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Objectives: As condoms are effective tools for pathogen-avoidance in sexual intercourse, seeking information about condoms online may be a reactive response to the COVID-19 according to the behavioral immune system theory. Design: Taking an infodemiology perspective, this research employed multilevel analyses to examine how COVID-19 online query data (i.e., Google topic search terms Coronavirus and COVID-19) and coronavirus epidemiological data (i.e., COVID-19 cases per million and case fatality rate) would predict condom information seeking behavior online (i.e., Google topic search term Condom) throughout the pandemic across American states (Study 1) and 102 countries/territories (Study 2), after accounting for death-thought accessibility (i.e., illness-related searches), interest in birth control (i.e., birth-control-related searches), COVID-19 control policy, stay at home behavior, season, religious holidays, yearly trends, autocorrelation, and contextual variables such as HIV prevalence rate and socioeconomic development indicators (GINI index, urbanization, etc.). Results: When there were high levels of COVID-19 concerns in cyberspace in a given week, search volume for condoms increased from the previous week across American states and different countries/territories. By contrast, the effect of actual coronavirus threat was non-significant. Conclusion: Seeking information about condoms online could be a reactive response to high levels of COVID-19 concerns across different populations. [ABSTRACT FROM AUTHOR]

We aim to evaluate the utility of internet search query data in ophthalmology by: (1) Evaluating trends in searches for styes in the United States and worldwide, and (2) Performing a review of literature of infodemiological data in ophthalmology. Google Trends search data for "stye" was analyzed from January 2004 to January 2020 in the United States and worldwide. Spearman's correlation coefficient and sinusoidal modeling were performed to assess the significance and seasonality of trends. Review of literature included searches for "ophthalmology Google trends," "ophthalmology twitter trends," "ophthalmology infodemiology," "eye google trends," and "social media ophthalmology." Searches for styes were cyclical in the United States and globally with a steady increase from 2004 to 2020 (sum-of-squares F-test for sinusoidal model: p <.0001, r2 = 0.96). Peak search volume index (SVI) months were 7.9 months in the United States and 6.8 months worldwide. U.S. temperature and SVI for stye were correlated in the United States at the state, divisional, and country-wide levels (p <.005; p <.005; p <.01 respectively). Seven articles met our literature review inclusion criteria. We present a novel finding of seasonality with global and U.S. searches for stye, and association of searches with temperature in the United States. Within ophthalmology, infodemiological literature has been used to track trends and identify seasonal disease patterns, perform disease surveillance, improve resource optimization by identifying regional hotspots, tailor marketing, and monitor institutional reputation. Future research into this domain may help identify further trends, improve prevention efforts, and reduce medical costs. [ABSTRACT FROM AUTHOR]

Unlabelled: Through Jimmy Buffett's unfortunate battle with lymphoma originating from Merkel cell carcinoma and subsequent media coverage of his death, public interest in skin cancer, Merkel cell carcinoma, and the health effects of sunlight exposure increased, as evidenced by our results., (© Macy Haight, Hayden R Jacobs, Sarah K Boltey, Kelly A Murray, Micah Hartwell. Originally published in JMIR Dermatology (http://derma.jmir.org).)

