Prevalence of HIV, total (% of population ages 15-49) - Country Ranking

Definition: Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.

Source: UNAIDS estimates.

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Eswatini 27.30 2018
2 Lesotho 23.60 2018
3 South Africa 20.40 2018
4 Botswana 20.30 2018
5 Zimbabwe 12.70 2018
6 Mozambique 12.60 2018
7 Namibia 11.80 2018
8 Zambia 11.30 2018
9 Malawi 9.20 2018
10 Equatorial Guinea 7.10 2018
11 Uganda 5.70 2018
12 Kenya 4.70 2018
13 Tanzania 4.60 2018
14 Gabon 3.80 2018
15 Central African Republic 3.60 2018
15 Cameroon 3.60 2018
17 Guinea-Bissau 3.50 2018
18 Côte d'Ivoire 2.60 2018
18 Congo 2.60 2018
20 Rwanda 2.50 2018
21 Togo 2.30 2018
22 Haiti 2.00 2018
22 Angola 2.00 2018
24 Jamaica 1.90 2018
24 The Gambia 1.90 2018
24 Belize 1.90 2018
27 The Bahamas 1.80 2018
28 Ghana 1.70 2018
29 Nigeria 1.50 2018
29 Barbados 1.50 2018
29 Sierra Leone 1.50 2018
32 Guinea 1.40 2018
32 Suriname 1.40 2018
32 Guyana 1.40 2018
32 Mali 1.40 2018
36 Chad 1.30 2018
36 Liberia 1.30 2018
36 Mauritius 1.30 2018
39 Djibouti 1.20 2018
40 Thailand 1.10 2018
41 Ethiopia 1.00 2018
41 Benin 1.00 2018
41 Ukraine 1.00 2018
41 Burundi 1.00 2018
45 Dominican Republic 0.90 2018
45 Estonia 0.90 2018
45 Panama 0.90 2018
48 Dem. Rep. Congo 0.80 2018
48 Papua New Guinea 0.80 2018
48 Myanmar 0.80 2018
51 Burkina Faso 0.70 2018
51 Eritrea 0.70 2018
53 Uruguay 0.60 2018
53 Moldova 0.60 2018
53 Cabo Verde 0.60 2018
53 El Salvador 0.60 2018
57 Cambodia 0.50 2018
57 Portugal 0.50 2018
57 Brazil 0.50 2018
57 Paraguay 0.50 2018
57 Chile 0.50 2018
57 Belarus 0.50 2018
63 Ecuador 0.40 2018
63 Argentina 0.40 2018
63 United States 0.40 2016
63 Costa Rica 0.40 2018
63 Cuba 0.40 2018
63 Georgia 0.40 2018
63 Colombia 0.40 2018
63 Malaysia 0.40 2018
63 Senegal 0.40 2018
63 Guatemala 0.40 2018
63 Indonesia 0.40 2018
63 Latvia 0.40 2018
75 Bhutan 0.30 2018
75 France 0.30 2018
75 Vietnam 0.30 2018
75 Italy 0.30 2018
75 Lao PDR 0.30 2018
75 Luxembourg 0.30 2018
75 Honduras 0.30 2018
75 Niger 0.30 2018
75 Peru 0.30 2018
75 Madagascar 0.30 2018
75 Bolivia 0.30 2018
75 Spain 0.30 2018
87 Sudan 0.20 2018
87 Armenia 0.20 2018
87 Mauritania 0.20 2018
87 Mexico 0.20 2018
87 Singapore 0.20 2018
87 Oman 0.20 2018
87 Libya 0.20 2018
87 Netherlands 0.20 2017
87 Kyrgyz Republic 0.20 2018
87 Nicaragua 0.20 2018
87 Tajikistan 0.20 2018
87 Kazakhstan 0.20 2018
87 Israel 0.20 2018
87 United Kingdom 0.20 2017
87 Ireland 0.20 2018
87 Uzbekistan 0.20 2018
103 Iceland 0.10 2018
103 Montenegro 0.10 2018
103 Tunisia 0.10 2018
103 Afghanistan 0.10 2018
103 Pakistan 0.10 2018
103 Syrian Arab Republic 0.10 2018
103 Slovak Republic 0.10 2018
103 Denmark 0.10 2018
103 Egypt 0.10 2018
103 Norway 0.10 2018
103 Mongolia 0.10 2018
103 Philippines 0.10 2018
103 Serbia 0.10 2018
103 Bangladesh 0.10 2018
103 Algeria 0.10 2018
103 Finland 0.10 2018
103 Jordan 0.10 2018
103 Lebanon 0.10 2018
103 Sri Lanka 0.10 2018
103 Comoros 0.10 2018
103 Czech Republic 0.10 2018
103 Croatia 0.10 2018
103 Nepal 0.10 2018
103 Bosnia and Herzegovina 0.10 2018
103 Bulgaria 0.10 2018
103 Slovenia 0.10 2018
103 Kuwait 0.10 2018
103 Somalia 0.10 2018
103 Romania 0.10 2018
103 Morocco 0.10 2018
103 Germany 0.10 2018
103 North Macedonia 0.10 2018
103 New Zealand 0.10 2018
103 Japan 0.10 2018
103 Hungary 0.10 2018
103 Iran 0.10 2018
103 Yemen 0.10 2018
103 Australia 0.10 2018

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Limitations and Exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information.

Statistical Concept and Methodology: HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable. Data on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.

Aggregation method: Weighted average

Periodicity: Annual