Google Trends en Gastroenterología / Google Trends in Gastroenterology

Google Trends (GT) is an online portal that provides data on user search patterns. It is currently widely used in the vast majority of medical specialties. Objective: to analyze publications in gastroenterology that have used GT as an epidemiological tool. Methods: Using PubMed, Lilacs, Google Schoolar Academic and Scopus, we searched for gastroenterology articles that contained GT in their title or abstract between the years 2011 to 2021. Titles/abstracts had to also include at least one out of 49 terms related to digestive diseases from symptoms to treatments. Results: The 30 articles selected addressed topics such as symptoms, different pathologies including infectious, diagnostic methods and diets, among others. Conclusions: GT is a very useful tool to measure what people search for on the Internet and allows us to detect epidemic outbreaks, evaluate the impact of the days dedicated to some pathology as well as the impact of publications on the network of the public and doctors.

Google Trends (GT) es un portal en línea que proporciona datos sobre patrones de búsqueda de los usuarios. Actualmente muy utilizado en la gran mayoría de las especialidades médicas. Objetivo: analizar las publicaciones en gastroenterología que han usado a GT como herramienta epidemiológica. Material y Método: Mediante PubMed, Lilacs, Google Schoolar Academic y Scopus buscamos los artículos de gastroenterología que contenían a GT en su título o en el resumen entre los años 2011 a 2021. Los títulos/resúmenes debían incluir además, al menos uno de 49 términos relacionados a enfermedades digestivas desde síntomas hasta tratamientos. Resultados: Los 30 artículos seleccionados abordan temas como síntomas, distintas patologías incluyendo infecciosas, métodos diagnósticos y dietas, entre otras. Conclusiones: GT es una herramienta de gran utilidad para medir lo que las personas buscan en internet y permite detectar brotes epidémicos, evaluar el impacto de los días dedicados a de alguna patología así como el impacto de publicaciones en la red del público y médicos.

Associations between COVID-19 mobility restrictions and economic, mental health, and suicide-related concerns in the US using cellular phone GPS and Google search volume data.

During the COVID-19 pandemic, US populations have experienced elevated rates of financial and psychological distress that could lead to increases in suicide rates. Rapid ongoing mental health monitoring is critical for early intervention, especially in regions most affected by the pandemic, yet traditional surveillance data are available only after long lags. Novel information on real-time population isolation and concerns stemming from the pandemic's social and economic impacts, via cellular mobility tracking and online search data, are potentially important interim surveillance resources. Using these measures, we employed transfer function model time-series analyses to estimate associations between daily mobility indicators (proportion of cellular devices completely at home and time spent at home) and Google Health Trends search volumes for terms pertaining to economic stress, mental health, and suicide during 2020 and 2021 both nationally and in New York City. During the first pandemic wave in early-spring 2020, over 50% of devices remained completely at home and searches for economic stressors exceeded 60,000 per 10 million. We found large concurrent associations across analyses between declining mobility and increasing searches for economic stressor terms (national proportion of devices at home: cross-correlation coefficient (CC) = 0.6 (p-value <0.001)). Nationally, we also found strong associations between declining mobility and increasing mental health and suicide-related searches (time at home: mood/anxiety CC = 0.53 (<0.001), social stressor CC = 0.51 (<0.001), suicide seeking CC = 0.37 (0.006)). Our findings suggest that pandemic-related isolation coincided with acute economic distress and may be a risk factor for poor mental health and suicidal behavior. These emergent relationships warrant ongoing attention and causal assessment given the potential for long-term psychological impact and suicide death. As US populations continue to face stress, Google search data can be used to identify possible warning signs from real-time changes in distributions of population thought patterns.

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.

Wikipedia, Google Trends and Diet: Assessment of Temporal Trends in the Internet Users' Searches in Italy before and during COVID-19 Pandemic.

We obtained data from Google Trends and Wikipedia in order to assess whether an analysis of Internet searches could provide information on the Internet users' behaviour/interest in diets. Differences in seasonality, year and before/during COVID-19 pandemic were assessed. From Wikipedia, we extracted the number of times a page is viewed by users, aggregated on monthly and seasonal bases. We also used Google Trends to evaluate the frequency of the users' web searches. The Mediterranean diet was the most frequently (33.9%), followed by the pescatarian diet (9.0%). Statistically, significant seasonal differences were found for the Mediterranean, vegetarian, Atkins, Scarsdale, and zone diets and pescetarianism. The most commonly searched diet and consequent diet-related queries on Google resulted to be: Dukan diet, Dukan and weight loss. Ketogenic, FODMAP and intermittent fasting diets were statistically more frequently searched during the pandemic compared with before. Our data show a different trend of searches based on the seasonality, year and the pandemic. These data could be useful for scientists, practitioners and policy makers because they can inform educational campaigns via the Internet, especially in periods when the population is more receptive.

