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.

181 data pointsWorldUN Habitat

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Complete Data Rankings

Rank
1
South Sudan flag
South Sudan
94.2 %
2
Chad flag
Chad
82 %
3
Congo, Democratic Republic of the flag
Congo, Democratic Republic of the
78.132 %
4
Sudan flag
Sudan
73.7 %
5
Afghanistan flag
Afghanistan
73.3 %
6
Niger flag
Niger
70.444 %
7
Central African Republic flag
Central African Republic
68.913 %
8
Madagascar flag
Madagascar
68.621 %
9
Comoros flag
Comoros
68.6 %
10
Benin flag
Benin
68.13 %
11
Equatorial Guinea flag
Equatorial Guinea
64.796 %
12
Ethiopia flag
Ethiopia
64.314 %
13
Liberia flag
Liberia
63.885 %
14
Guinea-Bissau flag
Guinea-Bissau
62.615 %
15
Angola flag
Angola
62.591 %
16
Myanmar flag
Myanmar
58.281 %
17
Ecuador flag
Ecuador
57.8 %
18
Pakistan flag
Pakistan
56.736 %
19
Mozambique flag
Mozambique
56.716 %
20
Mauritania flag
Mauritania
56 %
21
Uganda flag
Uganda
55.357 %
22
Côte d'Ivoire flag
Côte d'Ivoire
53.211 %
23
Djibouti flag
Djibouti
52.655 %
24
Eritrea flag
Eritrea
52.655 %
25
Mauritius flag
Mauritius
52.655 %
26
Seychelles flag
Seychelles
52.655 %
27
Somalia flag
Somalia
52.655 %
28
Sao Tome and Principe flag
Sao Tome and Principe
52.6 %
29
Bangladesh flag
Bangladesh
52.191 %
30
Sierra Leone flag
Sierra Leone
52.015 %
31
Kenya flag
Kenya
50.813 %
32
Bhutan flag
Bhutan
50.546 %
33
Iran flag
Iran
50.546 %
34
Sri Lanka flag
Sri Lanka
50.546 %
35
Nigeria flag
Nigeria
50.238 %
36
Malawi flag
Malawi
49.785 %
37
Haiti flag
Haiti
49.216 %
38
Zambia flag
Zambia
49.034 %
39
Guinea flag
Guinea
48.59 %
40
Iraq flag
Iraq
48.567 %
41
Cabo Verde flag
Cabo Verde
47.938 %
42
Bolivia flag
Bolivia
46.626 %
43
Gabon flag
Gabon
44.333 %
44
Yemen flag
Yemen
44.2 %
45
Congo flag
Congo
44.184 %
46
Mali flag
Mali
44.026 %
47
Peru flag
Peru
43.974 %
48
Tanzania flag
Tanzania
41.945 %
49
Namibia flag
Namibia
41.4 %
50
Nepal flag
Nepal
40.282 %
51
Gambia flag
Gambia
39.794 %
52
Cambodia flag
Cambodia
39.7 %
53
Botswana flag
Botswana
39.594 %
54
Togo flag
Togo
39.291 %
55
Rwanda flag
Rwanda
39.22 %
56
Jordan flag
Jordan
39.15 %
57
Burundi flag
Burundi
38.153 %
58
Guatemala flag
Guatemala
37.6 %
59
Philippines flag
Philippines
36.967 %
60
Maldives flag
Maldives
35.124 %
61
Cameroon flag
Cameroon
34.306 %
62
Timor-Leste flag
Timor-Leste
33.9 %
63
Ghana flag
Ghana
33.487 %
64
Senegal flag
Senegal
33.382 %
65
Honduras flag
Honduras
29.973 %
66
Burkina Faso flag
Burkina Faso
29.333 %
67
Lesotho flag
Lesotho
27.618 %
68
Venezuela flag
Venezuela
25.7 %
69
Syrian Arab Republic flag
Syrian Arab Republic
25.378 %
70
South Africa flag
South Africa
24.191 %
71
Laos flag
Laos
22.7 %
72
Papua New Guinea flag
Papua New Guinea
22.6 %
73
Brunei Darussalam flag
Brunei Darussalam
22.082 %
74
Zimbabwe flag
Zimbabwe
21.866 %
75
Libya flag
Libya
20.032 %
76
Mongolia flag
Mongolia
19.865 %
77
Indonesia flag
Indonesia
19.824 %
78
State of Palestine flag
State of Palestine
19.5 %
79
Mexico flag
Mexico
17.6 %
80
El Salvador flag
El Salvador
16.5 %
81
Panama flag
Panama
16.3 %
82
Belize flag
Belize
15.727 %
83
Suriname flag
Suriname
15.382 %
84
Algeria flag
Algeria
15.218 %
85
Paraguay flag
Paraguay
15.076 %
86
Brazil flag
Brazil
14.897 %
87
Argentina flag
Argentina
14.5 %
88
Turkey flag
Turkey
14.126 %
89
Azerbaijan flag
Azerbaijan
14.02 %
90
Guyana flag
Guyana
12.964 %
91
Dominican Republic flag
Dominican Republic
11.249 %
92
Morocco flag
Morocco
10.851 %
93
Eswatini flag
Eswatini
10.808 %
94
Cuba flag
Cuba
10.018 %
95
Colombia flag
Colombia
9.7 %
96
Fiji flag
Fiji
9.4 %
97
Montenegro flag
Montenegro
9.4 %
98
Turkmenistan flag
Turkmenistan
8.632 %
99
Ireland flag
Ireland
8.5 %
100
Armenia flag
Armenia
8.395 %
101
Trinidad and Tobago flag
Trinidad and Tobago
8.064 %
102
Tunisia flag
Tunisia
7.893 %
103
Georgia flag
Georgia
7.463 %
104
