Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study

Population Interest in Information on Obesity, Nutrition, and Occupational Health and Its Relationship with the Prevalence of Obesity: An Infodemiological Study

OBJECTIVE

To identify and analyze population interest in obesity, nutrition, and occupational health and safety and its relationship with the worldwide prevalence of obesity through information search trends.

METHOD

In this ecological study, data were obtained through online access to Google Trends using the topics "obesity", "nutrition", and "occupational health and safety". Obesity data were obtained from the World Health Organization (WHO) website for crude adult prevalence and estimates by region. The variables studied were relative search volume (RSV), temporal evolution, milestone, trend, and seasonality. The temporal evolution of the search trends was examined by regression analysis (R2). To assess the relationship between quantitative variables, the Spearman correlation coefficient (Rho) was used. Seasonality was verified using the augmented Dickey-Fuller (ADF) test.

RESULTS

The RSV trends were as follows: obesity (R2 = 0.04, p = 0.004); nutrition (R2 = 0.42, p < 0.001); and occupational health and safety (R2 = 0.45, p < 0.001). The analysis of seasonality showed the absence of a temporal pattern (p < 0.05 for all terms). The associations between world obesity prevalence (WOP) and the different RSVs were as follows: WOP versus RSV obesity, Rho = -0.79, p = 0.003; WOP versus RSV nutrition, Rho = 0.57, p = 0.044; and WOP versus RSV occupational health and safety, Rho = -0.93, p = 0.001.

CONCLUSIONS

Population interest in obesity continues to be a trend in countries with the highest prevalence, although there are clear signs popularity loss in favor of searches focused on possible solutions and treatments, with a notable increase in searches related to nutrition and diet. Despite the fact that most people spend a large part of their time in the workplace and that interventions including various strategies have been shown to be useful in combating overweight and obesity, there has been a decrease in the population's interest in information related to obesity in the workplace. This information can be used as a guide for public health approaches to obesity and its relationship to nutrition and a healthy diet, approaches that are of equal utility and applicability in occupational health.

Occupational Health Applied Infodemiological Studies of Nutritional Diseases and Disorders: Scoping Review with Meta-Analysis

(1) Objective: to identify and review existing infodemiological studies on nutritional disorders applied to occupational health and to analyse the effect of the intervention on body mass index (BMI) or alternatively body weight (BW); (2) Methods: This study involved a critical analysis of articles retrieved from MEDLINE (via PubMed), Embase, Cochrane Library, PsycINFO, Scopus, Web of Science, Latin American, and Caribbean Health Sciences Literature (LILACS) and Medicina en Español (MEDES) using the descriptors "Nutrition Disorders, "Occupational Health" and "Infodemiology", applying the filters "Humans" and "Adult: 19+ years". The search was conducted on 29 May 2021; (3) Results: a total of 357 references were identified from the bibliographic database searches; after applying the inclusion and exclusion criteria, a total of 11 valid studies were obtained for the review. Interventions could be categorised into (1) interventions related to lifestyle, physical activity, and dietary changes through education programmes, (2) interventions associated with lifestyle, physical activity, and dietary changes through the use of telemonitoring systems or self-help applications, (3) interventions tied to lifestyle, physical activity, and dietary changes through control and/or social network support groups, and (4) interventions linked to changes in the work environment, including behavioural change training and work environment training tasks. The meta-analysis demonstrated that the heterogeneity present when analysing the results for BMI was 72% (p < 0.01), which decreased to 0% (p = 0.57) when analysing the outcomes for weight, in which case the null hypothesis of homogeneity could be accepted. In all instances, the final summary of the effect was on the decreasing side for both BMI and BW; (4) Conclusions: Despite the high heterogeneity of the results reported, the trend shown in all cases indicates that the intervention methodologies implemented by empowering individuals through Web 2.0 technologies are positive in terms of the problem of overweight. Further implementation of novel strategies to support individuals is needed to overcome obesity, and, at least in the early studies, these strategies seem to be making the necessary change.

Reacting, Sharing, and Commenting: How Many Facebook Users Are Engaging with Posts Related to Dental Caries That Contain Misinformation?

Recent studies have been concerned about the vast amount of misinformation detected on social media that directly hampers the prevention and control of chronic diseases. Based on these facts, the aim of this study was to identify and characterize misinformation about dental caries-related content found on Facebook, regarding the predictive factors of user interaction with posts. Then, CrowdTangle retrieved 2,436 posts published in English, ordered by the total interaction of the highest users. A total of 1,936 posts were selected for inclusion and exclusion criteria to select a sample of 500 posts. Subsequently, two independent investigators characterized the posts by their time of publication, author's profile, motivation, the aim of content, content facticity, and sentiment. The statistical analysis was performed using Mann-Whitney U and χ2 tests and multiple logistic regression models to determine differences and associations between dichotomized characteristics. p values <0.05 were considered significant. In general, posts were predominantly originated from the USA (74.8%), related to business profiles (89%), presented preventive content (58.6%), and noncommercial motivation (91.6%). Furthermore, misinformation was detected in 40.8% of the posts and was positively associated with positive sentiment (OR = 3.43), business profile (OR = 2.22), and treatment of dental caries (OR = 1.60). While the total interaction was only positively associated with misinformation (OR = 1.44), the overperforming score was associated with posts from the business profile (OR = 5.67), older publications (OR = 1.57), and positive sentiment (OR = 0.66). In conclusion, misinformation was the unique predictive factor of increased user interaction with dental caries-related posts on Facebook. However, it did not predict the performance of the diffusion of posts such as business profiles, older publications, and negative/neutral sentiment. Therefore, it is essential to promote the development of specific policies toward good quality information on social media, which includes the production of adequate materials, the increase of the critical sense of consuming health content, and information filtering mediated by digital solutions.

