 % |
91 | Dominican Republic | 11.249 % |
92 | Morocco | 10.851 % |
93 | Eswatini | 10.808 % |
94 | Cuba | 10.018 % |
95 | Colombia | 9.7 % |
96 | Fiji | 9.4 % |
97 | Montenegro | 9.4 % |
98 | Turkmenistan | 8.632 % |
99 | Ireland | 8.5 % |
100 | Armenia | 8.395 % |
101 | Trinidad and Tobago | 8.064 % |
102 | Tunisia | 7.893 % |
103 | Georgia | 7.463 % |
104 | Chile | 7.319 % |
105 | Kiribati | 6.225 % |
106 | South Korea | 6.2 % |
107 | Vietnam | 5.766 % |
108 | Nicaragua | 5.519 % |
109 | Hungary | 5.455 % |
110 | India | 5.41 % |
111 | Uzbekistan | 4.943 % |
112 | Cayman Islands | 4.815 % |
113 | Kyrgyzstan | 4.675 % |
114 | Republic of Moldova | 4.615 % |
115 | Lebanon | 4.5 % |
116 | Vanuatu | 4.15 % |
117 | Albania | 4.05 % |
118 | Costa Rica | 4.003 % |
119 | Poland | 4 % |
120 | Russia | 2.8 % |
121 | Antigua and Barbuda | 2.646 % |
122 | Bosnia and Herzegovina | 2.156 % |
123 | Thailand | 2 % |
124 | Solomon Islands | 1.95 % |
125 | Romania | 1.7 % |
126 | Uruguay | 1.3 % |
127 | Nauru | 1.197 % |
128 | Marshall Islands | 1.16 % |
129 | Tuvalu | 0.942 % |
130 | Egypt | 0.9 % |
131 | Austria | 0.863 % |
132 | Canada | 0.8 % |
133 | Kazakhstan | 0.794 % |
134 | Ukraine | 0.645 % |
135 | Latvia | 0.6 % |
136 | Tonga | 0.475 % |
137 | Saint Lucia | 0.45 % |
138 | Serbia | 0.375 % |
139 | Cyprus | 0.3 % |
140 | Palau | 0.3 % |
141 | Croatia | 0.25 % |
142 | Lithuania | 0.25 % |
143 | Samoa | 0.25 % |
144 | Bulgaria | 0.225 % |
145 | United Arab Emirates | 0.163 % |
146 | North Macedonia | 0.15 % |
147 | United States | 0.15 % |
148 | British Virgin Islands | 0.136 % |
149 | Bermuda | 0.1 % |
150 | Estonia | 0.1 % |
151 | Sweden | 0.1 % |
152 | United Kingdom | 0.1 % |
153 | Oman | 0.075 % |
154 | Czech Republic | 0.05 % |
155 | Portugal | 0.05 % |
156 | Slovakia | 0.05 % |
157 | Tajikistan | 0.05 % |
158 | Spain | 0.048 % |
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 | Qatar | 0 % |
179 | Singapore | 0 % |
180 | Switzerland | 0 % |
181 | Greece | -0.125 % |
↑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
Madagascar
- #9
Comoros
- #10
Benin
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
↓Bottom 10 Countries
- #181
Greece
- #180
Switzerland
- #179
Singapore
- #178
Qatar
- #177
Norway
- #176
New Zealand
- #175
Netherlands
- #174
Monaco
- #173
Kuwait
- #172
Iceland
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
The "Population living in slums" statistic for 2019 sheds light on urban poverty and living conditions around the globe. This metric measures the percentage of a country's population residing in slums, providing crucial insights into housing challenges and the quality of life in rapidly urbanizing areas. Understanding these figures is vital for policymakers, urban planners, and global organizations aiming to improve living conditions and promote sustainable urban development.
Global Context and Importance
In 2019, the global landscape of slum populations provided a mixed picture of urban development. As cities expand, the demand for affordable housing grows, often outpacing supply, which leads to the proliferation of slums. Slums represent not only a lack of infrastructure but also a concentration of poverty, where residents face challenges related to health, education, and employment. Addressing these issues is a cornerstone of the United Nations' Sustainable Development Goals, particularly Goal 11, which aims to make cities inclusive, safe, resilient, and sustainable.
Regional Clustering and Comparative Analysis
Analyzing the 2019 data reveals specific regional patterns. India, with a slum population statistic of 5.41%, stood out as having the highest percentage among the countries recorded. This is indicative of the rapid urbanization and economic disparities within the country. In contrast, Belarus reported a remarkably low figure of 0.004%, suggesting more effective urban management and housing policies. Thailand, with 2%, finds itself in the middle, reflecting a balance between urban development and challenges in housing infrastructure.
Year-Over-Year Trends and Insights
Examining the year-over-year changes in 2019 shows that the average percentage of populations living in slums remained static at 2.47%. India, despite its large population and significant urban challenges, did not experience an increase in this percentage, remaining stable, a possible indication of efforts to address urban poverty. This stagnation in growth offers a nuanced understanding that while progress in reducing slum populations was limited, the situation did not worsen, allowing room for policy impact analysis and strategic planning.
Policy Impact and Urban Management
Effective urban management and policies are critical in addressing the challenges posed by slum populations. In countries like Belarus, the negligible percentage of populations living in slums may reflect robust housing policies, efficient urban planning, and the provision of affordable housing. In contrast, India’s high percentage suggests a need for comprehensive policy interventions focusing on slum upgrading, affordable housing, and improved urban infrastructure. International cooperation and financial support can also play a pivotal role in enabling countries facing acute urban challenges to implement effective solutions.
Future Outlook and Strategic Approaches
Looking forward, the trend in slum populations highlights the need for sustainable urbanization strategies. As urban areas continue to expand, innovative solutions such as public-private partnerships, community-driven development projects, and smart city technologies can offer new pathways to tackle the challenges of urban poverty. Furthermore, integrating slum areas into the broader economic and social fabric of cities can promote resilience and enhance the quality of life for millions, aligning with international development goals and fostering inclusive growth.
In conclusion, the 2019 data on populations living in slums underscores the complex interplay of socio-economic factors, urbanization, and policy interventions. By understanding and addressing these dynamics, countries can make strides towards reducing slum populations, enhancing urban resilience, and improving living conditions for vulnerable communities worldwide.
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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