Background: In the fall of 2020, the COVID-19 infodemic began to affect public confidence in and demand for COVID-19 vaccines in the United States. While polls indicated what consumers felt regarding COVID-19 vaccines, they did not provide an understanding of why they felt that way or the social and informational influences that factored into vaccine confidence and uptake. It was essential for us to better understand how information ecosystems were affecting the confidence in and demand for COVID-19 vaccines in the United States., Objective: The US Centers for Disease Control and Prevention (CDC) established an Insights Unit within the COVID-19 Response's Vaccine Task Force in January 2021 to assist the agency in acting more swiftly to address the questions, concerns, perceptions, and misinformation that appeared to be affecting uptake of COVID-19 vaccines. We established a novel methodology to rapidly detect and report on trends in vaccine confidence and demand to guide communication efforts and improve programmatic quality in near real time., Methods: We identified and assessed data sources for inclusion through an informal landscape analysis using a snowball method. Selected data sources provided an expansive look at the information ecosystem of the United States regarding COVID-19 vaccines. The CDC's Vaccinate with Confidence framework and the World Health Organization's behavioral and social drivers for vaccine decision-making framework were selected as guiding principles for interpreting generated insights and their impact. We used qualitative thematic analysis methods and a consensus-building approach to identify prevailing and emerging themes, assess their potential threat to vaccine confidence, and propose actions to increase confidence and demand., Results: As of August 2022, we have produced and distributed 34 reports to >950 recipients within the CDC and externally. State and local health departments, nonprofit organizations, professional associations, and congressional committees have referenced and used the reports for learning about COVID-19 vaccine confidence and demand, developing communication strategies, and demonstrating how the CDC monitored and responded to misinformation. A survey of the reports' end users found that nearly 75% (40/53) of respondents found them "very" or "extremely" relevant and 52% (32/61) used the reports to inform communication strategies. In addition, our methodology underwent continuous process improvement to increase the rigor of the research process, the validity of the findings, and the usability of the reports., Conclusions: This methodology can serve as a diagnostic technique for rapidly identifying opportunities for public health interventions and prevention. As the methodology itself is adaptable, it could be leveraged and scaled for use in a variety of public health settings. Furthermore, it could be considered beyond acute public health crises to support adherence to guidance and recommendations and could be considered within routine monitoring and surveillance systems., (©Jessica Kolis, Kathryn Brookmeyer, Yulia Chuvileva, Christopher Voegeli, Sarina Juma, Atsuyoshi Ishizumi, Katy Renfro, Elisabeth Wilhelm, Hannah Tice, Hannah Fogarty, Irma Kocer, Jordan Helms, Anisha Verma. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 24.10.2024.)

At the writing of this article at the start of November 2021, 247,416,351 persons have died of COVID-19 worldwide and 46,815,210 have died in the United States.1 Along with the tragic loss has come an infodemic–the widespread of misinformation in social media and published literature. Infodemiology is the study of analyzing the relationship between channels of health information demands and health information supply. Healthcare providers have an important role to quash this misinformation at all information access points. Hospital Librarians and other health information professionals also have a role to play to work with other health professionals, to dispel this misinformation. This article speaks to those two subjects and highlights Dear Pandemic.org and "Those Nerdy Girls." [ABSTRACT FROM AUTHOR]

Objective Evidence has shown that Google searches for clinical symptom keywords correlates with the number of new weekly patients with COVID-19. This multinational study assessed whether demand for SARS-CoV-2 tests could also be predicted by Google searches for key COVID-19 symptoms. Methods The weekly number of SARS-CoV-2 tests performed in Italy and the United States was retrieved from official sources. A concomitant electronic search was performed in Google Trends, using terms for key COVID-19 symptoms. Results The model that provided the highest coefficient of determination for the United States (R 2 = 82.8%) included a combination of searching for cough (with a time lag of 2 weeks), fever (with a time lag of 2 weeks), and headache (with a time lag of 3 weeks; the time lag refers to the amount of time between when a search was conducted and when a test was administered). In Italy, headache provided the model with the highest adjusted R 2 (86.8%), with time lags of both 1 and 2 weeks. Conclusion Weekly monitoring of Google Trends scores for nonspecific COVID-19 symptoms is a reliable approach for anticipating SARS-CoV-2 testing demands ~2 weeks in the future. [ABSTRACT FROM AUTHOR]

Background: In response to the prioritization of healthcare resources towards the COVID-19 pandemic, routine cancer screening and diagnostic have been disrupted, potentially explaining the apparent COVID-era decline in cancer cases and mortality. In this study, we identified temporal trends in public interest in cancer-related health information using the nowcasting tool Google Trends.Methods: We used Google Trends to query search terms related to cancer types for short-term (September 2019-September 2020) and long-term (September 2016-September 2020) trends in the US. We compared average relative search volumes (RSV) for specified time ranges to detect recent and seasonal variation.Results: General search interest declined for all cancer types beginning in March 2020, with changes in search interest for "Breast cancer," "Colorectal cancer," and "Melanoma" of - 30.6%, - 28.2%, and - 26.7%, respectively, and compared with the mean RSV of the two previous months. In the same time range, search interest for "Telemedicine" has increased by + 907.1% and has reached a 4-year peak with a sustained increased level of search interest. Absolute cancer mortality has declined and is presently at a 4-year low; however, search interest in cancer has been recuperating since July 2020.Conclusion: We observed a marked decline in searches for cancer-related health information that mirrors the reduction in new cancer diagnoses and cancer mortality during the COVID-19 pandemic. Health professions need to be prepared for the coming demand for cancer-related healthcare, foreshadowed by recovering interest in cancer-related information on Google Trends. [ABSTRACT FROM AUTHOR]

