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

Women's share of population ages 15+ living with HIV (%) in Serbia was 14.70 as of 2020. Its highest value over the past 30 years was 27.80 in 1999, while its lowest value was 14.70 in 2020.

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 25.60
1991 26.10
1992 26.50
1993 26.80
1994 27.00
1995 27.20
1996 27.40
1997 27.50
1998 27.70
1999 27.80
2000 27.70
2001 27.60
2002 27.30
2003 26.60
2004 25.70
2005 25.00
2006 24.30
2007 23.50
2008 22.80
2009 22.00
2010 21.20
2011 20.40
2012 19.70
2013 19.00
2014 18.20
2015 17.60
2016 16.90
2017 16.30
2018 15.80
2019 15.20
2020 14.70

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