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 27.70 2014
2 Botswana 25.20 2014
3 Lesotho 23.40 2014
4 South Africa 18.90 2014
5 Zimbabwe 16.70 2014
6 Namibia 16.00 2014
7 Zambia 12.40 2014
8 Mozambique 10.60 2014
9 Malawi 10.00 2014
10 Uganda 7.30 2014
11 Equatorial Guinea 6.20 2014
12 Tanzania 5.30 2014
12 Kenya 5.30 2014
14 Cameroon 4.80 2014
15 Central African Republic 4.30 2014
16 Gabon 3.90 2014
17 Guinea-Bissau 3.70 2014
18 Côte d'Ivoire 3.50 2014
19 Nigeria 3.20 2014
20 Congo 2.80 2014
20 Rwanda 2.80 2014
22 Chad 2.50 2014
23 Togo 2.40 2014
23 Angola 2.40 2014
25 Haiti 1.90 2014
26 Guyana 1.80 2014
26 The Gambia 1.80 2014
28 Jamaica 1.60 2014
28 Guinea 1.60 2014
28 Djibouti 1.60 2014
31 Ghana 1.50 2014
32 Mali 1.40 2014
32 Sierra Leone 1.40 2014
34 Belize 1.20 2014
34 Liberia 1.20 2014
34 Ethiopia 1.20 2014
34 Ukraine 1.20 2014
38 Burundi 1.10 2014
38 Cabo Verde 1.10 2014
38 Benin 1.10 2014
38 Thailand 1.10 2014
42 Suriname 1.00 2014
42 Dominican Republic 1.00 2014
42 Dem. Rep. Congo 1.00 2014
45 Burkina Faso 0.90 2014
45 Mauritius 0.90 2014
47 São Tomé and Principe 0.80 2014
48 Papua New Guinea 0.70 2014
48 Mauritania 0.70 2014
48 Eritrea 0.70 2014
48 Uruguay 0.70 2014
48 Myanmar 0.70 2014
53 Cambodia 0.60 2014
53 Venezuela 0.60 2014
53 Moldova 0.60 2014
53 Panama 0.60 2014
57 Somalia 0.50 2014
57 Malaysia 0.50 2014
57 Senegal 0.50 2014
57 El Salvador 0.50 2014
57 Niger 0.50 2014
57 Argentina 0.50 2014
57 Belarus 0.50 2014
57 Indonesia 0.50 2014
57 Vietnam 0.50 2014
57 Guatemala 0.50 2014
67 Tajikistan 0.40 2014
67 Colombia 0.40 2014
67 Honduras 0.40 2014
67 Peru 0.40 2014
67 Paraguay 0.40 2014
72 Madagascar 0.30 2014
72 Bolivia 0.30 2014
72 Chile 0.30 2014
72 Costa Rica 0.30 2014
72 Ecuador 0.30 2014
72 Cuba 0.30 2014
72 Georgia 0.30 2014
72 Kyrgyz Republic 0.30 2014
72 Nicaragua 0.30 2014
72 Ireland 0.30 2014
72 Lao PDR 0.30 2014
83 Sweden 0.20 2014
83 Uzbekistan 0.20 2014
83 Denmark 0.20 2014
83 Nepal 0.20 2014
83 Mexico 0.20 2014
83 Kazakhstan 0.20 2014
83 Armenia 0.20 2014
83 Norway 0.20 2014
83 Oman 0.20 2014
83 Sudan 0.20 2014
93 Yemen 0.10 2014
93 Iran 0.10 2014
93 Poland 0.10 2014
93 Philippines 0.10 2014
93 Azerbaijan 0.10 2014
93 Bangladesh 0.10 2014
93 Algeria 0.10 2014
93 Pakistan 0.10 2014
93 Lebanon 0.10 2014
93 Slovenia 0.10 2014
93 Sri Lanka 0.10 2014
93 Morocco 0.10 2014
93 Egypt 0.10 2014
93 Tunisia 0.10 2014
93 Syrian Arab Republic 0.10 2014
93 Slovak Republic 0.10 2014
93 Afghanistan 0.10 2014
93 Fiji 0.10 2014

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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. For example, improved software was used to model the course of HIV epidemics and their impacts, making full use of information on HIV prevalence trends from surveillance data as well as survey data. The software explicitly includes the effect of antiretroviral therapy when calculating HIV incidence and models reduced infectivity among people receiving antiretroviral therapy, which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer. The software also allows for changes in urbanization over time - important because prevalence is higher in urban areas and because many countries have seen rapid urbanization over the past two decades. The estimates include plausible bounds, not shown in the Indicator data, which reflect the certainty associated with each of the estimates. The bounds are available at http://data.worldbank.org and from the original source.

Aggregation method: Weighted average

Periodicity: Annual