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

Abstract

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.

Searching for HIV and AIDS Health Information in South Africa, 2004-2019: Analysis of Google and Wikipedia Search Trends

“…This work contributes to the growing literature on infodemiology , which seeks to employ search engine data in the service of health information seeking, forecasting, and surveillance [ 35 ]. Previous research has covered a wide variety of infectious diseases such as influenza [ 36 ], dengue [ 37 ], norovirus [ 38 ], COVID-19 [ 39 ], and sexually transmitted infections [ 40 ], as well as other topics like cancer [ 22 , 23 ], dementia [ 18 ], and mental health [ 20 ]. Among the limited literature exploring HIV/AIDS with internet search data, the methodology is often restricted to qualitative [ 41 ] or parametric methodology [ 42 ], with limited research on Africa.…”

“…Drawing on feedback from the scientific community on the best practices of big data research [ 24 , 25 , 28 , 29 ], particularly paying attention to integrating both big data and “small data” (eg, survey data and other traditional data collection mechanisms) to create more complete and accurate data sets, they have made significant advances in this field. This paper advances the hypothesis that the online search behavior of people looking for health information can be used to understand their health information needs, and also for health surveillance and monitoring [ 10 , 18 - 23 ].…”

Searching for HIV and AIDS Health Information in South Africa, 2004-2019: Analysis of Google and Wikipedia Search Trends (Preprint)

“…Drawing on feedback from the scientific community on the best practices of big data research [24,25,28,29], particularly paying attention to integrating both big data and "small data" (eg, survey data and other traditional data collection mechanisms) to create more complete and accurate data sets, they have made significant advances in this field. This paper advances the hypothesis that the online search behavior of people looking for health information can be used to understand their health information needs, and also for health surveillance and monitoring [10,[18][19][20][21][22][23].…”

Using Google Health Trends to investigate COVID-19 incidence in Africa

“…Digital tools have been used in many instances to predict disease incidence (Althouse et al, 2011; Xu et al, 2020; Zhang et al, 2017) including COVID-19. Kurian et al, 2020, evaluated the applicability of Google Trends (GT) in predicting COVID-19 cases in the United States (U.S.) in a state-by-state analysis.…”