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

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.

Community mobility reports predict the national spread of COVID-19 in Indonesia in the new normal era

Indonesia government encouraging to new normal life with obeys the health protocol. In Malaysia, the new normal had a significant impact on mobility trends. This study aimed to analyze the community mobility trend (including six categories) and coronavirus disease (COVID-19) daily cases in Indonesia in new normal era. An observational analytic using cross-sectional design. The community mobility data, include mobility trends for six different location categories, were obtained from Google COVID-19 Community Mobility Reports from May 15-July 14, 2020. The Indonesian’s COVID-19 daily cases data were taken from (http://covid19.go.id//) from May 15-July 17, 2020. Time-lag correlation to analyzed community mobility of each location category and COVID-19 daily cases in Indonesia using Pearson Correlation with significance ≤0.05. Recreation, parks, and transit stations have positively strong to very strong, while the residential has negatively strong, and the grocery and pharmacy and workplaces were positively weak to moderate correlations. The community mobility was significantly correlated with the COVID-19 transmission in Indonesia during new normal era, especially in transit stations, retail and recreation. Indonesia government is expected to improve their effort to manage the COVID-19 transmission and consider new policy to curb the COVID-19 transmission.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.