Use of Google Trends as a Novel Epidemiological Tool

Abstract

Introduction Heart Failure (HF) is an important healthcare issue with wide ranging impacts. Traditional census and epidemiological tools do not adequately address the need for dynamic quantification of disease burden. Analysis of Google search data using Google Trends (GT) can offer dynamic digital insight into epidemiology of heart disease. Hypothesis GT data for HF mirror the trends of HF mortality across the country. It can also be used to detect the efficacy of public outreach program such as Heart Failure Awareness Week (HFAW) in capturing public interest and raising awareness about the disease. Methods GT data (reported as Search Volume Index [SVI]) from 2005-2018 for HF were obtained from Google Trends website. HF age adjusted mortality rates (AAMR) data were obtained from CDC wonder website. JoinPoint regression model was used to analyze temporal trends in HF mortality from 2005-2018. Quadratic regression model was used to analyze association between HF mortality and GT data. One way ANOVA test followed by Tukey post hoc test was used to find differences between monthly GT data. Results Heart failure AAMR decreased significantly during 2005-2011 at an annual percentage change of -2.52 (95%CI: -3.85- -1.17). AAMR increased significantly during the next period 2011-2016 at an APC of 3.51 (95%CI: 2.49 - 4.54). (Figure 1a) These trends had strong positive correlation with the GT data for HF (R = 0.875, p Conclusions GT data mirror the national trends of HF mortality. Google searches for HF were significantly higher in states that had higher HF mortality. GT data can also be used to assess the efficacy of public outreach program such as HFAW. Thus, it can be concurred that GT is an effective and indispensable epidemiological tool that is not currently being used to its potential.