NOROVIRUS outbreaks may soon be easier to detect thanks to a novel approach combining Google search trends and wastewater surveillance. A new study has demonstrated how internet search data can be used to model wastewater virus concentrations, providing a rapid, low-cost method for identifying infectious disease outbreaks.
Researchers found strong correlations between Google Trends data and wastewater viral loads for multiple infectious diseases, including influenza A, respiratory syncytial virus (RSV), norovirus, and mpox. For norovirus, a highly contagious gastrointestinal virus, search trends aligned closely with wastewater concentrations, achieving a predictive accuracy (R²) of up to 0.66.
To validate their approach, the researchers examined a documented 2021 norovirus outbreak in Hartford, Conneticut. Their model showed that Google Trends indicators spiked in tandem with rising wastewater virus levels, potentially providing an earlier warning than clinical case reports. This finding highlights the potential for internet search data to serve as an early detection tool, especially in regions with limited clinical testing infrastructure.
Three different predictive models, simple linear regression, stepwise selection, and principal component analysis, were developed to analyze the relationship between search trends and viral concentrations. Despite some limitations, such as the influence of media coverage and regional variations in search behavior, the study suggests that integrating online search patterns with wastewater surveillance could enhance outbreak forecasting and public health response efforts.
This approach offers an innovative complement to traditional surveillance methods, helping healthcare professionals and public health officials anticipate and mitigate infectious disease outbreaks more effectively.
Reference: Zulli A et al. Utilizing Internet Search Trends and Wastewater Surveillance to Identify Infectious Disease Outbreaks in Communities. Environ Sci Technol. 2025;59(7).
Anaya Malik | AMJ
