Google unveils a glimpse of allergic rhinitis in the real world

A holistic big data approach to understand and manage increasing pollen-induced respiratory allergies under global change

Nearly a third of the world's population suffers from pollen‐induced respiratory allergies—and the number is rising. For those affected, the situation is becoming more stressful every year with climate change, rising atmospheric CO2 levels, and urbanization. These phenomena form a complex interface between human health and global change, yet the critical information needed to unravel it remains fragmented. A holistic big data approach, with close collaboration between Earth system scientists and health experts, is urgently needed to achieve meaningful insights that advance our understanding and management of increasing pollen‐induced respiratory allergies under global change.

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.

Online public attention toward allergic rhinitis in Wuhan, China: Infodemiology study using Baidu index and meteorological data

Background

With the popularization of the Internet and medical knowledge, more and more people are learning about allergic rhinitis (AR) on the Internet.

Objective

This study aims to analyze the epidemiological characteristics and online public attention to AR in Wuhan, China, utilizing the most popular search engine in mainland China and meteorological data of Wuhan.

Methods

To study the Internet attention and epidemiological characteristics of AR in Wuhan, the search volume (SV) of "Allergic Rhinitis" in Mandarin and AR-related search terms from 1 January 2014 through 31 December 2021 were recorded. For user interest, the search and demand data were collected and analyzed.

Results

The yearly average Baidu SV of AR in both Wuhan and China increased year by year but began to decline gradually after the COVID-19 pandemic. Baidu SV of AR in Wuhan exhibited significant seasonal variation, with the first peak was from March to May and the second peak occurring between September and October. Correlation analysis revealed a moderate positive correlation between the monthly average SV of "Allergic Rhinitis" and "Mites" and "Mites + Pollen Allergy" in Wuhan, a weak positive correlation between the monthly average SV of "Allergic Rhinitis" and "Pollen Allergy," and a positive correlation between monthly SV of "Allergic Rhinitis" and the meteorological index of pollen allergy (MIPA).

Conclusion

The attention given to the topic on the internet, as measured by the search volume, was reflective of the situation in Wuhan, China. It has the potential to predict the epidemiological characteristics of AR and help medical professionals more effectively plan seasonal AR health education.

Usage patterns of oral H1-antihistamines in 10 European countries: A study using MASK-air® and Google Trends real-world data

Real-world data represent an increasingly important source of knowledge in health care. However, assessing their representativeness can be challenging. We compared (i) real-world data from a mobile app for allergic rhinitis (MASK-air®) on the usage of oral H1-antihistamines from 2016 to 2020 in 10 European countries with (ii) Google Trends data on the relative volume of searches for such antihistamines. For each country, we sorted 5 different oral H1-antihistamines by their frequency of use and volume of searches. We found perfect agreement on the order of antihistamine use in MASK-air® and in Google Trends searches in 4 countries (France, Germany, Sweden, and the United Kingdom). Different levels of agreement were observed in the remaining countries (kappa coefficient from −0.50 to 0.75). Oral H1-antihistamine data from Google Trends and MASK-air® were consistent with nationwide medication sales data from France, Germany, and the United Kingdom. These results suggest that MASK-air® data may be consistent with other sources of real-world data, although assessing the representativeness of their users may require further studies.

Scoliosis surgery in social media: a natural language processing approach to analyzing the online patient perspective

PURPOSE

The purpose of this study is to analyze posts shared on Instagram, Twitter, and Reddit referencing scoliosis surgery to evaluate content, tone, and perspective.

METHODS

Public posts from Instagram, Twitter, and Reddit were parsed in 2020-2021 and selected based on inclusion of the words 'scoliosis surgery' or '#scoliosissurgery. 100 Reddit posts, 5022 Instagram posts, and 1414 tweets were included in analysis. The Natural Language Toolkit (NLTK) python library was utilized to perform computational text analysis to determine content and sentiment analysis to estimate the tone of posts across each platform.

RESULTS

46.4% of Tweets were positive in tone, 39.4% were negative, and 13.8% were neutral. Positive content focused on patients, friends, or hospitals sharing good outcomes after a patient's surgery. Negative content focused on long wait times to receive scoliosis surgery. 64.7% of Instagram posts were positive in tone, 16.3% were negative, and 19.0% were neutral. Positive content centered around post-operative progress reports and educational resources, while negative content focused on long-term back pain. 37% of Reddit posts were positive in tone, 38% were negative, and 25% were neutral. Positive posts were about personal post-operative progress reports, while negative posts were about fears prior to scoliosis surgery and questions about risks of the procedure.

