Google trends and COVID-19 in Italy: could we brace for impact?

Effect of IUCN Red List category on public attention to mammals

Cultural data is a powerful tool to analyze public awareness of key societal issues, including the conservation of nature. I used two publicly available repositories of cultural data, Google Trends and Google Ngram, to quantify the effect of the International Union for the Conservation of Nature (IUCN) Red List conservation status on public attention toward 4539 mammal species. With Google Trends, I calculated whether Google searches for their common and scientific names have been increasing or decreasing over time. I also ran an anomaly detection analysis to investigate whether a change in red-list status directly results in an increase in Google searches. Additionally, I quantified the mentions of species' common and scientific names in English texts with Google Ngram. Overall, Google searches for most mammal species remained at similar levels or increased since 2008. The severity of species' IUCN Red List status was a significant predictor of increasing Google searches, although the effect size was relatively small. Red-list status seemed strongly confounded with mammal body size. Species that moved to a higher-risk category spiked significantly in Google searches directly after the new designation. The mention of species' common names in the Google Ngram's English 2019 corpus significantly increased as the red-list category increased. These results provide valuable insight into the importance of the IUCN Red List for increasing public awareness and the usefulness of publicly available cultural data on examining the effectiveness of specific conservation efforts and thus evaluating targets for support and funding.

An Analysis by State on The Effect of Movement Control Order (MCO) 3.0 Due to COVID-19 on Malaysians’ Mental Health: Evidence from Google Trends

Due to significant social and economic upheavals brought on by the COVID-19 pandemic, there is a great deal of psychological pain. Google Trends data have been seen as a corollary measure to assess population-wide trends via observing trends in search results. Judicious analysis of Google Trends data can have both analytical and predictive capacities. This study aimed to compare nation-wide and inter-state trends in mental health before and after the Malaysian Movement Control Order 3.0 (MCO 3.0) commencing 12 May 2021. This was through assessment of two terms, “stress” and “sleep” in both the Malay and English language. Google Trends daily data between March 6 and 31 May in both 2019 and 2021 was obtained, and both series were re-scaled to be comparable. Searches before and after MCO 3.0 in 2021 were compared to searches before and after the same date in 2019. This was carried out using the differences in difference (DiD) method. This ensured that seasonal variations between states were not the source of our findings. We found that DiD estimates, β_3 for “sleep” and “stress” were not significantly different from zero, implying that MCO 3.0 had no effect on psychological distress in all states. Johor was the only state where the DiD estimates β_3 were significantly different from zero for the search topic ‘Tidur’. For the topic ‘Tekanan’, there were two states with significant DiD estimates, β_3, namely Penang and Sarawak. This study hence demonstrates that there are particular state-level differences in Google Trend search terms, which gives an indicator as to states to prioritise interventions and increase surveillance for mental health. In conclusion, Google Trends is a powerful tool to examine larger population-based trends especially in monitoring public health parameters such as population-level psychological distress, which can facilitate interventions.

The Relationship between Searches for COVID-19 Vaccines and Dynamics of Vaccinated People in Poland: An Infodemiological Study

BACKGROUND

Google Trends has turned out to be an appropriate tool for evaluating correlations and prognostic modelling regarding infectious diseases. The possibility of selecting a vaccine against COVID-19 has increased social interest in particular vaccines. The objective of this study was to show dependencies between the frequency of searches for COVID-19 vaccinations and the number of vaccinated people in Poland, along with epidemiological data.

METHODS

Data were collected regarding Google searches for COVID-19 vaccines, the number of people in Poland vaccinated against COVID-19, the number of new cases, and the number of deaths due to COVID-19. Data were filtered from 27 December 2020 to 1 September 2021.

RESULTS

The number of new vaccinations smoothed per million correlated most strongly with searches for the word 'Pfizer' in Google Trends (Kendall's tau = 0.46, p < 0.001). The number of new deaths correlated most strongly with the search phrase 'AstraZeneca' (Kendall's tau = 0.46, p < 0.001). The number of new cases per million correlated most strongly with searches for 'AstraZeneca' (Kendall's tau = 0.49, p < 0.001). The maximum daily number of searches ranged between 110 and 130. A significant interest in COVID-19 vaccines was observed from February to June 2021, i.e., in the period of a considerable increase in the number of new cases and new deaths due to COVID-19.

