Google Trends: Opportunities and limitations in health and health policy research

Online Search Behavior Related to COVID-19 Vaccines: Infodemiology Study

BACKGROUND

Vaccination against COVID-19 is an important public health strategy to address the ongoing pandemic. Examination of online search behavior related to COVID-19 vaccines can provide insights into the public's awareness, concerns, and interest regarding COVID-19 vaccination.

OBJECTIVE

The aim of this study is to describe online search behavior related to COVID-19 vaccines during the start of public vaccination efforts in the United States.

METHODS

We examined Google Trends data from January 1, 2021, through March 16, 2021, to determine the relative search volume for vaccine-related searches on the internet. We also examined search query log data for COVID-19 vaccine-related searches and identified 5 categories of searches: (1) general or other information, (2) vaccine availability, (3) vaccine manufacturer, (4) vaccine side-effects and safety, and (5) vaccine myths and conspiracy beliefs. In this paper, we report on the proportion and trends for these different categories of vaccine-related searches.

RESULTS

In the first quarter of 2021, the proportion of all web-based search queries related to COVID-19 vaccines increased from approximately 10% to nearly 50% of all COVID-19-related queries (P<.001). A majority of COVID-19 vaccine queries addressed vaccine availability, and there was a particularly notable increase in the proportion of queries that included the name of a specific pharmacy (from 6% to 27%; P=.01). Queries related to vaccine safety and side-effects (<5% of total queries) or specific vaccine-related myths (<1% of total queries) were uncommon, and the relative frequency of both types of searches decreased during the study period.

CONCLUSIONS

This study demonstrates an increase in online search behavior related to COVID-19 vaccination in early 2021 along with an increase in the proportion of searches related to vaccine availability at pharmacies. These findings are consistent with an increase in public interest and intention to get vaccinated during the initial phase of public COVID-19 vaccination efforts.

In Pursuit of Freedom from COVID-19 Awareness in India: An Infodemiological Analysis

How to cite this article: Sarkar S, Khanna P. In Pursuit of Freedom from COVID-19 Awareness in India: An Infodemiological Analysis. Indian J Crit Care Med 2021;25(4):470–472.

Hey Google! will New Zealand vote to legalise cannabis? Using Google Trends data to predict the outcome of the 2020 New Zealand cannabis referendum

BACKGROUND

New Zealand held a referendum on the legalisation of recreational cannabis in October 2020. Polls preceding the referendum provided contrasting outcomes. We investigated whether internet search data from Google Trends could provide an alternative estimate of the referendum outcome.

METHODS

We assessed various methods for accessing Google Trends data, downloading search probability data for google.com searches from New Zealand via trends.google.com, PyTrends and Google Trends Extended for Health. We used daily data for the three months prior to the final referendum date, and hourly data for the final week. We defined two smaller time frames each from daily and hourly data, allowing comparisons over the entire time frames, and progressively closer to the end. Using the selected keyword combination of 'cannabis referendum yes/no' we calculated the proportions of 'yes' and 'no' searches for each time frame/data source combination, aiming for a prediction within 2% of the final result.

RESULTS

Data from different sources varied slightly. The method used to aggregate search probabilities over the selected time frame (mean/median) resulted in changes in the predicted outcome for hourly-, but not daily data. On 20 October we predicted the 'no' vote at 51.9%-55.4% for daily-, and 60% for hourly data when aggregated using the median, but only 49% for mean hourly data. Hourly data performed poorly at predicting the final 51.2% 'no' result, while predictions based on mean daily data for the full voting period provided the best prediction, differing by 0.1-0.2%.

CONCLUSION

Predictions based on Google Trends data broadly agreed with polling predictions, but the exact method used affected the eventual prediction. While polls are subject to influence from methodological considerations (e.g., sampling), it is clear that Google Trends data can be used to make a prediction, but do not present a magic bullet solution to polling problems.

