Infodemiology of systemic lupus erythematous using Google Trends

Google trends in infodemiology: Methodological steps to avoid irreproducible results and invalid conclusions

BACKGROUND

Google Trends is a widely used tool for infodemiological surveys. However, irregularities in the random sampling and aggregation algorithms compromise the reliability of the relative search volume (RSV) and the regional online interest (ROI).

OBJECTIVE

The study aims to unmask methodological criticalities commonly ignored in carrying out infodemiological surveys via Google Trends. A guide to avoiding these shortcomings is also provided.

MATERIAL AND METHODS

The Google Topic "Coronavirus disease 2019" has been investigated using different timelapses, categories, and IP addresses. The same samples were manually collected multiple times to evaluate the RSV and ROI stability. Stability was estimated through indicators of variability (e.g., coefficient of percentage variation "CV%" and its 4-surprisal interval "4-I"). The content aggregation capacity of the algorithms relating to topics and categories was evaluated through the quantitative analysis of RSV and ROI and the qualitative examination of the related queries.

RESULTS

The stability of Google Trends' RSV and ROI is not linked exclusively to the dataset dimension or the IP address. Subregional datasets can be highly unstable (e.g., CV% = 10, 4-I: [8,13]). Google Trends categories and topics can exclude relevant queries or include unnecessary queries. The statistical scenario is consistent with the following hypotheses: i) datasets containing too few queries are highly unstable, ii) the "interest over time" data format is generally reliable for evaluating trends and correlations, iii) Google Trends improvements have altered the RSV historical trends.

CONCLUSIONS

Google Trends can be an effective and efficient infodemiological tool as long as the reliability of web search indexes is appropriately analyzed and weighted for the scientific goal. The methodological steps discussed in this study are critical to drawing valid and relevant scientific conclusions.

Online information-seeking behavior of Iranian web users on Google about Henoch-Schönlein purpura (HSP): an infodemiology study

BACKGROUNDS

Previous studies have indicated that users' health information-seeking behavior can serve as a reflection of current health issues within a community. This study aimed to investigate the online information-seeking behavior of Iranian web users on Google about Henoch-Schönlein purpura (HSP).

METHODS

Google Trends (GTr) was utilized to collect big data from the internet searches conducted by Iranian web users. A focus group discussion was employed to identify users' selected keywords when searching for HSP. Additionally, keywords related to the disease's symptoms were selected based on recent clinical studies. All keywords were queried in GTr from January 1, 2012 to October 30, 2022. The outputs were saved in an Excel format and analyzed using SPSS.

RESULTS

The highest and lowest search rates of HSP were recorded in winter and summer, respectively. There was a significant positive correlation between HSP search rates and the terms "joint pain" (P = 0.007), "vomiting" (P = 0.032), "hands and feet swelling" (P = 0.041) and "seizure" (P < 0.001).

CONCLUSION

The findings were in accordance with clinical facts about HSP, such as its seasonal pattern and accompanying symptoms. It appears that the information-seeking behavior of Iranian users regarding HSP can provide valuable insights into the outbreak of this disease in Iran.

In.To. COVID-19 socio-epidemiological co-causality

Social media can forecast disease dynamics, but infoveillance remains focused on infection spread, with little consideration of media content reliability and its relationship to behavior-driven epidemiological outcomes. Sentiment-encoded social media indicators have been poorly developed for expressed text to forecast healthcare pressure and infer population risk-perception patterns. Here we introduce Infodemic Tomography (InTo) as the first web-based interactive infoveillance cybertechnology that forecasts and visualizes spatio-temporal sentiments and healthcare pressure as a function of social media positivity (i.e., Twitter here), considering both epidemic information and potential misinformation. Information spread is measured on volume and retweets, and the Value of Misinformation (VoMi) is introduced as the impact on forecast accuracy where misinformation has the highest dissimilarity in information dynamics. We validated InTo for COVID-19 in New Delhi and Mumbai by inferring distinct socio-epidemiological risk-perception patterns. We forecast weekly hospitalization and cases using ARIMA models and interpolate spatial hospitalization using geostatistical kriging on inferred risk perception curves between tweet positivity and epidemiological outcomes. Geospatial tweet positivity tracks accurately [Formula: see text]60[Formula: see text] of hospitalizations and forecasts hospitalization risk hotspots along risk aversion gradients. VoMi is higher for risk-prone areas and time periods, where misinformation has the highest non-linear predictability, with high incidence and positivity manifesting popularity-seeking social dynamics. Hospitalization gradients, VoMi, effective healthcare pressure and spatial model-data gaps can be used to predict hospitalization fluxes, misinformation, healthcare capacity gaps and surveillance uncertainty. Thus, InTo is a participatory instrument to better prepare and respond to public health crises by extracting and combining salient epidemiological and social surveillance at any desired space-time scale.