XAV-939 inhibits epithelial-mesenchymal transformation in pulmonary fibrosis induced by crystalline silica via the Wnt signaling pathway

Silicosis is an occupational lung disease that results from long-term inhalation of free silica dust, the expression is sustained inflammation response, fibroblast hyperplasia, and excessive collagen deposit, bringing about pulmonary interstitial fibrosis. Wnt signaling pathway exists in various kinds of eukaryotic cells, is a highly conservative signaling pathway in biological evolution, and participates in cell proliferation, differentiation, migration, and polarity of physiological activity, such as in embryonic development, organ morphology, and tumor. In addition, it plays an important role in the progress of fibrosis disease. At present, studies related to silicosis are increasing, but the pathogenesis of silicosis still is not clear. In recent years, more and more studies have suggested that the Wnt signaling pathway could participate in the pathogenesis of silicosis fibrosis. In the study, we explored the mechanism of the Wnt signaling pathway in the pathogenesis of silicosis fibrosis and evaluated the effect of XAV-939 treatment epithelial-mesenchymal transformation (EMT) induced by silica. In addition, the results showed that EMT and activation of the Wnt signaling pathway would occur after stimulation of silica or TGF-β1. However, after treatment with the Wnt signaling pathway inhibitor XAV-939, EMT was reversed and the expression of the β-catenin decreased. These results suggested that the Wnt signaling pathway is associated with EMT induced by silica and it could be a potential target for the treatment of silicosis.

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.

Mpox panic, infodemic, and stigmatization of the 2SLGBTQIAP+ community: geospatial analysis, topic modeling, and sentiment analysis of a large, multilingual social media database (Preprint)

BACKGROUND

The global Mpox (formerly, Monkeypox) outbreak is disproportionately affecting the gay and bisexual men having sex with men community.

OBJECTIVE

The aim of this study is to use social media to study country-level variations in topics and sentiments toward Mpox and Two-Spirit, Lesbian, Gay, Bisexual, Transgender, Queer or Questioning, Intersex, Asexual (2SLGBTQIAP+)-related topics. Previous infectious outbreaks have shown that stigma intensifies an outbreak. This work helps health officials control fear and stop discrimination.

METHODS

In total, 125,424 Twitter and Facebook posts related to Mpox and the 2SLGBTQIAP+ community were extracted from May 1 to December 25, 2022, using Twitter application programming interface academic accounts and Facebook-scraper tools. The tweets' main topics were discovered using Latent Dirichlet Allocation in the sklearn library. The pysentimiento package was used to find the sentiments of English and Spanish posts, and the CamemBERT package was used to recognize the sentiments of French posts. The tweets' and Facebook posts' languages were understood using the Twitter application programming interface platform and pycld3 library, respectively. Using ArcGis Online, the hot spots of the geotagged tweets were identified. Mann-Whitney U, ANOVA, and Dunn tests were used to compare the sentiment polarity of different topics and countries.

RESULTS

The number of Mpox posts and the number of posts with Mpox and 2SLGBTQIAP+ keywords were 85% correlated (P<.001). Interestingly, the number of posts with Mpox and 2SLGBTQIAP+ keywords had a higher correlation with the number of Mpox cases (correlation=0.36, P<.001) than the number of posts on Mpox (correlation=0.24, P<.001). Of the 10 topics, 8 were aimed at stigmatizing the 2SLGBTQIAP+ community, 3 of which had a significantly lower sentiment score than other topics (ANOVA P<.001). The Mann-Whitney U test shows that negative sentiments have a lower intensity than neutral and positive sentiments (P<.001) and neutral sentiments have a lower intensity than positive sentiments (P<.001). In addition, English sentiments have a higher negative and lower neutral and positive intensities than Spanish and French sentiments (P<.001), and Spanish sentiments have a higher negative and lower positive intensities than French sentiments (P<.001). The hot spots of the tweets with Mpox and 2SLGBTQIAP+ keywords were recognized as the United States, the United Kingdom, Canada, Spain, Portugal, India, Ireland, and Italy. Canada was identified as having more tweets with negative polarity and a lower sentiment score (P<.04).

CONCLUSIONS

The 2SLGBTQIAP+ community is being widely stigmatized for spreading the Mpox virus on social media. This turns the community into a highly vulnerable population, widens the disparities, increases discrimination, and accelerates the spread of the virus. By identifying the hot spots and key topics of the related tweets, this work helps decision makers and health officials inform more targeted policies.

