Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study

Online searches for hepatocellular carcinoma drugs mirror prescription trends across specialties and changes in guideline recommendations

Background & aims

The treatment options for systemically progressed hepatocellular carcinoma (HCC) have significantly expanded in recent years. In this study, we aimed to evaluate the potential of Google searches as a reflection of prescription rates for HCC drugs in the United States (US).

Methods

We conducted an in-depth analysis of US prescription data obtained from the IQVIA National Prescription Audit (NPA) and corresponding Google Trends data from January 2017 to December 2022. We focused on drugs used in the first line and second or later treatment lines for HCC, collecting data on their prescriptions and search rates. Search volumes were collected as aggregated search queries for both generic drugs and their respective brand names.

Results

During the study period from Q1 2017 to Q4 2022, monthly prescriptions for drugs used in HCC treatment showed an 173% increase (from 1253 to 3422). Conversely online searches increased by 3.5% (from 173 to 179 per 10 million searches). Notably, strong correlations were observed between search interest and prescriptions for newer drugs, which indicates increasing usage, while older drugs with declining usage displayed limited correlation. Our findings suggest a growing role of non-physician professions in managing systemically progressed HCC within the US healthcare system, although oncologists remained primarily responsible for drug prescriptions.

Conclusions

In conclusion, online search monitoring can offer the potential to reflect prescription trends specifically related to the treatment of HCC. This approach provides a swift and accessible means of evaluating the evolving landscape of HCC treatment.

The 2022 Summer record-breaking heatwave and health information-seeking behaviours: an infodemiology study in Mainland China

INTRODUCTION

Heatwave is a major global health concern. Many countries including China suffered a record-breaking heatwave during the summer of 2022, which may have a significant effect on population health or health information-seeking behaviours but is yet to be examined.

METHODS

We derived health information-seeking data from the Baidu search engine (similar to Google search engine). The data included city-specific daily search queries (also referred to Baidu Search Index) for heat-sensitive diseases from 2021 to 2022, including heatstroke, hospital visits, cardiovascular diseases and diabetes, respiratory diseases, mental health and urological diseases. For each city, the record-breaking heatwave days in 2022 were matched to days in the same calendar month in 2021.

RESULTS

The 2022 record-breaking heatwave hit most cities (83.64%) in Mainland China. The average heatwave duration was 13 days and the maximum temperature was 3.60°C higher than that in 2021 (p<0.05). We observed increased population behaviours of seeking information on respiratory diseases (RR=1.014, 95% CI: 1.008 to 1.020), urological diseases (RR=1.011, 95% CI: 1.006 to 1.016) and heatstroke (RR=1.026, 95% CI: 1.016 to 1.036) associated with the heatwave intensity in 2022 (per 1°C increase). The heatwave duration in 2022 (per 1 day increase) was also associated with an increase in seeking information on cardiovascular diseases and diabetes (RR=1.003, 95% CI: 1.002 to 1.004), urological diseases (RR=1.005, 95% CI: 1.002 to 1.008), mental health (RR=1.009, 95% CI: 1.006 to 1.012) and heatstroke (RR=1.038, 95% CI: 1.032 to 1.043). However, there were substantial geographical variations in the effect of the 2022 heatwave intensity and duration on health information-seeking behaviours.

CONCLUSION

This infodemiology study suggests that the 2022 summer unprecedented heatwave in Mainland China has significantly increased population demand for health-related information, especially for heatstroke, urological diseases and mental health. Population-based research of real-time disease data is urgently needed to estimate the negative health impact of the exceptional heatwave in Mainland China and elsewhere.

