Evidence from internet search data shows information-seeking responses to news of local COVID-19 cases

Abstract

The COVID-19 outbreak is a global pandemic with community circulation in many countries, including the United States, with confirmed cases in all states. The course of this pandemic will be shaped by how governments enact timely policies and disseminate information and by how the public reacts to policies and information. Here, we examine information-seeking responses to the first COVID-19 case public announcement in a state. Using an event study framework for all US states, we show that such news increases collective attention to the crisis right away. However, the elevated level of attention is short-lived, even though the initial announcements are followed by increasingly strong policy measures. Specifically, searches for "coronavirus" increased by about 36% (95% CI: 27 to 44%) on the day immediately after the first case announcement but decreased back to the baseline level in less than a week or two. We find that people respond to the first report of COVID-19 in their state by immediately seeking information about COVID-19, as measured by searches for coronavirus, coronavirus symptoms, and hand sanitizer. On the other hand, searches for information regarding community-level policies (e.g., quarantine, school closures, testing) or personal health strategies (e.g., masks, grocery delivery, over-the-counter medications) do not appear to be immediately triggered by first reports. These results are representative of the study period being relatively early in the epidemic, and more-elaborate policy responses were not yet part of the public discourse. Further analysis should track evolving patterns of responses to subsequent flows of public information.

Keywords: COVID-19; Google Trends; information.

Fig. 1.

Time-varying effects of announcements of the first COVID-19 case in a state on searches for coronavirus. The period prior to the treatment (first confirmed case) is set as a reference: gray vertical bar. In red are the estimated coefficients (95% CI, gray band) in the Poisson model (differences in log-expected counts of search relative to the period prior to the event). The average search frequency of this term is 97,023.9 per state per day.

Fig. 2.

Time-varying effects of announcements of the first COVID-19 case in a state on searches for 1) symptoms and treatments (red), 2) hand sanitizer and diagnostic tests (green), 3) coordinated responses (orange), and 4) narratives that undermine public responses (blue). Point estimated coefficients are the dotted lines (95% CI, gray band) in the Poisson models (differences in log-expected counts of search relative to the period prior to the event). Average search frequency per state per day for the terms: coronavirus symptoms (8,522.6), coronavirus treatment (448.2), hand sanitizer (3,214.7), testing near me (381.6), quarantine (2,158.2), isolation (631.2), coronavirus conspiracy (205.1), and coronavirus hoax (123.0).