The association between nomophobia and loneliness among the general population in the Kingdom of Saudi Arabia

Background

Nomophobia progresses through phases (initiation, affirmation, need, and dependency), similarly to addiction, and manifests in a variety of ways, including socially, physiologically, and physically. The objective of the study is to examine the association between nomophobia and feelings of loneliness among a sample of the general population from the KSA. Data were gathered between 5 March and 5 April 2022 using a descriptive, cross-sectional survey design. Five hundred twenty-six participants make up the sample for this study. The information is gathered using a sociodemographic data sheet, Internet usage profiles, a nomophobia questionnaire, and the Loneliness Scale.

Results

The majority of people in the study sample use the Internet for between 4 and 9 h, most immediately in the morning, on waking, for gaming, and for social communication. For nomophobia levels among the study population, the highest percentage is for a moderate level of nomophobia, with the highest means being for factor 1 (unable to communicate), followed by factor 4 (giving up convenience). They also have a moderate level of loneliness.

Conclusions

The multivariate analysis shows that the total loneliness score is strongly and positively correlated with the total nomophobia score and its four factors and the duration of daily mobile Internet use. There are also negative correlations with age and education level. Additionally, the overall nomophobia score has an inverse relationship with income level and age, but a high relationship with the frequency of daily mobile Internet use. The study suggests that there is a need for psychoeducation for a variety of sociodemographic groups to raise awareness about the psychological repercussions of nomophobia, practices that will help to reduce the time spent online for arbitrary reasons, to discover new and entertaining ways of communicating with each other.

Global and national burden and trends of mortality and disability-adjusted life years for silicosis, from 1990 to 2019: results from the Global Burden of Disease study 2019

Background

Silicosis, as an important type of pneumoconiosis, leads to progressive and irreversible conditions from the beginning of inflammation and fibrosis. However, the data on the global burden of silicosis and long-term trends were limited.

Methods

Derived from the Global Burden of Disease study 2019 (online publicly available: Global Health Data Exchange), data on both crude and age-standardized rates (ASR) per 100,00 people of mortality and disability-adjusted life years (DALYs) due to silicosis was collected and analyzed. The burden and trends of mortality and DALYs due to silicosis was assessed by 204 countries and territories, by 5-year interval of age group and by sex from 1990 to 2019. And all the regions were divided into 5 categories according to Sociodemographic Index (SDI). Temporal trends in mortality and DALY were evaluated only to ASR by the Joinpoint regression model.

Results

More than 12.9 thousand [95% Uncertainty Intervals (UI): 10.9, 16.2] death cases occurred due to silicosis worldwide, and 655.7 thousand (95% UI: 519.3, 828.0) DALYs were attributed to silicosis in 2019. From 1990 to 2019, global number of mortality and DALYs in countries with high SDI quintile decreased by 0.35% (95% UI: − 0.45, − 0.17) and 0.32% (95% UI: − 0.45, − 0.01), respectively. There was a greater burden in low- and middle-income countries were estimated in 2019 according to ASRs. The global number of mortality and DALYs among males accounted for over 95% of all in 2019. Both age-sex-specific mortality and DALY rate were increasing with aging and reached their peak at 85–89 age group. During the past 30 years, ASR of mortality and DALYs showed a decreasing trend with average annual percentage change at -3.0% [95% Confidence Intervals (CI): − 3.2, − 2.9] and − 2.0 (95% CI: − 1.7, − 2.2), respectively.

Conclusions

Silicosis remains an important health issue and causes a potentially serious burden worldwide. Attention should be paid to making preventable, affordable and effective measures in lower SDI regions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02040-9.

Trends and Seasonality of Information Searches Carried Out through Google on Nutrition and Healthy Diet in Relation to Occupational Health: Infodemiological Study

This study aimed to analyze and relate the population interest through information search trends on Nutrition and Healthy Diet (HD) with the Occupational Health (OH). Ecological and correlational study of the Relative Search Volume (RSV) obtained from Google Trends query, segmented in two searched periods concerning antiquity; date of query: 20 April 2021. The RSV trends for the analyzed three Topics were: Nutrition (R² = 0.02), HD (R² = 0.07) and OH (R² = -0.72). There was a good positive correlation between Nutrition and OH (R = 0.56, p < 0.001) and a moderate one between HD and OH (R = 0.32, p < 0.001). According to seasons, differences were verified between RSV means in the Topics HD (p < 0.01) and OH (p < 0.001). Temporal dependence was demonstrated on Nutrition searches (Augmented Dickey-Fuller = -2.35, p > 0.05). There was only a significant relationship between the RSV Topic HD (p < 0.05) for the Developing and Least Developed countries. The data on the analyzed RSV demonstrated diminishing interest in the search information on HD and OH as well as a clearly positive trend change in recent years for Nutrition. A good positive correlation was observed between the RSV of nutrition and OH whereas the correlation between HD and OH was moderate. There were no milestones found that may report a punctual event leading to the improvement of information searches. Temporal dependence was corroborated in the RSV on Nutrition, but not in the other two Topics. Strangely, only an association was found on HD searches between the Developing and Least Developed Countries. The study of information search trends may provide useful information on the population's interest in the disease data, as well as would gradually allow the analysis of differences in popularity, or interest even between different countries. Thus, this information might be used as a guide for public health approaches regarding nutrition and a healthy diet at work.