Exploring online search behavior for COVID-19 preventive measures: The Philippine case

Public health agencies have suggested nonpharmaceutical interventions to curb the spread of the COVID-19 infections. The study intended to explore the information-seeking behavior and information needs on preventive measures for COVID-19 in the Philippine context. The search interests and related queries for COVID-19 terms and each of the preventive measures for the period from December 31, 2019 to April 6, 2020 were generated from Google Trends. The search terms employed for COVID-19 were coronavirus, ncov, covid-19, covid19 and “covid 19.” The search terms of the preventive measures considered for this study included “community quarantine”, “cough etiquette”, “face mask” or facemask, “hand sanitizer”, handwashing or “hand washing” and “social distancing.” Spearman’s correlation was employed between the new daily COVID-19 cases, COVID-19 terms and the different preventive measures. The relative search volume for the coronavirus disease showed an increase up to the pronouncement of the country’s first case of COVID-19. An uptrend was also evident after the country’s first local transmission was confirmed. A strong positive correlation (r_s = .788, p < .001) was observed between the new daily cases and search interests for COVID-19. The search interests for the different measures and the new daily cases were also positively correlated. Similarly, the search interests for the different measures and the COVID-19 terms were all positively correlated. The search interests for “face mask” or facemask, “hand sanitizer” and handwashing or “hand washing” were more correlated with the search interest for COVID-19 than with the number of new daily COVID-19 cases. The search interests for “cough etiquette”, “social distancing” and “community quarantine” were more correlated with the number of new daily COVID-19 cases than with the search interest for COVID-19. The public sought for additional details such as type, directions for proper use, and where to purchase as well as do-it-yourself alternatives for personal protective items. Personal protective or community measures were expected to be accompanied with definitions and guidelines as well as be available in translated versions. Google Trends could be a viable option to monitor and address the information needs of the public during a disease outbreak. Capturing and analyzing the search interests of the public could support the design and timely delivery of appropriate information essential to drive preventive measures during a disease outbreak.

Population's health information-seeking behaviors and geographic variations of stroke in Malaysia: an ecological correlation and time series study

Stroke has emerged as a major public health concern in Malaysia. We aimed to determine the trends and temporal associations of real-time health information-seeking behaviors (HISB) and stroke incidences in Malaysia. We conducted a countrywide ecological correlation and time series study using novel internet multi-timeline data stream of 6,282 hit searches and conventional surveillance data of 14,396 stroke cases. We searched popular search terms related to stroke in Google Trends between January 2004 and March 2019. We explored trends by comparing average relative search volumes (RSVs) by month and weather through linear regression bootstrapping methods. Geographical variations between regions and states were determined through spatial analytics. Ecological correlation analysis between RSVs and stroke incidences was determined via Pearson's correlations. Forecasted model was yielded through exponential smoothing. HISB showed both cyclical and seasonal patterns. Average RSV was significantly higher during Northeast Monsoon when compared to Southwest Monsoon (P < 0.001). "Red alerts" were found in specific regions and states. Significant correlations existed within stroke related queries and actual stroke cases. Forecasted model showed that as HISB continue to rise, stroke incidence may decrease or reach a plateau. The results have provided valuable insights for immediate public health policy interventions.

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.

Infodemiology and Infoveillance: Scoping Review

BACKGROUND

Web-based sources are increasingly employed in the analysis, detection, and forecasting of diseases and epidemics, and in predicting human behavior toward several health topics. This use of the internet has come to be known as infodemiology, a concept introduced by Gunther Eysenbach. Infodemiology and infoveillance studies use web-based data and have become an integral part of health informatics research over the past decade.

