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

Prevalence of HIV, total (% of population ages 15-49) in El Salvador was 0.600 as of 2018. Its highest value over the past 28 years was 0.700 in 2014, while its lowest value was 0.200 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 0.200
1991 0.200
1992 0.200
1993 0.300
1994 0.300
1995 0.400
1996 0.400
1997 0.500
1998 0.500
1999 0.600
2000 0.600
2001 0.600
2002 0.700
2003 0.700
2004 0.700
2005 0.700
2006 0.700
2007 0.700
2008 0.700
2009 0.700
2010 0.700
2011 0.700
2012 0.700
2013 0.700
2014 0.700
2015 0.600
2016 0.600
2017 0.600
2018 0.600

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


Topic: Health Indicators

Sub-Topic: Risk factors