Global Trends in Phytohormone Research: Google Trends Analysis Revealed African Countries Have Higher Demand for Phytohormone Information

The lines of research conducted within a country often reflect its focus on current and future economic needs. Analyzing "search" trends on the internet can provide important insight into predicting the direction of a country in regards to agriculture, health, economy, and other areas. 'Google Trends' collects data on search terms from different countries, and this information can be used to better understand sentiments in different countries and regions. Agricultural output is responsible for feeding the world and there is a continuous quest to find ways to make agriculture more productive, safe, and reliable. The application of phytohormones has been used in agriculture world-wide for many years to improve crop production and continues to be an active area of research for the application in plants. Therefore, in the current study, we searched 'Google Trends' using the phytohormone search terms, abscisic acid, auxins, brassinosteroids, cytokinin, ethylene, gibberellins, jasmonic acid, salicylic acid, and strigolactones. The results indicated that the African country Zambia had the greatest number of queries on auxin research, and Kenya had the most queries in cytokinin and gibberellin research world-wide. For other phytohormones, India had the greatest number of queries for abscisic acid and South Korea had the greatest number of ethylene and jasmonic acid search world-wide. Queries on salicylic acid have been continuously increasing while the least number of queries were related to strigolactones. Only India and United States of America had significant numbers of queries on all nine phytohormones while queries on one or more phytohormones were absent in other countries. India is one of the top five crop-producing countries in the world for apples, millet, orange, potato, pulses, rice, sugarcane, tea, and wheat. Similarly, the United States of America is one of the top five crop-producing countries of the world for apples, grapes, maze, orange, potato, sorghum, sugarcane, and wheat. These might be the most possible factors for the search queries found for all the nine phytohormones in India and the United States of America.

Cross-Country Comparison of Public Awareness, Rumors, and Behavioral Responses to the COVID-19 Epidemic: Infodemiology Study

BACKGROUND

Understanding public behavioral responses to the coronavirus disease (COVID-19) epidemic and the accompanying infodemic is crucial to controlling the epidemic.

OBJECTIVE

The aim of this study was to assess real-time public awareness and behavioral responses to the COVID-19 epidemic across 12 selected countries.

METHODS

Internet surveillance was used to collect real-time data from the general public to assess public awareness and rumors (China: Baidu; worldwide: Google Trends) and behavior responses (China: Ali Index; worldwide: Google Shopping). These indices measured the daily number of searches or purchases and were compared with the numbers of daily COVID-19 cases. The trend comparisons across selected countries were observed from December 1, 2019 (prepandemic baseline) to April 11, 2020 (at least one month after the governments of selected countries took actions for the pandemic).

RESULTS

We identified missed windows of opportunity for early epidemic control in 12 countries, when public awareness was very low despite the emerging epidemic. China's epidemic and the declaration of a public health emergency of international concern did not prompt a worldwide public reaction to adopt health-protective measures; instead, most countries and regions only responded to the epidemic after their own case counts increased. Rumors and misinformation led to a surge of sales in herbal remedies in China and antimalarial drugs worldwide, and timely clarification of rumors mitigated the rush to purchase unproven remedies.

CONCLUSIONS

Our comparative study highlights the urgent need for international coordination to promote mutual learning about epidemic characteristics and effective control measures as well as to trigger early and timely responses in individual countries. Early release of official guidelines and timely clarification of rumors led by governments are necessary to guide the public to take rational action.

Fluctuation of Public Interest in COVID-19 in the United States: Retrospective Analysis of Google Trends Search Data

BACKGROUND

In the absence of vaccines and established treatments, nonpharmaceutical interventions (NPIs) are fundamental tools to control coronavirus disease (COVID-19) transmission. NPIs require public interest to be successful. In the United States, there is a lack of published research on the factors that influence public interest in COVID-19. Using Google Trends, we examined the US level of public interest in COVID-19 and how it correlated to testing and with other countries.

