Problem Up to Mac Catalina, by default, installing R packages with OpenMP support (e.g. data.table, TMB) has been compiled without it. For TMB codes, changes such as use parallel_accumulator() or include OpenMP’s headers and library, and add #pragma openmp parallel for before for loop in the likelihood calculation done after installing TMB from CRAN are not relevant – TMB was already compiled with _OPENMP flag undefined.

Younger age, non-cohabiting, and recent STIs were consistently identified as predicting future HIV infection for women in sub-Saharan African settings. Given the heterogeneous context and baseline prevalence, HIV risk scores had only low to moderate discriminatory ability to predict future infection. Further evidence on the importance of specific factors and data outside high-risk study populations will help inform optimal implementation in HIV programmes.

The Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data.

HIV incidence declined in all age groups and shifted slightly, but not dramatically, to older ages. Disproportionate new HIV infections occur among 15-24-year-old women and 20-29-year-old men, supporting focused prevention in these groups. But 40-60% of infections were outside these ages, emphasising the importance of providing appropriate HIV prevention to adults of all ages.

We found that distributional regression with a sinh-arcsinh distribution replicated observed partner age distributions most accurately across three geographically diverse data sets. This framework can be extended with well-known hierarchical modelling tools and can help improve estimates of sexual age-mixing dynamics.