scholarly journals Detecting epidemiological relevance among adenoid hypertrophy, rhinosinusitis, and allergic rhinitis through Internet search

2021 ◽  
Author(s):  
Yingchao Yang ◽  
Xinyi Li ◽  
Qiang Ma ◽  
Zhihui Fu ◽  
Kaiming Su
Keyword(s):  
Allergic Rhinitis ◽  
Search Engine ◽  
Correlation Coefficients ◽  
Adenoid Hypertrophy ◽  
Internet Search ◽  
Search Terms ◽  
Search Volume ◽  
Internet Search Engine ◽  
Search Data

Abstract Purpose : This study aimed to verify that adenoid hypertrophy (AH) and rhinosinusitis share similar epidemiologic patterns and that AH and allergic rhinitis (AR) are not related. Methods: Internet search engine query data from January 2011 to December 2019 were retrieved from the Baidu index. Monthly search volume was obtained in China for the following search terms in Chinese: “adenoid hypertrophy,” “rhinosinusitis,” and “allergic rhinitis”; the data obtained were then presented as percentages. Pearson’s and Spearman’ s correlation coefficients were used to detect the correlation among the search volumes of AH, rhinosinusitis, and AR. We also collected search data from the first 5 months of 2020, when segregation was implemented in China due to the coronavirus disease 2019 epidemic. Then, we compared the search data to those obtained during the same period in 2019 to detect the effects of segregation on AH and AR to varying degrees. Results: Statistically significant differences were found between the search variations of AH and rhinosinusitis during 2011–2019 (R=0.643, P<0.05). However, search variations of AH and AR were negatively related (R=-0.239, P<0.05). The average monthly search volume of AH and rhinosinusitis correlated well (R=0.836, P<0.01), but no correlation was found between AH and AR. The search volume of AH and rhinosinusitis during the first 5 months in 2020 decreased, whereas that of AR increased during January–February. Conclusions: AH and rhinosinusitis are epidemiologically related, whereas AH and AR are not correlated with each other.

scholarly journals Detecting Lung Cancer Trends by Leveraging Real-World and Internet-Based Data: Infodemiology Study (Preprint)

2019 ◽  
Author(s):  
Chenjie Xu ◽  
Hongxi Yang ◽  
Li Sun ◽  
Xinxi Cao ◽  
Yabing Hou ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Correlation Coefficients ◽  
State Level ◽  
Mortality Rates ◽  
Internet Search ◽  
Search Terms ◽  
Search Volume ◽  
Incidence And Mortality ◽  
Search Data ◽  
Relative Search Volume

BACKGROUND Internet search data on health-related terms can reflect people’s concerns about their health status in near real time, and hence serve as a supplementary metric of disease characteristics. However, studies using internet search data to monitor and predict chronic diseases at a geographically finer state-level scale are sparse. OBJECTIVE The aim of this study was to explore the associations of internet search volumes for lung cancer with published cancer incidence and mortality data in the United States. METHODS We used Google relative search volumes, which represent the search frequency of specific search terms in Google. We performed cross-sectional analyses of the original and disease metrics at both national and state levels. A smoothed time series of relative search volumes was created to eliminate the effects of irregular changes on the search frequencies and obtain the long-term trends of search volumes for lung cancer at both the national and state levels. We also performed analyses of decomposed Google relative search volume data and disease metrics at the national and state levels. RESULTS The monthly trends of lung cancer-related internet hits were consistent with the trends of reported lung cancer rates at the national level. Ohio had the highest frequency for lung cancer-related search terms. At the state level, the relative search volume was significantly correlated with lung cancer incidence rates in 42 states, with correlation coefficients ranging from 0.58 in Virginia to 0.94 in Oregon. Relative search volume was also significantly correlated with mortality in 47 states, with correlation coefficients ranging from 0.58 in Oklahoma to 0.94 in North Carolina. Both the incidence and mortality rates of lung cancer were correlated with decomposed relative search volumes in all states excluding Vermont. CONCLUSIONS Internet search behaviors could reflect public awareness of lung cancer. Research on internet search behaviors could be a novel and timely approach to monitor and estimate the prevalence, incidence, and mortality rates of a broader range of cancers and even more health issues.

