Flu season is fast approaching. To monitor influenza activity and map trends, public health officials will need to collect and analyze data across a broad population. It is now well understood that tracking and aggregating population-level health data can help improve decisions on public safety, cost, quality, and outcomes of care. While bringing together and analyzing information on a large scale can be very informative, there are privacy risks associated with collecting and processing personal data that is maintained in large centralized databases. To reduce these privacy risks, the Markle Common Framework and the Markle Decision-Making for Population Health “First Principles” emphasize an approach in which detailed personal data remains local with the data holders and is shared based on the core tenets of Fair Information Practice Principles (FIPPs) which, among other things, require that the purpose of the data being shared is specified and only the minimum necessary data is shared. In this distributed approach, whenever possible, de-identified data is shared across a network to answer specific population health questions.
The Distribute (Distributed Surveillance Taskforce for Real-time Influenza Burden Tracking and Evaluation) model for flu surveillance exemplifies these principles. Distribute is a syndromic surveillance project managed by the International Society for Disease Surveillance (ISDS). In contrast to flu surveillance efforts of the past that relied on bringing patient-level information about individual flu cases together in a centralized place, the Distribute model only shares counts of flu aggregated to the public health jurisdiction level. This model proved to be efficient and easy for public health entities to implement. It was adopted by the Centers for Disease Control and Prevention (CDC) to support tracking of the 2009 H1N1 pandemic, and has been influential in helping to demonstrate the feasibility and advantages of a distributed model for this and other population health questions. This and other new data-sharing models are also informing the redesign of the BioSense program by the CDC, and the ONC effort Query Health.
To learn more about the Distribute model and the history of flu surveillance, read a summary of the history and development of the project at the Public Library of Science (PLOS), or visit the Distribute website.