CONCLUSION

This study highlights scoliosis surgery content in social media formats and stratifies how this content is portrayed based on the platform it is on. Surgeons can use this knowledge to better educate and connect with their own patients, thus harnessing the power and reach of social media.

LEVEL OF EVIDENCE

IV.

Annual trends in Google searches provides insights related to rhinosinusitis exacerbations

Purpose

Temporal trends of disease-specific internet searches may provide novel insights into seasonal dynamics of disease burden and, by extension, disease pathophysiology. The aim of this study was to define the temporal trends in rhinosinusitis-specific internet searches.

Methods

This was a cross sectional analysis of search volume for predefined search terms. Google trends was used to explore the volume of searches for five specific search terms related to rhinosinusitis: nose, mucus, sinus, sinusitis, chronic sinusitis, which were entered into Google web search between 2004 and 2019. Results were analyzed within search “context” which included temporally associated related searches. Relative search volume (RSV) was analyzed for English and non-English speaking countries from the Northern and Southern hemispheres. Analysis of seasonality was performed using the cosinor model.

Results

The five specific search terms were most related to rhinosinusitis-related search contexts, indicating that they were appropriately reflective of internet queries by patients for rhinosinusitis. The RSV for rhinosinusitis-related terms and more general search terms increased with each passing year indicating constant interest in rhinosinusitis. Cosinor time series analysis revealed inquiry peaks in winter months for all five specific rhinosinusitis-related search terms independent from the hemisphere.

Conclusion

Over a 15-year period, Google searches with rhinosinusitis-specific search terms consistently peaked during the winter around the world. These findings indirectly support the model of viral infection or exposure as the predominant cause of acute rhinosinusitis and acute exacerbations of chronic rhinosinusitis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00405-021-06806-5.

Internet searches offer insight into early-season pollen patterns in observation-free zones

Tracking concentrations of regional airborne pollen is valuable for a variety of fields including plant and animal ecology as well as human health. However, current methods for directly measuring regional pollen concentrations are labor-intensive, requiring special equipment and manual counting by professionals leading to sparse data availability in select locations. Here, we use publicly available Google Trends data to evaluate whether searches for the term "pollen" can be used to approximate local observed early-season pollen concentrations as reported by the National Allergy Bureau across 25 U.S. regions from 2012-2017, in the context of site-specific characteristics. Our findings reveal that two major factors impact the ability of internet search data to approximate observed pollen: (1) volume/availability of internet search data, which is tied to local population size and media use; and (2) signal intensity of the seasonal peak in searches. Notably, in regions and years where internet search data was abundant, we found strong correlations between local search patterns and observed pollen, thus revealing a potential source of daily pollen data across the U.S. where observational pollen data are not reliably available.

A demonstration project of Global Alliance against Chronic Respiratory Diseases: Prediction of interactions between air pollution and allergen exposure-the Mobile Airways Sentinel NetworK-Impact of air POLLution on Asthma and Rhinitis approach

This review analyzes the state and recent progress in the field of information support for pollen allergy sufferers. For decades, information available for the patients and allergologists consisted of pollen counts, which are vital but insufficient. New technology paves the way to substantial increase in amount and diversity of the data. This paper reviews old and newly suggested methods to predict pollen and air pollutant concentrations in the air and proposes an allergy risk concept, which combines the pollen and pollution information and transforms it into a qualitative risk index. This new index is available in an app (Mobile Airways Sentinel NetworK-air) that was developed in the frame of the European Union grant Impact of Air POLLution on sleep, Asthma and Rhinitis (a project of European Institute of Innovation and Technology-Health). On-going transformation of the pollen allergy information support is based on new technological solutions for pollen and air quality monitoring and predictions. The new information-technology and artificial-intelligence-based solutions help to convert this information into easy-to-use services for both medical practitioners and allergy sufferers.

Seasonal Variations in Public Inquiries into Laryngitis: An Infodemiology Study

OBJECTIVES

Acute laryngitis is a common disease with self-limiting nature. Since the leading cause is attributed to viral infections and thus self-limiting, many affected individuals do not seek professional medical help. However, because the major symptom of hoarseness imposes a substantial burden in everyday life, it might be speculated that web-based search interest on this condition follows incidence rates, with highest peaks during winter months. The aim of this study was to evaluate global public health-information seeking behaviour on laryngitis-related search terms.