OBJECTIVE

The aim of this study was to determine how public interest in COVID-19 in the United States changed over time and the key factors that drove this change, such as testing. US public interest in COVID-19 was compared to that in countries that have been more successful in their containment and mitigation strategies.

METHODS

In this retrospective study, Google Trends was used to analyze the volume of internet searches within the United States relating to COVID-19, focusing on dates between December 31, 2019, and March 24, 2020. The volume of internet searches related to COVID-19 was compared to that in other countries.

RESULTS

Throughout January and February 2020, there was limited search interest in COVID-19 within the United States. Interest declined for the first 21 days of February. A similar decline was seen in geographical regions that were later found to be experiencing undetected community transmission in February. Between March 9 and March 12, 2020, there was a rapid rise in search interest. This rise in search interest was positively correlated with the rise of positive tests for SARS-CoV-2 (6.3, 95% CI -2.9 to 9.7; P<.001). Within the United States, it took 52 days for search interest to rise substantially after the first positive case; in countries with more successful outbreak control, search interest rose in less than 15 days.

CONCLUSIONS

Containment and mitigation strategies require public interest to be successful. The initial level of COVID-19 public interest in the United States was limited and even decreased during a time when containment and mitigation strategies were being established. A lack of public interest in COVID-19 existed in the United States when containment and mitigation policies were in place. Based on our analysis, it is clear that US policy makers need to develop novel methods of communicating COVID-19 public health initiatives.

Forecasting seasonal influenza-like illness in South Korea after 2 and 30 weeks using Google Trends and influenza data from Argentina

We aimed to identify variables for forecasting seasonal and short-term targets for influenza-like illness (ILI) in South Korea, and other input variables through weekly time-series of the variables. We also aimed to suggest prediction models for ILI activity using a seasonal autoregressive integrated moving average, including exogenous variables (SARIMAX) models. We collected ILI, FluNet surveillance data, Google Trends (GT), weather, and air-pollution data from 2010 to 2019, applying cross-correlation analysis to identify the time lag between the two respective time-series. The relationship between ILI in South Korea and the input variables were evaluated with Linear regression models. To validate selected input variables, the autoregressive moving average, including exogenous variables (ARMAX) models were used to forecast seasonal ILI after 2 and 30 weeks with a three-year window for the training set used in the fixed rolling window analysis. Moreover, a final SARIMAX model was constructed. Influenza A virus activity peaks in South Korea were roughly divided between the 51st and the 7th week, while those of influenza B were divided between the 3rd and 14th week. GT showed the highest correlation coefficient with forecasts from a week ahead, and seasonal influenza outbreak patterns in Argentina showed a high correlation with those 30 weeks ahead in South Korea. The prediction models after 2 and 30 weeks using ARMAX models had R2 values of 0.789 and 0.621, respectively, indicating that reference models using only the previous seasonal ILI could be improved. The currently eligible input variables selected by the cross-correlation analysis helped propose short-term and long-term predictions for ILI in Korea. Our findings indicate that influenza surveillance in Argentina can help predict seasonal ILI patterns after 30 weeks in South Korea, and these can help the Korea Centers for Disease Control and Prevention determine vaccine strategies for the next ILI season.

Correlation between the Spread of COVID-19 and the Interest in Personal Protective Measures in Poland and Portugal

The pandemic of the coronavirus disease 2019 (COVID-19), has gained extensive coverage in public media and global news, generated international and national communication campaigns to educate the communities worldwide and raised the attention of everyone. The coronavirus has caused viral pneumonia in tens of thousands of people around the world, and the COVID-19 outbreak changed most countries’ routines and concerns and transformed social behaviour. This study explores the potential use of Google Trends (GT) in monitoring interest in the COVID-19 outbreak and, specifically, in personal protective equipment and hand hygiene, since these have been promoted by official health care bodies as two of the most protective measures. GT was chosen as a source of reverse engineering data, given the interest in the topic and the novelty of the research. Current data on COVID-19 are retrieved from GT using keywords in two languages—Portuguese and Polish. The geographical settings for GT are two countries: Poland and Portugal. The period under analysis is 20 January 2020, when the first cases outside China were known, to 15 June 2020. The results show that there is a correlation between the spread of COVID-19 and the search for personal protective equipment and hand hygiene and that GT can help, to a certain extent, understand people’s concerns, behaviour and reactions to sanitary problems and protection recommendations.