How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic

SARS-CoV2 is a novel coronavirus, responsible for the COVID-19 pandemic declared by the World Health Organization. Thanks to the latest advancements in the field of molecular and computational techniques and information and communication technologies (ICTs), artificial intelligence (AI) and Big Data can help in handling the huge, unprecedented amount of data derived from public health surveillance, real-time epidemic outbreaks monitoring, trend now-casting/forecasting, regular situation briefing and updating from governmental institutions and organisms, and health facility utilization information. The present review is aimed at overviewing the potential applications of AI and Big Data in the global effort to manage the pandemic.

Digital behavior surveillance for monitoring the interests of Google users in amber necklace in different countries

AIM

To determine the interests of Google users in information about amber necklace in distinct countries over time.

DESIGN

This longitudinal retrospective study analyzed the amber necklace-related computational data generated from the activity of Google users from17 countries, by the application of Google Trends. Four search strategies were defined in English, Spanish, Portuguese, and Italian, for retrieving the monthly variation of relative search volume (RSV) between January 2004 and September 2018, including all categories and sources of search. Trends and 12-month predictive interests of users were analyzed by forecasting autoregressive integrated moving average models, while the influences of seasonality were evaluated by generalized additive models. The most popular queries employed for Google users were determined to qualitative analysis. P values < 0.05 were considered significant.

RESULTS

In general, RSV curves were characterized by uptrends in most studied countries over the years, without the influence of monthly or quarterly seasonality. The queries were frequently associated with a desire for additional information, with respect to the definition, usability, and teething symptoms relief promoted by amber jewelries.

CONCLUSIONS

These findings indicate an increasing interest of Google users in amber necklace-related topics in different countries.

Big Data in occupational medicine: the convergence of -omics sciences, participatory research and e-health

Background:

New occupational hazards and risks are emerging in our progressively globalized society, in which ageing, migration, wild urbanization and rapid economic growth have led to unprecedented biological, chemical and physical exposures, linked to novel technologies, products and duty cycles. A focus shift from worker health to worker/citizen and community health is crucial. One of the major revolutions of the last decades is the computerization and digitization of the work process, the so-called “work 4.0”, and of the workplace.

Objectives:

To explore the roles and implications of Big Data in the new occupational medicine settings.

Methods:

Comprehensive literature search.

Results:

Big Data are characterized by volume, variety, veracity, velocity, and value. They come both from wet-lab techniques (“molecular Big Data”) and computational infrastructures, including databases, sensors and smart devices (“computational Big Data” and “digital Big Data”).

Conclusions:

In the light of novel hazards and thanks to new analytical approaches, molecular and digital underpinnings become extremely important in occupational medicine. Computational and digital tools can enable us to uncover new relationships between exposures and work-related diseases; to monitor the public reaction to novel risk factors associated to occupational diseases; to identify exposure-related changes in disease natural history; and to evaluate preventive workplace practices and legislative measures adopted for workplace health and safety.

Psychometric properties of the Brief Symptom Inventory in nomophobic subjects: insights from preliminary confirmatory factor, exploratory factor, and clustering analyses in a sample of healthy Italian volunteers

Background

The Brief Symptom Inventory (BSI), developed by Derogatis in 1975, represents an important standardized screening instrument that enables one to quantitatively assess psychological distress and psychiatric disorders. The BSI is a 53-item self-report scale, measuring nine dimensions that can be summed up to reflect three global indices, including the General Severity Index (GSI). In the era of new information and communication technologies, nomophobia (“no mobile phobia”) is an emerging disorder, characterized by the fear of being out of mobile phone contact. Nothing is known, however, about the factor structure and reliability of the BSI in a population of nomophobic subjects. This study aimed at addressing this gap in knowledge.

Methods

A sample of 403 subjects aged 27.91±8.63 years (160 males, 39.7% of the entire sample, and 243 females, 60.3%), recruited via snowball sampling, volunteered to take part in the study. The Italian versions of the Nomophobia questionnaire and the BSI were administered. Exploratory factor analyses, confirmatory factor analyses, and clustering analysis were carried out together with correlation analysis, analysis of variance, and multivariate regression analysis.

Results

For each BSI subscale, scores were significantly higher than the norms. The nine subscales exhibited acceptable-to-good Cronbach’s alpha coefficients, varying from 0.733 for psychoticism to 0.875 for depression. Overall, the reliability of the entire instrument proved to be excellent (alpha coefficient=0.972). Furthermore, all BSI subscales as well as BSI synthetic indexes correlated with nomophobia in a significant way. Stratifying the population according to the severity of nomophobia (mild, 206 individuals, 51.1% of the sample; moderate, 167 subjects, 41.4%; and severe, 30 individuals, 7.4%), the GSI score could distinguish (P<0.001) between mild and moderate (0.99±0.71 vs 1.32±0.81) and between mild and severe (0.99±0.71 vs 1.54±0.79) nomophobia, although not between moderate and severe nomophobia (P>0.05). Similar patterns could be found for the other subscales of the BSI. Finally, looking at the fit indexes, the second-order 9-factor model best fit the data compared with the Derogatis 1-factor model.