METHODS

We utilized Google Trends to assess country-specific, representative laryngitis-related search terms for English and non-English speaking countries of both hemispheres. Extracted time series data from Australia, Brazil, Canada, Germany, the United Kingdom, and the United States of America, covering a timeframe between 2004 and 2019 were first assessed for reliability, followed by seasonality analysis using the cosinor model.

RESULTS

Direct comparisons revealed different, representative laryngitis-related search terms for English- and non-English speaking countries. Extracted data showed a trend of higher reliability in countries with more inhabitants. Subsequent graphical analysis revealed winter peaks in all countries from both hemispheres. Cosinor analysis confirmed these seasonal variations to be significant (all P < 0.001).

CONCLUSION

Public interest in laryngitis-related, online health information displayed seasonal variations in countries from both hemispheres, with highest interest during winter months. These findings emphasize the importance to optimize the distribution of reliable, web-based health education in order to prevent the spread of misinformation and to improve health literacy among general populations.

Correlations in Trends of Sinusitis-Related Online Google Search Queries in the United States

BACKGROUND

Online search query trends have been shown to correlate with real-life epidemiologic phenomena.

OBJECTIVE

The aim of this study was to analyze correlations in trends in Google online search volumes of sinusitis-related terms, including symptomatology and similar disease states.

METHODS

Terms clinically associated with "sinusitis" were determined by consensus. Terms of symptomatology were derived from the validated 22-item sinonasal outcome test (SNOT-22) as well as terminology encountered with the authors' clinical experience. Terms of disease states that could overlap in symptomatology with sinusitis were then chosen. Google Trends, an online tool for extracting relative frequencies from a public database of search queries, was used to query normalized monthly volumes in the United States from January 2004 to September 2017 of searches related to the topics decided upon by consensus. Bivariate Pearson correlation was used to compare the search queries.

RESULTS

Online search volumes of "sinusitis" have a distinct seasonal variation, with consistent annual peaks and troughs. In terms of symptomatology, "postnasal drip," "nasal congestion," "cough," "rhinorrhea," and "sore throat" most highly correlated with "sinusitis" search volumes with statistical significance. "sinusitis" search query volume had a higher positive correlation with "common cold" and "acute sinusitis" than "chronic sinusitis" with regard to disease states.

CONCLUSIONS

Trends in Google online search volumes over time of "sinusitis" symptomatology mimic real-world clinical phenomena and provide insight into the issues affecting the general population.

Access to Primary Care and Internet Searches for Walk-In Clinics and Emergency Departments in Canada: Observational Study Using Google Trends and Population Health Survey Data

Background

Access to primary care is a challenge for many Canadians. Models of primary care vary widely among provinces, including arrangements for same-day and after-hours access. Use of walk-in clinics and emergency departments (EDs) may also vary, but data sources that allow comparison are limited.

Objective

We used Google Trends to examine the relative frequency of searches for walk-in clinics and EDs across provinces and over time in Canada. We correlated provincial relative search frequencies from Google Trends with survey responses about primary care access from the Commonwealth Fund’s 2016 International Health Policy Survey of Adults in 11 Countries and the 2016 Canadian Community Health Survey.

Methods

We developed search strategies to capture the range of terms used for walk-in clinics (eg, urgent care clinic and after-hours clinic) and EDs (eg, emergency room) across Canadian provinces. We used Google Trends to determine the frequencies of these terms relative to total search volume within each province from January 2011 to December 2018. We calculated correlation coefficients and 95% CIs between provincial Google Trends relative search frequencies and survey responses.

Results

Relative search frequency of walk-in clinic searches increased steadily, doubling in most provinces between 2011 and 2018. Relative frequency of walk-in clinic searches was highest in the western provinces of British Columbia, Alberta, Saskatchewan, and Manitoba. At the provincial level, higher walk-in clinic relative search frequency was strongly positively correlated with the percentage of survey respondents who reported being able to get same- or next-day appointments to see a doctor or a nurse and inversely correlated with the percentage of respondents who reported going to ED for a condition that they thought could have been treated by providers at usual place of care. Relative search frequency for walk-in clinics was also inversely correlated with the percentage of respondents who reported having a regular medical provider. ED relative search frequencies were more stable over time, and we did not observe statistically significant correlation with survey data.