CONCLUSIONS

A significant increase in interest in COVID-19 vaccines was observed from February to June 2021, i.e., in the period of gradually extended access to vaccinations, as well as a considerable increase in the number of new cases and new deaths due to COVID-19. The use of Google Trends with relevant keywords and a comparison with the course of the COVID-19 pandemic facilitates evaluation of the relationship between the frequency and types of searches for COVID-19 vaccines and epidemiological data.

Seasonal Patterns and Trends in Dermatoses in Poland

Background: The amount of data available online is constantly increasing, including search behavior and tracking trends in domains such as Google. Analyzing the data helps to predict patient needs and epidemiological events more accurately. Our study aimed to identify dermatology-related terms that occur seasonally and any search anomalies during the SARS-CoV-2 pandemic. Methods: The data were gathered using Google Trends, with 69 entries between January-2010 and December-2020 analyzed. We conducted the Seasonal Mann–Kendal Test to determine the strength of trends. The month with the highest seasonal component (RSV) and the lowest seasonal component (RSV) was indicated for every keyword. Groups of keywords occurring together regularly at specific periods of the year were shown. Results: We found that some topics were seasonally searched in winter (e.g., herpes, scabies, candida) and others in summer (e.g., erythema, warts, urticaria). Conclusions: Interestingly, downward trends in searches on sexually transmitted diseases in comparison with increased infection rates reported officially show a strong need for improved sexual education in Poland. There were no significant differences in trends for coronavirus-related cutaneous symptoms during 2020. We have shown that the seasonality of dermatologically related terms searched in Poland via Google did not differ significantly during SARS-CoV-2 pandemic.

Interest in COVID-19 in Latin America and the Caribbean: an infodemiological study using Google Trends

Infodemiology has been widely used to assess epidemics. In light of the recent pandemic, we use Google Search data to explore online interest about COVID-19 and related topics in 20 countries of Latin America and the Caribbean. Data from Google Trends from December 12, 2019, to April 25, 2020, regarding COVID-19 and other related topics were retrieved and correlated with official data on COVID-19 cases and with national epidemiological indicators. The Latin American and Caribbean countries with the most interest for COVID-19 were Peru (100%) and Panama (98.39%). No correlation was found between this interest and national epidemiological indicators. The global and local response time were 20.2 ± 1.2 days and 16.7 ± 15 days, respectively. The duration of public attention was 64.8 ± 12.5 days. The most popular topics related to COVID-19 were: the country's situation (100 ± 0) and coronavirus symptoms (36.82 ± 16.16). Most countries showed a strong or moderated (r = 0.72) significant correlation between searches related to COVID-19 and daily new cases. In addition, the highest significant lag correlation was found on day 13.35 ± 5.76 (r = 0.79). Interest shown by Latin American and Caribbean countries for COVID-19 was high. The degree of online interest in a country does not clearly reflect the magnitude of their epidemiological indicators. The response time and the lag correlation were greater than in European and Asian countries. Less interest was found for preventive measures. Strong correlation between searches for COVID-19 and daily new cases suggests a predictive utility.

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 a supplement to traditional surveillance. Google Trends™ (GT) (Google, Mountain View, CA, United States) 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

Data was obtained 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 behavior in India between January 1 and May 31, 2020 in the form of relative search volume (RSV). We also 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 the national level. In 5 high-burden states, high correlation was observed for these 5 terms along with "Corona." Peaks in RSV, both at the national level and in 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 curiosity.

The Causality Inference of Public Interest in Restaurants and Bars on Daily COVID-19 Cases in the United States: Google Trends Analysis

BACKGROUND

The COVID-19 pandemic has affected virtually every region in the world. At the time of this study, the number of daily new cases in the United States was greater than that in any other country, and the trend was increasing in most states. Google Trends provides data regarding public interest in various topics during different periods. Analyzing these trends using data mining methods may provide useful insights and observations regarding the COVID-19 outbreak.

