Google Searches for Taste and Smell Loss Anticipate Covid-19 Epidemiology

Abstract

BackgroundAs evidence emerged that loss of taste and/or loss of smell is frequently triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, we investigated whether Google searches volume for these two disease-specific symptoms could be associated with disease epidemiology in United States (US).Materials and MethodsWe performed an electronic search in Google Trends using the keywords “taste loss” and “smell loss” within the US. The Google searches volume was correlated with the number of new weekly cases of coronavirus disease 2019 (COVID-19) in the country.ResultsThe weekly Google searches for taste and smell loss exhibited a trend similar to that of new weekly SARS-CoV-2 infections in the US. A nearly perfect correlation was found between Google Trends scores of taste and smell loss (r=0.98; 95% CI, 0.97-0.99; p<0.001). Although a significant association was found between Google searches for the two symptoms and the concomitant number of new weekly SARS-CoV-2 infections reported during the same week, the correlation improved over time. The highest correlation was found comparing Google Trends scores for taste or smell loss and the number of new weekly SARS-CoV-2 infections two weeks later. The correlation coefficient of summing Google Trends scores for the two symptoms and the number of new weekly SARS-CoV-2 infections two weeks later was 0.82 (95% CI, 0.68-0.90; p<0.001), and was associated 0.89 diagnostic accuracy.ConclusionsThese findings suggest that Google searches numbers for olfactory and gustatory dysfunctions may help predicting the epidemiological trajectory of COVID-19 early before official reporting.

Utility of Google Trends in anticipating Coronavirus Disease 2019 (COVID-19) outbreaks in Poland

“…While some studies employed less specific symptoms such as fever, dry cough, fatigue, nasal congestion and dyspnea [9], particularly strong correlations have also been illustrated between the more pathognomonic symptoms such as anosmia and dysgeusia and future COVID-19 incidence patterns [5]. Notably, a study by Lippi et al found that this association becomes stronger when correlating Google Trends with COVID-19 cases reported two weeks later, as opposed to cases reported in the same week [6]. Our findings support this, as both smell and taste loss produced the highest cross correlation coefficients in comparison to all non-pathognomonic symptoms, taking into account the time delay required for optimal correlation.…”

“…The value of infodemiological data in Poland is promising, given that 66.7% of the Polish population use the internet for health-related queries [4]. Emerging evidence suggests that the volume of COVID-19 specific Google searches using symptom keywords correlates with the number of actual COVID-19 cases reported [5,6]. COVID-19 infodemiology may be aided by the presence of pathognomonic symptoms, in particular, loss of taste or smell.…”

Clinical Predictors of SARS-CoV-2 Testing Pressure on Clinical Laboratories: A Multinational Study Analyzing Google Trends and Over 100 Million Diagnostic Tests

“…This result contrasts with data previously observed for predicting the number of patients diagnosed weekly with COVID-19 using the same symptom keywords, in which specific symptoms, ie, taste loss and smell loss, were the best predictors. 5 We suspect that this contrast is because nonspecific COVID-19 symptoms can result from numerous other conditions, which may also have seasonal variability, such as the common cold or allergies, all of which are likely to lead individuals to seek SARS-CoV-2 testing.…”

“…As previously shown, tracking the number of weekly Google searches for clinical symptom keywords, in particular the loss of taste and the loss of smell, correlated strongly with the number of weekly cases of patients diagnosed with COVID-19 2 weeks later. 5 However, the demand for laboratory tests may be impacted by many factors other than the number of actual patients with SARS-CoV-2, such as the circulation of common cold viruses, influenza, or even seasonal allergies, all of which can mimic COVID-19 symptoms. As such, in this retrospective, multinational study, we aimed to assess whether the demand for SARS-CoV-2 tests could be accurately predicted by Google searches for key COVID-19 symptoms.…”

Symptomatology associated with the diffusion of the SARS-CoV-2 Lambda variant in Peru: An infodemiologic analysis

“…6 Over the course of the ongoing Coronavirus Disease 2019 (COVID-19) pandemic, we have shown that infodemiology, which utilizes the volume of Google web searches for specific COVID-19 symptoms (i.e. keywords), is effective and reliable for predicting regional epidemiological trends 7,8 and anticipating demand for SARS-CoV-2 testing 9 , assuming that symptomatology (i.e. the set of symptoms characteristic of a medical condition) of any emerging variants in the region remain consistent over time.…”