Evidence From Web-Based Dietary Search Patterns to the Role of B12 Deficiency in Non-Specific Chronic Pain: A Large-Scale Observational Study.
ABSTRACT: BACKGROUND:Profound vitamin B12 deficiency is a known cause of disease, but the role of low or intermediate levels of B12 in the development of neuropathy and other neuropsychiatric symptoms, as well as the relationship between eating meat and B12 levels, is unclear. OBJECTIVE:The objective of our study was to investigate the role of low or intermediate levels of B12 in the development of neuropathy and other neuropsychiatric symptoms. METHODS:We used food-related Internet search patterns from a sample of 8.5 million people based in the US as a proxy for B12 intake and correlated these searches with Internet searches related to possible effects of B12 deficiency. RESULTS:Food-related search patterns were highly correlated with known consumption and food-related searches (ρ=.69). Awareness of B12 deficiency was associated with a higher consumption of B12-rich foods and with queries for B12 supplements. Searches for terms related to neurological disorders were correlated with searches for B12-poor foods, in contrast with control terms. Popular medicines, those having fewer indications, and those which are predominantly used to treat pain, were more strongly correlated with the ability to predict neuropathic pain queries using the B12 contents of food. CONCLUSIONS:Our findings show that Internet search patterns are a useful way of investigating health questions in large populations, and suggest that low B12 intake may be associated with a broader spectrum of neurological disorders than previously thought.
Project description:Despite the tremendous economic and health costs imposed on China by tobacco use, China lacks a proactive and systematic tobacco control surveillance and evaluation system, hampering research progress on tobacco-focused surveillance and evaluation studies.This paper uses online search query analyses to investigate changes in online search behavior among Chinese Internet users in response to the adoption of the national indoor public place smoking ban. Baidu Index and Google Trends were used to examine the volume of search queries containing three key search terms "Smoking Ban(s)," "Quit Smoking," and "Electronic Cigarette(s)," along with the news coverage on the smoking ban, for the period 2009-2011.Our results show that the announcement and adoption of the indoor public place smoking ban in China generated significant increases in news coverage on smoking bans. There was a strong positive correlation between the media coverage of smoking bans and the volume of "Smoking Ban(s)" and "Quit Smoking" related search queries. The volume of search queries related to "Electronic Cigarette(s)" was also correlated with the smoking ban news coverage.To the extent it altered smoking-related online searches, our analyses suggest that the smoking ban had a significant effect, at least in the short run, on Chinese Internet users' smoking-related behaviors. This research introduces a novel analytic tool, which could serve as an alternative tobacco control evaluation and behavior surveillance tool in the absence of timely or comprehensive population surveillance system. This research also highlights the importance of a comprehensive approach to tobacco control in China.
Project description:The use of Internet-based systems for infectious disease surveillance has been increasingly explored in recent years. However, few studies have used Internet search query or social media data to monitor spatial and temporal trends of avian influenza in China. This study investigated the potential of using search query and social media data in detecting and monitoring avian influenza A (H7N9) cases in humans in China. We collected weekly data on laboratory-confirmed H7N9 cases in humans, as well as H7N9-related Baidu Search Index (BSI) and Weibo Posting Index (WPI) data in China from 2013 to 2017, to explore the spatial and temporal trends of H7N9 cases and H7N9-related Internet search queries. Our findings showed a positive relationship of H7N9 cases with BSI and WPI search queries spatially and temporally. The outbreak threshold time and peak time of H7N9-related BSI and WPI searches preceded H7N9 cases in most years. Seasonal autoregressive integrated moving average (SARIMA) models with BSI (??=?0.008, p?<?0.001) and WPI (??=?0.002, p?=?0.036) were used to predict the number of H7N9 cases. Regression tree model analysis showed that the average H7N9 cases increased by over 2.4-fold (26.8/11) when BSI for H7N9 was?>??=?11524. Both BSI and WPI data could be used as indicators to develop an early warning system for H7N9 outbreaks in the future.
