IDA blend | Prevalence of HIV, female (% ages 15-24)

Prevalence of HIV, female is the percentage of females who are infected with HIV. Youth rates are as a percentage of the relevant age group. 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.
Publisher
The World Bank
Origin
IDA blend
Records
63
Source
IDA blend | Prevalence of HIV, female (% ages 15-24)
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990 1.70908693
1991 2.03248203
1992 2.35569454
1993 2.59195798
1994 2.67002686
1995 2.71531703
1996 2.65425644
1997 2.543693
1998 2.40339884
1999 2.22144729
2000 2.02667683
2001 1.84700978
2002 1.68856896
2003 1.5717192
2004 1.44273833
2005 1.33141864
2006 1.27025992
2007 1.19053057
2008 1.14637065
2009 1.10628504
2010 1.05138493
2011 1.02458728
2012 1.00976645
2013 0.98929729
2014 0.97403214
2015 0.95856436
2016 0.89772987
2017 0.86952085
2018 0.8464893
2019 0.81510221
2020 0.75995395
2021 0.73422516
2022

IDA blend | Prevalence of HIV, female (% ages 15-24)

Prevalence of HIV, female is the percentage of females who are infected with HIV. Youth rates are as a percentage of the relevant age group. 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.
Publisher
The World Bank
Origin
IDA blend
Records
63
Source