Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study

Investigating the Prevalence of Reactive Online Searching in the COVID-19 Pandemic: Infoveillance Study

BACKGROUND

The ongoing pandemic has placed an unprecedented strain on global society, health care, governments, and mass media. Public dissemination of government policies, medical interventions, and misinformation has been remarkably rapid and largely unregulated during the COVID-19 pandemic, resulting in increased misinterpretations, miscommunication, and public panic. Being the first full-scale global pandemic of the digital age, COVID-19 has presented novel challenges pertinent to government advice, the spread of news and misinformation, and the trade-off between the accessibility of science and the premature public use of unproven medical interventions.

OBJECTIVE

This study aims to assess the use of internet search terms relating to COVID-19 information and misinformation during the global pandemic, identify which were most used in six affected countries, investigate any temporal trends and the likely propagators of key search terms, and determine any correlation between the per capita cases and deaths with the adoption of these search terms in each of the six countries.

METHODS

This study uses relative search volume data extracted from Google Trends for search terms linked to the COVID-19 pandemic alongside per capita case and mortality data extracted from the European Open Data Portal to identify the temporal dynamics of the spread of news and misinformation during the global pandemic in six affected countries (Australia, Germany, Italy, Spain, the United Kingdom, and the United States). A correlation analysis was carried out to ascertain any correlation between the temporal trends of search term use and the rise of per capita mortality and disease cases.

RESULTS

Of the selected search terms, most were searched immediately following promotion by governments, public figures, or viral circulation of information, but also in relation to the publication of scientific resources, which were sometimes misinterpreted before further dissemination. Strong correlations were identified between the volume of these COVID-19-related search terms (overall mean Spearman rho 0.753, SD 0.158), and per capita mortality (mean per capita deaths Spearman rho 0.690, SD 0.168) and cases (mean per capita cases Spearman rho 0.800, SD 0.112).

CONCLUSIONS

These findings illustrate the increased rate and volume of the public consumption of novel information during a global health care crisis. The positive correlation between mortality and online searching, particularly in countries with lower COVID-19 testing rates, may demonstrate the imperative to safeguard official communications and dispel misinformation in these countries. Online news, government briefings, and social media provide a powerful tool for the dissemination of important information to the public during pandemics, but their misuse and the presentation of misrepresented medical information should be monitored, minimized, and addressed to safeguard public safety. Ultimately, governments, public health authorities, and scientists have a moral imperative to safeguard the truth and maintain an accessible discourse with the public to limit fear.

Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index

BACKGROUND

The COVID-19 pandemic has become a global public health event, attracting worldwide attention. As a tool to monitor public awareness, internet search engines have been widely used in public health emergencies.

OBJECTIVE

This study aims to use online search data (Baidu Index) to monitor the public's attention and verify internet search engines' function in public attention monitoring of public health emergencies.

METHODS

We collected the Baidu Index and the case monitoring data from January 20, 2020, to April 20, 2020. We combined the Baidu Index of keywords related to COVID-19 to describe the public attention's temporal trend and spatial distribution, and conducted the time lag cross-correlation analysis.

RESULTS

The Baidu Index temporal trend indicated that the changes of the Baidu Index had a clear correspondence with the development time node of the pandemic. The Baidu Index spatial distribution showed that in the regions of central and eastern China, with denser populations, larger internet user bases, and higher economic development levels, the public was more concerned about COVID-19. In addition, the Baidu Index was significantly correlated with six case indicators of new confirmed cases, new death cases, new cured discharge cases, cumulative confirmed cases, cumulative death cases, and cumulative cured discharge cases. Moreover, the Baidu Index was 0-4 days earlier than new confirmed and new death cases, and about 20 days earlier than new cured and discharged cases while 3-5 days later than the change of cumulative cases.

CONCLUSIONS

The national public's demand for epidemic information is urgent regardless of whether it is located in the hardest hit area. The public was more sensitive to the daily new case data that represents the progress of the epidemic, but the public's attention to the epidemic situation in other areas may lag behind. We could set the Baidu Index as the sentinel and the database in the online infoveillance system for infectious disease and public health emergencies. According to the monitoring data, the government needs to prevent and control the possible outbreak in advance and communicate the risks to the public so as to ensure the physical and psychological health of the public in the epidemic.

Identifying the outbreak signal of COVID-19 before the response of the traditional disease monitoring system

SYNOPSIS

Early identification of the emergence of an outbreak of a novel infectious disease is critical to generating a timely response. The traditional monitoring system is adequate for detecting the outbreak of common diseases; however, it is insufficient for the discovery of novel infectious diseases. In this study, we used COVID-19 as an example to compare the delay time of different tools for identifying disease outbreaks. The results showed that both the abnormal spike in influenza-like illnesses and the peak of online searches of key terms could provide early signals. We emphasize the importance of testing these findings and discussing the broader potential to use syndromic surveillance, internet searches, and social media data together with traditional disease surveillance systems for early detection and understanding of novel emerging infectious diseases.

