Using PEPFAR's Operational Analytics for Equity, Governance, and Real-Time Decision-Making: From HIV Monitoring Dashboards to Community Health Surveillance

The growing popularity of dashboards within the domain of the public health systems has not only changed the way global health is being tracked, but the example of the United States President Emergency Population Relief Program (PEPFAR) stands out as one of such prominent. PEPFAR successfully built high-frequency reporting, anomaly detection, and equity surveillance functions in the originally version of their real-time dashboards planned to manage HIV/AIDS. With the use of these tools, it is possible to respond quickly to the arisen health crisis, so the effective distribution of funds occurs. The experiences of PEPFAR in monitoring of the HIV program can also be an example in increasing the scope of surveillance activities to community related activities such as non-communicable diseases, material health, and disaster management in pandemics.

One of the most important transitions in this change is the adaptation of methods, such as Extraction, Transformation, and Loading (ETL) processes, Bayesian hierarchical modeling, and machine learning, to utilize variety of health data. Through such techniques, such health systems have an opportunity to enhance their decision-making processes by using real-time data analytics to make sure that indicators of health equity and social justice are handled as immediate as possible. Specifically, data disaggregation based on the factors like geography, gender, and socio-economic status enables the identification of health disparities, which could be further taken into action to enhance service provision in underserved populations.

Similar challenges remain such as threat of data overload, poor consistency in data quality and need to ensure a sustainable funding module to sustain such systems. Furthermore, the issue of privacy protection and openness and accountability in using data need to be critical. Nonetheless, there is a possibility of linking the PEPFAR dashboard model to larger community health surveillance in order to impact more positively health outcomes in the world since thoughtful, data-driven decision-making would become feasible.