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

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

Mapping population mental health concerns related to COVID-19 and the consequences of physical distancing: a Google trends analysis

Background: The 2020 Coronavirus pandemic is a major international public health challenge.  Governments have taken public health protection measures to reduce the spread of the virus through non-pharmalogical measures. The impact of the pandemic and the public health response on individual and population mental health is unknown.  Methods: We used Google Trends data (1 Jan 2020 -  30 Mar 2020) to investigate the impact of the pandemic and government measures to curb it on people's concerns, as indexed by changes in search frequency for topics indicating mental distress, social and economic stressors and mental health treatment-seeking. We explored the changes of key topics in Google trends in Italy, Spain, USA, UK, and Worldwide in relation to sentinel events during the pandemic. Results: Globally there appears to be significant concerns over the financial and work-related consequences of the pandemic, with some evidence that levels of fear are rising. Conversely relative searching for topics related to depression and suicide fell after the pandemic was announced, with some evidence that searches for the latter have risen recently. Concerns over education and access to medication appear to be particular social stressors. Whilst searches for face-to-face treatments have declined, those for self-care have risen. Conclusions: Monitoring Google trends shows promise as a means of tracking changing public concerns. In weeks to come it may enable policy makers to assess the impact of their interventions including those aiming to limit negative consequences, such as government funded financial safety nets.

Association of the COVID-19 pandemic with Internet Search Volumes: A Google TrendsTM Analysis

OBJECTIVES

To assess the association of public interest in coronavirus infections with the actual number of infected cases for selected countries across the globe.

METHODS

We performed a Google Trends^TM search for "Coronavirus" and compared Relative Search Volumes (RSV) indices to the number of reported COVID-19 cases by the European Center for Disease Control (ECDC) using time-lag correlation analysis.

RESULTS

Worldwide public interest in Coronavirus reached its first peak end of January when numbers of newly infected patients started to increase exponentially in China. The worldwide Google Trends^TM index reached its peak on the 12th of March 2020 at a time when numbers of infected patients started to increase in Europe and COVID-19 was declared a pandemic. At this time the general interest in China but also the Republic of Korea has already been significantly decreased as compared to end of January. Correlations between RSV indices and number of new COVID-19 cases were observed across all investigated countries with highest correlations observed with a time lag of -11.5 days, i.e. highest interest in coronavirus observed 11.5 days before the peak of newly infected cases. This pattern was very consistent across European countries but also holds true for the US. In Brazil and Australia, highest correlations were observed with a time lag of -7 days. In Egypt the highest correlation is given with a time lag of 0, potentially indicating that in this country, numbers of newly infected patients will increase exponentially within the course of April.

CONCLUSIONS

Public interest indicated by RSV indices can help to monitor the progression of an outbreak such as the current COVID-19 pandemic. Public interest is on average highest 11.5 days before the peak of newly infected cases.

Conversations and Medical News Frames on Twitter: Infodemiological Study on COVID-19 in South Korea

Background

SARS-CoV-2 (severe acute respiratory coronavirus 2) was spreading rapidly in South Korea at the end of February 2020 following its initial outbreak in China, making Korea the new center of global attention. The role of social media amid the current coronavirus disease (COVID-19) pandemic has often been criticized, but little systematic research has been conducted on this issue. Social media functions as a convenient source of information in pandemic situations.

Objective

Few infodemiology studies have applied network analysis in conjunction with content analysis. This study investigates information transmission networks and news-sharing behaviors regarding COVID-19 on Twitter in Korea. The real time aggregation of social media data can serve as a starting point for designing strategic messages for health campaigns and establishing an effective communication system during this outbreak.

