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 Swaziland 27.20 2016
2 Lesotho 25.00 2016
3 Botswana 21.90 2016
4 South Africa 18.90 2016
5 Namibia 13.80 2016
6 Zimbabwe 13.50 2016
7 Zambia 12.40 2016
8 Mozambique 12.30 2016
9 Malawi 9.20 2016
10 Uganda 6.50 2016
11 Equatorial Guinea 6.20 2016
12 Kenya 5.40 2016
13 Tanzania 4.70 2016
14 Central African Republic 4.00 2016
15 Cameroon 3.80 2016
16 Gabon 3.60 2016
17 The Bahamas 3.30 2016
18 Rwanda 3.10 2016
18 Congo 3.10 2016
18 Guinea-Bissau 3.10 2016
21 Nigeria 2.90 2016
22 Côte d'Ivoire 2.70 2016
23 Haiti 2.10 2016
23 Togo 2.10 2016
25 Angola 1.90 2016
26 Belize 1.80 2016
27 Sierra Leone 1.70 2016
27 Jamaica 1.70 2016
27 The Gambia 1.70 2016
30 Ghana 1.60 2016
30 Liberia 1.60 2016
30 Guyana 1.60 2016
33 Guinea 1.50 2016
34 Suriname 1.40 2016
35 Chad 1.30 2016
35 Barbados 1.30 2016
35 Djibouti 1.30 2016
38 Trinidad and Tobago 1.20 2016
39 Ethiopia 1.10 2016
39 Burundi 1.10 2016
39 Thailand 1.10 2016
42 Dominican Republic 1.00 2016
42 Mali 1.00 2016
42 Benin 1.00 2016
45 Ukraine 0.90 2016
45 Papua New Guinea 0.90 2016
47 Burkina Faso 0.80 2016
47 Cabo Verde 0.80 2016
47 Myanmar 0.80 2016
47 Panama 0.80 2016
51 Latvia 0.70 2016
51 Dem. Rep. Congo 0.70 2016
53 Uruguay 0.60 2016
53 Eritrea 0.60 2016
53 Brazil 0.60 2016
53 El Salvador 0.60 2016
53 Cambodia 0.60 2016
53 Moldova 0.60 2016
53 Venezuela 0.60 2016
60 Georgia 0.50 2016
60 Paraguay 0.50 2016
60 Chile 0.50 2016
60 Mauritania 0.50 2016
60 Guatemala 0.50 2016
60 United States 0.50 2014
66 Vietnam 0.40 2016
66 Colombia 0.40 2016
66 Malaysia 0.40 2016
66 Senegal 0.40 2016
66 Honduras 0.40 2016
66 Costa Rica 0.40 2016
66 Somalia 0.40 2016
66 Argentina 0.40 2016
66 Belarus 0.40 2016
66 Spain 0.40 2016
66 France 0.40 2016
66 Indonesia 0.40 2016
66 Niger 0.40 2016
66 Cuba 0.40 2016
80 Peru 0.30 2016
80 Bolivia 0.30 2016
80 India 0.30 2016
80 Mexico 0.30 2016
80 Ecuador 0.30 2016
80 Tajikistan 0.30 2016
80 Italy 0.30 2016
80 Lao PDR 0.30 2016
88 Kyrgyz Republic 0.20 2016
88 Nicaragua 0.20 2016
88 Nepal 0.20 2016
88 Armenia 0.20 2016
88 Netherlands 0.20 2016
88 Kazakhstan 0.20 2016
88 Sweden 0.20 2016
88 Ireland 0.20 2016
88 Madagascar 0.20 2016
88 Sudan 0.20 2016
88 Lithuania 0.20 2016
99 Jordan 0.10 2016
99 Lebanon 0.10 2016
99 Serbia 0.10 2016
99 Iran 0.10 2016
99 Sri Lanka 0.10 2016
99 Qatar 0.10 2016
99 Comoros 0.10 2016
99 Australia 0.10 2016
99 Macedonia 0.10 2016
99 Saudi Arabia 0.10 2016
99 Morocco 0.10 2016
99 Yemen 0.10 2016
99 Romania 0.10 2016
99 Bulgaria 0.10 2016
99 Montenegro 0.10 2016
99 Bahrain 0.10 2016
99 Czech Republic 0.10 2016
99 Philippines 0.10 2016
99 Albania 0.10 2016
99 Mongolia 0.10 2016
99 Azerbaijan 0.10 2016
99 Croatia 0.10 2016
99 Malta 0.10 2016
99 Kuwait 0.10 2016
99 Slovak Republic 0.10 2016
99 Tunisia 0.10 2016
99 Afghanistan 0.10 2016
99 Egypt 0.10 2016
99 Bangladesh 0.10 2016
99 Algeria 0.10 2016
99 Pakistan 0.10 2016
99 Slovenia 0.10 2016
99 Fiji 0.10 2016

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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