Researchers have developed varied methods for forecasting influenza activity using surveillance data with predictive models, but real-world applications in public health programs are rare. To inform consideration of whether and how public health practice should incorporate influenza forecasting, we conducted a systematic review of these methods.

Objective

To assess studies of epidemiological forecasting models for human influenza activity.

Surveillance systems utilizing early indicator of disease activity would be useful for monitoring community disease pattern and facilitating timely decision making on public health interventions in an evidence-based manner. School absenteeism has been previously considered as a possible syndromic approach for monitoring influenza activity.

The Influenza Division (ID) in the Centers for Disease Control and Prevention (CDC) maintains the WHO/NREVSS surveillance system, a network of laboratories in the U.S. that report influenza testing results. This system has seen many changes during the past 40 years, especially since the 2009 H1N1 pandemic. This was due in large part to increased adoption of HL7 messaging via PHLIP. PHLIP data is detailed, standardized influenza testing information, reported in near real-time.