Methods

Korean COVID-19-related Twitter data were collected on February 29, 2020. Our final sample comprised of 43,832 users and 78,233 relationships on Twitter. We generated four networks in terms of key issues regarding COVID-19 in Korea. This study comparatively investigates how COVID-19-related issues have circulated on Twitter through network analysis. Next, we classified top news channels shared via tweets. Lastly, we conducted a content analysis of news frames used in the top-shared sources.

Results

The network analysis suggests that the spread of information was faster in the Coronavirus network than in the other networks (Corona19, Shincheon, and Daegu). People who used the word “Coronavirus” communicated more frequently with each other. The spread of information was faster, and the diameter value was lower than for those who used other terms. Many of the news items highlighted the positive roles being played by individuals and groups, directing readers’ attention to the crisis. Ethical issues such as deviant behavior among the population and an entertainment frame highlighting celebrity donations also emerged often. There was a significant difference in the use of nonportal (n=14) and portal news (n=26) sites between the four network types. The news frames used in the top sources were similar across the networks (P=.89, 95% CI 0.004-0.006). Tweets containing medically framed news articles (mean 7.571, SD 1.988) were found to be more popular than tweets that included news articles adopting nonmedical frames (mean 5.060, SD 2.904; N=40, P=.03, 95% CI 0.169-4.852).

Conclusions

Most of the popular news on Twitter had nonmedical frames. Nevertheless, the spillover effect of the news articles that delivered medical information about COVID-19 was greater than that of news with nonmedical frames. Social media network analytics cannot replace the work of public health officials; however, monitoring public conversations and media news that propagates rapidly can assist public health professionals in their complex and fast-paced decision-making processes.

Mapping population mental health concerns related to COVID-19 and the consequences of physical distancing: a Google trends analysis

Background: The 2020 Coronavirus pandemic is a major international public health challenge.  Governments have taken public health protection measures to reduce the spread of the virus through non-pharmalogical measures. The impact of the pandemic and the public health response on individual and population mental health is unknown.  Methods: We used Google Trends data (1 Jan 2020 - 1 Apr 2020) to investigate the impact of the pandemic and government measures to curb it on people's concerns, as indexed by changes in search frequency for topics indicating mental distress, social and economic stressors and mental health treatment-seeking. We explored the changes of key topics in Google trends in Italy, Spain, USA, UK, and Worldwide in relation to sentinel events during the pandemic. Results: Globally there appears to be significant concerns over the financial and work-related consequences of the pandemic, with some evidence that levels of fear are rising. Conversely searching for topics related to depression and suicide fell after the pandemic was announced, with some evidence that searches for the latter have risen recently. Concerns over education and access to medication appear to be particular social stressors. Whilst searches for face-to-face treatments have declined, those for self-care have risen. Conclusions: Monitoring Google trends shows promise as a means of tracking changing public concerns. In weeks to come it may enable policy makers to assess the impact of their interventions including those aiming to limit negative consequences, such as government funded financial safety nets.

Association of the COVID-19 pandemic with Internet Search Volumes: A Google TrendsTM Analysis

OBJECTIVES

To assess the association of public interest in coronavirus infections with the actual number of infected cases for selected countries across the globe.

METHODS

We performed a Google Trends^TM search for "Coronavirus" and compared Relative Search Volumes (RSV) indices to the number of reported COVID-19 cases by the European Center for Disease Control (ECDC) using time-lag correlation analysis.

