scholarly journals Will I die of coronavirus? Google Trends data reveal that politics determine virus fears

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258189
Author(s):  
Joan C. Timoneda ◽  
Sebastián Vallejo Vera
Keyword(s):  
General Population ◽  
Epidemiological Data ◽  
Google Trends ◽  
Search Queries ◽  
Search Volume ◽  
Political Preferences ◽  
2016 Election ◽  
Election Results ◽  
Epidemiological Trends ◽  
Abundant Data

Is Google Trends (GT) useful to survey populations? Extant work has shown that certain search queries reflect the attitudes of hard-to-survey populations, but we do not know if this extends to the general population. In this article, we leverage abundant data from the Covid-19 pandemic to assess whether people’s worries about the pandemic match epidemiological trends as well as political preferences. We use the string ‘will I die from coronavirus’ on GT as the measure for people’s level of distress regarding Covid-19. We also test whether concern for coronavirus is a partisan issue by contrasting GT data and 2016 election results. We find strong evidence that (1) GT search volume close matches epidemiological data and (2) significant differences exist between states that supported Clinton or Trump in 2016.

scholarly journals Using Google Trends to Examine the Spatio-Temporal Incidence and Behavioral Patterns of Dengue Disease: A Case Study in Metropolitan Manila, Philippines

2018 ◽  
Author(s):  
Howell T. Ho ◽  
Thaddeus M. Carvajal ◽  
John Robert Bautista ◽  
Jayson Dale R. Capistrano ◽  
Katherine M. Viacrusis ◽  
...  
Keyword(s):  
Thematic Analysis ◽  
Cross Correlation ◽  
Temporal Relationship ◽  
The Philippines ◽  
Google Trends ◽  
Health Concern ◽  
Epidemiological Methods ◽  
Search Queries ◽  
Search Volume ◽  
Dengue Outbreaks

AbstractDengue is a major public health concern and an economic burden in the Philippines. Despite the country’s improved dengue surveillance, it still suffers from various setbacks and therefore needs to be complemented with alternative approaches. Previous studies have demonstrated the potential of internet-based surveillance such as Google Dengue Trends (GDT) in supplementing current epidemiological methods for predicting future dengue outbreaks and patterns. With this, our study aims to assess the temporal relationship of GDT and dengue incidence in Metropolitan Manila from previous years and examine web search behavior of the population towards the disease. The study collated and organized the population statistics and reported dengue cases in Metropolitan Manila from respective government agencies to calculate the spatial and temporal dengue incidence. The relative search volume of the term ‘dengue’ and top dengue-related search queries in Metropolitan Manila were obtained and organized from the Google trends platform. Data processing of GDT and dengue incidence was performed by conducting an ‘adjustment’ procedure and subsequently used for correlation and cross-correlation analyses. Moreover, a thematic analysis was employed on the top dengue-related search queries. Results revealed a high temporal relationship between GDT and dengue incidence when either one of the variables is adjusted. Cross-correlation showed that there is delayed effect (1-2 weeks) of GDT to dengue incidence, demonstrating its potential in predicting future dengue outbreaks and patterns in Metropolitan Manila. Thematic analysis of dengue-related search queries indicated 5 categories namely; (a) dengue, (b) sign and symptoms of dengue, (c) treatment and prevention, (d) mosquito and (e) other diseases where the majority of the search queries was ‘signs and symptoms’ which indicate the health-seeking behavior of the population towards the disease.

scholarly journals Using Application Programming Interfaces to Access Google Data for Health Research: Protocol for a Methodological Framework (Preprint)

2019 ◽  
Author(s):  
Anne Zepecki ◽  
Sylvia Guendelman ◽  
John DeNero ◽  
Ndola Prata
Keyword(s):  
Real Time ◽  
Birth Control ◽  
Google Trends ◽  
Search Term ◽  
Health Trends ◽  
Search Queries ◽  
Search Volume ◽  
Application Programming ◽  
Relative Search Volume ◽  
Google Search