Conclusion

The findings of our study show that the BSI is a reliable and valid instrument with acceptable psychometric properties, and can be administered to populations of nomophobic subjects.

Forecasting the West Nile Virus in the United States: An Extensive Novel Data Streams-Based Time Series Analysis and Structural Equation Modeling of Related Digital Searching Behavior

BACKGROUND

West Nile virus is an arbovirus responsible for an infection that tends to peak during the late summer and early fall. Tools monitoring Web searches are emerging as powerful sources of data, especially concerning infectious diseases such as West Nile virus.

OBJECTIVE

This study aimed at exploring the potential predictive power of West Nile virus-related Web searches.

METHODS

Different novel data streams, including Google Trends, WikiTrends, YouTube, and Google News, were used to extract search trends. Data regarding West Nile virus cases were obtained from the Centers for Disease Control and Prevention. Data were analyzed using regression, times series analysis, structural equation modeling, and clustering analysis.

RESULTS

In the regression analysis, an association between Web searches and "real-world" epidemiological figures was found. The best seasonal autoregressive integrated moving average model with explicative variable (SARIMAX) was found to be (0,1,1)x(0,1,1)4. Using data from 2004 to 2015, we were able to predict data for 2016. From the structural equation modeling, the consumption of West Nile virus-related news fully mediated the relation between Google Trends and the consumption of YouTube videos, as well as the relation between the latter variable and the number of West Nile virus cases. Web searches fully mediated the relation between epidemiological figures and the consumption of YouTube videos, as well as the relation between epidemiological data and the number of accesses to the West Nile virus-related Wikipedia page. In the clustering analysis, the consumption of news was most similar to the Web searches pattern, which was less close to the consumption of YouTube videos and least similar to the behavior of accessing West Nile virus-related Wikipedia pages.

CONCLUSIONS

Our study demonstrated an association between epidemiological data and search patterns related to the West Nile virus. Based on this correlation, further studies are needed to examine the practicality of these findings.

SleepOMICS: How Big Data Can Revolutionize Sleep Science

Sleep disorders have reached epidemic proportions worldwide, affecting the youth as well as the elderly, crossing the entire lifespan in both developed and developing countries. "Real-life" behavioral (sensor-based), molecular, digital, and epidemiological big data represent a source of an impressive wealth of information that can be exploited in order to advance the field of sleep research. It can be anticipated that big data will have a profound impact, potentially enabling the dissection of differences and oscillations in sleep dynamics and architecture at the individual level ("sleepOMICS"), thus paving the way for a targeted, "one-size-does-not-fit-all" management of sleep disorders ("precision sleep medicine").

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.

Trends of infodemiology studies: a scoping review

INTRODUCTION

The health care industry is rich in data and information. Web technologies, such as search engines and social media, have provided an opportunity for the management of user generated data in real time in the form of infodemiology studies. The aim of this study was to investigate infodemiology studies conducted during 2002-2016, and compare them based on developed, developing and in transition countries.

METHODS

This scoping review was conducted in 2017 with the help of the PRISMA guidelines. PubMed, Scopus, Science Direct, Web of Knowledge, Google Scholar, Wiley and Springer databases were searched between the years 2002 and 2016. Finally, 56 articles were included in the review and analysed.

RESULTS

The initial infodemiology studies pertain to the quality assessment of the hospital's websites. Most of the studies were on developed countries, based on flu, and published in the Journal of Medical Internet Research.

CONCLUSION

The infodemiology approach provides unmatched opportunities for the management of health data and information generated by the users. Using this potential will provide unique opportunities for the health information need assessment in real time by health librarians and thereby provide evidence based health information to the people.

Searching the Internet for psychiatric disorders among Arab and Jewish Israelis: insights from a comprehensive infodemiological survey

Israel represents a complex and pluralistic society comprising two major ethno-national groups, Israeli Jews and Israeli Arabs, which differ in terms of religious and cultural values as well as social constructs. According to the so-called “diversification hypothesis”, within the framework of e-health and in the era of new information and communication technologies, seeking online health information could be a channel to increase health literacy, especially among disadvantaged groups. However, little is known concerning digital seeking behavior and, in particular, digital mental health literacy. This study was conducted in order to fill in this gap. Concerning raw figures, unadjusted for confounding variables (time, population size, Internet penetration index, disease rate), “depression” searched in Hebrew was characterized by 1.5 times higher search volumes, slightly declining throughout time, whereas relative search volumes (RSVs) related to “depression” searched in Arabic tended to increase over the years. Similar patterns could be detected for “phobia” (in Hebrew 1.4-fold higher than in Arabic) and for “anxiety” (with the searches performed in Hebrew 2.3 times higher than in Arabic). “Suicide” in Hebrew was searched 2.0-fold more than in Arabic (interestingly for both languages search volumes exhibited seasonal cyclic patterns). Eating disorders were searched more in Hebrew: 8.0-times more for “bulimia”, whilst “anorexia” was searched in Hebrew only. When adjusting for confounding variables, association between digital seeking behavior and ethnicity remained statistically significant (p-value < 0.0001) for all psychiatric disorders considered in the current investigation, except for “bulimia” (p = 0.989). More in details, Israeli Arabs searched for mental health disorders less than Jews, apart from “depression”. Arab and Jewish Israelis, besides differing in terms of language, religion, social and cultural values, have different patterns of usage of healthcare services and provisions, as well as e-healthcare services concerning mental health. Policy- and decision-makers should be aware of this and make their best efforts to promote digital health literacy among the Arab population in Israel.