RESULTS

Worldwide public interest in Coronavirus reached its first peak end of January when numbers of newly infected patients started to increase exponentially in China. The worldwide Google Trends^TM index reached its peak on the 12th of March 2020 at a time when numbers of infected patients started to increase in Europe and COVID-19 was declared a pandemic. At this time the general interest in China but also the Republic of Korea has already been significantly decreased as compared to end of January. Correlations between RSV indices and number of new COVID-19 cases were observed across all investigated countries with highest correlations observed with a time lag of -11.5 days, i.e. highest interest in coronavirus observed 11.5 days before the peak of newly infected cases. This pattern was very consistent across European countries but also holds true for the US. In Brazil and Australia, highest correlations were observed with a time lag of -7 days. In Egypt the highest correlation is given with a time lag of 0, potentially indicating that in this country, numbers of newly infected patients will increase exponentially within the course of April.

CONCLUSIONS

Public interest indicated by RSV indices can help to monitor the progression of an outbreak such as the current COVID-19 pandemic. Public interest is on average highest 11.5 days before the peak of newly infected cases.

Is There Decreasing Public Interest in Renal Transplantation? A Google TrendsTM Analysis

BACKGROUND AND OBJECTIVES

Renal transplantation is the preferred form of renal replacement therapy for the majority of patients with end stage renal disease (ESRD). The Internet is a key tool for people seeking healthcare-related information. This current work explored the interest in kidney transplantation based on Internet search queries using Google Trends^TM.

DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS

We performed a Google Trends^TM search with the search term "kidney transplantation" between 2004 (year of inception) and 2018. We retrieved and analyzed data on the worldwide trend as well as data from the United Network for Organ Sharing (UNOS), the Organización Nacional de Trasplantes (ONT), the Eurotransplant area, and the National Health Service (NHS) Transplant Register. Google Trends^TM indices were investigated and compared to the numbers of performed kidney transplants, which were extracted from the respective official websites of UNOS, ONT, Eurotransplant, and the NHS.

RESULTS

During an investigational period of 15 years, there was a significant decrease of the worldwide Google Trends^TM index from 76.3 to 25.4, corresponding to an absolute reduction of -50.9% and a relative reduction by -66.7%. The trend was even more pronounced for the UNOS area (-75.2%), while in the same time period the number of transplanted kidneys in the UNOS area increased by 21.9%. Events of public interest had an impact on the search queries in the year of occurrence, as shown by an increase in the Google Trends^TM index by 39.2% in the year 2005 in Austria when a person of public interest received his second live donor kidney transplant.

CONCLUSIONS

This study indicates a decreased public interest in kidney transplantation. There is a clear need to raise public awareness, since transplantation represents the best form of renal replacement therapy for patients with ESRD. Information should be provided on social media, with a special focus on readability and equitable access, as well as on web pages.

Google Health Trends performance reflecting dengue incidence for the Brazilian states

BACKGROUND

Dengue fever is a mosquito-borne infection transmitted by Aedes aegypti and mainly found in tropical and subtropical regions worldwide. Since its re-introduction in 1986, Brazil has become a hotspot for dengue and has experienced yearly epidemics. As a notifiable infectious disease, Brazil uses a passive epidemiological surveillance system to collect and report cases; however, dengue burden is underestimated. Thus, Internet data streams may complement surveillance activities by providing real-time information in the face of reporting lags.

METHODS

We analyzed 19 terms related to dengue using Google Health Trends (GHT), a free-Internet data-source, and compared it with weekly dengue incidence between 2011 to 2016. We correlated GHT data with dengue incidence at the national and state-level for Brazil while using the adjusted R squared statistic as primary outcome measure (0/1). We used survey data on Internet access and variables from the official census of 2010 to identify where GHT could be useful in tracking dengue dynamics. Finally, we used a standardized volatility index on dengue incidence and developed models with different variables with the same objective.

RESULTS

From the 19 terms explored with GHT, only seven were able to consistently track dengue. From the 27 states, only 12 reported an adjusted R squared higher than 0.8; these states were distributed mainly in the Northeast, Southeast, and South of Brazil. The usefulness of GHT was explained by the logarithm of the number of Internet users in the last 3 months, the total population per state, and the standardized volatility index.

