Utilizing Internet Search Trends and Wastewater Surveillance to Identify Infectious Disease Outbreaks in Communities

Area of Science:

• Environmental microbiology
• Epidemiology
• Digital epidemiology

Background:

• Wastewater surveillance is a key tool for monitoring infectious diseases.
• Traditional clinical data can have reporting delays, limiting timely public health interventions.
• Digital data sources offer potential for rapid, low-cost public health insights.

Purpose of the Study:

• To investigate the utility of Google Trends search data for modeling and predicting wastewater virus concentrations.
• To assess the correlation between Google Trends, wastewater data, and clinical cases for various viral pathogens.
• To develop and validate predictive models for viral outbreaks using Google Trends.

Main Methods:

• Correlational analysis between Google Trends search terms and wastewater viral concentrations.
• Development of three distinct modeling approaches: simple linear, stepwise selection, and principal component analysis.
• Validation of models using a case study of a norovirus outbreak.

Main Results:

• Strong correlations observed between Google Trends and wastewater concentrations for influenza A (R²=0.76) and respiratory syncytial virus (R²=0.66).
• Significant correlations found for norovirus and mpox, even with limited clinical data.
• Predictive models demonstrated strong performance for norovirus (up to R²=0.66) and mpox (up to R²=0.60).

Conclusions:

• Google Trends data provide a valuable, complementary stream for wastewater-based infectious disease surveillance.
• This approach can offer earlier outbreak detection compared to clinical data, especially where clinical infrastructure is limited.
• The method shows promise for rapid, cost-effective public health monitoring, though potential confounding factors require consideration.