Changes in National Google Trends and Local Healthcare Utilization After High-Impact Gastroenterology Publications.

INTRODUCTION: We examined national Google Trends and local healthcare utilization after 3 high-impact gastroenterology publications. METHODS: Changes in US Google Trends and Olmsted County health utilization were studied. RESULTS: Publication views within 30 days were 51,458 (Imperiale), 49,759 (Pimentel), and 18,750 (Gomm). Colonoscopy searches (P = 0.04) and Cologuard tests performed (P < 0.01) increased while colonoscopies decreased (P < 0.01). Searches for rifaximin (P = 0.05), irritable bowel syndrome (P < 0.01), diarrhea (P < 0.01), and rifaximin prescriptions (P = 0.02) increased. Increase in hydrogen-2 blocker searches (P = 0.02) and prescriptions (P < 0.01) and gastroesophageal reflux disease (P < 0.01) and dementia office visits (P < 0.01) occurred. DISCUSSION: High-impact gastroenterology publications influence Google searches and local population-based healthcare utilization.

Public Interest in Immunity and the Justification for Intervention in the Early Stages of the COVID-19 Pandemic: Analysis of Google Trends Data.

BACKGROUND: The use of social big data is an important emerging concern in public health. Internet search volumes are useful data that can sensitively detect trends of the public's attention during a pandemic outbreak situation. OBJECTIVE: Our study aimed to analyze the public's interest in COVID-19 proliferation, identify the correlation between the proliferation of COVID-19 and interest in immunity and products that have been reported to confer an enhancement of immunity, and suggest measures for interventions that should be implemented from a health and medical point of view. METHODS: To assess the level of public interest in infectious diseases during the initial days of the COVID-19 outbreak, we extracted Google search data from January 20, 2020, onward and compared them to data from March 15, 2020, which was approximately 2 months after the COVID-19 outbreak began. In order to determine whether the public became interested in the immune system, we selected coronavirus, immune, and vitamin as our final search terms. RESULTS: The increase in the cumulative number of confirmed COVID-19 cases that occurred after January 20, 2020, had a strong positive correlation with the search volumes for the terms coronavirus (R=0.786; P<.001), immune (R=0.745; P<.001), and vitamin (R=0.778; P<.001), and the correlations between variables were all mutually statistically significant. Moreover, these correlations were confirmed on a country basis when we restricted our analyses to the United States, the United Kingdom, Italy, and Korea. Our findings revealed that increases in search volumes for the terms coronavirus and immune preceded the actual occurrences of confirmed cases. CONCLUSIONS: Our study shows that during the initial phase of the COVID-19 crisis, the public's desire and actions of strengthening their own immune systems were enhanced. Further, in the early stage of a pandemic, social media platforms have a high potential for informing the public about potentially helpful measures to prevent the spread of an infectious disease and provide relevant information about immunity, thereby increasing the public's knowledge.

Google Trends for Pain Search Terms in the World's Most Populated Regions Before and After the First Recorded COVID-19 Case: Infodemiological Study.

BACKGROUND: Web-based analysis of search queries has become a very useful method in various academic fields for understanding timely and regional differences in the public interest in certain terms and concepts. Particularly in health and medical research, Google Trends has been increasingly used over the last decade. OBJECTIVE: This study aimed to assess the search activity of pain-related parameters on Google Trends from among the most populated regions worldwide over a 3-year period from before the report of the first confirmed COVID-19 cases in these regions (January 2018) until December 2020. METHODS: Search terms from the following regions were used for the analysis: India, China, Europe, the United States, Brazil, Pakistan, and Indonesia. In total, 24 expressions of pain location were assessed. Search terms were extracted using the local language of the respective country. Python scripts were used for data mining. All statistical calculations were performed through exploratory data analysis and nonparametric Mann-Whitney U tests. RESULTS: Although the overall search activity for pain-related terms increased, apart from pain entities such as headache, chest pain, and sore throat, we observed discordant search activity. Among the most populous regions, pain-related search parameters for shoulder, abdominal, and chest pain, headache, and toothache differed significantly before and after the first officially confirmed COVID-19 cases (for all, P<.001). In addition, we observed a heterogenous, marked increase or reduction in pain-related search parameters among the most populated regions. CONCLUSIONS: As internet searches are a surrogate for public interest, we assume that our data are indicative of an increased incidence of pain after the onset of the COVID-19 pandemic. However, as these increased incidences vary across geographical and anatomical locations, our findings could potentially facilitate the development of specific strategies to support the most affected groups.

Information-Seeking Patterns During the COVID-19 Pandemic Across the United States: Longitudinal Analysis of Google Trends Data.

