South Africa District HIV Estimates combine district-level data about HIV from several sources in a statistical model:

District HIV estimates are developed using the Naomi model, a small-area estimation model for estimating HIV prevalence and PLHIV, ART coverage, and new HIV infections at district level by sex and five-year age group. The model combines district-level data about multiple outcomes from several sources in a Bayesian statistical model to produce consistent estimates of multiple outcomes of interest.


Download Naomi estimates calibrated to Thembisa 4.6 outputs (by sex and 5-year age group)

For raw (uncalibrated) Naomi estimates or previous versions, see the tab Previous versions.

About

South Africa District Estimates are developed through a technical collaboration of:

in partnership with the South Africa Department of Health, South Africa National AIDS Council, UNAIDS, US Centers for Disease Control (CDC), and the Human Sciences Research Council (HSRC).

Estimates are reviewed by the South Africa Estimates and Modelling Technical Working Group, chaired by the National Department of Health and South Afria National AIDS Council.

For further information, questions, or feedback about South Africa District HIV Estimates, please contact:


Download full results

Full estimates in spreadsheet format:

Naomi estimates calibrated to Thembisa 4.6 outputs (by sex and 5-year age group) Naomi estimates calibrated to Thembisa 4.6 outputs (by sex and coarse <15/15+ age groups)
Raw Naomi estimates (Not adjusted to Thembisa 4.5 outputs)

For planning purposes the version of estimates calibrated to Thembisa 4.6 outputs by sex and 5-year age group are recommended.

Within the zipped folder, the spreadsheet indicators.csv contains estimates of all indicators stratified by:

  • Area: national, province, district
  • Sex: both, female, male
  • Age group: 5-year age groups, all ages, 0-14, 15-49, 15-64, 15+, 50+, 15-24, 25-34, 35-49, 50-64, 64+, age 0, 1-4
  • Time: June 2017, September 2022, September 2023 (selected indicators projected to September 2024 and September 2025)

For each estimate, the mean estimate and 95% uncertainty range are reported.

The file boundaries.geojson contains geographic boundaries, which can be used producing maps of estimates.


Relationship to Thembisa estimates

Thembisa is a mathematical model of the South African HIV epidemic at national and province level. The Thembisa model represents the behaviours and processes that determine HIV transmission, disease progression, and effects of interventions. Thembisa reconstructs the full trajectory of the HIV epidemic in South Africa with medium range projections (1985-2040).

The Naomi model is a statistical model that balances evidence from multiple data sources at district level, but does not represent mechanisms of HIV transmission. Naomi is focused on current estimates (2022-23) for district-level planning purposes.

For some policy and planning purposes, it is useful for central values for district, provincial, and national estimates to exactly align. After fitting the model, a second version of district estimates are produced that are adjusted such that aggregated district estimates match to Thembisa provincial estimates, interpolated to the relevant quarter for district estimates. Before adjusting district estimates, Thembisa provincial estimates are first adjusted to match Thembisa national estimates.

The table below summarises key elements of Thembisa and Naomi
Thembisa Naomi
Geographical level National, provincial District
Demographic inputs CARe model District estimates by Statistics SA, adjusted to Thembisa
Age stratification Single year (0, 1, …, 89, 90+) Five-year age groups 0 to 80+
Migration Migration between provinces contributes to changes in HIV prevalence Migration is not explicitly modelled
HIV incidence Population is divided into risk groups, key populations. Assumptions about sexual risk behaviour and HIV transmission drive incidence. By sex, age, and district (10+ population only). Depends on transmission rate, district prevalence, and district ART coverage
HIV disease progression Acute HIV + 4 CD4 stages Not explicitly modelled
Diagnosis, testing Testing rates depend on age, sex, CD4 stage, year Not included
ART uptake Depends on CD4 stage, sex, age, year Depends on district, sex, age, year
Adjustment for cross-border ART None Persons have a small probability of receiving ART at facilities in a neighbouring district to their residence
Mortality Depends on age, sex, current CD4 (if untreated), time since ART start and baseline CD4 (if treated) HIV survival based on survival probabilities from Thembisa by sex, age, province (not a model output)
Calibration to HIV prevalence data HSRC & DHS surveys; Antenatal prevalence surveys; Key population surveys HSRC 2017 & DHS surveys; Routine antenatal HIV testing prevalence
Inclusion of programme data HIV testing data, ART totals, viral suppression, VMMCs ART totals
Most recent programme data March 2022 September 2022
Other calibration data Recorded deaths (national); Self-reported testing history ART coverage among women attending first ANC

Methods: Naomi model

South Africa District HIV Estimates are developed using the Naomi model. The Naomi model is a small-area estimation model for estimating HIV prevalence and PLHIV, ART coverage, and new HIV infections at district level by sex and five-year age group. The model combines district-level data about multiple outcomes from several sources in a Bayesian statistical model to produce consistent estimates of multiple outcomes of interest.

The model focuses on current estimates and short-term one-year ahead projections for HIV programme planning purposes.

Population

District-level population estimates by sex and age group are drawn from the Statistics South Africa Mid-Year Population Estimates1 and adjusted to match the Thembisa 4.6 province-level population by sex and age group.