Project description:BACKGROUND:South Korea is among the best-performing countries in tackling the coronavirus pandemic by using mass drive-through testing, face mask use, and extensive social distancing. However, understanding the patterns of risk perception could also facilitate effective risk communication to minimize the impacts of disease spread during this crisis. OBJECTIVE:We attempt to explore patterns of community health risk perceptions of COVID-19 in South Korea using internet search data. METHODS:Google Trends (GT) and NAVER relative search volumes (RSVs) data were collected using COVID-19-related terms in the Korean language and were retrieved according to time, gender, age groups, types of device, and location. Online queries were compared to the number of daily new COVID-19 cases and tests reported in the Kaggle open-access data set for the time period of December 5, 2019, to May 31, 2020. Time-lag correlations calculated by Spearman rank correlation coefficients were employed to assess whether correlations between new COVID-19 cases and internet searches were affected by time. We also constructed a prediction model of new COVID-19 cases using the number of COVID-19 cases, tests, and GT and NAVER RSVs in lag periods (of 1-3 days). Single and multiple regressions were employed using backward elimination and a variance inflation factor of <5. RESULTS:The numbers of COVID-19-related queries in South Korea increased during local events including local transmission, approval of coronavirus test kits, implementation of coronavirus drive-through tests, a face mask shortage, and a widespread campaign for social distancing as well as during international events such as the announcement of a Public Health Emergency of International Concern by the World Health Organization. Online queries were also stronger in women (r=0.763-0.823; P<.001) and age groups ?29 years (r=0.726-0.821; P<.001), 30-44 years (r=0.701-0.826; P<.001), and ?50 years (r=0.706-0.725; P<.001). In terms of spatial distribution, internet search data were higher in affected areas. Moreover, greater correlations were found in mobile searches (r=0.704-0.804; P<.001) compared to those of desktop searches (r=0.705-0.717; P<.001), indicating changing behaviors in searching for online health information during the outbreak. These varied internet searches related to COVID-19 represented community health risk perceptions. In addition, as a country with a high number of coronavirus tests, results showed that adults perceived coronavirus test-related information as being more important than disease-related knowledge. Meanwhile, younger, and older age groups had different perceptions. Moreover, NAVER RSVs can potentially be used for health risk perception assessments and disease predictions. Adding COVID-19-related searches provided by NAVER could increase the performance of the model compared to that of the COVID-19 case-based model and potentially be used to predict epidemic curves. CONCLUSIONS:The use of both GT and NAVER RSVs to explore patterns of community health risk perceptions could be beneficial for targeting risk communication from several perspectives, including time, population characteristics, and location.
Project description:Obesity is highly correlated with the development of chronic diseases and has become a critical public health issue that must be countered by aggressive action. This study determined whether data from Google Trends could provide insight into trends in obesity-related search behaviors in Taiwan.Using Google Trends, we examined how changes in economic conditions-using business cycle indicators as a proxy-were associated with people's internet search behaviors related to obesity awareness, health behaviors, and fast food restaurants.Monthly business cycle indicators were obtained from the Taiwan National Development Council. Weekly Taiwan Stock Exchange (TWSE) weighted index data were accessed and downloaded from Yahoo Finance. The weekly relative search volumes (RSV) of obesity-related terms were downloaded from Google Trends. RSVs of obesity-related terms and the TWSE from January 2007 to December 2011 (60 months) were analyzed using correlation analysis.During an economic recession, the RSV of obesity awareness and health behaviors declined (r=.441, P<.001; r=.593, P<.001, respectively); however, the RSV for fast food restaurants increased (r=-.437, P<.001). Findings indicated that when the economy was faltering, people tended to be less likely to search for information related to health behaviors and obesity awareness; moreover, they were more likely to search for fast food restaurants.Macroeconomic conditions can have an impact on people's health-related internet searches.