BACKGROUND Individuals are increasingly turning to search engines like Google to obtain health information and access resources. Analysis of Google search queries offers a novel approach, which is part of the methodological toolkit for infodemiology or infoveillance researchers, to understanding population health concerns and needs in real time or near-real time. While searches predominantly have been examined with the Google Trends website tool, newer application programming interfaces (APIs) are now available to academics to draw a richer landscape of searches. These APIs allow users to write code in languages like Python to retrieve sample data directly from Google servers. OBJECTIVE The purpose of this paper is to describe a novel protocol to determine the top queries, volume of queries, and the top sites reached by a population searching on the web for a specific health term. The protocol retrieves Google search data obtained from three Google APIs: Google Trends, Google Health Trends (also referred to as Flu Trends), and Google Custom Search. METHODS Our protocol consisted of four steps: (1) developing a master list of top search queries for an initial search term using Google Trends, (2) gathering information on relative search volume using Google Health Trends, (3) determining the most popular sites using Google Custom Search, and (4) calculating estimated total search volume. We tested the protocol following key procedures at each step and verified its usefulness by examining search traffic on <i>birth control</i> in 2017 in the United States. Two separate programmers working independently achieved similar results with insignificant variation due to sample variability. RESULTS We successfully tested the methodology on the initial search term <i>birth control</i>. We identified top search queries for <i>birth control</i>, of which <i>birth control pill</i> was the most popular and obtained the relative and estimated total search volume for the top queries: relative search volume was 0.54 for the pill, corresponding to an estimated 9.3-10.7 million searches. We used the estimates of the proportion of search activity for the top queries to arrive at a generated list of the most popular websites: for the pill, the Planned Parenthood website was the top site. CONCLUSIONS The proposed methodological framework demonstrates how to retrieve Google query data from multiple Google APIs and provides thorough documentation required to systematically identify search queries and websites, as well as estimate relative and total search volume of queries in real time or near-real time in specific locations and time periods. Although the protocol needs further testing, it allows researchers to replicate the steps and shows promise in advancing our understanding of population-level health concerns. INTERNATIONAL REGISTERED REPORT RR1-10.2196/16543

scholarly journals Using Application Programming Interfaces to Access Google Data for Health Research: Protocol for a Methodological Framework

10.2196/16543 ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. e16543
Author(s):  
Anne Zepecki ◽  
Sylvia Guendelman ◽  
John DeNero ◽  
Ndola Prata
Keyword(s):  
Real Time ◽  
Birth Control ◽  
Google Trends ◽  
Search Term ◽  
Health Trends ◽  
Search Queries ◽  
Search Volume ◽  
Application Programming ◽  
Relative Search Volume ◽  
Google Search

Background Individuals are increasingly turning to search engines like Google to obtain health information and access resources. Analysis of Google search queries offers a novel approach, which is part of the methodological toolkit for infodemiology or infoveillance researchers, to understanding population health concerns and needs in real time or near-real time. While searches predominantly have been examined with the Google Trends website tool, newer application programming interfaces (APIs) are now available to academics to draw a richer landscape of searches. These APIs allow users to write code in languages like Python to retrieve sample data directly from Google servers. Objective The purpose of this paper is to describe a novel protocol to determine the top queries, volume of queries, and the top sites reached by a population searching on the web for a specific health term. The protocol retrieves Google search data obtained from three Google APIs: Google Trends, Google Health Trends (also referred to as Flu Trends), and Google Custom Search. Methods Our protocol consisted of four steps: (1) developing a master list of top search queries for an initial search term using Google Trends, (2) gathering information on relative search volume using Google Health Trends, (3) determining the most popular sites using Google Custom Search, and (4) calculating estimated total search volume. We tested the protocol following key procedures at each step and verified its usefulness by examining search traffic on birth control in 2017 in the United States. Two separate programmers working independently achieved similar results with insignificant variation due to sample variability. Results We successfully tested the methodology on the initial search term birth control. We identified top search queries for birth control, of which birth control pill was the most popular and obtained the relative and estimated total search volume for the top queries: relative search volume was 0.54 for the pill, corresponding to an estimated 9.3-10.7 million searches. We used the estimates of the proportion of search activity for the top queries to arrive at a generated list of the most popular websites: for the pill, the Planned Parenthood website was the top site. Conclusions The proposed methodological framework demonstrates how to retrieve Google query data from multiple Google APIs and provides thorough documentation required to systematically identify search queries and websites, as well as estimate relative and total search volume of queries in real time or near-real time in specific locations and time periods. Although the protocol needs further testing, it allows researchers to replicate the steps and shows promise in advancing our understanding of population-level health concerns. International Registered Report Identifier (IRRID) RR1-10.2196/16543

scholarly journals Google, Tell Me. Is He Gay? Masculinity, Heterosexuality, and Gendered Anxieties in Google Search Queries about Sexuality

2021 ◽  
pp. 073112142110019
Author(s):  
Emma Mishel ◽  
Tristan Bridges ◽  
Mónica L. Caudillo
Keyword(s):  
Social Desirability ◽  
Google Trends ◽  
Social Desirability Bias ◽  
Same Sex ◽  
Search Queries ◽  
Sexual Identities ◽  
Google Search

