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

Prevalence of HIV, male (% ages 15-24) in IDA total was 0.460 as of 2020. Its highest value over the past 30 years was 0.826 in 1995, while its lowest value was 0.460 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 0.641
1991 0.704
1992 0.770
1993 0.799
1994 0.813
1995 0.826
1996 0.808
1997 0.774
1998 0.735
1999 0.696
2000 0.661
2001 0.614
2002 0.591
2003 0.574
2004 0.559
2005 0.553
2006 0.543
2007 0.540
2008 0.542
2009 0.545
2010 0.551
2011 0.556
2012 0.556
2013 0.555
2014 0.548
2015 0.532
2016 0.516
2017 0.506
2018 0.480
2019 0.476
2020 0.460

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