scholarly journals Suitability of Google Trends™ for digital surveillance during ongoing COVID-19 epidemic: a case study from India

2021 ◽  
pp. 1-28
Author(s):  
Parmeshwar Satpathy ◽  
Sanjeev Kumar ◽  
Pankaj Prasad
Keyword(s):  
Information Seeking ◽  
Media Coverage ◽  
Time Lag ◽  
National Level ◽  
Google Trends ◽  
Health Seeking ◽  
High Burden ◽  
Search Volume ◽  
Digital Surveillance ◽  
Time Lag Correlation

Abstract Objective: Digital surveillance has shown mixed results as supplement to traditional surveillance. Google Trends™ (GT) has been used for digital surveillance of H1N1, Ebola and MERS. We used GT to correlate the information seeking on COVID-19 with number of tests and cases in India. Methods: We obtained data on daily tests and cases from WHO, ECDC and covid19india.org. We used a comprehensive search strategy to retrieve GT data on COVID-19 related information-seeking behaviour in India between 1st January and 31st May 2020 in the form of relative search volume (RSV). We used time-lag correlation analysis to assess the temporal relationships between RSV and daily new COVID-19 cases and tests. Results: GT RSV showed high time-lag correlation with both daily reported tests and cases for the terms “COVID 19”, “COVID”, “social distancing”, “soap” and “lockdown” at national level. In five high-burden states, high correlation was observed for these five terms along with “Corona”. Peaks in RSV both at national level and high-burden states corresponded with media coverage or government declarations on the ongoing pandemic. Conclusion: The correlation observed between GT data and COVID-19 tests/cases in India may be either due to media-coverage induced curiosity or health-seeking.

scholarly journals Suitability of Google Trends ™ for digital surveillance during ongoing COVID-19 epidemic: a case study from India

2020 ◽  
Author(s):  
Parmeshwar D Satpathy ◽  
Sanjeev Kumar ◽  
Pankaj Prasad
Keyword(s):  
Media Coverage ◽  
Time Lag ◽  
National Level ◽  
High Time ◽  
Google Trends ◽  
High Burden ◽  
Social Distancing ◽  
Digital Surveillance ◽  
Traditional Surveillance ◽  
Time Lag Correlation

Background: India went into the largest population-level lockdown on 25th March 2020 in response to the declaration of COVID-19 pandemic by World Health Organization (WHO). Digital surveillance has been shown to be useful to supplement the traditional surveillance. Google Trends ™ (GT) is one such platform reported to be useful during pandemics of H1N1, Ebola and MERS. Objective: We used GT to correlate the information seeking behaviour regarding COVID-19 of Indians with curiosity and apprehensiveness generated through media coverage as well as status of the epidemic both at national and state levels. Methods: We retrieved GT data between 1st January 2020 to 31st May 2020 for India using a comprehensive search strategy. We obtained data on daily tests and cases from WHO, ECDC and covid19india.org websites. We explored the trends of COVID-19 in the form of relative search volume (RSV) from GT platform and correlated them with media reports. We used time-lag correlation analysis to assess the temporal relationships between Google search terms and daily new COVID-19 cases and daily tests for 14 days. Results: Peaks in RSV correlated with media coverage or government declarations suggestive of curiosity and apprehensiveness both at national level and high-burden states. High time-lag correlation was observed between both the daily reported number of tests and cases and RSV for the terms ″COVID 19″, ″COVID″, ″social distancing″, ″soap″ and ″lockdown″ at national level. Similar high time-lag correlation was observed for the terms ″COVID 19″, ″COVID″, ″Corona″, ″social distancing″, ″soap″, ″lockdown″ in five high-burden states. Conclusion: This study reveals the advantages of infodemiology using GT to monitor an emerging infectious disease like COVID-19 in India. Google searches in India during the ongoing COVID-19 pandemic reflects mostly curiosity and apprehension of citizens. GT can also complement traditional surveillance in India as well as high burden states.

