Mathematical modelling to inform 'treat all' implementation in sub-Saharan Africa: a scoping review

Objective: Despite widespread uptake, only half of sub-Saharan African countries have fully implemented the World Health Organization's 'treat all' policy, hindering achievement of global HIV targets. We examined literature on mathematical modelling studies that sought to inform scale-up and implementation of 'treat all' in sub-Saharan Africa. Methods: We conducted a scoping review, a research synthesis to assess emerging evidence and identify gaps, of peer-reviewed literature, extracting study characteristics on 'treat all' policies and assumptions, setting, key populations, outcomes and findings. Studies were narratively summarised and potential gaps characterised. Results: We identified 16 studies examining 'treat all' alone (n=12) or with expanded testing (n=7) and/or care continuum improvements (n=6). Twelve studies examined 'treat all' for Southern African countries, while none did so for Central Africa. Four included the role of resistance; one evaluated any key population. A range of health and economic outcomes were reported, although fewer studies formally assessed budget impact. Fourteen studies involved co-authors with any in-country affiliation; one study also had co-authors with local government affiliation. Overall, 'treat all' improves health outcomes and is cost-effective compared to deferred HIV treatment; 'treat all' with expanded testing or care continuum improvements may provide further health benefits. However, studies generally used optimistic assumptions about the implementation of expanded testing or care continuum improvements. Conclusions: The modelling literature demonstrates improved health and economic benefits of 'treat all'. Using mathematical modelling to inform real-world implementation of 'treat all' requires realistic assumptions about expanded testing and care continuum interventions across a wide range of settings and populations.