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

Women's share of population ages 15+ living with HIV (%) in Zambia was 61.80 as of 2020. Its highest value over the past 30 years was 61.80 in 2020, while its lowest value was 55.70 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 55.70
1991 56.20
1992 56.70
1993 57.00
1994 57.40
1995 57.70
1996 57.90
1997 58.10
1998 58.40
1999 58.60
2000 58.80
2001 58.90
2002 59.10
2003 59.30
2004 59.40
2005 59.60
2006 59.70
2007 59.80
2008 59.90
2009 59.90
2010 60.00
2011 60.00
2012 60.10
2013 60.20
2014 60.30
2015 60.50
2016 60.70
2017 60.90
2018 61.20
2019 61.50
2020 61.80

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