Suitability of Google Trends™ for digital surveillance during ongoing COVID-19 epidemic: a case study from India (Preprint)

2020 ◽  
Author(s):  
Parmeshwar Satpathy ◽  
Sanjeev Kumar ◽  
Pankaj Prasad
Keyword(s):  
Media Coverage ◽  
Time Lag ◽  
National Level ◽  
High Time ◽  
Google Trends ◽  
High Burden ◽  
Social Distancing ◽  
Digital Surveillance ◽  
Traditional Surveillance ◽  
Time Lag Correlation

BACKGROUND Digital surveillance has shown mixed results as supplement to the traditional surveillance. Google Trends™ (GT) is a digital platform explored for surveillance during pandemics of H1N1, Ebola and MERS. Similar efforts have been reported for the ongoing COVID-19 pandemic too. OBJECTIVE We used GT to correlate the information seeking on COVID-19 with number of tests and cases reported both at national and state levels. METHODS We obtained data on daily tests and cases from WHO, ECDC and covid19india.org websites. We retrieved GT data between 1st January 2020 to 31st May 2020 for India using a comprehensive search strategy in the form of relative search volume (RSV). We used time-lag correlation analysis to assess the temporal relationships between RSV and daily new COVID-19 cases and daily tests. RESULTS High time-lag correlation was observed between both the daily reported number of tests and cases and RSV for the terms “COVID 19”, “COVID”, “social distancing”, “soap” and “lockdown” at national level. Similar high time-lag correlation was observed for the terms “COVID 19”, “COVID”, “Corona”, “social distancing”, “soap”, “lockdown” in five high-burden states. Peaks in RSV both at national level and high-burden states corresponded with media coverage or government declarations on the ongoing pandemic. CONCLUSIONS The results of this study show that Google Trends™ data are highly correlated with COVID-19 tests and cases in India. This correlation may be because of search behaviour induced either by media-coverage of the pandemic or health-seeking for COVID-19 illness. We argue that GT can supplement the traditional surveillance system, more easily and at a lower cost.

scholarly journals Increase in public interest concerning alternative medicine during the COVID-19 pandemic in Indonesia: a Google Trends study

F1000Research ◽  
2021 ◽  
Vol 9 ◽  
pp. 1201
Author(s):  
Dewi Rokhmah ◽  
Khaidar Ali ◽  
Serius Miliyani Dwi Putri ◽  
Khoiron Khoiron
Keyword(s):  
Alternative Medicine ◽  
Public Interest ◽  
Time Lag ◽  
Google Trends ◽  
Rank Test ◽  
Search Term ◽  
Alternative Medicines ◽  
Search Volume ◽  
Relative Search Volume ◽  
Time Lag Correlation

Background: The COVID-19 pandemic has triggered individuals to increase their healthy behaviour in order to prevent transmission, including improving their immunity potentially through the use of alternative medicines. This study aimed to examine public interest on alternative medicine during the COVID-19 pandemic using Google Trends in Indonesia. Methods: Employing a quantitative study, the Spearman rank test was used to analyze the correlation between Google Relative Search Volume (RSV) of various search terms, within the categories of alternative medicine, herbal medicine and practical activity, with COVID-19 cases. In addition, time lag correlation was also investigated. Results: Public interest toward alternative medicine during COVID-19 pandemic in Indonesia is dramatically escalating. All search term categories (alternative medicine, medical herbal, and alternative medicine activities) were positively associated with COVID-19 cases (p<0.05). The terms ‘ginger’ (r=0.6376), ‘curcumin’ (r=0.6550) and ‘planting ginger’ (0.6713) had the strongest correlation. Furthermore, time lag correlation between COVID-19 and Google RSV was also positively significant (p<0.05). Conclusion: Public interest concerning alternative medicine related terms dramatically increased after the first COVID-19 confirmed case was reported in Indonesia. Time lag correlation showed good performance using weekly data. The Indonesian Government will play an important role to provide and monitor information related to alternative medicine in order for the population to receive the maximum benefit.

scholarly journals Increase in public interest concerning alternative medicine during the COVID-19 pandemic in Indonesia: a Google Trends study