OBJECTIVE

The objective of this study is to consider the predictive ability of different search terms not directly related to COVID-19 with regard to the increase of daily cases in the United States. In particular, we are concerned with searches related to dine-in restaurants and bars. Data were obtained from the Google Trends application programming interface and the COVID-19 Tracking Project.

METHODS

To test the causation of one time series on another, we used the Granger causality test. We considered the causation of two different search query trends related to dine-in restaurants and bars on daily positive cases in the US states and territories with the 10 highest and 10 lowest numbers of daily new cases of COVID-19. In addition, we used Pearson correlations to measure the linear relationships between different trends.

RESULTS

Our results showed that for states and territories with higher numbers of daily cases, the historical trends in search queries related to bars and restaurants, which mainly occurred after reopening, significantly affected the number of daily new cases on average. California, for example, showed the most searches for restaurants on June 7, 2020; this affected the number of new cases within two weeks after the peak, with a P value of .004 for the Granger causality test.

CONCLUSIONS

Although a limited number of search queries were considered, Google search trends for restaurants and bars showed a significant effect on daily new cases in US states and territories with higher numbers of daily new cases. We showed that these influential search trends can be used to provide additional information for prediction tasks regarding new cases in each region. These predictions can help health care leaders manage and control the impact of the COVID-19 outbreak on society and prepare for its outcomes.

The association between COVID-19 cases and deaths and web-based public inquiries

BACKGROUND

Corona Virus Disease 2019 (COVID-19) emerged in December 2019 and rapidly spread globally. Since there is still no specific treatment available, prevention of disease spread is crucial to manage the pandemic. Adequate public information is very important. To assess the optimal timing, the aim of this study was to investigate the association between web-based interest and new cases and deaths due to COVID-19.

METHODS

Web-based interest for queries related to 'coronavirus' was assessed between 1 January and 19 June 2020, using Google Trends in Australia, Brazil, Canada, Germany, Italy, South Africa, South Korea, Spain, United Kingdom, and the United States of America. Reliability analysis of the used search terms was performed using the intraclass correlation coefficient. To investigate the association between web-based interest and new COVID-19 cases or deaths, the relative search volume was analysed for correlation with new cases and deaths.

RESULTS

Reliability analysis revealed excellent reliability for COVID-19 search terms in all countries. Web-based interest peaked between 23 February and 5 April 2020, which was prior to the peak of new infections and deaths in most included countries. There was a moderate to strong correlation between COVID-19 related queries and new cases or new deaths.

CONCLUSION

Web-based interest in COVID-19 peaked prior to the peak of new infections and deaths in most countries included. Thus, monitoring public interest via Google Trends might be useful to select the optimal-timing of web-based disease-specific information and preventive measures.

Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature

BACKGROUND

The COVID-19 pandemic is favoring digital transitions in many industries and in society as a whole. Health care organizations have responded to the first phase of the pandemic by rapidly adopting digital solutions and advanced technology tools.

OBJECTIVE

The aim of this review is to describe the digital solutions that have been reported in the early scientific literature to mitigate the impact of COVID-19 on individuals and health systems.

METHODS

We conducted a systematic review of early COVID-19-related literature (from January 1 to April 30, 2020) by searching MEDLINE and medRxiv with appropriate terms to find relevant literature on the use of digital technologies in response to the pandemic. We extracted study characteristics such as the paper title, journal, and publication date, and we categorized the retrieved papers by the type of technology and patient needs addressed. We built a scoring rubric by cross-classifying the patient needs with the type of technology. We also extracted information and classified each technology reported by the selected articles according to health care system target, grade of innovation, and scalability to other geographical areas.

RESULTS

The search identified 269 articles, of which 124 full-text articles were assessed and included in the review after screening. Most of the selected articles addressed the use of digital technologies for diagnosis, surveillance, and prevention. We report that most of these digital solutions and innovative technologies have been proposed for the diagnosis of COVID-19. In particular, within the reviewed articles, we identified numerous suggestions on the use of artificial intelligence (AI)-powered tools for the diagnosis and screening of COVID-19. Digital technologies are also useful for prevention and surveillance measures, such as contact-tracing apps and monitoring of internet searches and social media usage. Fewer scientific contributions address the use of digital technologies for lifestyle empowerment or patient engagement.

