Seasonal trends in tinnitus symptomatology: evidence from Internet search engine query data

Meteorological extremes and their impact on tinnitus-related emergency room visits: a time-series analysis

PURPOSE

Extreme weather events are rising due to the accelerating pace of climate change. These events impact human health and increase emergency room visits (EV) for many morbidities. Tinnitus is a common cause of EVs within otolaryngology in Germany and Austria. The effect of extreme weather conditions on tinnitus-related EVs is unknown.

METHODS

A total of 526 tinnitus-related EVs at a tertiary care hospital in Vienna were identified. A distributed lag non-linear model with a maximum lag period of 14 days was fitted to investigate the immediate and delayed effect of single-day and prolonged (three-day) extreme atmospheric pressure, relative humidity, mean temperature, precipitation and mean wind speed on EV rates. Extreme conditions were defined as the 1st, 5th, 95th, and 99th percentile of the meteorological variables. Relative risk (RR) is defined as risk for tinnitus-related EVs at an extreme condition compared to the risk at the median weather condition. Cumulative RR (cRR) is the total cumulated EV risk for a given time period.

RESULTS

High relative humidity increased same-day RR for tinnitus-related EVs to 1.75. Both low and high atmospheric pressure raised cRR as early as three days after an event to a maximum of 3.24. Low temperatures mitigated cRR within 4 days, while high temperatures tended to increase risk. Prolonged precipitation reduced cRR within one day.

CONCLUSION

Extreme meteorological conditions are associated with tinnitus-related EV rates. Further investigation into potential causative links and underlying pathophysiological mechanisms is warranted.

Characterizing the most Popular Tinnitus Inquiries: Is Tinnitus Incidence on the Rise Since COVID-19?

OBJECTIVE

Approximately 50 million US adults experience chronic tinnitus, yet search behaviors and topics of concern to these patients have not been investigated on a national level.

STUDY DESIGN

Observational.

SETTING

Online database and tertiary otology clinic.

PATIENTS

Nationwide and institutional samples.

INTERVENTIONS

None.

MAIN OUTCOME MEASURE

A search engine optimization tool was utilized to extract metadata on "People Also Ask" (PAA) questions pertaining to tinnitus. Website quality was assessed using JAMA benchmark criteria. Search volume trends were investigated along with institutional-level data on tinnitus incidence.

RESULTS

Of the 500 PAA questions assessed, the majority (54.0%) contained value-type content. The most popular question categories pertained to tinnitus treatment (29.3%), alternative treatment approaches (21.5%), technical details (16.9%), and timeline of symptoms (13.4%). Patients were most interested in treatment with wearable masking devices and most commonly searched for tinnitus as being attributable to a neurologic etiology. Online searches pertaining to unilateral tinnitus symptoms have increased >3-fold since the onset of the COVID-19 pandemic. Likewise, review of patient encounters at our tertiary otology clinic revealed a nearly 2-fold increase in tinnitus consultations since 2020.

CONCLUSIONS

Topics of interest and concern identified herein may inform the development of patient education materials and help guide clinical practice. Online search data suggest an increase in tinnitus searches since the onset of COVID-19, which did correlate clinically with an increase in tinnitus consultations at our institution.

Real-Time Monitoring of Infectious Disease Outbreaks with a Combination of Google Trends Search Results and the Moving Epidemic Method: A Respiratory Syncytial Virus Case Study

The COVID-19 pandemic has disrupted the seasonal patterns of several infectious diseases. Understanding when and where an outbreak may occur is vital for public health planning and response. We usually rely on well-functioning surveillance systems to monitor epidemic outbreaks. However, not all countries have a well-functioning surveillance system in place, or at least not for the pathogen in question. We utilized Google Trends search results for RSV-related keywords to identify outbreaks. We evaluated the strength of the Pearson correlation coefficient between clinical surveillance data and online search data and applied the Moving Epidemic Method (MEM) to identify country-specific epidemic thresholds. Additionally, we established pseudo-RSV surveillance systems, enabling internal stakeholders to obtain insights on the speed and risk of any emerging RSV outbreaks in countries with imprecise disease surveillance systems but with Google Trends data. Strong correlations between RSV clinical surveillance data and Google Trends search results from several countries were observed. In monitoring an upcoming RSV outbreak with MEM, data collected from both systems yielded similar estimates of country-specific epidemic thresholds, starting time, and duration. We demonstrate in this study the potential of monitoring disease outbreaks in real time and complement classical disease surveillance systems by leveraging online search data.

