Low income | 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
Low income
Records
63
Source
Low income | Prevalence of HIV, female (% ages 15-24)
1960
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1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1.81622701 1990
1.95251223 1991
2.01824281 1992
2.0430535 1993
2.02894975 1994
1.963059 1995
1.91497546 1996
1.79756977 1997
1.71571465 1998
1.59344561 1999
1.49816892 2000
1.40944602 2001
1.30211044 2002
1.23701438 2003
1.14685671 2004
1.09644674 2005
1.04388545 2006
0.99983546 2007
0.98147838 2008
0.9605869 2009
0.93388341 2010
0.89981927 2011
0.88421699 2012
0.86851978 2013
0.85641791 2014
0.82191108 2015
0.77713721 2016
0.75618388 2017
0.72644102 2018
0.67388252 2019
0.63291276 2020
0.60435689 2021
2022
Low income | 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
Low income
Records
63
Source