HIV prevalence

The first step is to produce cross-sectional estimates for HIV prevalence, ART coverage, and HIV incidence in June 2017, the mid-point of the most recent nationally-representative household surveys.

For HIV prevalence, the model is calibrated to survey data about HIV prevalence by district, sex, and five-year age group from the National HIV Prevalence, Incidence, Behaviour and Communication Survey (SABSSM) 20172 and Demographic and Health Survey (DHS) 20163. Since the survey sample size in each district is relatively small, routinely reported data about HIV prevalence among pregnant women attending their first ANC visit, extracted from the national District Health Management Information System (DHIS), are used to improve estimates of the spatial pattern of HIV.

ART coverage

ART coverage by district, age, and sex is estimated from household survey data about the presence of ARV biomarkers in HIV-positive survey respondents. Routinely reported ART coverage among pregnant women prior to first ANC visit is used as a covariate for the spatial pattern of ART coverage. The ART coverage and HIV prevalence are also calibrated so that total number on ART matches the number of adults and children accessing treatment in each district through public sector and private sector treatment provision, reported through the national DHIS and Council for Medical Schemes, respectively.

ART attendance in neighbouring districts

A challenge for estimating treatment coverage at district level is that persons may access ART services in a different district than their residence, for example if facilities are closer or perceived to provide better services. The model allows for a probability that resident PLHIV access ART in a neighbouring district. The prior assumption is that the large majority of PLHIV will access ART in their district of residence, but this probability can vary based on district data about the number receiving ART compared to HIV prevalence, ART coverage and population.

HIV incidence

HIV incidence in 2017 is estimated from the proportion recently infected from the SABSSM 2017 survey. HIV incidence is determined by the district-level HIV prevalence and ART coverage such that the estimated HIV incidence is related to the prevalence of unsuppressed HIV in the population. The sex and age distribution of new infections is estimated using incidence rate ratios from Thembisa.

Projection to September 2022 and 2023

The next step of the model is to conduct a one-step projection of the population to September 2022. Population estimates are updated with Statistics South Africa district projections. The number of PLHIV is projected from 2017 to 2022 based on survival estimates by province, sex, and age group from Thembisa over the same period (which accounts for HIV disease progression and effects of ART scale up on reducing AIDS mortality). ART coverage is updated based on the number on ART in September 2022 from DHIS and medical scheme reporting. Finally, for programme planning purposes, a short term projection is calculated to September 2023 using the same methods. The number on ART is projected based on Thembisa model projection for rates of further scale up.

Paediatric estimates

For paediatric estimates, where household survey data have low numbers of observed cases, the model uses the ratio of female adult HIV prevalence to child HIV prevalence from Thembisa provincial results to estimate the average district-level prevalence among children and the new paediatric infections between 2017 and 2022. Paediatric ART coverage is determined by the number of children receiving ART in each district and SABBSM survey data about ART coverage among children.

Versions

A preliminary version of the Naomi model was first developed in South Africa in 2019 and district estimate were publicly released at www.hivdata.org.za in November 2020.

The model has been used in UNAIDS-supported national HIV estimates in 40 other sub-Saharan African countries. Future development of Naomi will extend the model for additional data sources and indicators including the HIV care cascade and prevention indicators.


Prevalence & PLHIV

Prevalence is the estimated number of people (aged 15-49 years) living with HIV in the district divided by the total resident population aged 15-49 years.

ART coverage & Number on ART

ART coverage is the estimated number of residents in the district currently on ART (aged 15+ years) divided by the number of residents aged 15+ years living with HIV.

Hovering over each district shows the estimated number of residents on ART and the number of clients receiving ART at health facilities in the district. These numbers may be different because some residents obtain treatment at health facilities in neighbouring districts.

Incidence & New infections

HIV incidence rate is the number of new HIV infections occurring during the previous year among residents in the district (aged 15-49 years) divided by the number of HIV negative residents aged 15-49 years.

Previous versions

This page contains previously released versions of Naomi district estimates for archival purposes.

Each version of Naomi district estimates involves re-estimation of historical and current results for all districts with updated data inputs about each component of the model Therefore, changes in successive releases of Naomi estimates should not be used to estimate time trends in indicators. For uses cases where time trends are required, please contact developers () to discuss.


September 2022 (released 3 May 2023)

Naomi estimates for September 2022 were reviewed and adopted by the South Africa HIV Estimates Techincal Working Group in March 2023.

Estimates were produced using the Naomi model version 2.9.9 (code here).

Key updates in the September 2022 district estimates were:

  • Estimates were produced for September 2022 and projection to September 2023, with further projection of selected indicators to September 2024 and September 2025.
  • Outputs include new indicators for district-level ART target setting:
    • plhiv_attend representing the number of PLHIV in the health facility catchment for each district, accounting for estimated patterns of ART care seeking in neighbouring districts. This output should be used as a denominator for catchment ART coverage and target setting calculated using TROA as the numerator (public and private sector combined).
    • untreated_plhiv_attend representing the number of untreated PLHIV in the health facility catchment for each district. This is a direct estimates for the ‘treatment gap’ at health facilities.
  • Published estimates on www.hivdata.org.za reflect results calibrated to Thembisa 4.6 outputs by sex and 5-year age group in each province (instead of by age <15/15+).
    • Thembisa 4.6 provincial estimates were calibrated to align to Thembisa 4.6 national estimates.