Conclusions

Higher relative search frequency for walk-in clinics was positively correlated with the ability to get a same- or next-day appointment and inversely correlated with ED use for conditions treatable in the patient’s regular place of care and also with having a regular medical provider. Findings suggest that patient use of Web-based tools to search for more convenient or accessible care through walk-in clinics is increasing over time. Further research is needed to validate Google Trends data with administrative information on service use.

Google Trends and pollen concentrations in allergy and airway diseases in France

BACKGROUND

Google Trends (GTs) is a web-based surveillance tool that explores the searching trends of specific queries via Google. This tool proposes to reflect the real-life epidemiology of allergic rhinitis and asthma. However, the validation of GTs against pollen concentrations is missing at the country level.

OBJECTIVES

In the present study, we used GTs (a) to compare the terms related to allergy in France, (b) to assess seasonal variations across the country for 5 years and (c) to compare GTs and pollen concentrations for 2016.

METHODS

Google Trends queries were initially searched to investigate the terms reflecting pollen and allergic diseases. 13- and 5-year GTs were used in France. Then, 5-year GTs were assessed in all metropolitan French regions to assess the seasonality of GTs. Finally, GTs were compared with pollen concentrations (Réseau National de Surveillance en Aerobiology) for 2016 in seven regions (GTs) and corresponding cities (pollen concentrations).

RESULTS

The combination of searches for "allergy" as a disease, "pollen" as a disease cause and "ragweed" as a plant was needed to fully assess the pollen season in France. "Asthma" did not show any seasonality. Using the 5-year GTs, an annual and clear seasonality of queries was found in all regions depending on the predicted pollen exposure for spring and a summer peak but not for winter peaks. The agreement between GT queries and pollen concentrations is usually poor except for spring trees and grasses. Moreover, cypress pollens are insufficiently reported by GTs.

CONCLUSIONS

Google Trends cannot predict the pollen season in France.

Google Searches and Detection of Conjunctivitis Epidemics Worldwide

PURPOSE

Epidemic and seasonal infectious conjunctivitis outbreaks can impact education, workforce, and economy adversely. Yet conjunctivitis typically is not a reportable disease, potentially delaying mitigating intervention. Our study objective was to determine if conjunctivitis epidemics could be identified using Google Trends search data.

DESIGN

Search data for conjunctivitis-related and control search terms from 5 years and countries worldwide were obtained. Country and term were masked. Temporal scan statistics were applied to identify candidate epidemics. Candidates then were assessed for geotemporal concordance with an a priori defined collection of known reported conjunctivitis outbreaks, as a measure of sensitivity.

PARTICIPANTS

Populations by country that searched Google's search engine using our study terms.

MAIN OUTCOME MEASURES

Percent of known conjunctivitis outbreaks also found in the same country and period by our candidate epidemics, identified from conjunctivitis-related searches.

RESULTS

We identified 135 candidate conjunctivitis epidemic periods from 77 countries. Compared with our a priori defined collection of known reported outbreaks, candidate conjunctivitis epidemics identified 18 of 26 (69% sensitivity) of the reported country-wide or island nationwide outbreaks, or both; 9 of 20 (45% sensitivity) of the reported region or district-wide outbreaks, or both; but far fewer nosocomial and reported smaller outbreaks. Similar overall and individual sensitivity, as well as specificity, were found on a country-level basis. We also found that 83% of our candidate epidemics had start dates before (of those, 20% were more than 12 weeks before) their concurrent reported outbreak's report issuance date. Permutation tests provided evidence that on average, conjunctivitis candidate epidemics occurred geotemporally closer to outbreak reports than chance alone suggests (P < 0.001) unlike control term candidates (P = 0.40).

CONCLUSIONS

Conjunctivitis outbreaks can be detected using temporal scan analysis of Google search data alone, with more than 80% detected before an outbreak report's issuance date, some as early as the reported outbreak's start date. Future approaches using data from smaller regions, social media, and more search terms may improve sensitivity further and cross-validate detected candidates, allowing identification of candidate conjunctivitis epidemics from Internet search data potentially to complementarily benefit traditional reporting and detection systems to improve epidemic awareness.