Integrating Smart Health in the US Health Care System: Infodemiology Study of Asthma Monitoring in the Google Era

BACKGROUND

With the internet's penetration and use constantly expanding, this vast amount of information can be employed in order to better assess issues in the US health care system. Google Trends, a popular tool in big data analytics, has been widely used in the past to examine interest in various medical and health-related topics and has shown great potential in forecastings, predictions, and nowcastings. As empirical relationships between online queries and human behavior have been shown to exist, a new opportunity to explore the behavior toward asthma-a common respiratory disease-is present.

OBJECTIVE

This study aimed at forecasting the online behavior toward asthma and examined the correlations between queries and reported cases in order to explore the possibility of nowcasting asthma prevalence in the United States using online search traffic data.

METHODS

Applying Holt-Winters exponential smoothing to Google Trends time series from 2004 to 2015 for the term "asthma," forecasts for online queries at state and national levels are estimated from 2016 to 2020 and validated against available Google query data from January 2016 to June 2017. Correlations among yearly Google queries and between Google queries and reported asthma cases are examined.

RESULTS

Our analysis shows that search queries exhibit seasonality within each year and the relationships between each 2 years' queries are statistically significant (P<.05). Estimated forecasting models for a 5-year period (2016 through 2020) for Google queries are robust and validated against available data from January 2016 to June 2017. Significant correlations were found between (1) online queries and National Health Interview Survey lifetime asthma (r=-.82, P=.001) and current asthma (r=-.77, P=.004) rates from 2004 to 2015 and (2) between online queries and Behavioral Risk Factor Surveillance System lifetime (r=-.78, P=.003) and current asthma (r=-.79, P=.002) rates from 2004 to 2014. The correlations are negative, but lag analysis to identify the period of response cannot be employed until short-interval data on asthma prevalence are made available.

CONCLUSIONS

Online behavior toward asthma can be accurately predicted, and significant correlations between online queries and reported cases exist. This method of forecasting Google queries can be used by health care officials to nowcast asthma prevalence by city, state, or nationally, subject to future availability of daily, weekly, or monthly data on reported cases. This method could therefore be used for improved monitoring and assessment of the needs surrounding the current population of patients with asthma.

Big Data's Role in Precision Public Health

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts.

An infodemiological investigation of the so-called "Fluad effect" during the 2014/2015 influenza vaccination campaign in Italy: Ethical and historical implications

Influenza vaccines represent a major tool to contain the clinical and epidemiological burden generated by influenza. However, in spite of their effectiveness, vaccines are victims of prejudices and false myths, which contribute to the increasing phenomenon of vaccine hesitancy and loss of confidence. Media and, mainly, new media, and information and communication technologies play a major role in disseminating health-related information. While, on the one hand, they can be extremely promising in promoting disease prevention, on the other hand, they can also have a negative impact on population's health attitudes and behaviors when delivering information not based on scientific evidences. The "Fluad-case" is an excellent example of the crucial role of an adequate information campaign. Following the cluster of deaths allegedly related to the administration of the adjuvanted influenza vaccine "Fluad" during the 2014-2015 influenza campaign, the Italian health authorities and regulatory bodies decided the withdrawal of two potentially contaminated Fluad batches. This fostered a huge media coverage, with resulted in negatively impacting on influenza vaccination coverage. Monitoring and tracking the Fluad-related web searches, we showed that Liguria resulted the Italian region with the highest number of Fluad-related website searches and that, interestingly, Fluad was searched also in Regions in which this vaccine was not distributed. A positive moderate correlation between accessing Fluad-related websites and overall influenza vaccination coverage was found (r = 0.66 ([95%CI 0.29-0.86], p = 0.0026). Considering subjects ≥65 years, who are the subjects for which the Fluad vaccination is recommended, the correlation resulted r = 0.49 ([95%CI 0.03-0.78], p = 0.0397). As such, health authorities and decision-makers should promote high-quality communication campaigns in order to raise awareness of vaccination practices.

The Media Response to the ACGME's 2017 Relaxed Resident Duty-Hour Restrictions

PURPOSE

In March 2017, the ACGME relaxed resident duty-hour restrictions to allow first-year residents to work 24-hour shifts, affecting the internship experience of incoming radiology residents. The aim of this study was to assess the media response to this duty-hour change, comparing news articles with favorable and unfavorable views.

