Validation of syndromic surveillance for respiratory pathogen activity

Area of Science:

• Public Health
• Epidemiology
• Infectious Disease Surveillance

Background:

• Syndromic surveillance systems are increasingly utilized for early detection of unusual illness patterns.
• Validating the data sources used in syndromic surveillance is crucial for accurate interpretation of public health trends.

Purpose of the Study:

• To retrospectively assess how well six different respiratory syndromes reflect actual respiratory pathogen activity.
• To determine the reliability of various data sources for syndromic surveillance of respiratory illnesses.

Main Methods:

• Retrospective analysis of six respiratory syndromes derived from different medical registries.
• Correlation analysis between syndrome data and laboratory counts of key respiratory pathogens (e.g., Streptococcus pneumoniae, respiratory syncytial virus, influenza virus).
• Multiple linear regression models to quantify the proportion of syndrome variation explained by pathogen counts.

Main Results:

• Syndromes exhibited higher levels during winter, correlating with increased pathogen activity.
• Respiratory pathogen counts explained up to 86% of the variation in most studied syndromes.
• Absenteeism and pharmacy syndromes may also indicate non-respiratory conditions.
• A temporal lag was observed, with absenteeism data preceding hospital, pharmacy, and mortality data.
• Unexplained elevations in fall suggested potential rhinovirus activity.

Conclusions:

• The studied respiratory syndromes are valuable for syndromic surveillance, accurately reflecting respiratory pathogen activity.
• Syndromic surveillance data, particularly absenteeism, can provide early signals of respiratory illness outbreaks.
• Further investigation is needed to understand unexplained seasonal variations and the inclusion of non-respiratory conditions in certain data streams.