Background: Alpha-gal syndrome is an emerging allergy characterized by an immune reaction to the carbohydrate molecule alpha-gal found in red meat. This unique food allergy is likely triggered by a tick bite. Cases of the allergy are on the rise, but prevalence estimates do not currently exist. Furthermore, varying symptoms and limited awareness of the allergy among health care providers contribute to delayed diagnosis, leading individuals to seek out their own information and potentially self-diagnose., Objective: The study aimed to (1) describe the volume and patterns of information-seeking related to alpha-gal, (2) explore correlations between alpha-gal and lone star ticks, and (3) identify specific areas of interest that individuals are searching for in relation to alpha-gal., Methods: Google Trends Supercharged-Glimpse, a new extension of Google Trends, provides estimates of the absolute volume of searches and related search queries. This extension was used to assess trends in searches for alpha-gal and lone star ticks (lone star tick, alpha gal, and meat allergy, as well as food allergy for comparison) in the United States. Time series analyses were used to examine search volume trends over time, and Spearman correlation matrices and choropleth maps were used to explore geographic and temporal correlations between alpha-gal and lone star tick searches. Content analysis was performed on related search queries to identify themes and subcategories that are of interest to information seekers., Results: Time series analysis revealed a rapidly increasing trend in search volumes for alpha-gal beginning in 2015. After adjusting for long-term trends, seasonal trends, and media coverage, from 2015 to 2022, the predicted adjusted average annual percent change in search volume for alpha-gal was 33.78%. The estimated overall change in average search volume was 627%. In comparison, the average annual percent change was 9.23% for lone star tick, 7.34% for meat allergy, and 2.45% for food allergy during this time. Geographic analysis showed strong significant correlations between alpha-gal and lone star tick searches especially in recent years (ρ=0.80; P<.001), with primary overlap and highest search rates found in the southeastern region of the United States. Content analysis identified 10 themes of primary interest: diet, diagnosis or testing, treatment, medications or contraindications of medications, symptoms, tick related, specific sources of information and locations, general education information, alternative words for alpha-gal, and unrelated or other., Conclusions: The study provides insights into the changing information-seeking patterns for alpha-gal, indicating growing awareness and interest. Alpha-gal search volume is increasing at a rapid rate. Understanding specific questions and concerns can help health care providers and public health educators to tailor communication strategies. The Google Trends Supercharged-Glimpse tool offers enhanced features for analyzing information-seeking behavior and can be valuable for infodemiology research. Further research is needed to explore the evolving prevalence and impact of alpha-gal syndrome., (©Jamie L Romeiser, Nicole Jusko, Augusta A Williams. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.05.2024.)

Background: Previous work suggests that Google searches could be useful in identifying conjunctivitis epidemics. Content-based assessment of social media content may provide additional value in serving as early indicators of conjunctivitis and other systemic infectious diseases., Objective: We investigated whether large language models, specifically GPT-3.5 and GPT-4 (OpenAI), can provide probabilistic assessments of whether social media posts about conjunctivitis could indicate a regional outbreak., Methods: A total of 12,194 conjunctivitis-related tweets were obtained using a targeted Boolean search in multiple languages from India, Guam (United States), Martinique (France), the Philippines, American Samoa (United States), Fiji, Costa Rica, Haiti, and the Bahamas, covering the time frame from January 1, 2012, to March 13, 2023. By providing these tweets via prompts to GPT-3.5 and GPT-4, we obtained probabilistic assessments that were validated by 2 human raters. We then calculated Pearson correlations of these time series with tweet volume and the occurrence of known outbreaks in these 9 locations, with time series bootstrap used to compute CIs., Results: Probabilistic assessments derived from GPT-3.5 showed correlations of 0.60 (95% CI 0.47-0.70) and 0.53 (95% CI 0.40-0.65) with the 2 human raters, with higher results for GPT-4. The weekly averages of GPT-3.5 probabilities showed substantial correlations with weekly tweet volume for 44% (4/9) of the countries, with correlations ranging from 0.10 (95% CI 0.0-0.29) to 0.53 (95% CI 0.39-0.89), with larger correlations for GPT-4. More modest correlations were found for correlation with known epidemics, with substantial correlation only in American Samoa (0.40, 95% CI 0.16-0.81)., Conclusions: These findings suggest that GPT prompting can efficiently assess the content of social media posts and indicate possible disease outbreaks to a degree of accuracy comparable to that of humans. Furthermore, we found that automated content analysis of tweets is related to tweet volume for conjunctivitis-related posts in some locations and to the occurrence of actual epidemics. Future work may improve the sensitivity and specificity of these methods for disease outbreak detection., (©Michael S Deiner, Natalie A Deiner, Vagelis Hristidis, Stephen D McLeod, Thuy Doan, Thomas M Lietman, Travis C Porco. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 01.03.2024.)

