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In 2023, UNAIDS developed an approach to estimate the number (i.e., the denominator) of priority groups at risk for acquiring HIV at sub-national level (provinces and/or districts) who need intensified HIV prevention programmes. The resulting tool, the Sub-national HIV Estimates in Priority Populations (SHIPP) Tool, is pre-populated with relevant data for 34 priority countries in Sub-Saharan Africa. The countries included correspond to those with validated Naomi data and recent behavioural survey data. 

The estimates are generated from a combination of survey data and mathematical model outputs. The approach goes beyond just using population sizes of priority groups in high incidence districts and reflect variations in risk by behavioural risk factors. Both the HIV Incidence estimates and HIV-related behavioural risk categories used in the model are based on the Global AIDS Strategy 2021-2026. And for the estimates of HIV incidence, the SHIPP Tool draws on the Naomi small-area estimation model. Background HIV incidence in each district is classified into the following four levels – “low”, “moderate”, “high” and “very high”. The HIV-related behavioural risk categories employed in the SHIPP Tool are based on sexual behaviour and relationship status – “not sex sexually active”, “sexually active, one cohabiting partner”, “non-regular sexual partners” and “key populations” for females, women who sell sex. For men, men who have sex with men and men who inject drugs. The Tool uses estimates of the prevalence of behaviours from the most recent Demographic Health Surveys (DHS) and if that is not available, then either the AIDS Indicator Surveys and/or Population-based HIV Impact Assessment (PHIA) surveys in each country (by district and age group). 

A 2023 article applying the model to 13 countries in sub-saharan Africa found that risk group proportions varied substantially across age groups (65.9% of total variation explained), countries (20.9%), and between districts within each country (11.3%), but changed little over time (0.9%). Prioritisation based on behavioural risk, in combination with location- and age-based prioritisation, reduced the proportion of population required to be reached in order to find half of all expected new infections from 19.4% to 10.6%.

The tool is intended to facilitate HIV prevention program planning, partner coordination and resource allocation. Output tables and visualizations populate automatically making it easier for national programmatic teams to focus on what the numbers mean, rather than how they can be calculated.

UNAIDS, with support from Global Fund, gathered feedback on the approach and the tool, through webinars and virtual trainings, from a diverse audience of national government HIV prevention teams, UNAIDS Strategic advisors and other partners – this supports with updating the tool.  Additionally, a small group of countries received virtual and/or in-country technical support to use the estimates to select priority settings and populations and/or to set targets to include in their Global Fund applications. They were Angola, Mozambique, Kenya, Cameroon and the Central African Republic. 

Recognizing that interpreting the outputs may need some guidance, a user guide was developed to support all people interested in using the tool to understand how to use it, especially for people who are not comfortable with the data. 

UNAIDS plans to update the tool every year with the latest Naomi estimates and behavioural survey data available from the countries.