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.

POLLAR: Impact of air POLLution on Asthma and Rhinitis; a European Institute of Innovation and Technology Health (EIT Health) project

Allergic rhinitis (AR) is impacted by allergens and air pollution but interactions between air pollution, sleep and allergic diseases are insufficiently understood. POLLAR (Impact of air POLLution on sleep, Asthma and Rhinitis) is a project of the European Institute of Innovation and Technology (EIT Health). It will use a freely-existing application for AR monitoring that has been tested in 23 countries (the Allergy Diary, iOS and Android, 17,000 users, TLR8). The Allergy Diary will be combined with a new tool allowing queries on allergen, pollen (TLR2), sleep quality and disorders (TRL2) as well as existing longitudinal and geolocalized pollution data. Machine learning will be used to assess the relationship between air pollution, sleep and AR comparing polluted and non-polluted areas in 6 EU countries. Data generated in 2018 will be confirmed in 2019 and extended by the individual prospective assessment of pollution (portable sensor, TLR7) in AR. Sleep apnea patients will be used as a demonstrator of sleep disorder that can be modulated in terms of symptoms and severity by air pollution and AR. The geographic information system GIS will map the results. Consequences on quality of life (EQ-5D), asthma, school, work and sleep will be monitored and disseminated towards the population. The impacts of POLLAR will be (1) to propose novel care pathways integrating pollution, sleep and patients' literacy, (2) to study sleep consequences of pollution and its impact on frequent chronic diseases, (3) to improve work productivity, (4) to propose the basis for a sentinel network at the EU level for pollution and allergy, (5) to assess the societal implications of the interaction. MASK paper N°32.

Treatment of allergic rhinitis using mobile technology with real-world data: The MASK observational pilot study

BACKGROUND

Large observational implementation studies are needed to triangulate the findings from randomized control trials as they reflect "real-world" everyday practice. In a pilot study, we attempted to provide additional and complementary insights on the real-life treatment of allergic rhinitis (AR) using mobile technology.

METHODS

A mobile phone app (Allergy Diary, freely available in Google Play and Apple App stores) collects the data of daily visual analog scales (VAS) for (i) overall allergic symptoms, (ii) nasal, ocular, and asthma symptoms, (iii) work, as well as (iv) medication use using a treatment scroll list including all medications (prescribed and over the counter (OTC)) for rhinitis customized for 15 countries.

RESULTS

A total of 2871 users filled in 17 091 days of VAS in 2015 and 2016. Medications were reported for 9634 days. The assessment of days appeared to be more informative than the course of the treatment as, in real life, patients do not necessarily use treatment on a daily basis; rather, they appear to increase treatment use with the loss of symptom control. The Allergy Diary allowed differentiation between treatments within or between classes (intranasal corticosteroid use containing medications and oral H1-antihistamines). The control of days differed between no [best control], single, or multiple treatments (worst control).

CONCLUSIONS

This study confirms the usefulness of the Allergy Diary in accessing and assessing everyday use and practice in AR. This pilot observational study uses a very simple assessment (VAS) on a mobile phone, shows novel findings, and generates new hypotheses.

Differences in Reporting the Ragweed Pollen Season Using Google Trends across 15 Countries

BACKGROUND

Google Trends (GT) searches trends of specific queries in Google, which potentially reflect the real-life epidemiology of allergic rhinitis. We compared GT terms related to ragweed pollen allergy in American and European Union countries with a known ragweed pollen season. Our aim was to assess seasonality and the terms needed to perform the GT searches and to compare these during the spring and summer pollen seasons.

METHODS

We examined GT queries from January 1, 2011, to January 4, 2017. We included 15 countries with a known ragweed pollen season and used the standard 5-year GT graphs. We used the GT translation for all countries and the untranslated native terms for each country.

RESULTS

The results of "pollen," "ragweed," and "allergy" searches differed between countries, but "ragweed" was clearly identified in 12 of the 15 countries. There was considerable heterogeneity of findings when the GT translation was used. For Croatia, Hungary, Romania, Serbia, and Slovenia, the GT translation was inappropriate. The country patterns of "pollen," "hay fever," and "allergy" differed in 8 of the 11 countries with identified "ragweed" queries during the spring and the summer, indicating that the perception of tree and grass pollen allergy differs from that of ragweed pollen.

