Using Machine Learning to Direct Limited HIV Programme Resources to Communities with the Greatest Need

Machine learning can help direct limited HIV programme resources to communities with the greatest need by identifying relationships within data. This is particularly useful in HIV programmes where resources are often limited. A data-driven approach asks where an additional unit of resources will make the greatest difference. Engineers can use community-level variables such as HIV testing coverage, ART coverage, and treatment retention to inform their decisions. This approach can help optimize resource distribution and improve programme outcomes.