OBJECTIVE

The aim of this paper is to provide a scoping review of the state-of-the-art in infodemiology along with the background and history of the concept, to identify sources and health categories and topics, to elaborate on the validity of the employed methods, and to discuss the gaps identified in current research.

METHODS

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed to extract the publications that fall under the umbrella of infodemiology and infoveillance from the JMIR, PubMed, and Scopus databases. A total of 338 documents were extracted for assessment.

RESULTS

Of the 338 studies, the vast majority (n=282, 83.4%) were published with JMIR Publications. The Journal of Medical Internet Research features almost half of the publications (n=168, 49.7%), and JMIR Public Health and Surveillance has more than one-fifth of the examined studies (n=74, 21.9%). The interest in the subject has been increasing every year, with 2018 featuring more than one-fourth of the total publications (n=89, 26.3%), and the publications in 2017 and 2018 combined accounted for more than half (n=171, 50.6%) of the total number of publications in the last decade. The most popular source was Twitter with 45.0% (n=152), followed by Google with 24.6% (n=83), websites and platforms with 13.9% (n=47), blogs and forums with 10.1% (n=34), Facebook with 8.9% (n=30), and other search engines with 5.6% (n=19). As for the subjects examined, conditions and diseases with 17.2% (n=58) and epidemics and outbreaks with 15.7% (n=53) were the most popular categories identified in this review, followed by health care (n=39, 11.5%), drugs (n=40, 10.4%), and smoking and alcohol (n=29, 8.6%).

CONCLUSIONS

The field of infodemiology is becoming increasingly popular, employing innovative methods and approaches for health assessment. The use of web-based sources, which provide us with information that would not be accessible otherwise and tackles the issues arising from the time-consuming traditional methods, shows that infodemiology plays an important role in health informatics research.

Google Medical Update: Why Is the Search Engine Decreasing Visibility of Health and Medical Information Websites?

The Google search engine answers many health and medical information queries every day. People have become used to searching for this type of information. This paper presents a study which examined the visibility of health and medical information websites. The purpose of this study was to find out why Google is decreasing the visibility of such websites and how to measure this decrease. Since August 2018, Google has been more rigorously rating these websites, since they can potentially impact people’s health. The method of the study was to collect data about the visibility of health and medical information websites in sequential time snapshots. Visibility consists of combined data of unique keywords, positions, and URL results. The sample under study was made up of 21 websites selected from 10 European countries. The findings reveal that in sequential time snapshots, search visibility decreased. The decrease was not dependent on the country or the language. The main reason why Google is decreasing the visibility of such websites is that they do not meet high ranking criteria.

Global public interest in systemic lupus erythematosus: an investigation based on internet search data

Objective

This study aims at investigating the global public interest in seeking information about systemic lupus erythematosus (SLE) using Google Trends (GT).

Methods

An electronic search was performed using GT with the search term lupus as well as the option of disease from January 2004 to December 2018. Cosinor analysis was applied to detect the seasonality of SLE-related relative search volume (RSV). In addition, analysis on SLE-related topics including “hot topics” and “top rising topics” was also conducted.

Results

Overall, SLE-related RSV showed a decreasing trend from January 2004 to December 2013 and then demonstrated a slowly increasing trend from January 2014 to December 2018. Cosinor test showed no significant seasonal variation in SLE-related RSV ( p > .025). RSV peaked in May and reached the trough in November. The top seven rising topics were Selena Gomez, Sjögren syndrome, autoimmunity, rheumatoid arthritis, rheumatology, antinuclear antibody and autoimmune disease.

Conclusion

The results from GT analysis showed slowly increasing internet searches for SLE in recent years. This trend was followed by a peak of RSV in May and reached its lowest level in November. However, globally, the results did not reveal a significant seasonal variation in GT for SLE. Additionally, the top fast-growing topics regarding SLE may be valuable for doctors and nurses to provide timely education of the disease to patients, as well as promote the development of public health.