Is Idiopathic Sudden Sensorineural Hearing Loss Seasonal?

OBJECTIVE

To investigate the circannual rhythm (seasonal incidence) of idiopathic sudden sensorineural hearing loss (ISSNHL).

METHODS

Data were retrieved from the medical files of an original cohort of all consecutive patients with ISSNHL in a tertiary medical center between 2012 and 2020. A systematic literature search of "MEDLINE" via "PubMed," "Embase," and "Web of Science" on comparable published cases was performed. A Google Trends analysis of the term [sudden hearing loss] and related terms between 2014 and 2020 was also performed.

RESULTS

Most of the published series (9/12) reported the highest ISSNHL incidence in the spring and the lowest in the winter (8/12). In our local series, the incidence during the winter was significantly lower than that for the other seasons by a factor of 0.69 (95% confidence interval, 0.65-0.77; p = 0.041; r = 0.36). Google Trends data showed no significant correlation between the calendric month and the incidence of ISSNHL in any of the analyzed countries ( p = 0.873, r2 = 0.029).

CONCLUSION

The ISSNHL incidence was lowest during the winter season in our cohort and reported for other cohorts worldwide. Google Trends-based model analysis did not determine any circannual rhythm.

Global Prevalence and Incidence of Tinnitus: A Systematic Review and Meta-analysis

Importance

To date, no systematic review has taken a meta-analytic approach to estimating the prevalence and incidence of tinnitus in the general population.

Objective

To provide frequency estimates of tinnitus worldwide.

Data Sources

An umbrella review followed by a traditional systematic review was performed by searching PubMed-MEDLINE and Embase from inception through November 19, 2021.

Study Selection

Research data from the general population were selected, and studies based on patients or on subgroups of the population with selected lifestyle habits were excluded. No restrictions were applied according to date, age, sex, and country.

Data Extraction and Synthesis

Relevant extracted information included type of study, time and location, end point, population characteristics, and tinnitus definition. The study followed the Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guideline.

Main Outcomes and Measures

Pooled prevalence estimates of any tinnitus, severe tinnitus, chronic tinnitus, and diagnosed tinnitus as well as incidence of tinnitus were obtained using random-effects meta-analytic models; heterogeneity between studies was controlled using the χ2 test, and inconsistency was measured using the I2 statistic.

Results

Among 767 publications, 113 eligible articles published between 1972 and 2021 were identified, and prevalence estimates from 83 articles and incidence estimates from 12 articles were extracted. The pooled prevalence of any tinnitus among adults was 14.4% (95% CI, 12.6%-16.5%) and ranged from 4.1% (95% CI, 3.7%-4.4%) to 37.2% (95% CI, 34.6%-39.9%). Prevalence estimates did not significantly differ by sex (14.1% [95% CI, 11.6%-17.0%] among male individuals; 13.1% [95% CI, 10.5%-16.2%] among female individuals), but increased prevalence was associated with age (9.7% [95% CI, 7.4%-12.5%] among adults aged 18-44 years; 13.7% [95% CI, 11.0%-17.0%] among those aged 45-64 years; and 23.6% [95% CI, 19.4%-28.5%] among those aged ≥65 years; P < .001 among age groups). The pooled prevalence of severe tinnitus was 2.3% (95% CI, 1.7%-3.1%), ranging from 0.5% (95% CI, 0.3%-0.7%) to 12.6% (95% CI, 11.1%-14.1%). The pooled prevalence of chronic tinnitus was 9.8% (95% CI, 4.7%-19.3%) and the pooled prevalence of diagnosed tinnitus was 3.4% (95% CI, 2.1%-5.5%). The pooled incidence rate of any tinnitus was 1164 per 100 000 person-years (95% CI, 479-2828 per 100 000 person-years).

