Online Health Information Seeking for Mpox in Endemic and Nonendemic Countries: Google Trends Study

Abstract

Background The recent global outbreak of mpox (monkeypox) has already been declared a public health emergency of international concern by the World Health Organization. Given the health, social, and economic impacts of the COVID-19 pandemic, there is understandable concern and anxiety around the emergence of another infectious disease—especially one about which little is known. Objective We used Google Trends to explore online health information seeking patterns for mpox in endemic and nonendemic countries and investigated the impact of the publication of the first in-country case on internet search volume. Methods Google Trends is a publicly accessible and free data source that aggregates worldwide Google search data. Google search data were used as a surrogate measure of online health information seeking for 178 days between February 18 and August 18, 2022. Searching data were downloaded across this time period for nonendemic countries with the highest case count (United States, Spain, Germany, United Kingdom, and France) and 5 endemic countries (Democratic Republic of Congo, Nigeria, Ghana, Central African Republic, and Cameroon). Joinpoint regression analysis was used to measure changes in searching trends for mpox preceding and following the announcement of the first human case. Results Online health information seeking significantly increased after the publication of the first case in all the nonendemic countries—United States, Spain, Germany, United Kingdom, and France, as illustrated by significant joinpoint regression models. Joinpoint analysis revealed that models with 3 significant joinpoints were the most appropriate fit for these data, where the first joinpoint represents the initial rise in mpox searching trend, the second joinpoint reflects the start of the decrease in the mpox searching trend, and the third joinpoint represents searching trends’ return to searching levels prior to the first case announcement. Although this model was also found in 2 endemic countries (ie, Ghana and Nigeria), it was not found in Central African Republic, Democratic Republic of Congo, or Cameroon. Conclusions Findings demonstrate a surge in online heath information seeking relating to mpox after the first in-country case was publicized in all the nonendemic countries and in Ghana and Nigeria among the endemic counties. The observed increases in mpox searching levels are characterized by sharp but short-lived periods of searching before steep declines back to levels observed prior to the publication of the first case. These findings emphasize the importance of the provision of accurate, relevant online public health information during disease outbreaks. However, online health information seeking behaviors only occur for a short time period, and the provision of accurate information needs to be timely in relation to the publication of new case-related information.

Willingness to Use Digital Health Screening and Tracking Tools for Public Health in Sexual Minority Populations in a National Probability Sample: Quantitative Intersectional Analysis

“…Sexual minority populations require culturally responsive digital health approaches to address their needs, as opposed to motivational enhancement or other interventions to increase their willingness during public health events. The willingness of sexual minority adults across intersecting identities to use pandemic-related digital health tools, including mobile health apps, is noteworthy given the potential promise of digital health tools for other public health-related concerns, such as the recently ended mpox outbreak [78,79], which disproportionately affected sexual minority men [80][81][82], and obesity [83,84] and cardiovascular disease [85,86], which disproportionately affects sexual minority women [87,88]. Additionally, White heterosexual adults demonstrated a disproportionately low willingness to use digital health tools, and this may become an issue in the event that this population is adversely affected by a public health concern that can benefit from digital health technologies.…”

Impact of Sickle Cell Awareness Day on online health information seeking in Africa using Google Trends

“…Consequently, it is possible that the initial surge in seeking online health information lasts longer than the available data suggests, as it might be manifested through other data streams. It is recommended that future studies explore the connections between website traffic to disease-specific sources and relevant Google RSVs ( Shepherd et al ., 2023 ).…”

“…As part of this strategy June 19th was designated a Sickle Cell Awareness Day and is observed annually to increase public knowledge and understanding of SCD ( Thein and Thein, 2016 ). Effective health information seeking can lead to health-improving activities and serve as an essential tool for understanding how, why and when people access public health-related information ( Fang et al ., 2021 ; Shepherd et al ., 2023 ). However, measuring the impact and benefit of disease awareness days remains a challenge ( Tegegne et al ., 2022 ).…”

Marburg Virus Outbreak and a New Conspiracy Theory: Findings from a Comprehensive Analysis and Forecasting of Web Behavior

“…As a result of this outbreak and the high fatality rate of MVD [3], in the last few months people from all over the world have been spending a lot more time than ever before on social media platforms and the internet in general to seek, share, access, and disseminate information about MVD [4,5]. During virus outbreaks of the past such as COVID-19 [6][7][8], MPox [9][10][11], Ebola [12][13][14], H1N1 [15][16][17], and MERS [18][19][20], researchers from different disciplines such as Healthcare, Epidemiology, Big Data, Data Analysis, Data Science, and Computer Science have studied and analyzed the underlining web behavior, as web behavior provides insights into the public health needs, interests, motives, concerns, perspectives, and opinions related to virus outbreaks. Furthermore, web behavior analysis related to a virus outbreak has also had several applications related to the real-time surveillance of outbreaks [21], prediction of cases [22], forecasting the behavior of different strains of a virus [23], timely preparation of public health policies [24], better preparedness of healthcare systems [25], identification of the themes of conversations of the general public [26], and timely implementation of public health policies and guidelines [27].…”