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

Women's share of population ages 15+ living with HIV (%) in Sudan was 47.80 as of 2020. Its highest value over the past 30 years was 49.70 in 2011, while its lowest value was 40.10 in 1995.

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 49.50
1991 48.00
1992 45.80
1993 42.30
1994 40.70
1995 40.10
1996 40.60
1997 41.50
1998 42.60
1999 43.40
2000 44.40
2001 45.30
2002 46.00
2003 46.80
2004 47.40
2005 47.90
2006 48.40
2007 48.90
2008 49.30
2009 49.50
2010 49.60
2011 49.70
2012 49.60
2013 49.50
2014 49.30
2015 49.20
2016 48.90
2017 48.70
2018 48.40
2019 48.20
2020 47.80

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