Google Trends for health research: Its advantages, application, methodological considerations, and limitations in psychiatric and mental health infodemiology

The high utilization of infodemiological tools for psychiatric and mental health topics signals the emergence of a new discipline. Drawing on the definition of infodemiology by Eysenbach, this emerging field can be termed “psychiatric and mental health infodemiology,” defined as the science of distribution and determinants of information in an electronic medium, including the internet, or in a population to inform mental health services and policies. Since Google Trends is one of its popular tools, this minireview describes its advantages, application, methodological considerations, and limitations in psychiatric and mental health research. The advantage of Google Trends is the nature of its data, which may represent the actual behavior rather than their users' stated preferences in real-time through automatic anonymization. As such, it can provide readily available data about sensitive health topics like mental disorders. Therefore, Google Trends has been used to explore public concerns, interests, and behaviors about psychiatric and mental health phenomena, service providers, and specific disciplines. In this regard, several methodological can be considered by studies using Google Trends, including documenting their exact keywords, query category, time range, location, and date of retrieval. Likewise, its limitations should be accounted for in its interpretation, including restricted representation of people who use the Google search engine, limited validity in areas with low internet penetration or freedom of speech, does not provide absolute search volumes, unknown sampled queries, and limited transparency in its algorithm, especially the terms and idioms it subsumes under its “topic” keywords.

Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study

BACKGROUND

Anxiety disorders are the most prevalent mental disorders globally, with a substantial impact on quality of life. The prevalence of anxiety disorders has increased substantially following the COVID-19 pandemic, and it is likely to be further affected by a global economic recession. Understanding anxiety themes and how they change over time and across countries is crucial for preventive and treatment strategies.

OBJECTIVE

The aim of this study was to track the trends in anxiety themes between 2004 and 2020 in the 50 most populous countries with high volumes of internet search data. This study extends previous research by using a novel search-based methodology and including a longer time span and more countries at different income levels.

METHODS

We used a crowdsourced questionnaire, alongside Bing search query data and Google Trends search volume data, to identify themes associated with anxiety disorders across 50 countries from 2004 to 2020. We analyzed themes and their mutual interactions and investigated the associations between countries' socioeconomic attributes and anxiety themes using time-series linear models. This study was approved by the Microsoft Research Institutional Review Board.

RESULTS

Query volume for anxiety themes was highly stable in countries from 2004 to 2019 (Spearman r=0.89) and moderately correlated with geography (r=0.49 in 2019). Anxiety themes were predominantly long-term and personal, with "having kids," "pregnancy," and "job" the most voluminous themes in most countries and years. In 2020, "COVID-19" became a dominant theme in 27 countries. Countries with a constant volume of anxiety themes over time had lower fragile state indexes (P=.007) and higher individualism (P=.003). An increase in the volume of the most searched anxiety themes was associated with a reduction in the volume of the remaining themes in 13 countries and an increase in 17 countries, and these 30 countries had a lower prevalence of mental disorders (P<.001) than the countries where no correlations were found.

CONCLUSIONS

Internet search data could be a potential source for predicting the country-level prevalence of anxiety disorders, especially in understudied populations or when an in-person survey is not viable.

Psychological Impact of COVID-19 Lockdown and Its Evolution: A Case Study Based on Internet Searching Data during the Lockdown of Wuhan 2020 and Shanghai 2022

It has been three years since the initial outbreak of COVID-19 in Wuhan, China, which incurred huge damage both physically and psychologically on human's normal life. As a prevention measure, the lockdown was first adopted by Wuhan, then by a long list of Chinese cities and many other major cities around the world. Lockdown is the most restrictive social distancing strategy, turning out effective in mitigating the spreading of COVID-19 on the community level, which, however, cuts off all social interactions and isolates healthy people from each other. The isolated nature of the lockdown could induce severe mental health issues, forming one major source of depression and domestic violence. Given the potential side effect, a comprehensive investigation based on reliable data sources is needed to evaluate the real psychological impact of COVID-19 lockdown and its evolution over time, particularly in the time when the Omicron variant, known for its low death risk, dominates the pandemic. Based on the Baidu Searching Index data collected for Wuhan and Shanghai, two major cities in China that suffered from long-lasting (over two months) lockdowns in 2020 and 2022, respectively, it is found that the major psychological issue during the lockdown period is not induced by the spreading of COVID-19, but by the execution of lockdown. With the deepening of knowledge about COVID-19 and the decrease in the death risk, the psychological impact of lockdown keeps increasing, while the impact of virus spreading becomes less important and even irrelevant to depression and domestic violence issues. The findings reveal that from the psychological perspective, the negative effect of lockdown already overweighs the positive one, which is especially true for the Omicron variant provided its almost ignorable death risk. Therefore, it is necessary to re-evaluate the yield and cost of lockdown for those countries where the COVID-19 pandemic has not yet come to an end.