Conclusions and Relevance

Despite the substantial heterogeneity among studies, this comprehensive systematic review on the prevalence and incidence of tinnitus suggests that tinnitus affects more than 740 million adults globally and is perceived as a major problem by more than 120 million people, mostly aged 65 years or older. Health policy makers should consider the global burden of tinnitus, and greater effort should be devoted to boost research on tinnitus.

Prediction of Tinnitus Perception Based on Daily Life MHealth Data Using Country Origin and Season

Tinnitus is an auditory phantom perception without external sound stimuli. This chronic perception can severely affect quality of life. Because tinnitus symptoms are highly heterogeneous, multimodal data analyses are increasingly used to gain new insights. MHealth data sources, with their particular focus on country- and season-specific differences, can provide a promising avenue for new insights. Therefore, we examined data from the TrackYourTinnitus (TYT) mHealth platform to create symptom profiles of TYT users. We used gradient boosting engines to classify momentary tinnitus and regress tinnitus loudness, using country of origin and season as features. At the daily assessment level, tinnitus loudness can be regressed with a mean absolute error rate of 7.9% points. In turn, momentary tinnitus can be classified with an F1 score of 93.79%. Both results indicate differences in the tinnitus of TYT users with respect to season and country of origin. The significance of the features was evaluated using statistical and explainable machine learning methods. It was further shown that tinnitus varies with temperature in certain countries. The results presented show that season and country of origin appear to be valuable features when combined with longitudinal mHealth data at the level of daily assessment.

Biannual Differences in Interest Peaks for Web Inquiries Into Ear Pain and Ear Drops: Infodemiology Study

Background

The data retrieved with the online search engine, Google Trends, can summarize internet inquiries into specified search terms. This engine may be used for analyzing inquiry peaks for different medical conditions and symptoms.

Objective

The aim of this study was to analyze World Wide Web interest peaks for “ear pain,” “ear infection,” and “ear drops.”

Methods

We used Google Trends to assess the public online interest for search terms “ear pain,” “ear infection,” and “ear drops” in 5 English and non–English-speaking countries from both hemispheres based on time series data. We performed our analysis for the time frame between January 1, 2004, and December 31, 2019. First, we assessed whether our search terms were most relevant to the topics of ear pain, ear infection, and ear drops. We then tested the reliability of Google Trends time series data using the intraclass correlation coefficient. In a second step, we computed univariate time series plots to depict peaks in web-based interest. In the last step, we used the cosinor analysis to test the statistical significance of seasonal interest peaks.

Results

In the first part of the study, it was revealed that “ear infection,” “ear pain,” and “ear drops” were the most relevant search terms in the noted time frame. Next, the intraclass correlation analysis showed a moderate to excellent reliability for all 5 countries’ 3 primary search terms. The subsequent analysis revealed winter interest peaks for “ear infection” and “ear pain”. On the other hand, the World Wide Web search for “ear drops” peaked annually during the summer months. All peaks were statistically significant as revealed by the cosinor model (all P values <.001).

Conclusions

It can be concluded that individuals affected by otitis media or externa, possibly the majority, look for medical information online. Therefore, there is a need for accurate and easily accessible information on these conditions in the World Wide Web, particularly on differentiating signs and therapy options. Meeting this need may facilitate timely diagnosis, proper therapy, and eventual circumvention of potentially life-threatening complications.

Peaks in online inquiries into pharyngitis-related symptoms correspond with annual incidence rates

OBJECTIVE

To assess whether web-based public inquiries into pharyngitis-related search terms follow annual incidence peaks of acute pharyngitis in various countries from both hemispheres.

METHODS

Google Trends (GT) was utilized for systematic acquisition of pharyngitis-related search terms (sore throat, cough, fever, cold). Six countries from both hemispheres including four English (United Kingdom, United States, Canada, and Australia) and two non-English speaking countries (Austria and Germany) were selected for further analysis. Time series data on relative search interest for pharyngitis-related search terms, covering a timeframe between 2004 and 2019 were extracted. Following reliability analysis using the intra-class correlation coefficient, the cosinor time series analysis was utilized to determine annual peaks in public-inquiries.

