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

Online information seeking during the COVID-19 pandemic: A cross-country analysis

The aim of this study was to investigate the coronavirus-related web-searching patterns of people from the 10 most affected nations in September 2020. The authors extracted all searches for the sample nations, consisting of the two words ‘COVID-19’ and ‘coronavirus’ and their variations, from Google Trends for the complete year of 2020. The results showed a discrepancy due to the priority of the language used during searches for coronavirus-related information. The time span of the attention level of citizens towards coronavirus-related information was relatively short (about one month). This supports the assumption of the activation model of information exposure that information which generates a negative affect is not welcomed by users. The findings have practical implications for governments and health authorities in, for example, launching information services for citizens in the early months of a pandemic and them remaining as the preferred source of information for citizens.

Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review

The probability of future Coronavirus Disease (COVID)-19 waves remains high, thus COVID-19 surveillance and forecasting remains important. Online search engines harvest vast amounts of data from the general population in real time and make these data publicly accessible via such tools as Google Trends (GT). Therefore, the aim of this study was to review the literature about possible use of GT for COVID-19 surveillance and prediction of its outbreaks. We collected and reviewed articles about the possible use of GT for COVID-19 surveillance published in the first 2 years of the pandemic. We resulted in 54 publications that were used in this review. The majority of the studies (83.3%) included in this review showed positive results of the possible use of GT for forecasting COVID-19 outbreaks. Most of the studies were performed in English-speaking countries (61.1%). The most frequently used keyword was "coronavirus" (53.7%), followed by "COVID-19" (31.5%) and "COVID" (20.4%). Many authors have made analyses in multiple countries (46.3%) and obtained the same results for the majority of them, thus showing the robustness of the chosen methods. Various methods including long short-term memory (3.7%), random forest regression (3.7%), Adaboost algorithm (1.9%), autoregressive integrated moving average, neural network autoregression (1.9%), and vector error correction modeling (1.9%) were used for the analysis. It was seen that most of the publications with positive results (72.2%) were using data from the first wave of the COVID-19 pandemic. Later, the search volumes reduced even though the incidence peaked. In most countries, the use of GT data showed to be beneficial for forecasting and surveillance of COVID-19 spread.

Interest in dentistry in early months of the COVID-19 global pandemic: A Google Trends approach

Background

In early the COVID‐19 pandemic, routine dental treatments have been delayed due to the risk of disease transmission. This delay may lead public to search for information on the Internet for a solution.

Objectives

This study aims to evaluate the public interest in dentistry in the early months of the COVID‐19 global pandemic in the selected countries.

Methods

The daily numbers of new COVID‐19 cases were recorded for China, South Korea, Italy, Germany, Russia, Ukraine and Turkey. For these countries, Internet search interest of the keyword ‘dentistry’, ‘coronavirus’, ‘COVID‐19’, ‘SARS‐CoV‐2’ and ‘pandemic’ in the early months of the COVID‐19 pandemic was evaluated by using Google Trends data.

Results

In most countries included the public Internet search interest in ‘dentistry+coronavirus+COVID‐19+SARS‐CoV‐2+pandemic’ peaked prior to the peak of new COVID‐19 cases. While a statistically significant positive correlation was observed between the number of new cases and Google Trends data in China, South Korea, Italy and Germany, a statistically significant negative correlation was observed in Turkey.

Conclusion

The peak public interest in dentistry has been prior to the peak of COVID‐19 new cases in most countries. The use of Internet data can provide useful information about pandemics and many other diseases.

Biannual Differences in Interest Peaks for Web Inquiries Into Ear Pain and Ear Drops: Infodemiology Study

Background

The data retrieved with the online search engine, Google Trends, can summarize internet inquiries into specified search terms. This engine may be used for analyzing inquiry peaks for different medical conditions and symptoms.

Objective

The aim of this study was to analyze World Wide Web interest peaks for “ear pain,” “ear infection,” and “ear drops.”

Methods

We used Google Trends to assess the public online interest for search terms “ear pain,” “ear infection,” and “ear drops” in 5 English and non–English-speaking countries from both hemispheres based on time series data. We performed our analysis for the time frame between January 1, 2004, and December 31, 2019. First, we assessed whether our search terms were most relevant to the topics of ear pain, ear infection, and ear drops. We then tested the reliability of Google Trends time series data using the intraclass correlation coefficient. In a second step, we computed univariate time series plots to depict peaks in web-based interest. In the last step, we used the cosinor analysis to test the statistical significance of seasonal interest peaks.

Results

In the first part of the study, it was revealed that “ear infection,” “ear pain,” and “ear drops” were the most relevant search terms in the noted time frame. Next, the intraclass correlation analysis showed a moderate to excellent reliability for all 5 countries’ 3 primary search terms. The subsequent analysis revealed winter interest peaks for “ear infection” and “ear pain”. On the other hand, the World Wide Web search for “ear drops” peaked annually during the summer months. All peaks were statistically significant as revealed by the cosinor model (all P values <.001).

Conclusions

It can be concluded that individuals affected by otitis media or externa, possibly the majority, look for medical information online. Therefore, there is a need for accurate and easily accessible information on these conditions in the World Wide Web, particularly on differentiating signs and therapy options. Meeting this need may facilitate timely diagnosis, proper therapy, and eventual circumvention of potentially life-threatening complications.