CONCLUSIONS

The potential contribution of GHT in complementing traditional established surveillance strategies should be analyzed in the context of geographical resolutions smaller than countries. For Brazil, GHT implementation should be analyzed in a case-by-case basis. State variables including total population, Internet usage in the last 3 months, and the standardized volatility index could serve as indicators determining when GHT could complement dengue state level surveillance in other countries.

Google Medical Update: Why Is the Search Engine Decreasing Visibility of Health and Medical Information Websites?

The Google search engine answers many health and medical information queries every day. People have become used to searching for this type of information. This paper presents a study which examined the visibility of health and medical information websites. The purpose of this study was to find out why Google is decreasing the visibility of such websites and how to measure this decrease. Since August 2018, Google has been more rigorously rating these websites, since they can potentially impact people’s health. The method of the study was to collect data about the visibility of health and medical information websites in sequential time snapshots. Visibility consists of combined data of unique keywords, positions, and URL results. The sample under study was made up of 21 websites selected from 10 European countries. The findings reveal that in sequential time snapshots, search visibility decreased. The decrease was not dependent on the country or the language. The main reason why Google is decreasing the visibility of such websites is that they do not meet high ranking criteria.

All that glitters is not gold. The rise of gaming in the COVID-19 pandemic

The COVID-19 pandemic has led to an unprecedented situation, with incalculable health, social, and economic consequences. At the start of the outbreak, the financial markets collapsed, although not all sectors suffered equally. The gaming and eSports industry is one of those that has suffered the least from the fall in the markets. Millions of people locked up at home, bored, stressed, and anguished, gave gaming and eSports companies growing prominence throughout the first half of 2020. This prominence has elicited interest in analyzing which variables can influence the returns in an industry in better financial health than many others. Using a logit–probit model, this research aims to analyze the relationship between financial (VIX, S&P GSCI Gold Index) and social (worldwide daily variation in total deaths from COVID-19 and worldwide Google attention on coronavirus) variables and the returns offered by the video game and eSports exchange traded fund (ESPO). The results show that the influence of social variables is weaker than the influence of financial variables. There is a significant inverse relationship between market volatility and ESPO returns and a highly significant relationship between ESPO returns and gold returns. While the relationship of ESPO returns with worldwide Google attention on coronavirus is significant, the relationship with worldwide daily variation in total deaths from COVID-19 is not. The conclusions of the study are discussed at the end of the paper.

A Google–Wikipedia–Twitter Model as a Leading Indicator of the Numbers of Coronavirus Deaths

Forecasting the number of cases and the number of deaths in a pandemic provides critical information to governments and health officials, as seen in the management of the coronavirus outbreak. But things change. Thus, there is a constant search for real‐time and leading indicator variables that can provide insights into disease propagation models. Researchers have found that information about social media and search engine use can provide insights into the diffusion of flu and other diseases. Consistent with this finding, we found that a model with the number of Google searches, Twitter tweets, and Wikipedia page views provides a leading indicator model of the number of people in the USA who will become infected and die from the coronavirus. Although we focus on the current coronavirus pandemic, other recent viruses have threatened pandemics (e.g. severe acute respiratory syndrome). Since future and existing diseases are likely to follow a similar search for information, our insights may prove fruitful in dealing with the coronavirus and other such diseases, particularly in the early phases of the disease.

Subject terms: coronavirus, COVID‐19, unintentional crowd, Google searches, Wikipedia page views, Twitter tweets, models of disease diffusion.

