Incidence of Online Health Information Search: A Useful Proxy for Public Health Risk Perception

Background Internet users use search engines to look for information online, including health information. Researchers in medical informatics have found a high correlation of the occurrence of certain search queries and the incidence of certain diseases. Consumers’ search for information about diseases is related to current health status with regard to a disease and to the social environments that shape the public’s attitudes and behaviors. Objective This study aimed to investigate the extent to which public health risk perception as demonstrated by online information searches related to a health risk can be explained by the incidence of the health risk and social components of a specific population’s environment. Using an ecological perspective, we suggest that a population’s general concern for a health risk is formed by the incidence of the risk and social (eg, media attention) factors related with the risk. Methods We constructed a dataset that included state-level data from 32 states on the incidence of the flu; a number of social factors, such as media attention to the flu; private resources, such as education and health insurance coverage; public resources, such as hospital beds and primary physicians; and utilization of these resources, including inpatient days and outpatient visits. We then explored whether online information searches about the flu (seasonal and pandemic flu) can be predicted using these variables. We used factor analysis to construct indexes for sets of social factors (private resources, public resources). We then applied panel data multiple regression analysis to exploit both time-series and cross-sectional variation in the data over a 7-year period. Results Overall, the results provide evidence that the main effects of independent variables—the incidence of the flu ( P <.001); social factors, including media attention ( P <.001); private resources, including life quality ( P <.001) and health lifestyles ( P =.009); and public resources, such as hospital care utilization ( P =.008) and public health funds ( P =.02)—have significant effects on Web searches for queries related to the flu. After controlling for the number of reported disease cases and Internet access rate by state, we estimate the contribution of social factors to the public health risk perception levels by state ( R 2 =23.37%). The interaction effects between flu incidence and social factors for our search terms did not add to the explanatory power of our regression models ( R 2 <1%). Conclusions Our study suggests a practical way to measure the public’s health risk perception for certain diseases using online information search volume by state. The social environment influences public risk perception regardless of disease incidence. Thus, monitoring the social variables can be very helpful in being ready to respond to the public’s behavior in dealing with public health threats.