Global Interest in Telehealth During COVID-19 Pandemic: An Analysis of Google Trends™

Background

Since the outbreak, healthcare systems across the globe are overcrowded with coronavirus disease (COVID-19) patients. To sustain the response towards the pandemic, many hospitals have adapted to virtual healthcare and telemedicine. Google™ has become the most widely used search engine over the years. Google Trends™ can be used to depict the public interest over a certain topic. The output of the Google Trends™ is displayed as relative search volume (RSV) which is the proportionate search volume regarding a specific topic comparative to the total search volume in a specific time and region. The primary aim of this study was to evaluate the relationship between the daily reported number of new COVID-19 cases and deaths and the corresponding changes in Google Trends™ RSV of telehealth over six months.

Methods

A retrospective study was conducted from January 21, 2020 to July 21, 2020. About 17 countries that reported the total number of cases greater than 200,000 in the situation report of July 21, 2020 were selected to be a part of this study. The daily reported new cases and deaths globally and of the selected countries were extracted from the World Health Organization (WHO) situation reports. The combination of keywords used for obtaining the RSV data through Google Trends™ was “telehealth”, “telemedicine”, “mHealth”, and “eHealth”. These words were used with the “+” feature of Google Trends™ with “1/21/2020 to 7/21/2020” as time range, “all categories” for the category, and “web search” for the type of search. The worldwide RSV as well as the RSVs of the selected countries were obtained from the Google Trends™ website. Spearman’s correlation coefficient (ρ) was used to determine the strength of the relationship between new cases or deaths and RSVs related to telehealth.

Results

A positive fair correlation was established between the global interest in telehealth and the new cases (ρ=0.307, p-value<0.001) and deaths (ρ=0.469, p-value<0.001) reported worldwide. The United States of America (USA), India, and Bangladesh were found to have a positive fair correlation between the public interest regarding telehealth and the emerging new COVID-19 cases and deaths. The United Kingdom (UK) and Italy demonstrated a positive poor correlation between the rising new cases or deaths and RSV. Similar statistics were noted for the daily new cases of Chile. For Turkey, a positive fair correlation between new deaths and RSV while a positive poor correlation between new cases and RSV was observed. No significant correlation was observed for the rest of the selected countries.

Conclusion

This study highlights the steadily rising public interest in telehealth during the COVID-19 pandemic. Telemedicine can provide the necessary remote consultation and healthcare for patients in the current situation. However, previous studies have shown that the majority of the countries are inadequately equipped for the digitization of the healthcare system. Therefore, it has become necessary to incorporate telemedicine into the healthcare system to combat any possible pandemic in the future.

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)

Google Trends Insights Into Reduced Acute Coronary Syndrome Admissions During the COVID-19 Pandemic: Infodemiology Study

Background

During the coronavirus disease (COVID-19) pandemic, a reduction in the presentation of acute coronary syndrome (ACS) has been noted in several countries. However, whether these trends reflect a reduction in ACS incidence or a decrease in emergency room visits is unknown. Using Google Trends, queries for chest pain that have previously been shown to closely correlate with coronary heart disease were compared with searches for myocardial infarction and COVID-19 symptoms.

Objective

The current study evaluates if search terms (or topics) pertaining to chest pain symptoms correlate with the reported decrease in presentations of ACS.

Methods

Google Trends data for search terms “chest pain,” “myocardial infarction,” “cough,” and “fever” were obtained from June 1, 2019, to May 31, 2020. Related queries were evaluated for a relationship to coronary heart disease.

Results

Following the onset of the COVID-19 pandemic, chest pain searches increased in all countries studied by at least 34% (USA P=.003, Spain P=.007, UK P=.001, Italy P=.002), while searches for myocardial infarction dropped or remained unchanged. Rising searches for chest pain included “coronavirus chest pain,” “home remedies for chest pain,” and “natural remedies for chest pain.” Searches on COVID-19 symptoms (eg, cough, fever) rose initially but returned to baseline while chest pain–related searches remained elevated throughout May.

Conclusions

Search engine queries for chest pain have risen during the pandemic as have related searches with alternative attribution for chest pain or home care for chest pain, suggesting that recent drops in ACS presentations may be due to patients avoiding the emergency room and potential treatment in the midst of the COVID-19 pandemic.

The Infection Rate of COVID-19 in Wuhan, China: Combined Analysis of Population Samples

Background

The coronavirus disease (COVID-19) pandemic began in Wuhan, China, in December 2019. Wuhan had a much higher mortality rate than the rest of China. However, a large number of asymptomatic infections in Wuhan may have never been diagnosed, contributing to an overestimated mortality rate.

Objective

This study aims to obtain an accurate estimate of infections in Wuhan using internet data.

Methods

In this study, we performed a combined analysis of the infection rate among evacuated foreign citizens to estimate the infection rate in Wuhan in late January and early February.