Background: Health agencies have been widely adopting social media to disseminate important information, educate the public on emerging health issues, and understand public opinions. The Centers for Disease Control and Prevention (CDC) widely used social media platforms during the COVID-19 pandemic to communicate with the public and mitigate the disease in the United States. It is crucial to understand the relationships between the CDC's social media communications and the actual epidemic metrics to improve public health agencies' communication strategies during health emergencies., Objective: This study aimed to identify key topics in tweets posted by the CDC during the pandemic, investigate the temporal dynamics between these key topics and the actual COVID-19 epidemic measures, and make recommendations for the CDC's digital health communication strategies for future health emergencies., Methods: Two types of data were collected: (1) a total of 17,524 COVID-19-related English tweets posted by the CDC between December 7, 2019, and January 15, 2022, and (2) COVID-19 epidemic measures in the United States from the public GitHub repository of Johns Hopkins University from January 2020 to July 2022. Latent Dirichlet allocation topic modeling was applied to identify key topics from all COVID-19-related tweets posted by the CDC, and the final topics were determined by domain experts. Various multivariate time series analysis techniques were applied between each of the identified key topics and actual COVID-19 epidemic measures to quantify the dynamic associations between these 2 types of time series data., Results: Four major topics from the CDC's COVID-19 tweets were identified: (1) information on the prevention of health outcomes of COVID-19; (2) pediatric intervention and family safety; (3) updates of the epidemic situation of COVID-19; and (4) research and community engagement to curb COVID-19. Multivariate analyses showed that there were significant variabilities of progression between the CDC's topics and the actual COVID-19 epidemic measures. Some CDC topics showed substantial associations with the COVID-19 measures over different time spans throughout the pandemic, expressing similar temporal dynamics between these 2 types of time series data., Conclusions: Our study is the first to comprehensively investigate the dynamic associations between topics discussed by the CDC on Twitter and the COVID-19 epidemic measures in the United States. We identified 4 major topic themes via topic modeling and explored how each of these topics was associated with each major epidemic measure by performing various multivariate time series analyses. We recommend that it is critical for public health agencies, such as the CDC, to update and disseminate timely and accurate information to the public and align major topics with key epidemic measures over time. We suggest that social media can help public health agencies to inform the public on health emergencies and to mitigate them effectively., (©Shuhua Yin, Shi Chen, Yaorong Ge. Originally published in JMIR Infodemiology (https://infodemiology.jmir.org), 23.01.2024.)

Objectives: This is a demand-based infodemiology study using the Google Trends and AdWords tools to illustrate infodemiology's potential use in rheumatology. The study investigates three questions in North American countries: (1) What terms associated with "rheumatology" and "arthritis" do people search for on Google? (2) What is the search volume for disease-modifying antirheumatic drugs (DMARDs)? and (3) What is the search volume for the term "arthritis" compared with for "hepatitis C" and "breast cancer"?Methods: We conducted independent searches by country and search term for 2015-2017. Seventeen DMARDs were searched for 2015 through May 2018, with the turmeric remedy included for comparison. Data were exported to Excel for further analysis, adjusted by country population, and expressed as searches per 100,000 inhabitants (SpTh).Results: There were approximately 550 associated terms for "arthritis" in each country, and 5679 SpTh for DMARDs across the three countries. Searches for turmeric numbered slightly lower than for all DMARDs together in Canada and the USA, but were 70% higher in Mexico. Turmeric was also searched four times more than the most-searched biological DMARD in Canada and the USA, and 60 times more in Mexico. Arthritis was more commonly searched for in Canada than hepatitis C and breast cancer, but hepatitis C was highest in the USA and breast cancer in Mexico. Monthly trends did not show expected peaks associated with arthritis awareness campaigns.Conclusion: Infodemiology provides preliminary information that could help in generating hypotheses, assessing health-care interventions, or even in providing patient-centered care. [ABSTRACT FROM AUTHOR]