Forecasting type-specific seasonal influenza after 26 weeks in the United States using influenza activities in other countries

To identify countries that have seasonal patterns similar to the time series of influenza surveillance data in the United States and other countries, and to forecast the 2018-2019 seasonal influenza outbreak in the U.S., we collected the surveillance data of 164 countries using the FluNet database, search queries from Google Trends, and temperature from 2010 to 2018. Data for influenza-like illness (ILI) in the U.S. were collected from the Fluview database. We identified the time lag between two time-series which were weekly surveillances for ILI, total influenza (Total INF), influenza A (INF A), and influenza B (INF B) viruses between two countries using cross-correlation analysis. In order to forecast ILI, Total INF, INF A, and INF B of next season (after 26 weeks) in the U.S., we developed prediction models using linear regression, auto regressive integrated moving average, and an artificial neural network (ANN). As a result of cross-correlation analysis between the countries located in northern and southern hemisphere, the seasonal influenza patterns in Australia and Chile showed a high correlation with those of the U.S. 22 weeks and 28 weeks earlier, respectively. The R2 score of ANN models for ILI for validation set in 2015-2019 was 0.758 despite how hard it is to forecast 26 weeks ahead. Our prediction models forecast that the ILI for the U.S. in 2018-2019 may be later and less severe than those in 2017-2018, judging from the influenza activity for Australia and Chile in 2018. It allows to estimate peak timing, peak intensity, and type-specific influenza activities for next season at 40th week. The correlation between seasonal influenza patterns in the U.S., Australia, and Chile could be used to forecast the next seasonal influenza pattern, which can help to determine influenza vaccine strategy approximately six months ahead in the U.S.

The second information revolution: digitalization brings opportunities and concerns for public health

The spread of the written word, facilitated by the introduction of the printing press, was an information revolution with profound implications for European society. Now, a second information revolution is underway, a digital transformation that is shaping the way Europeans live and interact with each other and the world around them. We are confronted with an unprecedented expansion in ways to share and access information and experiences, to express ourselves and communicate. Yet while these changes have undoubtedly provided many benefits for health, from information sharing to improved surveillance and diagnostics, they also open up many potential threats. These come in many forms. Here we review some the pressing issues of concern; discrimination; breaches of privacy; iatrogenesis; disinformation and misinformation or 'fake news' and cyber-attacks. These have the potential to impact negatively on the health and wellbeing of individuals as well as entire communities and nations. We call for a concerted European response to maximize the benefits of the digital revolution while minimizing the harms, arguably one of the greatest challenges facing the public health community today.

Just Google it! Impact of media coverage of an outbreak of high-level azithromycin-resistant Neisseria gonorrhoeae on online searches, and attendances, testing and diagnoses at sexual health clinics in England between 2015 and 2016: an interrupted time series analysis using surveillance data

OBJECTIVES

To determine if media coverage of an outbreak of high-level azithromycin-resistant Neisseria gonorrhoeae (HL-AziR) impacted online search interest or was temporally associated with health-seeking behaviours in several English cities.

METHODS

A descriptive analysis of outbreak-related online media articles and relative search interest (RSI) using Google and an interrupted time series analysis using routine surveillance data from sexual health clinics (SHCs) in England (GUMCAD STI surveillance system). The main outcomes were adjusted incidence rate ratios (IRRs) of weekly attendances, gonorrhoea tests and diagnoses of gonorrhoea or 'any STI' in selected cities after media coverage of the outbreak in 2015 and 2016.

RESULTS

RSI for outbreak-related terms peaked during media coverage in September 2015 with smaller peaks coinciding with subsequent coverage. The greatest increase in RSI was in Leeds, which coincided with a 63% rise (n=1932; IRR 1.26, 95% CI 1.12 to 1.43) in SHC attendances by women. There was only a 7% (n=1358; IRR 1.01, 95% CI 0.91 to 1.11) increase in attendances by men. Modest increases in outcomes occurred in four other cities with a high RSI. There was no evidence of increases in outcomes in cities, other than Leeds, after subsequent media coverage of the outbreak.

CONCLUSIONS

National and local media coverage of the HL-AziR outbreak coincided with peak RSI for related terms, and a transient increase in attendances, gonorrhoea tests and diagnoses of gonorrhoea or 'any STI' in some cities with a high RSI. Our analysis demonstrates the potential for media coverage to influence health-seeking behaviours during high-profile STI outbreaks.