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1201
Author(s):  
Dewi Rokhmah ◽  
Khaidar Ali ◽  
Serius Miliyani Dwi Putri ◽  
Khoiron Khoiron
Keyword(s):  
Alternative Medicine ◽  
Public Interest ◽  
Time Lag ◽  
Google Trends ◽  
Rank Test ◽  
Search Term ◽  
Alternative Medicines ◽  
Search Volume ◽  
Relative Search Volume ◽  
Time Lag Correlation

Background: The COVID-19 pandemic has triggered individuals to increase their healthy behaviour in order to prevent transmission, including improving their immunity potentially through the use of alternative medicines. This study aimed to examine public interest on alternative medicine during the COVID-19 pandemic using Google Trends in Indonesia. Methods: Employing a quantitative study, the Spearman rank test was used to analyze the correlation between Google Relative Search Volume (RSV) of various search terms, within the categories of alternative medicine, herbal medicine and practical activity, with COVID-19 cases. In addition, time lag correlation was also investigated. Results: Public interest toward alternative medicine during COVID-19 pandemic in Indonesia is dramatically escalating. All search term categories (alternative medicine, medical herbal, and alternative medicine activities) were positively associated with COVID-19 cases (p<0.05). The terms ‘ginger’ (r=0.6376), ‘curcumin’ (r=0.6550) and ‘planting ginger’ (0.6713) had the strongest correlation. Furthermore, time lag correlation between COVID-19 and Google RSV was also positively significant (p<0.05). Conclusion: Public interest concerning alternative medicine related terms dramatically increased after the first COVID-19 confirmed case was reported in Indonesia. Time lag correlation showed good performance using weekly data. The Indonesian Government will play an important role to provide and monitor information related to alternative medicine in order for the population to receive the maximum benefit.

scholarly journals Potential use of personal protection online search during COVID-19 pandemic for predicting and monitoring public response

2020 ◽  
Vol 9 (4) ◽  
pp. 406
Author(s):  
Michael Chandra ◽  
Rizma Adlia Syakurah
Keyword(s):  
Public Health ◽  
Risk Communication ◽  
Pearson Correlation ◽  
Time Lag ◽  
Early Warning Systems ◽  
Google Trends ◽  
Series Data ◽  
Personal Protection ◽  
Search Volume ◽  
Time Lag Correlation

COVID-19 has become a global public health emergency in almost all over the world, including in Indonesia. Effective risk communication becomes an emergency response to increase awareness and determine appropriate interventions. The study aimed to assess the success of risk communication monitoring using Google Trends during the COVID-19 pandemic in Indonesia. Quantitative and qualitative research uses time-series data (31 December 2019-2 May 2020). The relative search volume (RSV) of keyword „masker‟ (mask) and „cuci tangan‟ (handwashing) from Google Trends (GT) and the number of COVID-19 daily cases were collected. Analyzed qualitatively. RSV search data and daily case comparisons were performed based on Pearson correlation analysis and time lag correlation with significance &lt;0.05. The keyword „masker‟ has four peaks and „cuci tangan‟ has three peaks with fluctuations due to the increase in mask prices, government policies, news, and official WHO recommendations. Validation using time-lag correlation shows the significant results between RSV keywords related to personal protection and the number of COVID-19 cases. The highest correlation was achieved by the keyword „masker‟ three days before the number of COVID-19 cases. Google Trends can potentially be used as a complement and support for early warning systems in the surveillance system and improve public health responses in Indonesia.

scholarly journals Analysis of public search interest towards immune system improvement during the COVID-19 pandemic using Google Trends

2020 ◽  
Vol 9 (4) ◽  
pp. 414
Author(s):  
Linda Amelia ◽  
Rizma Adlia Syakurah
Keyword(s):  
Immune System ◽  
Risk Communication ◽  
Public Awareness ◽  
Time Lag ◽  
Google Trends ◽  
Series Data ◽  
Search Term ◽  
Search Volume ◽  
System Improvement ◽  
Time Lag Correlation