CONCLUSIONS

To investigate ragweed pollen allergy using GT, the term "ragweed" as a plant is required and the translation of "ragweed" in the native language needed.

Prevalence of exceeding maximum daily dose of paracetamol, and seasonal variations in cold-flu season

AIMS

To estimate prevalence of excess intake of paracetamol and investigate seasonal variations therein.

METHODS

Between 2011 and 2016, 14 481 US adults who used paracetamol in the preceding 30 days were sampled from national online panels and completed a detailed online daily diary of paracetamol medication use for 7 days. Respondents were not told that the study concerned paracetamol. Cold/flu season (CFS), identified using Google Trends data, was contrasted to off-season in symptoms, use of paracetamol medications, and consumption exceeding 4 g (the recommended daily maximum).

RESULTS

Overall, 6.3% [95% confidence interval: 5.9-6.7%] of users exceeded 4 g on at least one day; 3.7% [3.5-3.8%] of usage days exceeded 4 g. Cold/flu symptoms were more likely to be experienced and treated with paracetamol in CFS than off-season. Paracetamol users were more likely to exceed 4 g during CFS (6.5% vs. 5.3%; odds ratio = 1.24, 1.04-1.48); days exceeding 4 g also increased (3.9% vs. 2.8%; odds ratio = 1.37, 1.11-1.69). This was not due to differences in characteristics of individuals using paracetamol in CFS, but primarily to increased use of over-the-counter combination medications designed to treat upper respiratory cold/flu symptoms (33.2% of usage days in CFS vs. 24.8% in off-season; odds ratio = 1.58, 1.46-1.72). When such medications were omitted, there was no statistically significant seasonal variation in exceeding 4 g.

CONCLUSIONS

Paracetamol use and over-dosing increases in CFS, primarily due to increased use of over-the-counter combinations treating upper respiratory cold/flu symptoms. Pharmacists should warn users to follow labelled dosing directions, especially during CFS.

Clinical Age-Specific Seasonal Conjunctivitis Patterns and Their Online Detection in Twitter, Blog, Forum, and Comment Social Media Posts

Purpose

We sought to determine whether big data from social media might reveal seasonal trends of conjunctivitis, most forms of which are nonreportable.

Methods

Social media posts (from Twitter, and from online forums and blogs) were classified by age and by conjunctivitis type (allergic or infectious) using Boolean and machine learning methods. Based on spline smoothing, we estimated the circular mean occurrence time (a measure of central tendency for occurrence) and the circular variance (a measure of uniformity of occurrence throughout the year, providing an index of seasonality). Clinical records from a large tertiary care provider were analyzed in a similar way for comparison.

Results

Social media posts machine-coded as being related to infectious conjunctivitis showed similar times of occurrence and degree of seasonality to clinical infectious cases, and likewise for machine-coded allergic conjunctivitis posts compared to clinical allergic cases. Allergic conjunctivitis showed a distinctively different seasonal pattern than infectious conjunctivitis, with a mean occurrence time later in the spring. Infectious conjunctivitis for children showed markedly greater seasonality than for adults, though the occurrence times were similar; no such difference for allergic conjunctivitis was seen.

Conclusions

Social media posts broadly track the seasonal occurrence of allergic and infectious conjunctivitis, and may be a useful supplement for epidemiologic monitoring.

Work productivity in rhinitis using cell phones: The MASK pilot study

Allergic rhinitis often impairs social life and performance. The aim of this cross-sectional study was to use cell phone data to assess the impact on work productivity of uncontrolled rhinitis assessed by visual analogue scale (VAS). A mobile phone app (Allergy Diary, Google Play Store and Apple App Store) collects data from daily visual analogue scales (VAS) for overall allergic symptoms (VAS-global measured), nasal (VAS-nasal), ocular (VAS-ocular) and asthma symptoms (VAS-asthma) as well as work (VAS-work). A combined nasal-ocular score is calculated. The Allergy Diary is available in 21 countries. The app includes the Work Productivity and Activity Impairment Allergic Specific Questionnaire (WPAI:AS) in six EU countries. All consecutive users who completed the VAS-work from 1 June to 31 October 2016 were included in the study. A total of 1136 users filled in 5818 days of VAS-work. Symptoms of allergic rhinitis were controlled (VAS-global <20) in approximately 60% of the days. In users with uncontrolled rhinitis, approximately 90% had some work impairment and over 50% had severe work impairment (VAS-work >50). There was a significant correlation between VAS-global calculated and VAS-work (Rho=0.83, P<0.00001, Spearman's rank test). In 144 users, there was a significant correlation between VAS-work and WPAI:AS (Rho=0.53, P<0.0001). This pilot study provides not only proof-of-concept data on the work impairment collected with the app but also data on the app itself, especially the distribution of responses for the VAS. This supports the interpretation that persons with rhinitis report both the presence and the absence of symptoms.