Google Trends in Infodemiology and Infoveillance: Methodology Framework

Internet data are being increasingly integrated into health informatics research and are becoming a useful tool for exploring human behavior. The most popular tool for examining online behavior is Google Trends, an open tool that provides information on trends and the variations of online interest in selected keywords and topics over time. Online search traffic data from Google have been shown to be useful in analyzing human behavior toward health topics and in predicting disease occurrence and outbreaks. Despite the large number of Google Trends studies during the last decade, the literature on the subject lacks a specific methodology framework. This article aims at providing an overview of the tool and data and at presenting the first methodology framework in using Google Trends in infodemiology and infoveillance, including the main factors that need to be taken into account for a strong methodology base. We provide a step-by-step guide for the methodology that needs to be followed when using Google Trends and the essential aspects required for valid results in this line of research. At first, an overview of the tool and the data are presented, followed by an analysis of the key methodological points for ensuring the validity of the results, which include selecting the appropriate keyword(s), region(s), period, and category. Overall, this article presents and analyzes the key points that need to be considered to achieve a strong methodological basis for using Google Trends data, which is crucial for ensuring the value and validity of the results, as the analysis of online queries is extensively integrated in health research in the big data era.

Potential uses of an infodemiology approach for health-care services for rheumatology

OBJECTIVES

This is a demand-based infodemiology study using the Google Trends and AdWords tools to illustrate infodemiology's potential use in rheumatology. The study investigates three questions in North American countries: (1) What terms associated with "rheumatology" and "arthritis" do people search for on Google? (2) What is the search volume for disease-modifying antirheumatic drugs (DMARDs)? and (3) What is the search volume for the term "arthritis" compared with for "hepatitis C" and "breast cancer"?

METHODS

We conducted independent searches by country and search term for 2015-2017. Seventeen DMARDs were searched for 2015 through May 2018, with the turmeric remedy included for comparison. Data were exported to Excel for further analysis, adjusted by country population, and expressed as searches per 100,000 inhabitants (SpTh).

RESULTS

There were approximately 550 associated terms for "arthritis" in each country, and 5679 SpTh for DMARDs across the three countries. Searches for turmeric numbered slightly lower than for all DMARDs together in Canada and the USA, but were 70% higher in Mexico. Turmeric was also searched four times more than the most-searched biological DMARD in Canada and the USA, and 60 times more in Mexico. Arthritis was more commonly searched for in Canada than hepatitis C and breast cancer, but hepatitis C was highest in the USA and breast cancer in Mexico. Monthly trends did not show expected peaks associated with arthritis awareness campaigns.

CONCLUSION

Infodemiology provides preliminary information that could help in generating hypotheses, assessing health-care interventions, or even in providing patient-centered care.

Assessing the quality, reliability and readability of online health information regarding systemic lupus erythematosus

Introduction Systemic lupus erythematosus (SLE) has complex pathophysiology and treatments, and patients often use the internet to better understand their condition. This report systematically assesses the quality, reliability and readability of online information. Methods The search term 'systemic lupus erythematosus' was used with Google™, Bing™ and Yahoo™ search engines sequentially. The first 25 websites returned ('hits') for each search engine (total 75 websites) were compiled. The search terms 'SLE' and 'lupus' were used in separate Google searches to assess for commonality. After removal of excluded hits, websites were assessed using the DISCERN instrument, Journal of the American Medical Association benchmarks and Gunning Fog Index for quality, reliability and readability and presence of 'Health on the Net Code' (HoN) standardisation recorded. Results There was a large degree of commonality among hits from the three different search engines using the search term 'systemic lupus erythematosus', as well as hits returned for the three different search terms using Google. The mean DISCERN score was 47.7 (SD 13.2) for 'systemic lupus erythematosus', 46.4 (SD 14.2) for 'SLE' and 45.2 (SD 10.1) for 'lupus', with no statistically significant difference. The mean number of JAMA benchmarks (maximum four) present for the 'systemic lupus erythematosus', 'SLE' and 'lupus' searches was 1.3 (SD 1.2), 1.4 (SD 1.3) and 1.2 (SD 1.0), respectively, with no statistically significance difference. The average readability of hits for the three different search terms was 9.3 (SD 3.4), 10.0 (SD 3.1) and 11.1 (SD 2.7), with no statistically significant difference. Conclusion There was a large degree of commonality of hits among the different search engines and the utilised search terms but they are not synonymous. Regardless of search term, the overall quality of websites was fair, whilst reliability was poor. Websites appearing higher in searches did not score better. Presence of the HoN did not represent better quality. Readability was higher than recommended for near-universal understanding. There was no difference in quality, reliability or readability of websites using the search terms 'systemic lupus erythematosus', 'SLE' or 'lupus', with some high-scoring websites appearing in only one search term result. This study reminds clinicians to direct patients to high-quality websites rather than rely on search engines.

