BackgroundWith the internet’s penetration and use constantly expanding, this vast amount of information can be employed in order to better assess issues in the US health care system. Google Trends, a popular tool in big data analytics, has been widely used in the past to examine interest in various medical and health-related topics and has shown great potential in forecastings, predictions, and nowcastings. As empirical relationships between online queries and human behavior have been shown to exist, a new opportunity to explore the behavior toward asthma—a common respiratory disease—is present.ObjectiveThis study aimed at forecasting the online behavior toward asthma and examined the correlations between queries and reported cases in order to explore the possibility of nowcasting asthma prevalence in the United States using online search traffic data.MethodsApplying Holt-Winters exponential smoothing to Google Trends time series from 2004 to 2015 for the term “asthma,” forecasts for online queries at state and national levels are estimated from 2016 to 2020 and validated against available Google query data from January 2016 to June 2017. Correlations among yearly Google queries and between Google queries and reported asthma cases are examined.ResultsOur analysis shows that search queries exhibit seasonality within each year and the relationships between each 2 years’ queries are statistically significant (P<.05). Estimated forecasting models for a 5-year period (2016 through 2020) for Google queries are robust and validated against available data from January 2016 to June 2017. Significant correlations were found between (1) online queries and National Health Interview Survey lifetime asthma (r=–.82, P=.001) and current asthma (r=–.77, P=.004) rates from 2004 to 2015 and (2) between online queries and Behavioral Risk Factor Surveillance System lifetime (r=–.78, P=.003) and current asthma (r=–.79, P=.002) rates from 2004 to 2014. The correlations are negative, but lag analysis to identify the period of response cannot be employed until short-interval data on asthma prevalence are made available.ConclusionsOnline behavior toward asthma can be accurately predicted, and significant correlations between online queries and reported cases exist. This method of forecasting Google queries can be used by health care officials to nowcast asthma prevalence by city, state, or nationally, subject to future availability of daily, weekly, or monthly data on reported cases. This method could therefore be used for improved monitoring and assessment of the needs surrounding the current population of patients with asthma.

Due to the increased interest in micropollutants, this paper aims at quantifying and analyzing the UK online interest in Diclofenac, Estradiol, Azithromycin, Clarithromycin, and Erythromycin, substances included in the EU watchlist for monitoring, in order to examine if the public's online behavior and the use of these substances, in terms of issued prescriptions, are correlated. Using time series data from Google Trends from January 2004 to December 2014, an analysis of these substances in the UK, and in each UK region, i.e., England, Wales, Scotland, and Northern Ireland, is at first performed, followed by an analysis of interest by substance. The results show high interest in Diclofenac with a slight decline, while the Macrolides are significantly less popular though increasing. For Estradiol, the interest is low and declining throughout the examined period, in contrast to the scientific community, where Estradiol is the most studied substance. Prescription items and Google hits are highly correlated in the UK for Diclofenac, Azithromycin, and Clarithromycin, while no correlation is observed for Estradiol. Results from this study indicated that online search traffic data can be valuable in examining the public's online behavior towards the monitored micropollutants, and could assist with the evaluation and forecasting of their concentrations in the waste, surface, and ground water in the UK.

Table A1 consists of the States by declining interest in the term 'Asthma' from 2004 to 2015, Table A2 consists of the normalized values for the online interest by State for each year from 2004 to 2015, and Tables A3 and A4 present the smoothing parameters and coefficients for the Holt-Winters forecasting by State, respectively.