National Utilization and Forecasting of Ototopical Antibiotics: Medicaid Data Versus "Dr. Google"

OBJECTIVES

To forecast national Medicaid prescription volumes for common ototopical antibiotics, and correlate prescription volumes with internet user search interest using Google Trends (GT).

STUDY DESIGN

National United States Medicaid prescription and GT user search database analysis.

METHODS

Quarterly national Medicaid summary drug utilization data and weekly GT search engine data for ciprofloxacin-dexamethasone (CD), ofloxacin (OF), and Cortisporin (CS) ototopicals were obtained from January 2008 to July 2014. Time series analysis was used to assess prescription seasonality, Holt-Winter's method for forecasting quarterly prescription volumes, and Pearson correlations to compare GT and Medicaid data.

RESULTS

Medicaid prescription volumes demonstrated sinusoidal seasonality for OF (r = 0.91), CS (r = 0.71), and CD (r = 0.62) with annual peaks in July, August, and September. In 2017, OF was forecasted to be the most widely prescribed ototopical, followed by CD. CS was the least prescribed, and volumes were forecasted to decrease 9.0% by 2017 from 2014. GT user search interest demonstrated analogous sinusoidal seasonality and significant correlations with Medicaid data prescriptions for CD (r = 0.38, p = 0.046), OF (r = 0.74, p < 0.001), CS (r = 0.49, p = 0.008).

CONCLUSION

We found that OF, CD, and CS ototopicals have sinusoidal seasonal variation with Medicaid prescription volume peaks occurring in the summer. After 2012, OF was the most commonly prescribed ototopical, and this trend was forecasted to continue. CS use was forecasted to decrease. Google user search interest in these ototopical agents demonstrated analogous seasonal variation. Analyses of GT for interest in ototopical antibiotics may be useful for health care providers and administrators as a complementary method for assessing healthcare utilization trends.

Google Trends terms reporting rhinitis and related topics differ in European countries

Google Trends (GT) searches trends of specific queries in Google and reflects the real-life epidemiology of allergic rhinitis. We compared Google Trends terms related to allergy and rhinitis in all European Union countries, Norway and Switzerland from 1 January 2011 to 20 December 2016. The aim was to assess whether the same terms could be used to report the seasonal variations of allergic diseases. Using the Google Trend 5-year graph, an annual and clear seasonality of queries was found in all countries apart from Cyprus, Estonia, Latvia, Lithuania and Malta. Different terms were found to demonstrate seasonality depending on the country - namely 'hay fever', 'allergy' and 'pollen' - showing cultural differences. A single set of terms cannot be used across all European countries, but allergy seasonality can be compared across Europe providing the above three terms are used. Using longitudinal data in different countries and multiple terms, we identified an awareness-related spike of searches (December 2016).

Pilot study of mobile phone technology in allergic rhinitis in European countries: the MASK-rhinitis study

BACKGROUND

The use of Apps running on smartphones and tablets profoundly affects medicine. The MASK-rhinitis (MACVIA-ARIA Sentinel NetworK for allergic rhinitis) App (Allergy Diary) assesses allergic rhinitis symptoms, disease control and impact on patients' lives. It is freely available in 20 countries (iOS and Android platforms).

AIMS

To assess in a pilot study whether (i) Allergy Diary users were able to properly provide baseline characteristics (ii) simple phenotypic characteristics based upon data captured by the Allergy Diary could be identified and (iii) information gathered by this study could suggest novel research questions.

METHODS

The Allergy Diary users were classified into six groups according to the baseline data that they entered into the App: (i) asymptomatic; (ii) nasal symptoms excluding rhinorrhea; (iii) rhinorrhea; (iv) rhinorrhea plus 1-2 nasal/ocular symptoms; (v) rhinorrhea plus ≥3 nasal/ocular symptoms; and (vi) rhinorrhea plus all nasal/ocular symptoms.