RESULTS

The extracted datasets of GT proved to be highly reliable with correlation coefficients ranging from 0.83 to 1.0. Graphical visualization showed annual seasonal peaks for pharyngitis-related search terms in all included countries. The cosinor time series analysis revealed these peaks to be statistically significant during winter months (all p < 0.001).

CONCLUSION

Our study revealed seasonal variations for pharyngitis-related terms which corresponded to winter incidence peaks of acute pharyngitis. These results highlight the need for easily accessible information on diagnosis, therapy, and red-flag symptoms for this common disease. Accurately informed patients might contribute to a reduction of unnecessary clinic visits and potentially cutback the futile antibiotic overuse.

The association between COVID-19 cases and deaths and web-based public inquiries

BACKGROUND

Corona Virus Disease 2019 (COVID-19) emerged in December 2019 and rapidly spread globally. Since there is still no specific treatment available, prevention of disease spread is crucial to manage the pandemic. Adequate public information is very important. To assess the optimal timing, the aim of this study was to investigate the association between web-based interest and new cases and deaths due to COVID-19.

METHODS

Web-based interest for queries related to 'coronavirus' was assessed between 1 January and 19 June 2020, using Google Trends in Australia, Brazil, Canada, Germany, Italy, South Africa, South Korea, Spain, United Kingdom, and the United States of America. Reliability analysis of the used search terms was performed using the intraclass correlation coefficient. To investigate the association between web-based interest and new COVID-19 cases or deaths, the relative search volume was analysed for correlation with new cases and deaths.

RESULTS

Reliability analysis revealed excellent reliability for COVID-19 search terms in all countries. Web-based interest peaked between 23 February and 5 April 2020, which was prior to the peak of new infections and deaths in most included countries. There was a moderate to strong correlation between COVID-19 related queries and new cases or new deaths.

CONCLUSION

Web-based interest in COVID-19 peaked prior to the peak of new infections and deaths in most countries included. Thus, monitoring public interest via Google Trends might be useful to select the optimal-timing of web-based disease-specific information and preventive measures.

Winter peaks in web-based public inquiry into epistaxis

PURPOSE

Epistaxis represents the most frequent ear, nose, throat-related emergency symptom. Seasonal variation in epistaxis incidence, with peaks during winter months, is widely accepted, although the literature itself remains inconclusive. The objective of this study was to evaluate public inquiry into nose bleeding, by considering Google-based search query frequency on "Epistaxis"-related search terms and to assess possible seasonal variations globally.

METHODS

Epistaxis-related search terms were systematically collected and compared using Google Trends (GT). Relative search volumes for the most relevant epistaxis-related terms, covering a timeframe from 2004 to 2019 were analysed using cosinor time series analysis for the United States of America, Germany, the United Kingdom, Italy, Canada, Australia, and New Zealand.

RESULTS

Graphical representation revealed seasonal variations with peaks during winter months in the majority of countries included. Subsequent cosinor analysis revealed these variations to be significant (all p < 0.001).

CONCLUSION

Public interest in seeking epistaxis-related information through the Internet displayed seasonal patterns in countries from both hemispheres, with the highest interest during winter months. Further studies exploring causality with environmental factors are warranted.

Epidemiology of Clinically Significant Tinnitus: A 10-Year Trend From Nationwide Health Claims Data in South Korea

OBJECTIVES

Prevalence of tinnitus has been reported to vary according to the target population and definition of tinnitus. To improve the understanding of tinnitus, authors used the nation-wide health claim data to study the tinnitus in the entire population of South Korea.

STUDY DESIGN

Retrospective big data review.

SETTING

Analysis of big data from the National Health Information Database.

PATIENTS

Patients diagnosed with tinnitus according to International Classification of Diseases code 10th edition (ICD-10) and requested to receive National Health Insurance claim at least once from January 2006 to December 2015.

INTERVENTION

None.

MAIN OUTCOME MEASURE

Epidemiologic data, association of tinnitus with the otologic and systemic diseases.