Purpose: In July 2022, the World Health Organization (WHO) declared monkeypox virus's global spread a "public health emergency of international concern." About a quarter of monkeypox cases feature ophthalmic symptoms. We assessed trends in worldwide search interest in monkeypox ophthalmic involvement and inclusion in online search engine queries., Methods: The following keywords were searched on Google Trends from April 1, 2022, to August 12, 2022: monkeypox + eye, pink eye, eye infection, eyelid, vision, blurry vision, vision loss, blindness, eye symptoms, eye problems, eye pain, eye redness, conjunctivitis, conjunctiva, cornea, keratitis, corneal ulcer, and blepharitis. We analyzed trends, correlated search interest with case count data, and compared popularity of search terms via nonparametric Mann-Whitney-U analysis. Inclusion of ophthalmic symptoms in Google search results for "monkeypox symptoms" was assessed., Results: "Monkeypox eye" had the highest average search interest worldwide and in the United States. Search interest peaked between mid-May and late July 2022. When compared to interest in "monkeypox rash," the most searched monkeypox symptom, the average interest in "monkeypox eye" was lower (p < 0.01). Of the first 50 results from the Google search of "monkeypox symptoms," 10/50 (20%) mentioned ophthalmic symptoms. 6/50 (12%) mentioned the eye as a route of virus transmission., Conclusion: Search interest in monkeypox ophthalmic symptoms corresponds with geographic and temporal trends, i.e., timing and location of the first reported non-endemic cases and WHO announcement. Although ophthalmic symptoms are not as widely searched currently, inclusion in public health messaging is key for diagnosis, appropriate management, and reduction of further transmission., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)

Background: During the early pandemic, there was substantial variation in public and government responses to COVID-19 in Europe and the United States. Mass media are a vital source of health information and news, frequently disseminating this information through social media, and may influence public and policy responses to the pandemic., Objective: This study aims to describe the extent to which major media outlets in the United States and Spain tweeted about health-related behaviors (HRBs) relevant to COVID-19, compare the tweeting patterns between media outlets of both countries, and determine user engagement in response to these tweets., Methods: We investigated tweets posted by 30 major media outlets (n=17, 57% from Spain and n=13, 43% from the United States) between December 1, 2019 and May 31, 2020, which included keywords related to HRBs relevant to COVID-19. We classified tweets into 6 categories: mask-wearing, physical distancing, handwashing, quarantine or confinement, disinfecting objects, or multiple HRBs (any combination of the prior HRB categories). Additionally, we assessed the likes and retweets generated by each tweet. Poisson regression analyses compared the average predicted number of likes and retweets between the different HRB categories and between countries., Results: Of 50,415 tweets initially collected, 8552 contained content associated with an HRB relevant to COVID-19. Of these, 600 were randomly chosen for training, and 2351 tweets were randomly selected for manual content analysis. Of the 2351 COVID-19-related tweets included in the content analysis, 62.91% (1479/2351) mentioned at least one HRB. The proportion of COVID-19 tweets mentioning at least one HRB differed significantly between countries (P=.006). Quarantine or confinement was mentioned in nearly half of all the HRB tweets in both countries. In contrast, the least frequently mentioned HRBs were disinfecting objects in Spain 6.9% (56/809) and handwashing in the United States 9.1% (61/670). For tweets from the United States mentioning at least one HRB, disinfecting objects had the highest median likes and retweets, whereas mask-wearing- and handwashing-related tweets achieved the highest median number of likes in Spain. Tweets from Spain that mentioned social distancing or disinfecting objects had a significantly lower predicted count of likes compared with tweets mentioning a different HRB (P=.02 and P=.01, respectively). Tweets from the United States that mentioned quarantine or confinement or disinfecting objects had a significantly lower predicted number of likes compared with tweets mentioning a different HRB (P<.001), whereas mask- and handwashing-related tweets had a significantly greater predicted number of likes (P=.04 and P=.02, respectively)., Conclusions: The type of HRB content and engagement with media outlet tweets varied between Spain and the United States early in the pandemic. However, content related to quarantine or confinement and engagement with handwashing was relatively high in both countries., (©Miguel Angel Alvarez-Mon, Victor Pereira-Sanchez, Elizabeth R Hooker, Facundo Sanchez, Melchor Alvarez-Mon, Alan R Teo. Originally published in JMIR Infodemiology (https://infodemiology.jmir.org), 22.08.2023.)

