A major advance in HIV prevention: A large-scale community health initiative in Kenya and Uganda has dramatically reduced new HIV infections by delivering testing, prevention, and treatment services directly within communities.
This innovative approach simplifies delivery of prevention medication and strengthens connections to care, helping reduce new HIV infections by about 70% compared to traditional clinic-based services.
Maya Petersen, Co-Principal Investigator of the project, and Laura Balzer both of the Center for Targeted Machine Learning and Causal Inference contributing to the study’s design, implementation, and advanced statistical analysis.
Their work exemplifies how rigorous causal inference and data-driven methods can directly inform scalable, community-centered public health strategies with measurable population-level impact.
Read the full Science article here:
https://www.science.org/content/article/community