scholarly journals Detecting Lung Cancer Trends by Leveraging Real-World and Internet-Based Data: Infodemiology Study

10.2196/16184 ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. e16184 ◽  
Author(s):  
Chenjie Xu ◽  
Hongxi Yang ◽  
Li Sun ◽  
Xinxi Cao ◽  
Yabing Hou ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Correlation Coefficients ◽  
State Level ◽  
Mortality Rates ◽  
Internet Search ◽  
Search Terms ◽  
Search Volume ◽  
Incidence And Mortality ◽  
Search Data ◽  
Relative Search Volume

Background Internet search data on health-related terms can reflect people’s concerns about their health status in near real time, and hence serve as a supplementary metric of disease characteristics. However, studies using internet search data to monitor and predict chronic diseases at a geographically finer state-level scale are sparse. Objective The aim of this study was to explore the associations of internet search volumes for lung cancer with published cancer incidence and mortality data in the United States. Methods We used Google relative search volumes, which represent the search frequency of specific search terms in Google. We performed cross-sectional analyses of the original and disease metrics at both national and state levels. A smoothed time series of relative search volumes was created to eliminate the effects of irregular changes on the search frequencies and obtain the long-term trends of search volumes for lung cancer at both the national and state levels. We also performed analyses of decomposed Google relative search volume data and disease metrics at the national and state levels. Results The monthly trends of lung cancer-related internet hits were consistent with the trends of reported lung cancer rates at the national level. Ohio had the highest frequency for lung cancer-related search terms. At the state level, the relative search volume was significantly correlated with lung cancer incidence rates in 42 states, with correlation coefficients ranging from 0.58 in Virginia to 0.94 in Oregon. Relative search volume was also significantly correlated with mortality in 47 states, with correlation coefficients ranging from 0.58 in Oklahoma to 0.94 in North Carolina. Both the incidence and mortality rates of lung cancer were correlated with decomposed relative search volumes in all states excluding Vermont. Conclusions Internet search behaviors could reflect public awareness of lung cancer. Research on internet search behaviors could be a novel and timely approach to monitor and estimate the prevalence, incidence, and mortality rates of a broader range of cancers and even more health issues.

Team Co-occurence in Internet Search Engine Queries: An Analysis of the Excite Data Set

2013 ◽  
Author(s):  
Dietmar Wolfram
Keyword(s):  
Search Engine ◽  
Internet Search ◽  
Data Set ◽  
Search Terms ◽  
Internet Search Engine ◽  
Term Pair ◽  
Empirical Regularities

Unique queries submitted to the Excite search engine were analyzed for empirical regularities in the co-occurrence of search terms. The distribution of frequency of term pair occurrences was fitted to three models used in informetric studies to determine whether the pattern of term usage followed a Zipfian distribution. Relatively poor fits were obtained for two of the models tested. . .

Can internet search engine queries be used to diagnose diabetes? Analysis of archival search data

2019 ◽  
Vol 56 (10) ◽  
pp. 1149-1154 ◽  
Author(s):  
Irit Hochberg ◽  
Deeb Daoud ◽  
Naim Shehadeh ◽  
Elad Yom-Tov
Keyword(s):  
Search Engine ◽  
Internet Search ◽  
Internet Search Engine ◽  
Search Data

Using internet search data to explore the global public concerns in ankylosing spondylitis

2020 ◽  
pp. postgradmedj-2019-137407
Author(s):  
Yong-Jun Mei ◽  
Yan-Mei Mao ◽  
Fan Cao ◽  
Tao Wang ◽  
Zhi-Jun Li
Keyword(s):  
Rheumatoid Arthritis ◽  
Ankylosing Spondylitis ◽  
Public Interest ◽  
Global Scale ◽  
Hla B27 ◽  
Internet Search ◽  
Search Volume ◽  
Significant Seasonal Variation ◽  
Search Data ◽  
Public Concerns

