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State of Victoria 95-95-95 Targets (2020) PLHIV : 7,959

90%

92%

96%

Source: Jointly provided by the Burnet Institute and the Kirby Institute at the University of NSW

State of Victoria HIV Care Continuum (2020) PLHIV: 7,959

90%

NA

83%

79%

Source: Jointly provided by the Burnet Institute and the Kirby Institute at the University of NSW

The following counters and charts portray the current epidemiology of HIV. The charts have hovers and are changeable by clicking on them. They are also downloadable-see the download button.

7,959

Source: Jointly provided by the Burnet Institute and the Kirby Institute at the University of NSW

7,155

Source: Jointly provided by the Burnet Institute and the Kirby Institute at the University of NSW

6,571

Source: Jointly provided by the Burnet Institute and the Kirby Institute at the University of NSW

6,310

Source: Jointly provided by the Burnet Institute and the Kirby Institute at the University of NSW

283

Source: Jointly provided by the Burnet Institute and the Kirby Institute at the University of NSW, 2016

217

Source: Jointly provided by the Burnet Institute and the Kirby Institute at the University of NSW, 2016

4,026

Source: Jointly provided by the Burnet Institute and the Kirby Institute at the University of NSW, 2016

Victoria

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Methodology

Victoria’s HIV cascade was calculated through an adapted version to the methodology used to estimate Australia’s national cascade that used locally sourced data. Australia’s cascade estimates use the following methods that are also reported in more detail at http://kirby.unsw.edu.au/surveillance/2016-annual-surveillance-report-hiv-viral-hepatitis-stis.

Estimating the number of people living with HIV
To estimate the overall number of people living with HIV (PLHIV), both diagnosed and undiagnosed, we used the European Center for Disease Control (ECDC) HIV Modelling Tool to estimate the proportion of PLHIV who are undiagnosed1.The ECDC tool is a multi-state back-calculation model using notifications data and estimates for the rate of CD4 decline to fit diagnoses rates over time. To run the model notifications data were split by CD4 strata, whether the patient had AIDS at the time of diagnosis, and optional risk of exposure categories. For the cascade estimates, annual notifications were divided into those attributed to male-to-male sex (representing gay and bisexual men), heterosexual contact, injecting drug use, and other. The ECDC tool was run for each exposure category as well as overall (with all groups combined) and excluding male-to-male sex. The tool’s diagnosis rate options where adjusted to best fit the CD4 count at diagnosis data. For validation, the model estimates for undiagnosed gay and bisexual men (GBM) were compared with empirical data from the COUNT study; the ECDC tool estimates closely matched those of COUNT2. The overall prevalence of HIV was then estimated by inflating the calculated number of people living with diagnosed infection by the estimated level of undiagnosed infection.

Estimating the number of people with diagnosed infection
To estimate the number of people living with diagnosed HIV (PLDHIV) we performed a simple calculation using annual notifications, estimated mortality rates, and interstate and overseas migration rates. Annual HIV notifications data was provided by Australia’s National HIV Registry, adjusted to account for duplicate notifications3.

Mortality among people diagnosed with HIV was estimated using a linkage study conducted between Australia’s National Death Index and the National HIV Registry for cases to the end of 2003. After 2003 the annual mortality rates from the Australian HIV Observational Database (AHOD)4 were used. Over 2004 – 2016, similar annual mortality rates were estimated for the AHOD cohort regardless of whether people were retained, lost or returned to follow up.

Overseas migration for PLDHIV was estimated using data from the Australian Bureau of Statistics (ABS) and recent follow-up data of people recently diagnosed in NSW (reporting up to 4% of PLDHIV move overseas soon after their diagnosis)5. As this data is for recent diagnoses in recent years, the rate was discounted to 2% overall with a range of 0 – 4% to reflect this initial migration.

The overall estimate of the number of PLDHIV in Australia each year is obtained by adding the number of unique notifications to the previous year’s estimate and subtracting the number of deaths and overseas migrants using the mortality and migration rates.

