Dem. Rep. Congo - Prevalence of HIV, male (% ages 15-24)

Prevalence of HIV, male (% ages 15-24) in Dem. Rep. Congo was 0.200 as of 2020. Its highest value over the past 30 years was 0.400 in 1998, while its lowest value was 0.200 in 2018.

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 0.400
1991 0.400
1992 0.400
1993 0.400
1994 0.400
1995 0.400
1996 0.400
1997 0.400
1998 0.400
1999 0.300
2000 0.300
2001 0.300
2002 0.300
2003 0.300
2004 0.300
2005 0.300
2006 0.300
2007 0.300
2008 0.300
2009 0.300
2010 0.300
2011 0.300
2012 0.300
2013 0.300
2014 0.300
2015 0.300
2016 0.300
2017 0.300
2018 0.200
2019 0.200
2020 0.200

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