In combating COVID-19, maintaining the immune system is important. Providing this information to the general population will increase public awareness towards improving their immune system. The use of Google Trends for exploring web behavior related to a topic or search term also considered as a tool for monitoring public awareness to help risk communication during the COVID-19 pandemic. Therefore, this study was conducted to assess the use of Google Trends to monitor public awareness to immune system improvement during the COVID-19 pandemic in Indonesia. This quantitative and qualitative research used time-series data from 31 December 2019 to 2 May 2020. The time-lag correlation analysis was performed to compare between relative search volume (RSV) of “Vitamin C”, “Vaksin” (Vaccine), “Berjemur” (Sunbathing) from Google Trends (GT), and the number of reported COVID-19 new cases. Validation using time-lag correlation shows the significant correlation between RSV keywords related to public awareness towards immune system improvement and the number of COVID-19 cases in Indonesia in 1-3 days before an increase in the number of cases occurs. Google Trends has the potential to become an early warning system and a tool for monitoring risk communication towards immune system improvement during the COVID-19 pandemic by Indonesia Government.

Who's Googling What? What Internet Searches Reveal about Hurricane Information Seeking

2011 ◽  
Vol 92 (8) ◽  
pp. 975-985 ◽  
Author(s):  
Kathleen Sherman-Morris ◽  
Jason Senkbeil ◽  
Robert Carver
Keyword(s):  
Hurricane Katrina ◽  
Information Seeking ◽  
Regional Variation ◽  
Seasonal Pattern ◽  
National Level ◽  
Track Forecast ◽  
Spatial And Temporal Patterns ◽  
Practical Applications ◽  
Search Volume ◽  
Free Data

Two freely available, searchable databases that track the normalized interest in specific search queries, Google Trends and Google Insights, were used to illustrate spatial and temporal patterns in hurricane information seeking. Searches for the word “hurricane” showed a seasonal pattern with spikes in hurricane searches that corresponded to the severity of the storms making landfall. Regional variation in “hurricane” searches was largely driven by the location and magnitude of hurricane landfalls. Catastrophic hurricanes such as Hurricane Katrina captured national attention. A great deal of regional variation in search volume existed prior to Hurricane Ike's landfall. Not as much variation was seen before Hurricane Gustav and Tropical Storm Fay. This variation appeared to be related to changes in the 5-day track forecast as well as other factors such as issuance of watches and warnings. Searches from Louisiana experienced a sharp decrease after the 5-day track forecast shifted away from the state, but before Ike made landfall. Normalized daily visits to Weather Underground during August/September 2008 followed the same pattern as the Google searches. The most popular hurricane-related search terms at the national level prior to landfall dealt with forecast track and evacuation information while searches after landfall included terms related to hurricane damage. There are limitations to using this free data source, but the study has implications for the literature as well as practical applications. This study provides new information about online search behavior before a hurricane that can be utilized by those who provide weather information to the public.

scholarly journals Online behavioural patterns for Coronavirus disease 2019 (COVID-19) in the United Kingdom

2020 ◽  
Vol 148 ◽  
Author(s):  
M. D. Walker ◽  
M. Sulyok
Keyword(s):  
United Kingdom ◽  
News Media ◽  
Media Coverage ◽  
Face Mask ◽  
Google Trends ◽  
Online Searching ◽  
The United Kingdom ◽  
Search Volume ◽  
Behavioural Patterns ◽  
The Relationship

Abstract The current coronavirus (COVID-19) pandemic offers a unique opportunity to conduct an infodemiological study examining patterns in online searching activity about a specific disease and how this relates to news media within a specific country. Google Trends quantifies volumes of online activity. The relative search volume was obtained for ‘Coronavirus’, ‘handwashing’, ‘face mask’ and symptom related keywords, for the United Kingdom, from the date of the first confirmed case until numbers peaked in April. The relationship between online search traffic and confirmed case numbers was examined. Search volumes varied over time; peaks appear related to events in the progression of the epidemic which were reported in the media. Search activity on ‘Coronavirus’ correlated well against confirmed case number as did ‘face mask’ and symptom-related keywords. User-generated online data sources such as Google Trends may aid disease surveillance, being more responsive to changes in disease occurrence than traditional disease reporting. The relationship between media coverage and online searching activity is rarely examined, but may be driving online behavioural patterns.

