Triggering interventions for influenza: the ALERT algorithm.

Area of Science:

• Epidemiology
• Public Health
• Infectious Disease Surveillance

Background:

• Timely identification of influenza season onset is crucial for effective public health interventions.
• Developing a reliable tool is needed to help practitioners define community-level influenza epidemic periods.
• Existing methods may lack the precision required for targeted control efforts.

Purpose of the Study:

• To develop and validate a novel algorithm for predicting the onset of seasonal influenza epidemics.
• To provide a tool for public health practitioners, researchers, and clinicians.
• To enhance the definition of community-level influenza activity.

Main Methods:

• The Above Local Elevated Respiratory Illness Threshold (ALERT) algorithm was developed using surveillance data.
• Data included weekly counts of laboratory-confirmed influenza A virus cases from two large hospitals serving Baltimore, MD, and Denver, CO.
• The algorithm identifies periods of highest seasonal influenza activity.

Main Results:

• The ALERT algorithm was prospectively applied to the 2011-2012 and 2012-2013 influenza seasons.
• Thresholds designed to capture 90% of cases were used.
• 71%-91% of all reported influenza cases were identified within the ALERT-defined period.

Conclusions:

• The ALERT algorithm offers a simple, robust, and accurate method for determining elevated influenza activity.
• This metric aids in defining the onset of community-level influenza epidemics.
• Findings can inform infection prevention, public health strategies, and healthcare delivery.