It is difficult to gauge people’s acceptance about same-sex sexualities, as responses to questionnaires are prone to social desirability bias. We offer a new proxy for understanding popular concern surrounding same-sex sexualities: prevalence of Google searches demonstrating concern over gay/lesbian sexual identities. Using Google Trends data, we find that Google searches about whether a specific person is gay or lesbian show patterned bias toward masculine searches, in that such searches are much more frequently conducted about boys and men compared with girls and women. We put these findings into context by comparing search frequencies with other popular Google searches about sexuality and otherwise. We put forth that the patterned bias toward masculine searches illustrates support for the enduring relationship between masculinity and heterosexuality and that it does so on a larger scale than previous research has been able to establish.

scholarly journals Increase in searches for erectile dysfunction during winter: seasonal variation evidence from Google Trends in the United States

2021 ◽  
Author(s):  
Belén Mora Garijo ◽  
Jonathan E. Katz ◽  
Aubrey Greer ◽  
Mia Gonzalgo ◽  
Alejandro García López ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
United States ◽  
Erectile Dysfunction ◽  
Seasonal Variation ◽  
Kidney Stones ◽  
Seasonal Pattern ◽  
The United States ◽  
Google Trends ◽  
Internet Search ◽  
Search Volume

AbstractSeveral diseases associated with erectile dysfunction (ED), such as type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD), are known to have seasonal variation, with increased incidence during winter months. However, no literature exists on whether this chronological-seasonal evolution is also present within ED symptomatology. We hypothesized ED would follow the seasonal pattern of its lifestyle-influenced comorbid conditions and exhibit increased incidence during winter months. In order to investigate the seasonal variation of ED in the United States between 2009 and 2019, Internet search query data were obtained using Google Trends. Normalized search volume was determined during the winter and summer seasons for ED, other diseases known to be significantly associated with ED (T2DM and CAD), kidney stones (positive control), and prostate cancer (negative control). There were significantly more internet search queries for ED during the winter than during the summer (p = 0.001). CAD and T2DM also had significantly increased search volume during winter months compared to summer months (p < 0.001 and p = 0.011, respectively). By contrast, searches for kidney stones were significantly increased in the summer than in the winter (p < 0.001). There was no significant seasonal variation in the relative search frequency for prostate cancer (p = 0.75). In conclusion, Google Trends internet search data across a ten-year period in the United States suggested a seasonal variation in ED, which implies an increase in ED during winter. This novel finding in ED epidemiology may help increase awareness of ED’s associated lifestyle risk factors, which may facilitate early medical evaluation and treatment for those at risk of both ED and cardiovascular disease.

scholarly journals Using Google Trends to Examine the Spatio-Temporal Incidence and Behavioral Patterns of Dengue Disease: A Case Study in Metropolitan Manila, Philippines

2018 ◽  
Vol 3 (4) ◽  
pp. 118 ◽  
Author(s):  
Howell T. Ho ◽  
Thaddeus M. Carvajal ◽  
John Robert Bautista ◽  
Jayson Dale R. Capistrano ◽  
Katherine M. Viacrusis ◽  
...  
Keyword(s):  
Public Health ◽  
Thematic Analysis ◽  
Cross Correlation ◽  
Google Trends ◽  
Health Concern ◽  
Epidemiological Methods ◽  
Health Seeking ◽  
Health Seeking Behavior ◽  
Search Queries ◽  
Seeking Behavior

Dengue is a major public health concern and an economic burden in the Philippines. Despite the country’s improved dengue surveillance, it still suffers from various setbacks and needs to be complemented with alternative approaches. Previous studies have demonstrated the potential of Internet-based surveillance such as Google Dengue Trends (GDT) in supplementing current epidemiological methods for predicting future dengue outbreaks and patterns. With this, our study has two objectives: (1) assess the temporal relationship of weekly GDT and dengue incidence in Metropolitan Manila from 2009–2014; and (2) examine the health-seeking behavior based on dengue-related search queries of the population. The study collated the population statistics and reported dengue cases in Metropolitan Manila from respective government agencies to calculate the dengue incidence (DI) on a weekly basis for the entire region and annually per city. Data processing of GDT and dengue incidence was performed by conducting an ‘adjustment’ and scaling procedures, respectively, and further analyzed for correlation and cross-correlation analyses using Pearson’s correlation. The relative search volume of the term ‘dengue’ and top dengue-related search queries in Metropolitan Manila were obtained and organized from the Google Trends platform. Afterwards, a thematic analysis was employed, and word clouds were generated to examine the health behavior of the population. Results showed that weekly temporal GDT pattern are closely similar to the weekly DI pattern in Metropolitan Manila. Further analysis showed that GDT has a moderate and positive association with DI when adjusted or scaled, respectively. Cross-correlation analysis revealed a delayed effect where GDT leads DI by 1–2 weeks. Thematic analysis of dengue-related search queries indicated 5 categories namely; (a) dengue, (b) sign and symptoms of dengue, (c) treatment and prevention, (d) mosquito, and (e) other diseases. The majority of the search queries were classified in ‘signs and symptoms’ which indicate the health-seeking behavior of the population towards the disease. Therefore, GDT can be utilized to complement traditional disease surveillance methods combined with other factors that could potentially identify dengue hotspots and help in public health decisions.

scholarly journals Epidemiological trends in digestive cancers compared to trends in alcohol consumption. Facts from Romania: correlation or coincidence?