Purpose: To identify periodic trends in internet searches for ocular symptoms and to determine the seasonal peaks and troughs., Methods: This cross-sectional study examined publicly available Google Trends data from the United States (01/01/2015 to 12/31/2019). A list of common ocular symptoms was compiled from the American Academy of Ophthalmology Eye Health website and Wills Eye Manual. Ocular symptoms were stratified into categories involving vision change, eye pain, or eye redness. The search volume over time for each term was modeled using periodic regression functions and the goodness-of-fit was reported. Fisher's exact tests were used to compare the characteristics of periodic vs. non-periodic query terms., Results: Seasonal trends were demonstrated by 45% (48/106) of the ocular symptoms included in this investigation. Search terms with best fit to the periodic model included stye (r 2  = 0.89), pink eye (r 2  = 0.82), dry eye (r 2  = 0.76), blurry vision (r 2  = 0.72), and swollen eye (r 2  = 0.71). Periodic search terms were more likely to involve eye redness (21% vs. 11%, p = .014) and less likely to involve vision change (11% vs. 36%; p < .001). Periodic queries involving eye redness most often peaked in the spring and those involving eye pain peaked in the summer., Conclusion: Ocular symptom queries directly reflect seasonal trends for allergic eye disease and ocular trauma. Search query analyses can serve as accurate epidemiological tools with research and real-world clinical applications.

Background: The US Food and Drug Administration (FDA) recently restricted characterizing flavors in tobacco products. As a result, ice hybrid-flavored e-cigarettes, which combine a cooling flavor with fruit or other flavors (eg, banana ice), emerged on the market. Like menthol, ice-flavored e-cigarettes produce a cooling sensory experience. It is unclear if ice hybrid-flavored e-cigarettes should be considered characterizing flavors or menthol, limiting regulatory action. Monitoring the public's conversations about ice-flavored e-cigarettes on Twitter may help inform the tobacco control community about these products and contribute to the US FDA policy targets in the future.Objective: This study documented the themes pertaining to vaping and ice flavor-related conversations on Twitter. Our goal was to identify key conversation trends and ascertain users' recent experiences with ice-flavored e-cigarette products.Methods: Posts containing vaping-related (eg, "vape," "ecig," "e-juice," or "e-cigarette") and ice-related (ie, "Ice," "Cool," "Frost," and "Arctic") terms were collected from Twitter's streaming application programming interface from January 1 to July 21, 2021. After removing retweets, a random sample of posts (N=2001) was selected, with 590 posts included in the content analysis. Themes were developed through an inductive approach. Theme co-occurrence was also examined.Results: Many of the 590 posts were marked as (or consisted of) marketing material (n=306, 51.9%), contained positive personal testimonials (n=180, 30.5%), and mentioned disposable pods (n=117, 19.8%). Other themes had relatively low prevalence in the sample: neutral personal testimonials (n=45, 7.6%), cannabidiol products (n=41, 7%), negative personal testimonials (n=41, 7%), "official" flavor description (n=37, 6.3%), ice-flavored JUUL (n=19, 3.2%), information seeking (n=14, 2.4%), and comparison to combustible tobacco (n=10, 1.7%). The most common co-occurring themes in a single tweet were related to marketing and disposable pods (n=73, 12.4%).Conclusions: Our findings offer insight into the public's experience with and understanding of ice-flavored e-cigarette products. Ice-flavored e-cigarette products are actively marketed on Twitter, and the messages about them are positive. Public health education campaigns on the harms of flavored e-cigarettes may help to reduce positive social norms about ice-flavored products. Future studies should evaluate the relationship between exposure to personal testimonials of ice-flavored vaping products and curiosity, harm perceptions, and experimentation with these products among priority populations. [ABSTRACT FROM AUTHOR]

