IDA blend - Prevalence of HIV, male (% ages 15-24)

Prevalence of HIV, male (% ages 15-24) in IDA blend was 0.384 as of 2020. Its highest value over the past 30 years was 0.909 in 1995, while its lowest value was 0.384 in 2020.

Definition: Prevalence of HIV, male is the percentage of males who are infected with HIV. Youth rates are as a percentage of the relevant age group.

Source: UNAIDS estimates.

See also:

Year Value
1990 0.648
1991 0.732
1992 0.829
1993 0.876
1994 0.888
1995 0.909
1996 0.862
1997 0.810
1998 0.749
1999 0.694
2000 0.643
2001 0.572
2002 0.529
2003 0.509
2004 0.489
2005 0.479
2006 0.467
2007 0.463
2008 0.458
2009 0.462
2010 0.472
2011 0.469
2012 0.463
2013 0.462
2014 0.460
2015 0.425
2016 0.423
2017 0.406
2018 0.397
2019 0.395
2020 0.384

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

General Comments: In many developing countries most new infections occur in young adults, with young women being especially vulnerable.

Classification

Topic: Health Indicators

Sub-Topic: Risk factors