The following data were updated in the September 2022 estimates:

  • Monthly ART and ANC testing NDOH programme data from DHIS2 were incorporated through September 2022.
  • Private sector ART data from Council for Medical Aid Schemes updated to December 2021.
  • The TIER.Net electronic register was used to provide data on the distribution of adults (15+) on ART by sex in each district.
    • This improves consistency of model results with ART programme data for number on ART by sex in each distict.
    • Partial Tier.NET data were available for Northern Cape province. These were used to inform ART sex/age distribution for districts in Northern Cape province.
  • An additional 76,000 cash-paying ART clients were incorporated into estimates based on SANAC-commissioned analysis of IQVIA pharmacy transaction data (no updated data since September 2021 estimates).
    • Around half of additional cash-paying clients were in Gauteng province and Western Cape also had disproportionate cash-paying clients.
  • HIV transmission rate, survival, and provincial population estimates were updated to Thembisa 4.6.
  • District population inputs were updated to Statistics South Africa Mid-Year Population Estimates 2022.

Download Naomi estimates for September 2022:


September 2021 (released 29 May 2022)

Naomi estimates for September 2021 were reviewed and adopted by the South Africa HIV Estimates Techincal Working Group in April 2022.

Key updates in the September 2021 district estimates were:

  • Estimates were produced for September 2021 and projection to September 2023.
  • Monthly ART and ANC testing NDOH programme data from DHIS2 were incorporated through September 2021.
  • Private sector ART data from Council for Medical Aid Schemes updated to June 2021.
  • The TIER.Net electronic register was used to provide data on the distribution of adults (15+) on ART by sex in each district.
    • This improves consistency of model results with ART programme data for number on ART by sex in each distict.
    • Tier.NET data are not available for Northern Cape province. Northern Cape ART data were disaggregated by sex based on number of individuals with viral load tests from NHLS data in 2019.
  • An additional 76,000 cash-paying ART clients were incorporated into estimates based on SANAC-commissioned analysis of IQVIA pharmacy transaction data.
    • Around half of additional cash-paying clients were in Gauteng province and Western Cape also had disproportionate cash-paying clients.
  • HIV transmission rate, survival, and provincial population estimates were updated to Thembisa 4.5.
  • District population inputs were updated to Statistics South Africa Mid-Year Population Estimates 2021.
  • Outputs include indicator plhiv_attend estimate for the number of PLHIV in the catchment for health facilities in each district.
    • This output should be used as a denominator for catchment ART coverage and target setting calculated using TROA as the numerator.
  • Published estimates on www.hivdata.org.za reflect results calibrated to Thembisa 4.5 outputs instead of raw Naomi estimates.

Download Naomi estimates for September 2021:


September 2020 (released 31 March 2021)

Naomi district HIV estimates for September 2020 were reviewed and adopted by the South Africa HIV Estimates Technical Working Group in March 2021.

Key updates in the September 2020 district estimates were:

  • Estimates were produced for September 2020 and projection to September 2021
  • District population estimates were updated to Stats SA Mid-Year Population Estimates 2020.
  • Public sector ART and ANC testing data were updated with montly data through September 2020 from the National District Health Information System (DHIS2).
  • Private sector ART data from Council for Medical Aid Schemes updated to June 2020.
    • Reflects arond 270,000 receiving ART through private sector, decline of around 50,000 from December 2019 reporting.
  • Provincial Thembisa 4.4 estimates were used as inputs.
  • A version of district outputs were produced that calibrated to Thembisa provincial outputs such that aggregate district estimates aligned exactly to Thembisa estimates.

Download Naomi estimates for September 2020:


March 2020 (released 17 November 2020)

District HIV estimates for March 2020 were first released via hivdata.org.za in November 2020 coinciding with a national HIV estimates launch webinar hosted by the South Africa National AIDS Control Council (SANAC).

Download March 2020 estimates: zaf_district_naomi-output_march-2020.zip




  1. Statistics South Africa. Mid-year population estimates 2022. 2022. Available: https://www.statssa.gov.za/publications/P0302/P03022022.pdf. Accessed 3 May 2023↩︎

  2. Simbayi LC, Zuma K, Zungu N, Moyo S, Marinda E, Jooste S, et al. South African National HIV Prevalence, Incidence, Behaviour and Communication Survey, 2017. Cape Town: Human Sciences Research Council; 2019. Available: https://www.hsrcpress.ac.za/books/south-african-national-hiv-prevalence-incidence-behaviour-and-communication-survey-2017. Accessed 6 Nov 2019↩︎

  3. Department of Health, Statistics South Africa, South African Medical Research Council, ICF. South Africa Demographic and Health Survey 2016. Pretoria; 2019. Available: https://www.dhsprogram.com/pubs/pdf/FR337/FR337.pdf. Accessed 19 March 2019↩︎