Background: Chatbots have become a promising tool to support public health initiatives. Despite their potential, little research has examined how individuals interacted with chatbots during the COVID-19 pandemic. Understanding user-chatbot interactions is crucial for developing services that can respond to people's needs during a global health emergency., Objective: This study examined the COVID-19 pandemic-related topics online users discussed with a commercially available social chatbot and compared the sentiment expressed by users from 5 culturally different countries., Methods: We analyzed 19,782 conversation utterances related to COVID-19 covering 5 countries (the United States, the United Kingdom, Canada, Malaysia, and the Philippines) between 2020 and 2021, from SimSimi, one of the world's largest open-domain social chatbots. We identified chat topics using natural language processing methods and analyzed their emotional sentiments. Additionally, we compared the topic and sentiment variations in the COVID-19-related chats across countries., Results: Our analysis identified 18 emerging topics, which could be categorized into the following 5 overarching themes: "Questions on COVID-19 asked to the chatbot" (30.6%), "Preventive behaviors" (25.3%), "Outbreak of COVID-19" (16.4%), "Physical and psychological impact of COVID-19" (16.0%), and "People and life in the pandemic" (11.7%). Our data indicated that people considered chatbots as a source of information about the pandemic, for example, by asking health-related questions. Users turned to SimSimi for conversation and emotional messages when offline social interactions became limited during the lockdown period. Users were more likely to express negative sentiments when conversing about topics related to masks, lockdowns, case counts, and their worries about the pandemic. In contrast, small talk with the chatbot was largely accompanied by positive sentiment. We also found cultural differences, with negative words being used more often by users in the United States than by those in Asia when talking about COVID-19., Conclusions: Based on the analysis of user-chatbot interactions on a live platform, this work provides insights into people's informational and emotional needs during a global health crisis. Users sought health-related information and shared emotional messages with the chatbot, indicating the potential use of chatbots to provide accurate health information and emotional support. Future research can look into different support strategies that align with the direction of public health policy., (©Hyojin Chin, Gabriel Lima, Mingi Shin, Assem Zhunis, Chiyoung Cha, Junghoi Choi, Meeyoung Cha. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.01.2023.)

Introduction: More than 1 in 7 children in the United States experience abuse annually with rates remaining consistent over the past 2 decades. During this timeframe, several high-profile cases of child abuse and neglect were publicized in national media in addition to multiple investigations uncovering Indigenous children dying from abuse at Indian Boarding Schools. Increased media attention among other public health and medical topics has been linked to increased public interest, thus, our objective was to investigate trends in public interest from 2004 to 2022., Methods: To assess trends in public interest, we extracted monthly relative search interest in child abuse from Google Trends. We constructed linear regression to determine the long-term trajectory of interest, and also compared the slope of the trend to other topics, such as domestic violence. Further, we compared mean relative search interest (RSI) from Child Abuse Awareness Month (April) to other months via t-test. Lastly, we assess by-state correlations of RSI and number of children abused., Results: Since 2004, search interest in child abuse has significantly declined in the United States-more than other related search terms. Child Abuse Awareness Month showed spikes in RSI which were greater than other months. By-state correlations of RSI and abuse were moderate to weak., Conclusion: Despite heavy media attention covering stories of child abuse during the past 2 decades, search interest in child abuse has significantly declined. This trend may be related to aversion to secondary traumatic stress as news broadcasts often include stories of violence-of which child abuse stories may be most provoking. Following journalism guidance from the Centers for Disease Control and Prevention, reporting with focus on resiliency and prevention, rather than the individuals who perpetrated the crime, may provide more community support and increased public interest., Competing Interests: Declaration of competing interest Dr. Hartwell receives research support through the National Institutes for Justice unrelated to the current work and the Health Resources Services Administration., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background: There is no recognized gold standard method for estimating the number of individuals with substance use disorders (SUDs) seeking help within a given geographical area. This presents a challenge to policy makers in the effective deployment of resources for the treatment of SUDs. Internet search queries related to help seeking for SUDs using Google Trends may represent a low-cost, real-time, and data-driven infoveillance tool to address this shortfall in information., Objective: This paper assesses the feasibility of using search query data related to help seeking for SUDs as an indicator of unmet treatment needs, demand for treatment, and predictor of the health harms related to unmet treatment needs. We explore a continuum of hypotheses to account for different outcomes that might be expected to occur depending on the demand for treatment relative to the system capacity and the timing of help seeking in relation to trajectories of substance use and behavior change., Methods: We used negative binomial regression models to examine temporal trends in the annual SUD help-seeking internet search queries from Google Trends by US state for cocaine, methamphetamine, opioids, cannabis, and alcohol from 2010 to 2020. To validate the value of these data for surveillance purposes, we then used negative binomial regression models to investigate the relationship between SUD help-seeking searches and state-level outcomes across the continuum of care (including lack of care). We started by looking at associations with self-reported treatment need using data from the National Survey on Drug Use and Health, a national survey of the US general population. Next, we explored associations with treatment admission rates from the Treatment Episode Data Set, a national data system on SUD treatment facilities. Finally, we studied associations with state-level rates of people experiencing and dying from an opioid overdose, using data from the Agency for Healthcare Research and Quality and the CDC WONDER database., Results: Statistically significant differences in help-seeking searches were observed over time between 2010 and 2020 (based on P<.05 for the corresponding Wald tests). We were able to identify outlier states for each drug over time (eg, West Virginia for both opioids and methamphetamine), indicating significantly higher help-seeking behaviors compared to national trends. Results from our validation analyses across different outcomes showed positive, statistically significant associations for the models relating to treatment need for alcohol use, treatment admissions for opioid and methamphetamine use, emergency department visits related to opioid use, and opioid overdose mortality data (based on regression coefficients having P≤.05)., Conclusions: This study demonstrates the clear potential for using internet search queries from Google Trends as an infoveillance tool to predict the demand for substance use treatment spatially and temporally, especially for opioid use disorders., (©Thomas Patton, Daniela Abramovitz, Derek Johnson, Eric Leas, Alicia Nobles, Theodore Caputi, John Ayers, Steffanie Strathdee, Annick Bórquez. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 01.12.2022.)