scholarly journals Determining the nutritional immunity information seeking behaviour during the COVID-19 pandemic in India: A Google Trends data analysis

2021 ◽  
pp. 1-26
Author(s):  
Savitesh Kushwaha ◽  
Poonam Khanna ◽  
Rachita Jain ◽  
Rachana Srivastava
Keyword(s):  
Information Seeking ◽  
Correlation Method ◽  
Daily Basis ◽  
Significant Rise ◽  
Google Trends ◽  
Western India ◽  
Nutritional Immunity ◽  
Search Volume ◽  
Information Seeking Behaviour ◽  
Google Search

Abstract Objective: During COVID-19, the internet was a prime source for getting relevant updates on guidelines and desirable information. The objective of the present study was to determine the nutritional immunity information seeking behaviour during COVID-19 in India. Design: Google Trends (GTs) data on relevant COVID-19 and nutritional topics were systematically selected and retrieved. Data on newly reported COVID-19 cases were also examined on a daily basis. The cross-correlation method was used to determine the correlation coefficient between the selected terms and daily new COVID-19 cases, and the joint point regression models were utilised to measure monthly percent change in relative search volumes. Setting: Online. Participants: People using google search during period 01-01-2020 to 31-08-2020 in India. Results: The date of peak searches can be attributed to the COVID-19 guidelines announcement dates. All the nutritional terms showed a significant increase in average monthly percentage change. The higher than the average daily rise in COVID-19 cases leads to a higher than average increase in RSVs of nutritional terms with the greatest association after 14 to 27 days. The highest mean relative search volume for nutritional terms was from Southern India (49.34±7.43), and the lowest was from Western India (31.10±6.30). Conclusion: There was a significant rise in the google searches of nutritional immunity topics during COVID-19 in India. The local/regional terms can be considered for better outreach of public health guidelines or recommendations. Further automation of Google Trends using programming languages can help in real-time monitoring and planning various health/nutritional events.

scholarly journals Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kenichiro Sato ◽  
Tatsuo Mano ◽  
Atsushi Iwata ◽  
Tatsushi Toda
Keyword(s):  
Granger Causality ◽  
Media Coverage ◽  
Rank Correlation ◽  
Google Trends ◽  
Spearman’S Rank Correlation ◽  
Search Volume ◽  
Increased Risk ◽  
Study Results ◽  
English Speaking ◽  
The Impact

Abstract Background Google Trends (GT) is being used as an epidemiological tool to study coronavirus disease (COVID-19) by identifying keywords in search trends that are predictive for the COVID-19 epidemiological burden. However, many of the earlier GT-based studies include potential statistical fallacies by measuring the correlation between non-stationary time sequences without adjusting for multiple comparisons or the confounding of media coverage, leading to concerns about the increased risk of obtaining false-positive results. In this study, we aimed to apply statistically more favorable methods to validate the earlier GT-based COVID-19 study results. Methods We extracted the relative GT search volume for keywords associated with COVID-19 symptoms, and evaluated their Granger-causality to weekly COVID-19 positivity in eight English-speaking countries and Japan. In addition, the impact of media coverage on keywords with significant Granger-causality was further evaluated using Japanese regional data. Results Our Granger causality-based approach largely decreased (by up to approximately one-third) the number of keywords identified as having a significant temporal relationship with the COVID-19 trend when compared to those identified by Pearson or Spearman’s rank correlation-based approach. “Sense of smell” and “loss of smell” were the most reliable GT keywords across all the evaluated countries; however, when adjusted with their media coverage, these keyword trends did not Granger-cause the COVID-19 positivity trends (in Japan). Conclusions Our results suggest that some of the search keywords reported as candidate predictive measures in earlier GT-based COVID-19 studies may potentially be unreliable; therefore, caution is necessary when interpreting published GT-based study results.

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