CONCLUSIONS

In the field of diagnosis, digital solutions that integrate with traditional methods, such as AI-based diagnostic algorithms based both on imaging and clinical data, appear to be promising. For surveillance, digital apps have already proven their effectiveness; however, problems related to privacy and usability remain. For other patient needs, several solutions have been proposed, such as telemedicine or telehealth tools. These tools have long been available, but this historical moment may actually be favoring their definitive large-scale adoption. It is worth taking advantage of the impetus provided by the crisis; it is also important to keep track of the digital solutions currently being proposed to implement best practices and models of care in future and to adopt at least some of the solutions proposed in the scientific literature, especially in national health systems, which have proved to be particularly resistant to the digital transition in recent years.

Google search volume predicts the emergence of COVID-19 outbreaks

Background and aim:

Digital epidemiology is increasingly used for supporting traditional epidemiology. This study was hence aimed to explore whether the Google search volume may have been useful to predict the trajectory of coronavirus disease 2019 (COVID-19) outbreak in Italy.

Materials and Methods:

We accessed Google Trends for collecting data on weekly Google searches for the keywords “tosse” (i.e., cough), “febbre” (i.e., fever) and “dispnea” (dyspnea) in Italy, between February and May 2020. The number of new weekly cases of COVID-19 in Italy was also obtained from the website of the National Institute of Health.

Results:

The peaks of Google searches for the three terms predicted by 3 weeks that of newly diagnosed COVID-19 cases. The peaks of weekly Google searches for “febbre” (fever), “tosse”( cough) and “dispnea” (dyspnea) were 1.7-, 2.2- and 7.7-fold higher compared to the week before the diagnosis of the first national case. No significant correlation was found between the number of newly diagnosed COVID-19 cases and Google search volumes of “tosse” (cough) and “febbre” (fever), whilst “dyspnea” (dyspnea) was significantly correlated (r= 0.50; p=0.034). The correlation between newly diagnosed COVID-19 cases and “tosse” (cough; r=0.65; p=0.008) or “febbre” (fever; 0.69; p=0.004) become statistically significant with a 3-week delay. All symptoms were also significantly inter-correlated.

Conclusions:

Continuously monitoring the volume of Google searches and mapping their origin can be a potentially valuable instrument to help predicting and identifying local recrudescence of COVID-19. (www.actabiomedica.it)

Analysis of dermatologic conditions in Turkey and Italy by using Google Trends analysis in the era of the COVID-19 pandemic

Many areas of life including patterns of dermatological diseases that patients attend to the hospital were tremendously affected by implementing stay-at-home orders during the COVID-19 pandemic. We aimed to identify the dermatologic interest of the public during the COVID-19 pandemic by using Google Trends. The terms "acne", "hair loss", "eczema", "genital warts", "molluscum contagiosum", "botox", "skin cancer", and "sunscreen" were analyzed on April 1, May 1, June1, 2020, and the corresponding period of the previous year in Turkey and Italy by using Google Trends. The searching spectrum was between March 31, 2019 and June 1, 2020. The relative change of search term "acne" was +10, +29, +13/-1, +17,+33, "hair loss" was +14, +40, +16/+3, +16, +15, and "eczema" was +2, +34, -4/ +3, +25, +18, on the other hand, the relative change of the "genital warts" was -15, -48, +10/-44, -30, +18 and "molluscum contagiosum" was -12, -2, -4/-4, -1, -12 while "botox" was, -10, -43, -8/-41, -31, +4, "skin cancer" was -27, -38, -38/-22,+33, -7 and sunscreen was -6, -25, -71/-13, 0, -45 in Turkey/Italy on April 1, May 1, and June 1, 2020, respectively. A statistically significant positive correlation was found between the number of COVID-19 cases in Turkey and search terms of the general dermatology group during the COVID-19 pandemic (P < 0.05). The search terms including "acne", "eczema", "hair loss" appears to be increasing while "molluscum contagiosum", "genital warts" "botox", "skin cancer", and "sunscreen" decreasing in the era of the COVID-19 pandemic. Understanding the trends and impacts of dermatologic diseases on public perceptions during the COVID-19 pandemic will allow for better preparation of dermatologists.