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

Prevalence of HIV, total (% of population ages 15-49) in Peru was 0.300 as of 2020. Its highest value over the past 30 years was 0.500 in 1992, while its lowest value was 0.300 in 2000.

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 0.500
1991 0.500
1992 0.500
1993 0.400
1994 0.400
1995 0.400
1996 0.400
1997 0.400
1998 0.400
1999 0.400
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 0.300
2019 0.300
2020 0.300

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