Temporal and Spatial Comparison of Online Searches and Confirmed Cases of Listeriosis Outbreak: An Exploratory Study of Google Trends in the US

Listeriosis or listeria infection is a rare, serious, and high mortality disease, which is the third leading cause of death from foodborne illness in the US. This disease is characterized by non-specific symptoms with a long incubation period ranging from one to four weeks, as late as 90 days after exposure. Traditional surveillance investigations of listeriosis' clusters and food sources remained limited due to a small number of geographically dispersed case-patients, long incubation period, and difficulties in patients’ recall of food exposures. Therefore, a timely and publicly accessible surveillance tool may allow better food safety advice and education campaigns. People with listeriosis may search online through Google Trends (GT), which appears to be a potential tool web-based for real-time surveillance of outbreaks. The present exploratory study compares the spatiotemporal dynamics of listeriosis searches on GT, in comparison with CDC’s surveillance data at state- and county-level within the state of Texas. The GT’s query volumes of disease terms, pathogen, and symptoms were extracted from 2005 and 2018. Results from spatial and temporal analyses manifest noticeably similar patterns between the search frequency and the actual listeriosis incidence. Time series analysis of the Google Trends showed a lag period of -1 months with the CDC reported data. This study contributed that the Google Trends search data hold a potential role in forecasting emerging rare infectious disease events, especially in resource-constrained areas. The competence to briskly gather and disseminate information about outbreaks is useful for food safety regulators in identifying the food sources and minimizing the contamination.