BACKGROUND: The COVID-19 pandemic has impacted people's lives at unprecedented speed and scale, including how they eat and work, what they are concerned about, how much they move, and how much they can earn. Traditional surveys in the area of public health can be expensive and time-consuming, and they can rapidly become outdated. The analysis of big data sets (such as electronic patient records and surveillance systems) is very complex. Google Trends is an alternative approach that has been used in the past to analyze health behaviors; however, most existing studies on COVID-19 using these data examine a single issue or a limited geographic area. This paper explores Google Trends as a proxy for what people are thinking, needing, and planning in real time across the United States. OBJECTIVE: We aimed to use Google Trends to provide both insights into and potential indicators of important changes in information-seeking patterns during pandemics such as COVID-19. We asked four questions: (1) How has information seeking changed over time? (2) How does information seeking vary between regions and states? (3) Do states have particular and distinct patterns in information seeking? (4) Do search data correlate with-or precede-real-life events? METHODS: We analyzed searches on 38 terms related to COVID-19, falling into six themes: social and travel; care seeking; government programs; health programs; news and influence; and outlook and concerns. We generated data sets at the national level (covering January 1, 2016, to April 15, 2020) and state level (covering January 1 to April 15, 2020). Methods used include trend analysis of US search data; geographic analyses of the differences in search popularity across US states from March 1 to April 15, 2020; and principal component analysis to extract search patterns across states. RESULTS: The data showed high demand for information, corresponding with increasing searches for coronavirus linked to news sources regardless of the ideological leaning of the news source. Changes in information seeking often occurred well in advance of action by the federal government. The popularity of searches for unemployment claims predicted the actual spike in weekly claims. The increase in searches for information on COVID-19 care was paralleled by a decrease in searches related to other health behaviors, such as urgent care, doctor's appointments, health insurance, Medicare, and Medicaid. Finally, concerns varied across the country; some search terms were more popular in some regions than in others. CONCLUSIONS: COVID-19 is unlikely to be the last pandemic faced by the United States. Our research holds important lessons for both state and federal governments in a fast-evolving situation that requires a finger on the pulse of public sentiment. We suggest strategic shifts for policy makers to improve the precision and effectiveness of non-pharmaceutical interventions and recommend the development of a real-time dashboard as a decision-making tool.

The Causality Inference of Public Interest in Restaurants and Bars on Daily COVID-19 Cases in the United States: Google Trends Analysis.

BACKGROUND: The COVID-19 pandemic has affected virtually every region in the world. At the time of this study, the number of daily new cases in the United States was greater than that in any other country, and the trend was increasing in most states. Google Trends provides data regarding public interest in various topics during different periods. Analyzing these trends using data mining methods may provide useful insights and observations regarding the COVID-19 outbreak. OBJECTIVE: The objective of this study is to consider the predictive ability of different search terms not directly related to COVID-19 with regard to the increase of daily cases in the United States. In particular, we are concerned with searches related to dine-in restaurants and bars. Data were obtained from the Google Trends application programming interface and the COVID-19 Tracking Project. METHODS: To test the causation of one time series on another, we used the Granger causality test. We considered the causation of two different search query trends related to dine-in restaurants and bars on daily positive cases in the US states and territories with the 10 highest and 10 lowest numbers of daily new cases of COVID-19. In addition, we used Pearson correlations to measure the linear relationships between different trends. RESULTS: Our results showed that for states and territories with higher numbers of daily cases, the historical trends in search queries related to bars and restaurants, which mainly occurred after reopening, significantly affected the number of daily new cases on average. California, for example, showed the most searches for restaurants on June 7, 2020; this affected the number of new cases within two weeks after the peak, with a P value of .004 for the Granger causality test. CONCLUSIONS: Although a limited number of search queries were considered, Google search trends for restaurants and bars showed a significant effect on daily new cases in US states and territories with higher numbers of daily new cases. We showed that these influential search trends can be used to provide additional information for prediction tasks regarding new cases in each region. These predictions can help health care leaders manage and control the impact of the COVID-19 outbreak on society and prepare for its outcomes.

Decreased public pursuit of cancer-related information during the COVID-19 pandemic in the United States.