Results

Based on our analysis, the combined infection rate of the foreign evacuees was 0.013 (95% CI 0.008-0.022). Therefore, we estimate the number of infected people in Wuhan to be 143,000 (range 88,000-242,000), which is significantly higher than previous estimates. Our study indicates that a large number of infections in Wuhan were not diagnosed, which has resulted in an overestimated case fatality rate.

Conclusions

Increased awareness of the original infection rate of Wuhan is critical for proper public health measures at all levels, as well as to eliminate panic caused by overestimated mortality rates that may bias health policy actions by the authorities.

Association of Search Query Interest in Gastrointestinal Symptoms With COVID-19 Diagnosis in the United States: Infodemiology Study

BACKGROUND

Coronavirus disease (COVID-19) is a novel viral illness that has rapidly spread worldwide. While the disease primarily presents as a respiratory illness, gastrointestinal symptoms such as diarrhea have been reported in up to one-third of confirmed cases, and patients may have mild symptoms that do not prompt them to seek medical attention. Internet-based infodemiology offers an approach to studying symptoms at a population level, even in individuals who do not seek medical care.

OBJECTIVE

This study aimed to determine if a correlation exists between internet searches for gastrointestinal symptoms and the confirmed case count of COVID-19 in the United States.

METHODS

The search terms chosen for analysis in this study included common gastrointestinal symptoms such as diarrhea, nausea, vomiting, and abdominal pain. Furthermore, the search terms fever and cough were used as positive controls, and constipation was used as a negative control. Daily query shares for the selected symptoms were obtained from Google Trends between October 1, 2019 and June 15, 2020 for all US states. These shares were divided into two time periods: pre-COVID-19 (prior to March 1) and post-COVID-19 (March 1-June 15). Confirmed COVID-19 case numbers were obtained from the Johns Hopkins University Center for Systems Science and Engineering data repository. Moving averages of the daily query shares (normalized to baseline pre-COVID-19) were then analyzed against the confirmed disease case count and daily new cases to establish a temporal relationship.

RESULTS

The relative search query shares of many symptoms, including nausea, vomiting, abdominal pain, and constipation, remained near or below baseline throughout the time period studied; however, there were notable increases in searches for the positive control symptoms of fever and cough as well as for diarrhea. These increases in daily search queries for fever, cough, and diarrhea preceded the rapid rise in number of cases by approximately 10 to 14 days. The search volumes for these terms began declining after mid-March despite the continued rises in cumulative cases and daily new case counts.

CONCLUSIONS

Google searches for symptoms may precede the actual rises in cases and hospitalizations during pandemics. During the current COVID-19 pandemic, this study demonstrates that internet search queries for fever, cough, and diarrhea increased prior to the increased confirmed case count by available testing during the early weeks of the pandemic in the United States. While the search volumes eventually decreased significantly as the number of cases continued to rise, internet query search data may still be a useful tool at a population level to identify areas of active disease transmission at the cusp of new outbreaks.

Silver lining of COVID-19: Heightened global interest in pneumococcal and influenza vaccines, an infodemiology study

BACKGROUND

Health-seeking behaviors change during pandemics and may increase with regard to illnesses with symptoms similar to the pandemic. The global reaction to COVID-19 may drive interest in vaccines for other diseases.

OBJECTIVES

Our study investigated the correlation between global online interest in COVID-19 and interest in CDC-recommended routine vaccines.

DESIGN, SETTINGS, MEASUREMENTS

This infodemiology study used Google Trends data to quantify worldwide interest in COVID-19 and CDC-recommended vaccines using the unit search volume index (SVI), which estimates volume of online search activity relative to highest volume of searches within a specified period. SVIs from December 30, 2019 to March 30, 2020 were collected for "coronavirus (Virus)" and compared with SVIs of search terms related to CDC-recommended adult vaccines. To account for seasonal variation, we compared SVIs from December 30, 2019 to March 30, 2020 with SVIs from the same months in 2015 to 2019. We performed country-level analyses in ten COVID-19 hotspots and ten countries with low disease burden.

RESULTS

There were significant positive correlations between SVIs for "coronavirus (Virus)" and search terms for pneumococcal (R = 0.89, p < 0.0001) and influenza vaccines (R = 0.93, p < 0.0001) in 2020, which were greater than SVIs for the same terms in 2015-2019 (p = 0.005, p < 0.0001, respectively). Eight in ten COVID-19 hotspots demonstrated significant positive correlations between SVIs for coronavirus and search terms for pneumococcal and influenza vaccines.

LIMITATIONS

SVIs estimate relative changes in online interest and do not represent the interest of people with no Internet access.

CONCLUSION

A peak in worldwide interest in pneumococcal and influenza vaccines coincided with the COVID-19 pandemic in February and March 2020. Trends are likely not seasonal in origin and may be driven by COVID-19 hotspots. Global events may change public perception about the importance of vaccines. Our findings may herald higher demand for pneumonia and influenza vaccines in the upcoming season.