Risk scores for predicting HIV incidence among the general population in sub-Saharan Africa: a systematic review and meta-analysis
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.
Naomi: A New Modelling Tool for Estimating HIV Epidemic Indicators at the District Level in Sub-Saharan Africa
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.
Evaluating distributional regression strategies for modelling self-reported sexual age-mixing
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.
Age patterns of HIV incidence in eastern and southern Africa
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.