ObjectiveThis study explored the changes of global public interest in internet search of ankylosing spondylitis (AS) based on Google Trends (GT) data, in order to reflect the characteristics of AS itself.MethodsGT was used to obtain the search popularity scores of the term ’AS’ on a global scale, between January 2004 and December 2018, under the ’health’ classification. Based on the global search data of AS provided by GT, the cosinor analysis was used to test whether there was seasonality in AS.ResultsIn general, AS related search volume demonstrated a decreasing trend from January 2004 to December 2014 and then remain stable from January 2015 to December 2018. No obvious seasonal variations were detected in AS related search volume (amplitude=1.54; phase: month=3.9; low point: month=9.9; p>0.025), which peaked in April and bottomed out in October. The top 17 rising topics were adalimumab, spondylolisthesis, Morbus, Vladimir Mikhailovich Bekhterev, autoimmune disease, rheumatoid arthritis, ankylosis, HLA- B27 positive, Crohn’s disease, rheumatology, spondylosis, arthritis, uveitis, rheumatism, sacroiliac, psoriatic arthritis and spondylitis.ConclusionsGlobally, there is no significant seasonal variation in GT for AS. The top fast-growing topics related to AS may be beneficial for doctors to provide targeted health education of the disease to patients and their families.

Seasonal variations and public search interests in Toxoplasma: a 16-year retrospective analysis of big data on Google Trends

2020 ◽  
Author(s):  
Lei Liu ◽  
Peng Wang ◽  
Su-Qin Jiang ◽  
Zi-Rong Zhong ◽  
Ting-Zheng Zhan ◽  
...  
Keyword(s):  
New Zealand ◽  
Google Trends ◽  
Seasonal Patterns ◽  
Search Term ◽  
Internet Search ◽  
Search Volume ◽  
The Usa ◽  
Search Data ◽  
Relative Search Volume ◽  
The Uk

Abstract Background This study aims to understand whether there is a seasonal change in the internet search interest for Toxoplasma by using the data derived from Google Trends (GT). Methods The present study searched for the relative search volume (RSV) for the search term ‘Toxoplasma’ in GT within six major English-speaking countries (Australia, New Zealand [Southern Hemisphere] and Canada, Ireland, the UK and the USA [Northern Hemisphere] from 1 January 2004 to 31 December 2019, utilizing the category of ‘health’. Data regarding the RSV of Toxoplasma was obtained and further statistical analysis was performed in R software using the ‘season’ package. Results There were significantly seasonal patterns for the RSV of the search term ‘Toxoplasma’ in five countries (all p&lt;0.05), except for the UK. A peak in December–March and a trough in July–September (Canada, Ireland, the UK and the USA) were observed, while a peak in June/August and a trough in December/February (Australia, New Zealand) were also found. Moreover, the presence of seasonal patterns regarding RSV for ‘Toxoplasma’ between the Southern and Northern Hemispheres was also found (both p&lt;0.05), with a reversed meteorological month. Conclusions Overall, our study revealed the seasonal variation for Toxoplasma in using internet search data from GT, providing additional evidence on seasonal patterns in Toxoplasma.

Discovering business information from search engine query data

2014 ◽  
Vol 38 (4) ◽  
pp. 562-574 ◽  
Author(s):  
Liwen Vaughan
Keyword(s):  
Search Engine ◽  
Business Performance ◽  
Google Trends ◽  
Volume Data ◽  
Content Type ◽  
Search Volume ◽  
Business Information ◽  
Position Data ◽  
Search Data ◽  
One Year

Purpose – The purpose of this paper is to examine the feasibility of discovering business information from search engine query data. Specifically the study tried to determine whether search volumes of company names are correlated with the companies’ business performance and position data. Design/methodology/approach – The top 50 US companies in the 2012 Fortune 500 list were included in the study. The following business performance and position data were collected: revenues, profits, assets, stockholders’ equity, profits as a percentage of revenues, and profits as a percentage of assets. Data on the search volumes of the company names were collected from Google Trends, which is based on search queries users enter into Google. Google Trends data were collected in the two scenarios of worldwide searches and US searches. Findings – The study found significant correlations between search volume data and business performance and position data, suggesting that search engine query data can be used to discover business information. Google Trends’ worldwide search data were better than the US domestic search data for this purpose. Research limitations/implications – The study is limited to only one country and to one year of data. Practical implications – Publicly available search engine query data such as those from Google Trends can be used to estimate business performance and position data which are not always publicly available. Search engine query data are timelier than business data. Originality/value – This is the first study to establish a relationship between search engine query data and business performance and position data.

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