Project description:The internet is becoming the main source of health-related information. We aimed to investigate data regarding heartburn-related searches made by Google users from Australia, Canada, Germany, Poland, the United Kingdom, and the United States. We retrospectively analyzed data from Google Ads Keywords Planner. We extracted search volumes of keywords associated with "heartburn" for June 2015 to May 2019. The data were generated in the respective primary language. The number of searches per 1,000 Google-user years was as follows: 177.4 (Australia), 178.1 (Canada), 123.8 (Germany), 199.7 (Poland), 152.5 (United Kingdom), and 194.5 (United States). The users were particularly interested in treatment (19.0 to 41.3%), diet (4.8 to 10.7%), symptoms (2.6 to 13.1%), and causes (3.7 to 10.0%). In all countries except Germany, the number of heartburn-related queries significantly increased over the analyzed period. For Canada, Germany, Poland, and the United Kingdom, query numbers were significantly lowest in summer; there was no significant seasonal trend for Australia and the United States. The number of heartburn-related queries has increased over the past four years, and a seasonal pattern may exist in certain regions. The trends in heartburn-related searches may reflect the scale of the complaint, and should be verified through future epidemiological studies.
Project description:BACKGROUND:Digital surveillance using internet search queries can improve both the sensitivity and timeliness of the detection of a health event, such as an influenza outbreak. While it has recently been estimated that the mobile search volume surpasses the desktop search volume and mobile search patterns differ from desktop search patterns, the previous digital surveillance systems did not distinguish mobile and desktop search queries. The purpose of this study was to compare the performance of mobile and desktop search queries in terms of digital influenza surveillance. METHODS AND RESULTS:The study period was from September 6, 2010 through August 30, 2014, which consisted of four epidemiological years. Influenza-like illness (ILI) and virologic surveillance data from the Korea Centers for Disease Control and Prevention were used. A total of 210 combined queries from our previous survey work were used for this study. Mobile and desktop weekly search data were extracted from Naver, which is the largest search engine in Korea. Spearman's correlation analysis was used to examine the correlation of the mobile and desktop data with ILI and virologic data in Korea. We also performed lag correlation analysis. We observed that the influenza surveillance performance of mobile search queries matched or exceeded that of desktop search queries over time. The mean correlation coefficients of mobile search queries and the number of queries with an r-value of ? 0.7 equaled or became greater than those of desktop searches over the four epidemiological years. A lag correlation analysis of up to two weeks showed similar trends. CONCLUSION:Our study shows that mobile search queries for influenza surveillance have equaled or even become greater than desktop search queries over time. In the future development of influenza surveillance using search queries, the recognition of changing trend of mobile search data could be necessary.
Project description:BACKGROUND:Search engines display helpline notices when people query for suicide-related information. OBJECTIVE:In this study, we aimed to examine if these notices and other information displayed in response to suicide-related queries are correlated with subsequent searches for suicide prevention rather than harmful information. METHODS:Anonymous suicide-related searches made on Bing and Google in the United States, the United Kingdom, Hong Kong, and Taiwan in a span of 10 months were extracted. Descriptive analyses and regression models were fit to the data to assess the correlation with observed behaviors. RESULTS:Display of helpline notices was not associated with an observed change in the likelihood of or future suicide searches (P=.42). No statistically significant differences were observed in the likelihood of people making future suicide queries (both generally and specific types of suicide queries) when comparing search engines in locations that display helpline notices versus ones that do not. Pages with higher rank, being neutral to suicide, and those shown among more antisuicide pages were more likely to be clicked on. Having more antisuicide Web pages displayed was the only factor associated with further searches for suicide prevention information (hazard=1.18, P=.002). CONCLUSIONS:Helpline notices are not associated with harm. If they cause positive change in search behavior, it is small. This is possibly because of the variability in intent of users seeking suicide-related information. Nonetheless, helpline notice should be displayed, but more efforts should be made to improve the visibility and ranking of suicide prevention Web pages.