RESULTS

The number of patients who received medical care because of tinnitus was 1.44% (0.78 million per 51 million) in 2015. There was a higher prevalence of tinnitus in women, and the overall prevalence increased with increasing age of patients and peaked at patients in their 70s (4.43%). The prevalence of tinnitus among patients aged 10 to 30 years, showed a tendency to increase during study period. In the regional analysis, highest prevalence was observed in Gwangju (2.02%). In comparison with the control group, the patients with tinnitus showed a higher frequency in otologic and systemic disease. Especially, noise induced hearing loss (adjusted odds ratio [AOR] = 82.1, 95% confidence interval [95% CI] = 74.8-90.2) and sudden sensorineueal hearing loss (AOR = 49.7, 95% CI = 48.4-51.0) showed high frequency in tinnitus patient group.

CONCLUSIONS

The prevalence and incidence of tinnitus in this study for entire nation were lower than previously reported studies. These results have limitation because the study only covered patient using the medical service for tinnitus and missed tinnitus sufferers not seeking medical service. However, this study is meaningful in that it was targeting entire nation, reflected the characteristics of clinically significant tinnitus patient enough to visit medical service.

Assessing the Methods, Tools, and Statistical Approaches in Google Trends Research: Systematic Review

Background

In the era of information overload, are big data analytics the answer to access and better manage available knowledge? Over the last decade, the use of Web-based data in public health issues, that is, infodemiology, has been proven useful in assessing various aspects of human behavior. Google Trends is the most popular tool to gather such information, and it has been used in several topics up to this point, with health and medicine being the most focused subject. Web-based behavior is monitored and analyzed in order to examine actual human behavior so as to predict, better assess, and even prevent health-related issues that constantly arise in everyday life.

Objective

This systematic review aimed at reporting and further presenting and analyzing the methods, tools, and statistical approaches for Google Trends (infodemiology) studies in health-related topics from 2006 to 2016 to provide an overview of the usefulness of said tool and be a point of reference for future research on the subject.

Methods

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for selecting studies, we searched for the term “Google Trends” in the Scopus and PubMed databases from 2006 to 2016, applying specific criteria for types of publications and topics. A total of 109 published papers were extracted, excluding duplicates and those that did not fall inside the topics of health and medicine or the selected article types. We then further categorized the published papers according to their methodological approach, namely, visualization, seasonality, correlations, forecasting, and modeling.

Results

All the examined papers comprised, by definition, time series analysis, and all but two included data visualization. A total of 23.1% (24/104) studies used Google Trends data for examining seasonality, while 39.4% (41/104) and 32.7% (34/104) of the studies used correlations and modeling, respectively. Only 8.7% (9/104) of the studies used Google Trends data for predictions and forecasting in health-related topics; therefore, it is evident that a gap exists in forecasting using Google Trends data.

Conclusions

The monitoring of online queries can provide insight into human behavior, as this field is significantly and continuously growing and will be proven more than valuable in the future for assessing behavioral changes and providing ground for research using data that could not have been accessed otherwise.

Measuring Global Disease with Wikipedia: Success, Failure, and a Research Agenda

Effective disease monitoring provides a foundation for effective public health systems. This has historically been accomplished with patient contact and bureaucratic aggregation, which tends to be slow and expensive. Recent internet-based approaches promise to be real-time and cheap, with few parameters. However, the question of when and how these approaches work remains open. We addressed this question using Wikipedia access logs and category links. Our experiments, replicable and extensible using our open source code and data, test the effect of semantic article filtering, amount of training data, forecast horizon, and model staleness by comparing across 6 diseases and 4 countries using thousands of individual models. We found that our minimal-configuration, language-agnostic article selection process based on semantic relatedness is effective for improving predictions, and that our approach is relatively insensitive to the amount and age of training data. We also found, in contrast to prior work, very little forecasting value, and we argue that this is consistent with theoretical considerations about the nature of forecasting. These mixed results lead us to propose that the currently observational field of internet-based disease surveillance must pivot to include theoretical models of information flow as well as controlled experiments based on simulations of disease.