RESULTS

By 1 June 2016, 3260 users had registered with the Allergy Diary and 2710 had completed the baseline questionnaire. Troublesome symptoms were found mainly in the users with the most symptoms. Around 50% of users with troublesome rhinitis and/or ocular symptoms suffered work impairment. Sleep was impaired by troublesome symptoms and nasal obstruction.

CONCLUSIONS

This is the first App (iOS and Android) to have tested for allergic rhinitis and conjunctivitis. A simple questionnaire administered by cell phones enables the identification of phenotypic differences between a priori defined rhinitis groups. The results suggest novel concepts and research questions in allergic rhinitis that may not be identified using classical methods.

Surveillance Tools Emerging From Search Engines and Social Media Data for Determining Eye Disease Patterns

IMPORTANCE

Internet-based search engine and social media data may provide a novel complementary source for better understanding the epidemiologic factors of infectious eye diseases, which could better inform eye health care and disease prevention.

OBJECTIVE

To assess whether data from internet-based social media and search engines are associated with objective clinic-based diagnoses of conjunctivitis.

DESIGN, SETTING, AND PARTICIPANTS

Data from encounters of 4143 patients diagnosed with conjunctivitis from June 3, 2012, to April 26, 2014, at the University of California San Francisco (UCSF) Medical Center, were analyzed using Spearman rank correlation of each weekly observation to compare demographics and seasonality of nonallergic conjunctivitis with allergic conjunctivitis. Data for patient encounters with diagnoses for glaucoma and influenza were also obtained for the same period and compared with conjunctivitis. Temporal patterns of Twitter and Google web search data, geolocated to the United States and associated with these clinical diagnoses, were compared with the clinical encounters. The a priori hypothesis was that weekly internet-based searches and social media posts about conjunctivitis may reflect the true weekly clinical occurrence of conjunctivitis.

MAIN OUTCOMES AND MEASURES

Weekly total clinical diagnoses at UCSF of nonallergic conjunctivitis, allergic conjunctivitis, glaucoma, and influenza were compared using Spearman rank correlation with equivalent weekly data on Tweets related to disease or disease-related keyword searches obtained from Google Trends.

RESULTS

Seasonality of clinical diagnoses of nonallergic conjunctivitis among the 4143 patients (2364 females [57.1%] and 1776 males [42.9%]) with 5816 conjunctivitis encounters at UCSF correlated strongly with results of Google searches in the United States for the term pink eye (ρ, 0.68 [95% CI, 0.52 to 0.78]; P < .001) and correlated moderately with Twitter results about pink eye (ρ, 0.38 [95% CI, 0.16 to 0.56]; P < .001) and with clinical diagnosis of influenza (ρ, 0.33 [95% CI, 0.12 to 0.49]; P < .001), but did not significantly correlate with seasonality of clinical diagnoses of allergic conjunctivitis diagnosis at UCSF (ρ, 0.21 [95% CI, -0.02 to 0.42]; P = .06) or with results of Google searches in the United States for the term eye allergy (ρ, 0.13 [95% CI, -0.06 to 0.32]; P = .19). Seasonality of clinical diagnoses of allergic conjunctivitis at UCSF correlated strongly with results of Google searches in the United States for the term eye allergy (ρ, 0.44 [95% CI, 0.24 to 0.60]; P < .001) and eye drops (ρ, 0.47 [95% CI, 0.27 to 0.62]; P < .001).

CONCLUSIONS AND RELEVANCE

Internet-based search engine and social media data may reflect the occurrence of clinically diagnosed conjunctivitis, suggesting that these data sources can be leveraged to better understand the epidemiologic factors of conjunctivitis.

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.

Latest developments in allergic rhinitis in Allergy for clinicians and researchers

Research efforts in allergic rhinitis have always been intense. Over the past 3 years, numerous breakthroughs in basic science and clinical research have been made, augmenting our understanding of this condition that afflicts a significant proportion of the global population. New epidemiological findings, novel insights into the molecular and cellular mechanisms of allergy, enhancement of current developmental theories, new concepts of the goals and endpoints of management, and latest therapeutic modalities that includes the harnessing of information technology and big data are some areas where important advances were made. We attempt to bring you a summary of the key research advances made in the field of allergic rhinitis from 2013 to 2015.