Heterogeneous responses in Google Trends measures of well-being to the COVID-19 dynamic quarantines in Chile

We study how the Chilean population’s well-being responded to the strategy implemented by their health authorities, known as Dynamic Quarantine, to contain the spread of coronavirus in which municipalities periodically entered and exited lockdowns. This unique scheme, together with the population’s socioeconomic heterogeneity, facilitates the estimation of changes in this well-being as differentiated by socioeconomic status. Using Google Trends to compute measures of well-being, we find strong evidence that socioeconomic status induces heterogeneity in these changes; thus, neglecting this heterogeneity may lead to misleading prescriptions for the public policy that addresses the psychological effects of lockdowns.

Online searches for SGLT-2 inhibitors and GLP-1 receptor agonists correlate with prescription rates in the United States: An infodemiological study

Several clinical trials have demonstrated that many SGLT-2 inhibitors (SGLT2i) and GLP-1 receptor agonists (GLP-1 RA) can reduce the risk of cardiovascular events in patients with Type 2 diabetes and atherosclerotic cardiovascular disease. Recent reports indicate an underutilization of new cardiometabolic drugs, including SGLT2i and GLP-1 RA. We aimed to evaluate the use of online search volumes to reflect United States prescription rates. A repeated cross-sectional analysis of Google search volumes and corresponding data from the IQVIA National Prescription Audit (NPA) of pharmacy dispensing of newly prescribed drugs was performed. Monthly data for online searches and prescription between January 1, 2016 and December 31, 2021 were collected for selected SGLT2i and GLP-1 RA. Prescription data for drugs classes (SGLT2i and GLP-1 RA) and individual drugs were calculated as the total of queried data for branded drug names. Trends were analyzed for visual and quantitative correlation as well as predictive patterns. Overall, online searches increased by 157.6% (95% CI: 142.2-173.1%) and 295.2% (95% CI: 257.7-332.6%) for SGLT2i and GLP-1RA between 2016 and 2021. Prescription rates raised by 114.6% (95% CI: 110.8-118.4%) and 221.0% (95% CI: 212.1-229.9%) for SGLT2i and GLP-1RA for this period. Correlation coefficients (range 0.86-0.99) were strongest for drugs with growing number of prescriptions, for example dapagliflozin, empagliflozin, ertugliflozin, dulaglutide, and semaglutide. Online searches might represent an additional tool to monitor the utilization trends of cardiometabolic drugs. Associations were strongest for drugs with reported cardioprotective effect. Thus, trends in online searches complement conventionally acquired data to reflect and forecast prescription trends of cardiometabolic drugs.

A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study

Background

Studies suggest diurnal patterns of occurrence of some eye conditions. Leveraging new information sources such as web-based search data to learn more about such patterns could improve the understanding of patients’ eye-related conditions and well-being, better inform timing of clinical and remote eye care, and improve precision when targeting web-based public health campaigns toward underserved populations.

Objective

To investigate our hypothesis that the public is likely to consistently search about different ophthalmologic conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to ophthalmologic conditions such as conjunctivitis. We assessed whether search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other.

Methods

We designed a study to analyze and compare hourly search data for eye-related and control search terms, using time series regression models with trend and periodicity terms to remove outliers and then estimate diurnal effects. We planned a Google Trends setting, extracting data from 10 US states for the entire year of 2018. The exposure was internet search, and the participants were populations who searched through Google’s search engine using our chosen study terms. Our main outcome measures included cyclical hourly and day-of-week web-based search patterns. For statistical analyses, we considered P<.001 to be statistically significant.

Results

Distinct diurnal (P<.001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented those reported from prior clinical studies. Of the eye-related terms, “pink eye” showed the largest diurnal amplitude-to-mean ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. By contrast, “dry eyes” had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening-to-morning period and peaking in early morning.

Conclusions

The frequency of web-based searches for various eye conditions can show cyclic patterns according to time of the day or week. Further studies to understand the reasons for these variations may help supplement the current clinical understanding of ophthalmologic symptom presentation and improve the timeliness of patient messaging and care interventions.