METHODS

Google News was used to identify 36 relevant unique news articles published over a 4-week period after the announcement. Articles' stance was categorized as favorable, unfavorable, or neutral. Additional article characteristics were explored.

RESULTS

Article sources were 58% national, 22% local, and 20% medical news. Article stance was most commonly unfavorable for national news sources (48%), compared with neutral for local (62%) and medical (72%) news sources. Most common reasons for unfavorable stance were sleep deprivation (n = 11), medical errors (n = 11), residents' health (n = 9), risk for car accidents (n = 9), a patriarchal hazing system (n = 6), and work-life balance (n = 5). Most common reasons for favorable stance were impact on resident education (n = 7) and continuity of care (n = 7). Supporting data were cited by 38% of unfavorable and 100% of favorable articles. Unfavorable articles most commonly quoted physicians affiliated with resident advocacy groups; favorable articles most commonly quoted physicians affiliated with the ACGME.

CONCLUSIONS

The relaxed duty-hour restrictions received an overall unfavorable media response, particularly in nonmedical news sources, driven by concerns regarding sleep-deprived doctors. Favorable articles ubiquitously cited data supporting the safety of relaxed duty hour restrictions. Further research is warranted to better understand the impact of relaxed resident duty-hour limits on sleep deprivation, residents' health and education, and the quality of patient care.

Discrepancies Between Classic and Digital Epidemiology in Searching for the Mayaro Virus: Preliminary Qualitative and Quantitative Analysis of Google Trends

Background

Mayaro virus (MAYV), first discovered in Trinidad in 1954, is spread by the Haemagogus mosquito. Small outbreaks have been described in the past in the Amazon jungles of Brazil and other parts of South America. Recently, a case was reported in rural Haiti.

Objective

Given the emerging importance of MAYV, we aimed to explore the feasibility of exploiting a Web-based tool for monitoring and tracking MAYV cases.

Methods

Google Trends is an online tracking system. A Google-based approach is particularly useful to monitor especially infectious diseases epidemics. We searched Google Trends from its inception (from January 2004 through to May 2017) for MAYV-related Web searches worldwide.

Results

We noted a burst in search volumes in the period from July 2016 (relative search volume [RSV]=13%) to December 2016 (RSV=18%), with a peak in September 2016 (RSV=100%). Before this burst, the average search activity related to MAYV was very low (median 1%). MAYV-related queries were concentrated in the Caribbean. Scientific interest from the research community and media coverage affected digital seeking behavior.

Conclusions

MAYV has always circulated in South America. Its recent appearance in the Caribbean has been a source of concern, which resulted in a burst of Internet queries. While Google Trends cannot be used to perform real-time epidemiological surveillance of MAYV, it can be exploited to capture the public’s reaction to outbreaks. Public health workers should be aware of this, in that information and communication technologies could be used to communicate with users, reassure them about their concerns, and to empower them in making decisions affecting their health.

On status epilepticus and pins: A systematic content analysis

Status epilepticus (SE) can be defined as abnormally prolonged, persistent, or recurrent clinical and/or electrographic epileptic activity and, as such, is a challenging medical emergency requiring an aggressive treatment aimed at promptly terminating the seizures. It imposes a relevant clinical burden, both in terms of comorbidity and mortality. In the era of the Web 2.0, most people search the Web to obtain SE-related information. The current investigation aimed at qualitatively characterizing the pins related to SE: Pinterest, "the world's catalog of ideas", is a visual social networking site that enables users to freely upload visual material, to bookmark, and to share it (repin). Using SE as a keyword, 192 pins were extracted and analyzed on the basis of their content. Fifty-five were found to meet the inclusion criteria. Fifty-six point four percent of the pins reported at least one cause of SE, the most quoted of which being remote brain injuries (47.3% of the pins); 54.5% and 45.5% of the included pins reported SE symptoms and diagnosis, respectively; 72.7% and 40.0% of pins focused on SE treatment and on prognosis, respectively; and 50.9%, 30.9%, and 40.0% of the pins were intended for physicians, medical/nursing students, and lay people, respectively. Only 12.7% of pins were patient-centered and devoted to fund-raising and advocacy. In the field of neurological diseases, Pinterest, despite being a "pinstructive" tool, is too much overlooked and underused for advocacy purposes. Healthcare workers and stakeholders should be aware of the opportunities offered by Pinterest and exploit this visual social networking site for raising awareness of the life-threatening condition of SE, promoting fund-raising campaigns.

Readability of Wikipedia Pages on Autoimmune Disorders: Systematic Quantitative Assessment

Background

In the era of new information and communication technologies, the Internet is being increasingly accessed for health-related information. Indeed, recently published patient surveys of people with autoimmune disorders confirmed that the Internet was reported as one of the most important health information sources. Wikipedia, a free online encyclopedia launched in 2001, is generally one of the most visited websites worldwide and is often consulted for health-related information.

Objective

The main objective of this investigation was to quantitatively assess whether the Wikipedia pages related to autoimmune disorders can be easily accessed by patients and their families, in terms of readability.