Estimating antiretroviral treatment coverage
The number of people receiving ART was estimated using a 10% random sample of Pharmaceutical Benefits Scheme (PBS) patient level script claims data from 2006‑present. Our people receiving ART estimate is determined from the number of unique patients in the PBS data set who filled in at least one script in the 12 months prior to the end of December 2016 multiplied by 10. To the PBS number we added the number of HIV+ temporary residents taking ART (temporary residents are ineligible for HIV public subsidy of drug dispensed and hence not counted in the 10% sample)estimated from the Australian HIV Observational Database Temporary Access Study (ATRAS)6

Estimating levels of virological suppression
We defined virological suppression as less than 200 viral copies per ml. The proportion of people on ART with viral suppression was taken to be the proportion of people recorded in AHOD who had less than 200 copies per ml at their last viral load test. The number of PLHIV on ART with viral suppression was estimated by multiplying this proportion and range by the estimated number of people receiving ART

  1. van Sighem A, Nakagawa F, De Angelis D, Quinten C, Bezemer D, de Coul EO, et al. Estimating HIV Incidence, Time to Diagnosis, and the Undiagnosed HIV Epidemic Using Routine Surveillance Data. Epidemiology (Cambridge,Mass). 2015;26(5):653 –60
  2. Holt M, Lea T, Asselin J, Hellard M, Prestage G, Wilson D, de Wit J, Stoové M. The prevalence and correlates of undiagnosed HIV among Australian gay and bisexual men: results of a national, community-based, bio-behavioural survey. Journal of the International AIDS Society. 2015;18:20526.
  3. Nakhaee F, Black D, Wand H, McDonald A, Law M. Changes in mortality following HIV and AIDS and estimation of the number of people living with diagnosed HIV/AIDS in Australia, 1981‑2003. Sex Health. 2009;6(2):129 – 34.
  4. The Kirby Institute. Australian HIV Observational Database Annual Report. Sydney, Australia: The Kirby Institute, UNSW Australia, 2014.
  5. NSW Government Health. NSW HIV Strategy 2016‑2020 Quarter 2 2016 Data Report. Sydney, NSW: NSW Government Health, 2016.
  6. Petoumenos K, Watson J, Whittaker B, Hoy J, Smith D, Bastian L, et al. Subsidized optimal ART for HIV‑positive temporary residents of Australia improves virological outcomes: results from the Australian HIV Observational Database Temporary Residents Access Study. J Int Aids Soc. 2015;18:19392.

Hover your mouse on bar for detailed data.

Hover your mouse on bar for detailed data.

Hover your mouse on bar for detailed data.

Methodology

Victoria’s HIV cascade was calculated through an adapted version to the methodology used to estimate Australia’s national cascade that used locally sourced data. Australia’s cascade estimates use the following methods that are also reported in more detail at http://kirby.unsw.edu.au/surveillance/2016-annual-surveillance-report-hiv-viral-hepatitis-stis.

Estimating the number of people living with HIV
To estimate the overall number of people living with HIV (PLHIV), both diagnosed and undiagnosed, we used the European Center for Disease Control (ECDC) HIV Modelling Tool to estimate the proportion of PLHIV who are undiagnosed1.The ECDC tool is a multi-state back-calculation model using notifications data and estimates for the rate of CD4 decline to fit diagnoses rates over time. To run the model notifications data were split by CD4 strata, whether the patient had AIDS at the time of diagnosis, and optional risk of exposure categories. For the cascade estimates, annual notifications were divided into those attributed to male-to-male sex (representing gay and bisexual men), heterosexual contact, injecting drug use, and other. The ECDC tool was run for each exposure category as well as overall (with all groups combined) and excluding male-to-male sex. The tool’s diagnosis rate options where adjusted to best fit the CD4 count at diagnosis data. For validation, the model estimates for undiagnosed gay and bisexual men (GBM) were compared with empirical data from the COUNT study; the ECDC tool estimates closely matched those of COUNT2. The overall prevalence of HIV was then estimated by inflating the calculated number of people living with diagnosed infection by the estimated level of undiagnosed infection.

