Correlations Between COVID-19 Cases and Google Trends Data in the United States: A State-by-State Analysis

Abstract

BACKGROUND Since January 2020, Coronavirus (COVID-19) cases have risen exponentially in the United States. Accurate data on COVID-19 cases has been difficult to report due to lack of testing as well as the overload of the U.S. healthcare system. This study aims to evaluate whether a digital surveillance model using Google Trends is feasible, and whether accurate predictions can be made regarding new cases. METHODS Data on total and daily new cases in each U.S. state was collected and used in this study from late January to early April. Information regarding ten keywords was collected and correlation analyses were performed for individual states as well as for the United States overall. RESULTS Ten keywords were analyzed from Google Trends. “Face mask”, “Lysol”, and “COVID stimulus check” had the strongest correlations when looking at the United States as a whole, with R values of 0.88, 0.82 and 0.79 respectively. Lag and lead Pearson correlations were assessed for every state and all ten keywords from 16 days before the first case in each state to 16 days after the first case. Strong correlations were seen up to 16 days prior to the first reported cases in some states. CONCLUSION This study demonstrates the feasibility of syndromic surveillance of internet search terms to monitor new infectious diseases such as COVID-19. This information could enable better preparation and planning of healthcare systems.

Google search volume trends for cancer screening terms during the COVID-19 pandemic

“…Internet search volume can be viewed as a measure of public interest in medical topics such as screening. Although other studies have found an increase in internet search volumes for certain health topics related to COVID-19, predominantly reflecting acute symptoms, 6 we found a significant decrease in searches for common cancer screening procedures during the first peak of the pandemic. This decrease in search volume for cancer screening terms might be explained by the postponement of elective visits during the first pandemic peak, as searches ordinarily might be initiated by discussions with providers or prompted by upcoming screenings.…”

Exploring the use of web searches for risk communication during COVID-19 in Germany

“…Numerous studies have shown how analysing web search queries can assist in describing and predicting outbreaks especially in the context of sparse data 19 – 21 . This approach has also been used for COVID-19 already 22 , 23 . However, web searches have also been analysed to describe public attention in relation to a public health issue.…”

Using Google Health Trends to investigate COVID-19 incidence in Africa

“…According to our results, surveillance for an ongoing epidemic via GHT might be useful in very specific situations. Google instruments to recover population search counts—GT and GHT—are powerful digital epidemiology tools that can lead to greater insight into disease dynamics, and should be studied and implemented depending on the particular context of an outbreak (Kurian et al, 2020; Nuti et al, 2014; Pelat et al, 2009; Romero-Alvarez et al, 2020; Samaras et al, 2020; Valdivia and Monge-Corella, 2010). Future directions to examine GHT on COVID-19 research include expansion of our analysis to a larger dataset both in time and space.…”

“…Digital tools have been used in many instances to predict disease incidence (Althouse et al, 2011; Xu et al, 2020; Zhang et al, 2017) including COVID-19. Kurian et al, 2020, evaluated the applicability of Google Trends (GT) in predicting COVID-19 cases in the United States (U.S.) in a state-by-state analysis. They found that certain keywords had a strong correlation with COVID-19 cases and concluded that GT may be a useful tool for predicting COVID-19 outbreaks.…”