Infodemiology of antiphospholipid syndrome: Merging informatics and epidemiology

OBJECTIVE

To investigate trends in Internet search volumes linked to Antiphospholipid Syndrome (APS), using Big Data monitoring and data mining.

METHODS

Based on the large amount of data generated by Google Trends and scientific search tools (SCOPUS, Medline/Pubmed, and ClinicalTrails.gov), we performed a longitudinal analysis based on the term "antiphospholipid" in a 5-year web-based research.

RESULTS

Google Trends captured that APS-related digital interest was generally steady in the study period (Relative Search Volume [RSV] mean value 71.1±9.3% [95%CI 55.6-89.4], median 72.0), with no significant peak based on different seasons (e.g. winter vs. summer time). When comparing the APS-related digital interest with search volumes generated in the same time period for Inherited Thrombophilias (IT) and Systemic Lupus Erythematosus (SLE), we found a digital interest 35-times higher for APS than for IT (RSV mean value 71.1±9.3% [95%CI 55.6-89.4] vs. 2±3.2% [95%CI 0.7-7.4]). When compared to SLE, APS reached a similar RSV, showing a comparable digital interest (RSV mean value 71.1±9.3% [95%CI 55.6-89.4] vs. 87±11.8% [95%CI 60.7-107.9]). When adjusting for relative search volumes of Google Trends, we found a relative prevalence of search volumes of 35.5% in Europe, 12.3% in the United States, 11.5% in South America, 11.2% in Australia, 9.2% in Canada, 9.2% in Japan, and 5.1% in India. We observed an overall similar distribution of search volumes from Google Trends compared to results from Medline/Pubmed, SCOPUS, and ClinicalTrials.gov. In brief, the United States and Europe (mainly Italy, the United Kingdom, Spain, France, and Germany) presented the higher RSV. Similarly, these countries showed a higher number of research publications and on-going trials in the field of APS.

CONCLUSION

In this study, we demonstrated that the interest in APS is not equally distributed globally. Thus, geopolitical differences might represent a challenge when attempting to estimate the prevalence of APS or designing worldwide investigations in APS. Combining the expanding framework of infodemiology with scientific networking collaborative efforts, such as AntiPhospholipid Syndrome Alliance For Clinical Trials and InternatiOnal Networking (APS ACTION), will help better define the syndrome in terms of prevalence, event occurrence ratios, and thrombosis risk assessment.

Antiphospholipid syndrome

Antiphospholipid syndrome (APS) is an autoimmune disease characterized by the presence of antiphospholipid antibodies, such as lupus anticoagulant, anticardiolipin antibodies and anti-β2-glycoprotein 1 antibodies. APS can present with a variety of clinical phenotypes, including thrombosis in the veins, arteries and microvasculature as well as obstetrical complications. The pathophysiological hallmark is thrombosis, but other factors such as complement activation might be important. Prevention of thrombotic manifestations associated with APS includes lifestyle changes and, in individuals at high risk, low-dose aspirin. Prevention and treatment of thrombotic events are dependent mainly on the use of vitamin K antagonists. Immunosuppression and anticomplement therapy have been used anecdotally but have not been adequately tested. Pregnancy morbidity includes unexplained recurrent early miscarriage, fetal death and late obstetrical manifestation such as pre-eclampsia, premature birth or fetal growth restriction associated with placental insufficiency. Current treatment to prevent obstetrical morbidity is based on low-dose aspirin and/or low-molecular-weight heparin and has improved pregnancy outcomes to achieve successful live birth in >70% of pregnancies. Although hydroxychloroquine and pravastatin might further improve pregnancy outcomes, prospective clinical trials are required to confirm these findings.