Afghanistan - Prevalence of HIV, total (% of population ages 15-49)

Prevalence of HIV, total (% of population ages 15-49) in Afghanistan was 0.100 as of 2018. Its highest value over the past 28 years was 0.100 in 2018, while its lowest value was 0.100 in 1990.

Definition: Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.

Source: UNAIDS estimates.

See also:

Year Value
1990 0.100
1991 0.100
1992 0.100
1993 0.100
1994 0.100
1995 0.100
1996 0.100
1997 0.100
1998 0.100
1999 0.100
2000 0.100
2001 0.100
2002 0.100
2003 0.100
2004 0.100
2005 0.100
2006 0.100
2007 0.100
2008 0.100
2009 0.100
2010 0.100
2011 0.100
2012 0.100
2013 0.100
2014 0.100
2015 0.100
2016 0.100
2017 0.100
2018 0.100

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

Classification

Topic: Health Indicators

Sub-Topic: Risk factors