Estimating the number of people with diagnosed infection
To estimate the number of people living with diagnosed HIV (PLDHIV) we performed a simple calculation using annual notifications, estimated mortality rates, and interstate and overseas migration rates. Annual HIV notifications data was provided by Australia’s National HIV Registry, adjusted to account for duplicate notifications3.

Mortality among people diagnosed with HIV was estimated using a linkage study conducted between Australia’s National Death Index and the National HIV Registry for cases to the end of 2003. After 2003 the annual mortality rates from the Australian HIV Observational Database (AHOD)4 were used. Over 2004 – 2016, similar annual mortality rates were estimated for the AHOD cohort regardless of whether people were retained, lost or returned to follow up.

Overseas migration for PLDHIV was estimated using data from the Australian Bureau of Statistics (ABS) and recent follow-up data of people recently diagnosed in NSW (reporting up to 4% of PLDHIV move overseas soon after their diagnosis)5. As this data is for recent diagnoses in recent years, the rate was discounted to 2% overall with a range of 0 – 4% to reflect this initial migration.

The overall estimate of the number of PLDHIV in Australia each year is obtained by adding the number of unique notifications to the previous year’s estimate and subtracting the number of deaths and overseas migrants using the mortality and migration rates.

Estimating antiretroviral treatment coverage
The number of people receiving ART was estimated using a 10% random sample of Pharmaceutical Benefits Scheme (PBS) patient level script claims data from 2006‑present. Our people receiving ART estimate is determined from the number of unique patients in the PBS data set who filled in at least one script in the 12 months prior to the end of December 2016 multiplied by 10. To the PBS number we added the number of HIV+ temporary residents taking ART (temporary residents are ineligible for HIV public subsidy of drug dispensed and hence not counted in the 10% sample)estimated from the Australian HIV Observational Database Temporary Access Study (ATRAS)6

Estimating levels of virological suppression
We defined virological suppression as less than 200 viral copies per ml. The proportion of people on ART with viral suppression was taken to be the proportion of people recorded in AHOD who had less than 200 copies per ml at their last viral load test. The number of PLHIV on ART with viral suppression was estimated by multiplying this proportion and range by the estimated number of people receiving ART

  1. van Sighem A, Nakagawa F, De Angelis D, Quinten C, Bezemer D, de Coul EO, et al. Estimating HIV Incidence, Time to Diagnosis, and the Undiagnosed HIV Epidemic Using Routine Surveillance Data. Epidemiology (Cambridge,Mass). 2015;26(5):653 –60
  2. Holt M, Lea T, Asselin J, Hellard M, Prestage G, Wilson D, de Wit J, Stoové M. The prevalence and correlates of undiagnosed HIV among Australian gay and bisexual men: results of a national, community-based, bio-behavioural survey. Journal of the International AIDS Society. 2015;18:20526.
  3. Nakhaee F, Black D, Wand H, McDonald A, Law M. Changes in mortality following HIV and AIDS and estimation of the number of people living with diagnosed HIV/AIDS in Australia, 1981‑2003. Sex Health. 2009;6(2):129 – 34.
  4. The Kirby Institute. Australian HIV Observational Database Annual Report. Sydney, Australia: The Kirby Institute, UNSW Australia, 2014.
  5. NSW Government Health. NSW HIV Strategy 2016‑2020 Quarter 2 2016 Data Report. Sydney, NSW: NSW Government Health, 2016.
  6. Petoumenos K, Watson J, Whittaker B, Hoy J, Smith D, Bastian L, et al. Subsidized optimal ART for HIV‑positive temporary residents of Australia improves virological outcomes: results from the Australian HIV Observational Database Temporary Residents Access Study. J Int Aids Soc. 2015;18:19392.

Hover your mouse on bar for detailed data.

Hover your mouse on bar for detailed data.

Hover your mouse on bar for detailed data.

Methodology

* 6-month repeat testing defined as any HIV test within 1-7 months of an index negative HIV test occuring before 5 June 2015

*Proportion of GBM clinical patients* tested for HIV who had at least one other HIV test in the previous six months (6 weeks - 7 month period)

**Proportion of GBM clinical patients* tested for HIV who had at least one other HIV test in the previous year (6 weeks - 13 month period)

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