BACKGROUND: In response to the prioritization of healthcare resources towards the COVID-19 pandemic, routine cancer screening and diagnostic have been disrupted, potentially explaining the apparent COVID-era decline in cancer cases and mortality. In this study, we identified temporal trends in public interest in cancer-related health information using the nowcasting tool Google Trends. METHODS: We used Google Trends to query search terms related to cancer types for short-term (September 2019-September 2020) and long-term (September 2016-September 2020) trends in the US. We compared average relative search volumes (RSV) for specified time ranges to detect recent and seasonal variation. RESULTS: General search interest declined for all cancer types beginning in March 2020, with changes in search interest for "Breast cancer," "Colorectal cancer," and "Melanoma" of - 30.6%, - 28.2%, and - 26.7%, respectively, and compared with the mean RSV of the two previous months. In the same time range, search interest for "Telemedicine" has increased by + 907.1% and has reached a 4-year peak with a sustained increased level of search interest. Absolute cancer mortality has declined and is presently at a 4-year low; however, search interest in cancer has been recuperating since July 2020. CONCLUSION: We observed a marked decline in searches for cancer-related health information that mirrors the reduction in new cancer diagnoses and cancer mortality during the COVID-19 pandemic. Health professions need to be prepared for the coming demand for cancer-related healthcare, foreshadowed by recovering interest in cancer-related information on Google Trends.

A predictive internet-based model for COVID-19 hospitalization census.

The COVID-19 pandemic has strained hospital resources and necessitated the need for predictive models to forecast patient care demands in order to allow for adequate staffing and resource allocation. Recently, other studies have looked at associations between Google Trends data and the number of COVID-19 cases. Expanding on this approach, we propose a vector error correction model (VECM) for the number of COVID-19 patients in a healthcare system (Census) that incorporates Google search term activity and healthcare chatbot scores. The VECM provided a good fit to Census and very good forecasting performance as assessed by hypothesis tests and mean absolute percentage prediction error. Although our study and model have limitations, we have conducted a broad and insightful search for candidate Internet variables and employed rigorous statistical methods. We have demonstrated the VECM can potentially be a valuable component to a COVID-19 surveillance program in a healthcare system.

Google search volume trends for cancer screening terms during the COVID-19 pandemic.

The COVID-19 pandemic has led to delays in cancer diagnosis, in part due to postponement of cancer screening. We used Google Trends data to assess public attention to cancer screening during the first peak of the COVID-19 pandemic. Search volume for terms related to established cancer screening tests ("colonoscopy," "mammogram," "lung cancer screening," and "pap smear") showed a marked decrease of up to 76% compared to the pre-pandemic period, a significantly greater drop than for search volume for terms denoting common chronic diseases. Maintaining awareness of cancer screening during future public health crises may decrease delays in cancer diagnosis.

The Popularity of the Biologically-Based Therapies During Coronavirus Pandemic Among the Google Users in the USA, UK, Germany, Italy and France.

OBJECT: The aim of this retrospective infodemiological study was to evaluate people's interests in biologically-based (B-B) complementary and alternative medicine (CAM) therapies such as herbs, foods, and supplements during the coronavirus pandemic via analysis of Google search engine statistics. DESIGN & SETTINGS: The category, period, and regions selected in the Google Trends were "health," "15 January-15 May 2020," in the United States of America (USA), the United Kingdom (UK), Germany, Italy, and France, respectively. The most commonly searched herbs, foods and supplements (n = 32) during the pandemic were determined from a pool of keywords (n = 1286) based on the terms' relative search volumes (RSVs) within the last five years. Correlation analyses were conducted to investigate associations between coronavirus-related parameters with each keyword's RSV for each country. Selected keywords (n = 25) were analyzed using the gtrendsR package in the R programming language; the ggplot2 package was used to visualize the data, the Prophet package was used to estimate the time series, and the dplyr package was used to create the data frame. RESULTS: Significantly strong positive correlations were identified between daily RSVs of the terms "black seed," "vitamin C," "zinc," and "quercetin," and search queries for "coronavirus" and "COVID-19" in the USA (Spearman's correlation coefficient > 0.8, p < 0.05), and between the RSVs of the terms "vitamin C" and "zinc," and daily search queries for "coronavirus" and/or "COVID-19" in the UK (Spearman's correlation coefficient > 0.8, p < 0.05). CONCLUSION: Google Trends can be a beneficial tool for following public interest in identifying outbreak-related misinformation, and scientific studies and statements from authorities and the media play a potential role in driving internet searches.

Use Internet search data to accurately track state level influenza epidemics.

For epidemics control and prevention, timely insights of potential hot spots are invaluable. Alternative to traditional epidemic surveillance, which often lags behind real time by weeks, big data from the Internet provide important information of the current epidemic trends. Here we present a methodology, ARGOX (Augmented Regression with GOogle data CROSS space), for accurate real-time tracking of state-level influenza epidemics in the United States. ARGOX combines Internet search data at the national, regional and state levels with traditional influenza surveillance data from the Centers for Disease Control and Prevention, and accounts for both the spatial correlation structure of state-level influenza activities and the evolution of people's Internet search pattern. ARGOX achieves on average 28% error reduction over the best alternative for real-time state-level influenza estimation for 2014 to 2020. ARGOX is robust and reliable and can be potentially applied to track county- and city-level influenza activity and other infectious diseases.