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

Women's share of population ages 15+ living with HIV (%) in Belarus was 33.60 as of 2020. Its highest value over the past 30 years was 33.60 in 2020, while its lowest value was 25.00 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 25.00
1991 25.60
1992 26.30
1993 26.90
1994 27.40
1995 27.70
1996 28.30
1997 28.60
1998 29.00
1999 29.40
2000 29.70
2001 30.00
2002 30.20
2003 30.40
2004 30.70
2005 30.80
2006 31.00
2007 31.10
2008 31.20
2009 31.30
2010 31.40
2011 31.70
2012 32.00
2013 32.30
2014 32.50
2015 32.70
2016 33.00
2017 33.30
2018 33.40
2019 33.50
2020 33.60

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