Web-based big data analytics provides a great opportunity to measure public interest in cardiac arrest (CA) and cardiopulmonary resuscitation (CPR). This study aimed to examine associations of online interest in CPR and CA with epidemiological characteristics of out-of-hospital CA (OHCA) and national socioeconomic indicators in a set of European countries.

Country-level online search popularity data for CPR and CA topics measured in relative search volume (RSV) with Google Trends (GT), published OHCA epidemiological indicators, and World Bank’s socioeconomic statistics of 28 European countries for the year 2017 were analyzed for correlation using Spearman’s rank correlation coefficient (r S ).

Whereas OHCA incidence, bystander CPR rate, and hospital survival did not correlate with RSV for CPR or CA, the rate of return of spontaneous circulation (ROSC) demonstrated a positive correlation with RSV for CPR (r S = 0.388; P = .042). Further, RSV for CPR positively correlated with countries’ gross domestic product and health expenditure (r S = 0.939 and 0.566; P ≤.002) and negatively correlated with mortality caused by road traffic injury (r S = –0.412; P = .029).

For the sample of European countries, public interest in CPR or CA showed no relationship with real bystander CPR rates and therefore could not be recommended as a proxy of community readiness to attempt resuscitation. The association of RSV for CPR with the rate of ROSC and countries’ socioeconomic characteristics suggests it could be used for identifying geographies with poor performance of prehospital systems in terms of managing CA, in particular where effective epidemiological surveillance for CA may be unavailable.

Digital surveillance has shown mixed results as a supplement to traditional surveillance. Google Trends™ (GT) (Google, Mountain View, CA, United States) has been used for digital surveillance of H1N1, Ebola and MERS. We used GT to correlate the information seeking on COVID-19 with number of tests and cases in India.

Data was obtained on daily tests and cases from WHO, ECDC and covid19india.org. We used a comprehensive search strategy to retrieve GT data on COVID-19 related information-seeking behavior in India between January 1 and May 31, 2020 in the form of relative search volume (RSV). We also used time-lag correlation analysis to assess the temporal relationships between RSV and daily new COVID-19 cases and tests.

GT RSV showed high time-lag correlation with both daily reported tests and cases for the terms “COVID 19,” “COVID,” “social distancing,” “soap,” and “lockdown” at the national level. In 5 high-burden states, high correlation was observed for these 5 terms along with “Corona.” Peaks in RSV, both at the national level and in high-burden states corresponded with media coverage or government declarations on the ongoing pandemic.

The correlation observed between GT data and COVID-19 tests/cases in India may be either due to media-coverage-induced curiosity, or health-seeking curiosity.