Project description:An extended discussion and research has been performed in recent years using data collected through search queries submitted via the Internet. It has been shown that the overall activity on the Internet is related to the number of cases of an infectious disease outbreak.The aim of the study was to define a similar correlation between data from Google Trends and data collected by the official authorities of Greece and Europe by examining the development and the spread of seasonal influenza in Greece and Italy.We used multiple regressions of the terms submitted in the Google search engine related to influenza for the period from 2011 to 2012 in Greece and Italy (sample data for 104 weeks for each country). We then used the autoregressive integrated moving average statistical model to determine the correlation between the Google search data and the real influenza cases confirmed by the aforementioned authorities. Two methods were used: (1) a flu score was created for the case of Greece and (2) comparison of data from a neighboring country of Greece, which is Italy.The results showed that there is a significant correlation that can help the prediction of the spread and the peak of the seasonal influenza using data from Google searches. The correlation for Greece for 2011 and 2012 was .909 and .831, respectively, and correlation for Italy for 2011 and 2012 was .979 and .933, respectively. The prediction of the peak was quite precise, providing a forecast before it arrives to population.We can create an Internet surveillance system based on Google searches to track influenza in Greece and Italy.
Project description:Background An increase in online searches on health topics may either mirror epidemiological changes or reflect media coverage. In the context of COVID-19, this is particularly relevant, as COVID-19 symptoms may be mistaken for those of respiratory disease exacerbations. Therefore, we aimed to assess Internet search patterns on asthma and chronic obstructive pulmonary disease (COPD) in the context of COVID-19, as compared to searches on other chronic diseases. Methods We retrieved Google Trends (GTs) data on two respiratory (asthma and COPD) and three non-respiratory (diabetes, hypertension, and Crohn’s disease) chronic diseases over the past 5 years (up to May 31, 2020). For 54 countries, and for each disease, we built autoregressive integrated moving average (ARIMA) models to predict GTs for 2020 based on 2015–2019 search patterns. In addition, we estimated the proportion of searches in which COVID-19-related terms were used. To assess the potential impact of media coverage on online searches, we assessed whether weekly “asthma” GTs correlated with the number of Google News items on asthma. Results Over the past 5 years, worldwide search volumes for asthma and COPD reached their maximum values in March 2020. Such was not observed for diabetes, hypertension and Crohn’s disease. In 38 (70%) countries, GTs on asthma were higher in March 2020 than the respective maximum predicted values. This compares to 19 countries for COPD, 23 for hypertension, 11 for Crohn’s disease, and 9 for diabetes. Queries with COVID-19-related terms represented up to 47.8% of the monthly searches on asthma, and up to 21.3% of COPD searches. In most of the assessed countries, moderate-strong correlations were observed between “asthma” GTs and the number of news items on asthma. Conclusions During March 2020, there was a peak in searches on asthma and COPD, which was probably mostly driven by media coverage, as suggested by their simultaneity in several countries with different epidemiological situations.
Project description:OBJECTIVES:Internet data are important sources of abundant information regarding HIV epidemics and risk factors. A number of case studies found an association between internet searches and outbreaks of infectious diseases, including HIV. In this research, we examined the feasibility of using search query data to predict the number of new HIV diagnoses in China. DESIGN:We identified a set of search queries that are associated with new HIV diagnoses in China. We developed statistical models (negative binomial generalised linear model and its Bayesian variants) to estimate the number of new HIV diagnoses by using data of search queries (Baidu) and official statistics (for the entire country and for Guangdong province) for 7 years (2010 to 2016). RESULTS:Search query data were positively associated with the number of new HIV diagnoses in China and in Guangdong province. Experiments demonstrated that incorporating search query data could improve the prediction performance in nowcasting and forecasting tasks. CONCLUSIONS:Baidu data can be used to predict the number of new HIV diagnoses in China up to the province level. This study demonstrates the feasibility of using search query data to predict new HIV diagnoses. Results could potentially facilitate timely evidence-based decision making and complement conventional programmes for HIV prevention.