Angola - Women's share of population ages 15+ living with HIV (%)

Women's share of population ages 15+ living with HIV (%) in Angola was 65.10 as of 2020. Its highest value over the past 30 years was 65.10 in 2020, while its lowest value was 56.70 in 1990.

Definition: Prevalence of HIV is the percentage of people who are infected with HIV. Female rate is as a percentage of the total population ages 15+ who are living with HIV.

Source: UNAIDS estimates.

See also:

Year Value
1990 56.70
1991 57.40
1992 58.00
1993 58.50
1994 58.90
1995 59.30
1996 59.60
1997 59.80
1998 60.00
1999 60.20
2000 60.40
2001 60.50
2002 60.60
2003 60.70
2004 60.80
2005 60.90
2006 61.00
2007 61.10
2008 61.30
2009 61.30
2010 61.40
2011 61.60
2012 61.80
2013 62.00
2014 62.50
2015 63.00
2016 63.50
2017 63.90
2018 64.30
2019 64.60
2020 65.10

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