Association Between Cancer Incidence and Mortality in Web-Based Data in China: Infodemiology Study

Xu, Chenjie; Wang, Yi; Yang, Hongxi; Hou, Jie; Sun, Li; Zhang, Xinyu; Cao, Xinxi; Hou, Yabing; Wang, Lan; Cai, Qiliang; Wang, Yaogang

doi:10.2196/10677

Cited by 50 publications

(47 citation statements)

References 33 publications

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“…Due to its potential, it has been used for epidemiological evaluation worldwide with reasonable success [14–18]. ‘Google Trends’ has also been used to correlate the amount of online searches on cancer with incidence and mortality rates of such disease [19–22].…”

Section: Introductionmentioning

confidence: 99%

The impact of cancer campaigns in Brazil: a Google Trends analysis

Quintanilha

Souza

Sanches

et al. 2019

ecancer

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It is estimated that more than 600,000 new cases of cancer will be reported in Brazil during the 2018–2019 biennium, especially with regard to prostate, breast, lung and colorectal cancers. Due to the high prevalence, incidence and mortality rates of these diseases, cancer campaigns such as ‘Pink October’ and ‘Blue November’ were strongly promoted in the past decade throughout the country to raise awareness of breast and prostate cancer, respectively. Nevertheless, whether the implementation of these campaigns has been proven efficient is still unknown. In the present study, we analysed the effectiveness of these campaigns on eliciting population online interest for cancer information. The Google Trends database was evaluated for the relative Internet search popularity for the terms ‘breast cancer’ and ‘prostate cancer’ from 2014 to 2019. Aside from some regional differences, we found that there was a high demand for ‘breast cancer’ and, to a lesser extent, ‘prostate cancer’ searches in a seasonal fashion (during October and November, respectively). Despite the worldwide high incidence of lung and colorectal cancers, searches including these keywords did not show increases in any specific period of the year, demonstrating the efficiency of the ‘Pink October’ and ‘Blue November’ campaigns in engaging the interest of the Brazilian population on the subject. These results allow us to infer that campaigns are effective in mobilising the attention of the Brazilian population with regard to breast and prostate cancers, but the practical aspects in reducing incidence and mortality should still be discussed.

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Section: Introductionmentioning

confidence: 99%

The impact of cancer campaigns in Brazil: a Google Trends analysis

Quintanilha

Souza

Sanches

et al. 2019

ecancer

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“…This study demonstrated the feasibility of combining historical information with search information for the early warning of NCDs, laying the foundation for future model optimization. As the most recent data publicly available from the Centers for Disease Control and Prevention is at least 2 years old while Google Trends data are available nearly instantaneously, this resource could potentially provide a more timely and cost-effective data source for public health researchers [ 28 ]. Thus, real-time internet searches could be particularly useful.…”

Section: Discussionmentioning

confidence: 99%

Leveraging Internet Search Data to Improve the Prediction and Prevention of Noncommunicable Diseases: Retrospective Observational Study

Xu¹,

Cao²,

Yang³

et al. 2020

J Med Internet Res

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Background As human society enters an era of vast and easily accessible social media, a growing number of people are exploiting the internet to search and exchange medical information. Because internet search data could reflect population interest in particular health topics, they provide a new way of understanding health concerns regarding noncommunicable diseases (NCDs) and the role they play in their prevention. Objective We aimed to explore the association of internet search data for NCDs with published disease incidence and mortality rates in the United States and to grasp the health concerns toward NCDs. Methods We tracked NCDs by examining the correlations among the incidence rates, mortality rates, and internet searches in the United States from 2004 to 2017, and we established forecast models based on the relationship between the disease rates and internet searches. Results Incidence and mortality rates of 29 diseases in the United States were statistically significantly correlated with the relative search volumes (RSVs) of their search terms (P<.05). From the perspective of the goodness of fit of the multiple regression prediction models, the results were closest to 1 for diabetes mellitus, stroke, atrial fibrillation and flutter, Hodgkin lymphoma, and testicular cancer; the coefficients of determination of their linear regression models for predicting incidence were 80%, 88%, 96%, 80%, and 78%, respectively. Meanwhile, the coefficient of determination of their linear regression models for predicting mortality was 82%, 62%, 94%, 78%, and 62%, respectively. Conclusions An advanced understanding of search behaviors could augment traditional epidemiologic surveillance and could be used as a reference to aid in disease prediction and prevention.

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“…The most popular tool for analyzing and aggregating patterns of search data is Google Trends, a public website that has provided real-time and archived data on Google queries by users since 2004 [ 3 ]. It has been used to study online behavior on diverse health topics, such as early detection of influenza epidemics [ 4 - 6 ], pertussis outbreak monitoring [ 7 ], asthma monitoring [ 8 ], and cancer detection [ 9 , 10 ]. The tool has also been used to study public interest in cancer [ 11 , 12 ], suicide assessment [ 13 , 14 ], depression-related information seeking [ 15 ], lifestyle-disease surveillance [ 16 ], bariatric surgery [ 17 ], herpes zoster vaccinations [ 18 ], searches for walk-in clinics and emergency departments [ 19 ], obesity-related behavior [ 20 ], and reproductive health [ 21 - 26 ].…”

Section: Introductionmentioning

confidence: 99%

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

Zepecki¹,

Guendelman²,

DeNero³

et al. 2020

JMIR Res Protoc

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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

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Association Between Cancer Incidence and Mortality in Web-Based Data in China: Infodemiology Study

Cited by 50 publications

References 33 publications

The impact of cancer campaigns in Brazil: a Google Trends analysis

The impact of cancer campaigns in Brazil: a Google Trends analysis

Leveraging Internet Search Data to Improve the Prediction and Prevention of Noncommunicable Diseases: Retrospective Observational Study

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

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