Methods

We obtained and downloaded a list of autoimmune disorders from the American Autoimmune Related Diseases Association (AARDA) website. We analyzed Wikipedia articles for their overall level of readability with 6 different quantitative readability scales: (1) the Flesch Reading Ease, (2) the Gunning Fog Index, (3) the Coleman-Liau Index, (4) the Flesch-Kincaid Grade Level, (5) the Automated Readability Index (ARI), and (6) the Simple Measure of Gobbledygook (SMOG). Further, we investigated the correlation between readability and clinical, pathological, and epidemiological parameters. Moreover, each Wikipedia analysis was assessed according to its content, breaking down the readability indices by main topic of each part (namely, pathogenesis, treatment, diagnosis, and prognosis plus a section containing paragraphs not falling into any of the previous categories).

Results

We retrieved 134 diseases from the AARDA website. The Flesch Reading Ease yielded a mean score of 24.34 (SD 10.73), indicating that the sites were very difficult to read and best understood by university graduates, while mean Gunning Fog Index and ARI scores were 16.87 (SD 2.03) and 14.06 (SD 2.12), respectively. The Coleman-Liau Index and the Flesch-Kincaid Grade Level yielded mean scores of 14.48 (SD 1.57) and 14.86 (1.95), respectively, while the mean SMOG score was 15.38 (SD 1.37). All the readability indices confirmed that the sites were suitable for a university graduate reading level. We found no correlation between readability and clinical, pathological, and epidemiological parameters. Differences among the different sections of the Wikipedia pages were statistically significant.

Conclusions

Wikipedia pages related to autoimmune disorders are characterized by a low level of readability. The onus is, therefore, on physicians and health authorities to improve the health literacy skills of patients and their families and to create, together with patients themselves, disease-specific readable sites, disseminating highly accessible health-related online information, in terms of both clarity and conciseness.

The Public Health Impact of the So-Called "Fluad Effect" on the 2014/2015 Influenza Vaccination Campaign in Italy: Ethical Implications for Health-Care Workers and Health Communication Practitioners

Seasonal influenza, causing complications, hospitalizations and deaths, generates a serious socio-economic burden, especially among elderly and high-risk subjects, as well as among adult individuals. Despite the availability and active free-of charge offer of influenza vaccines, vaccine coverage rates remain low and far from the target established by the Ministry of Health. Notwithstanding their effectiveness, vaccines are victims of prejudices and false myths, that contribute to the increasing phenomenon of vaccine hesitancy and loss of confidence. Media and, in particular, new media and information and communication technologies (ICTs) play a major role in disseminating health-related information. They are extremely promising devices for delivering health education and promoting disease prevention, including immunization. However, they can also have a negative impact on population's health attitudes and behaviors when channeling wrong, misleading information. During the 2014/2015 influenza vaccination campaign, the report of four deaths allegedly caused by administration of an adjuvanted influenza vaccine, Fluad - the so-called "Fluad case" - received an important media coverage, which contributed to the failure of the vaccination campaign, dramatically reducing the influenza vaccine uptake. In the extant literature, there is a dearth of information concerning the effect of the "Fluad case". The current study aims at quantifying the impact of the "Fluad effect" at the level of the Local Health Unit 3 (LHU3) ASL3 Genovese, Genoa, Italy. Ethical implications for health-care workers and health communication practitioners are also envisaged.

Public health awareness of autoimmune diseases after the death of a celebrity

Autoimmune disorders impose a high burden, in terms of morbidity and mortality worldwide. Vasculitis is an autoimmune disorder that causes inflammation and destruction of blood vessels. Harold Allen Ramis, a famous American actor, director, writer, and comedian, died on the February 24, 2014, of complications of an autoimmune inflammatory vasculitis. To investigate the relation between interests and awareness of an autoimmune disease after a relevant event such as the death of a celebrity, we systematically mined Google Trends, Wikitrends, Google News, YouTube, and Twitter, in any language, from their inception until October 31, 2016. Twenty-eight thousand eight hundred fifty-two tweets; 4,133,615 accesses to Wikipedia; 6780 news; and 11,400 YouTube videos were retrieved, processed, and analyzed. The Harold Ramis death of vasculitis resulted into an increase in vasculitis-related Google searches, Wikipedia page accesses, and tweet production, documenting a peak in February 2014. No trend could be detected concerning uploading YouTube videos. The usage of Big Data is promising in the fields of immunology and rheumatology. Clinical practitioners should be aware of this emerging phenomenon.

Infodemiological data concerning silicosis in the USA in the period 2004-2010 correlating with real-world statistical data

This article reports data concerning silicosis-related web-activities using Google Trends (GT) capturing the Internet behavior in the USA for the period 2004-2010. GT-generated data were then compared with the most recent available epidemiological data of silicosis mortality obtained from the Centers for Disease Control and Prevention for the same study period. Statistically significant correlations with epidemiological data of silicosis (r=0.805, p-value <0.05) and other related web searches were found. The temporal trend well correlated with the epidemiological data, as well as the geospatial distribution of the web-activities with the geographic epidemiology of silicosis.