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

Women's share of population ages 15+ living with HIV (%) in Guyana was 50.40 as of 2020. Its highest value over the past 30 years was 56.70 in 2004, while its lowest value was 39.00 in 1996.

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 51.30
1991 49.40
1992 46.80
1993 43.80
1994 41.10
1995 39.30
1996 39.00
1997 40.40
1998 43.30
1999 47.00
2000 50.60
2001 53.60
2002 55.50
2003 56.50
2004 56.70
2005 56.40
2006 55.80
2007 55.00
2008 54.10
2009 53.20
2010 52.50
2011 51.80
2012 51.20
2013 50.80
2014 50.50
2015 50.30
2016 50.20
2017 50.20
2018 50.20
2019 50.30
2020 50.40

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