Chile flag
Chile
7.319 %
105
Kiribati flag
Kiribati
6.225 %
106
South Korea flag
South Korea
6.2 %
107
Vietnam flag
Vietnam
5.766 %
108
Nicaragua flag
Nicaragua
5.519 %
109
Hungary flag
Hungary
5.455 %
110
India flag
India
5.41 %
111
Uzbekistan flag
Uzbekistan
4.943 %
112
Cayman Islands flag
Cayman Islands
4.815 %
113
Kyrgyzstan flag
Kyrgyzstan
4.675 %
114
Republic of Moldova flag
Republic of Moldova
4.615 %
115
Lebanon flag
Lebanon
4.5 %
116
Vanuatu flag
Vanuatu
4.15 %
117
Albania flag
Albania
4.05 %
118
Costa Rica flag
Costa Rica
4.003 %
119
Poland flag
Poland
4 %
120
Russia flag
Russia
2.8 %
121
Antigua and Barbuda flag
Antigua and Barbuda
2.646 %
122
Bosnia and Herzegovina flag
Bosnia and Herzegovina
2.156 %
123
Thailand flag
Thailand
2 %
124
Solomon Islands flag
Solomon Islands
1.95 %
125
Romania flag
Romania
1.7 %
126
Uruguay flag
Uruguay
1.3 %
127
Nauru flag
Nauru
1.197 %
128
Marshall Islands flag
Marshall Islands
1.16 %
129
Tuvalu flag
Tuvalu
0.942 %
130
Egypt flag
Egypt
0.9 %
131
Austria flag
Austria
0.863 %
132
Canada flag
Canada
0.8 %
133
Kazakhstan flag
Kazakhstan
0.794 %
134
Ukraine flag
Ukraine
0.645 %
135
Latvia flag
Latvia
0.6 %
136
Tonga flag
Tonga
0.475 %
137
Saint Lucia flag
Saint Lucia
0.45 %
138
Serbia flag
Serbia
0.375 %
139
Cyprus flag
Cyprus
0.3 %
140
Palau flag
Palau
0.3 %
141
Croatia flag
Croatia
0.25 %
142
Lithuania flag
Lithuania
0.25 %
143
Samoa flag
Samoa
0.25 %
144
Bulgaria flag
Bulgaria
0.225 %
145
United Arab Emirates flag
United Arab Emirates
0.163 %
146
North Macedonia flag
North Macedonia
0.15 %
147
United States flag
United States
0.15 %
148
British Virgin Islands flag
British Virgin Islands
0.136 %
149
Bermuda flag
Bermuda
0.1 %
150
Estonia flag
Estonia
0.1 %
151
Sweden flag
Sweden
0.1 %
152
United Kingdom flag
United Kingdom
0.1 %
153
Oman flag
Oman
0.075 %
154
Czech Republic flag
Czech Republic
0.05 %
155
Portugal flag
Portugal
0.05 %
156
Slovakia flag
Slovakia
0.05 %
157
Tajikistan flag
Tajikistan
0.05 %
158
Spain flag
Spain
0.048 %
159
Malta flag
Malta
0.038 %
160
Australia flag
Australia
0.035 %
161
Italy flag
Italy
0.02 %
162
Luxembourg flag
Luxembourg
0.017 %
163
Belarus flag
Belarus
0.004 %
164
Andorra flag
Andorra
0 %
165
Aruba flag
Aruba
0 %
166
Bahrain flag
Bahrain
0 %
167
Belgium flag
Belgium
0 %
168
Denmark flag
Denmark
0 %
169
Finland flag
Finland
0 %
170
France flag
France
0 %
171
Germany flag
Germany
0 %
172
Iceland flag
Iceland
0 %
173
Kuwait flag
Kuwait
0 %
174
Monaco flag
Monaco
0 %
175
Netherlands flag
Netherlands
0 %
176
New Zealand flag
New Zealand
0 %
177
Norway flag
Norway
0 %
178
Qatar flag
Qatar
0 %
179
Singapore flag
Singapore
0 %
180
Switzerland flag
Switzerland
0 %
181
Greece flag
Greece
-0.125 %

Top 10 Countries

  1. #1South Sudan flagSouth Sudan
  2. #2Chad flagChad
  3. #3Congo, Democratic Republic of the flagCongo, Democratic Republic of the
  4. #4Sudan flagSudan
  5. #5Afghanistan flagAfghanistan
  6. #6Niger flagNiger
  7. #7Central African Republic flagCentral African Republic
  8. #8Madagascar flagMadagascar
  9. #9Comoros flagComoros
  10. #10Benin flagBenin

Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.

Bottom 10 Countries

  1. #181Greece flagGreece
  2. #180Switzerland flagSwitzerland
  3. #179Singapore flagSingapore
  4. #178Qatar flagQatar
  5. #177Norway flagNorway
  6. #176New Zealand flagNew Zealand
  7. #175Netherlands flagNetherlands
  8. #174Monaco flagMonaco
  9. #173Kuwait flagKuwait
  10. #172Iceland flagIceland

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.

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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Historical Data by Year

Explore Population living in slums data across different years. Compare trends and see how statistics have changed over time.

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