2018 ◽  
Vol 91 (4) ◽  
pp. 376-386
Author(s):  
Simona Valean ◽  
Romeo Chira ◽  
Dan Dumitrascu
Keyword(s):  
Alcohol Consumption ◽  
Population Level ◽  
Epidemiological Data ◽  
Epidemiological Studies ◽  
Incidence Rates ◽  
Human Populations ◽  
Causative Relationship ◽  
Consumption Data ◽  
Digestive Cancers ◽  
Epidemiological Trends

Cancer has emerged as the leading cause of death in human populations, according to recent estimations. Epidemiological studies emphasized the role of life style and of environmental factors in promoting the risk for digestive cancers. The contribution of alcohol was highly suspected. Even for digestive cancers with dominant infection etiology, like liver cancer and gastric cancer, the contribution of alcohol should be assessed. At population level there is therefore a need to compare trends in epidemiological data of gastrointestinal cancers and data on alcohol consumption, in order to extrapolate any causative relationship. The purpose of this review was to analyze the time trend of digestive cancers in Romania, in terms of mortality rates (between 1955-2012), and incidence rates (between 2008-2012), in males and females, and to analyze the alcohol consumption data, aiming to find out if there is any association.

scholarly journals The Accumulation Effect

2005 ◽  
Vol 26 (2) ◽  
pp. 35-52 ◽  
Author(s):  
Raivo Palmaru
Keyword(s):  
Public Opinion ◽  
Political Parties ◽  
Local Elections ◽  
Political Preferences ◽  
Public Opinion Surveys ◽  
Accumulation Effect ◽  
General Elections ◽  
The Media ◽  
Election Results ◽  
Prevailing View

Abstract Although numerous studies over the past 20 years have revealed a clear connection between content analysis statistics and the results of public opinion surveys, the media’s “minimal effects” hypothesis still remains the overwhelmingly prevailing view. Among other things, it is not clear which of the two influences the other: Do people’s political preferences influence the media or do the media influence people’s preferences? In order to test this, the results of the 1999 and 2003 general elections and the 2002 local elections in Estonia, as well as the results of current public opinion surveys, were compared to the coverage given to the campaigning parties in the largest Estonian newspapers. The analysis showed that the coverage of political parties in the print media, as determined by the frequency of valuative notations, described the election results to a great extent. It is noteworthy that a change in media content was followed by a change in public opinion. At the same time, an accumulation effect became obvious: The voters’ preferences for political parties accumulated diachronically during the course of several weeks based on the information that was available to them.

Recognizing the Co-occurrence of Chronic Pain and Mental Illness

2020 ◽  
pp. 16-26
Author(s):  
Jan Jaracz
Keyword(s):  
Chronic Pain ◽  
General Population ◽  
Anxiety Disorders ◽  
Psychiatric Disorders ◽  
Epidemiological Data ◽  
Convincing Evidence ◽  
Medical Problems ◽  
Close Relationship ◽  
Negative Effect ◽  
Irritable Bowel

Epidemiological data regarding chronic pain and psychiatric disorders are reviewed. Particular attention is given to the interplay between pain and depressive and anxiety disorders. In the general population, 19 to 33% of responders report chronic pain, with higher rates in elderly people. Major depression is one of the most common medical problems, affecting nearly 6% of the population, with a lifetime prevalence of 11 to 14%. The presence of depression in persons with chronic pain is significantly higher (21%) than that in the general population, and this proportion is even higher (52–85%) in specific populations of patients attending specialist clinics. Conversely, convincing evidence published in numerous studies has documented that at least 50% of depressed patients report painful symptoms. Pain exerts a negative effect on treatment and a poorer outcome in multiple domains of quality of life. Moreover, pain increases the economic burden resulting from depression. A close relationship between pain and depression has been established in the functional somatic syndromes of fibromyalgia and irritable bowel syndrome. An association between anxiety disorders and pain has also been documented. Epidemiological studies have provided evidence suggesting the common co-occurrence of pain and selected psychiatric disorders. This is an indication for practitioners to examine patients with pain for symptoms of depression and anxiety disorders and conversely to interview patients with psychiatric disorders in regard to the presence or absence of pain. These studies also provide the inspiration for further investigations of the intriguing shared biological basis or pain and psychiatric disorders.

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