There has been a disparity in familiarity regarding the public interest in gastroenterology terminologies during the COVID-19 pandemic. This study aimed to understand the outcomes of the public's view on gastrointestinal topics and their potential social effects. This study is a comparative analysis of American Google Trends gastrointestinal terminology during the COVID-19 pandemic compared to a similar time frame (March 2018-February 2020) to determine how trends in the patient-seeking behavior of gastrointestinal terminology changed throughout the pandemic. The analysis discovered a substantial decrease in search volumes of gastrointestinal topics, more significantly in the first pandemic months. Later in the pandemic, search volumes trended toward pre-pandemic years in terms of public interest. In the case of gastrointestinal procedures, endoscopy and colonoscopies, they surpassed pre-pandemic interest levels statistically (p-values of 0.01 and 0.002). The public's decreased interest in gastrointestinal topics at the beginning of the COVID-19 pandemic may have adverse effects on the healthcare maintenance of patients who could have had a positive outcome in their gastrointestinal health with proper monitoring. Although gastrointestinal internet searches increased toward pre-pandemic levels as the seasons progressed, further research is needed to determine the social impact of decreased public interest., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: The human papillomavirus (HPV) vaccine is recommended for adolescents and young adults to prevent HPV-related cancers and genital warts. However, HPV vaccine uptake among the target age groups is suboptimal., Objective: The aim of this infodemiology study was to examine public online searches in the United States related to the HPV vaccine from January 2010 to December 2021., Methods: Google Trends (GT) was used to explore online searches related to the HPV vaccine from January 1, 2010, to December 31, 2021. Online searches and queries on the HPV vaccine were investigated using relative search volumes (RSVs). Analysis of variance was performed to investigate quarterly differences in HPV vaccine searches in each year from 2010 to 2021. A joinpoint regression was used to identify statistically significant changes over time; the α level was set to .05., Results: The year-wise online search volume related to the HPV vaccine increased from 2010 to 2021, often following federal changes related to vaccine administration. Joinpoint regression analysis showed that HPV vaccine searches significantly increased on average by 8.6% (95% CI 5.9%-11.4%) across each year from 2010 to 2021. Moreover, HPV vaccine searches demonstrated a similar pattern across years, with search interest increasing through August nearly every year. At the state level, the highest 12-year mean RSV was observed in California (59.9, SD 14.3) and the lowest was observed in Wyoming (17.4, SD 8.5) during the period of 2010-2021., Conclusions: Online searches related to the HPV vaccine increased by an average of 8.6% across each year from 2010 to 2021, with noticeable spikes corresponding to key changes in vaccine recommendations. We identified patterns across years and differences at the state level in the online search interest related to the HPV vaccine. Public health organizations can use GT as a tool to characterize the public interest in and promote the HPV vaccine in the United States., (©Akshaya Srikanth Bhagavathula, Philip M Massey. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 29.08.2022.)

Background: Twitter is becoming an increasingly important avenue for people to seek information about HIV prevention. Tweets about HIV prevention may reflect or influence current norms about the acceptability of different HIV prevention methods. Therefore, it may be useful to empirically investigate trends in the level of attention paid to different HIV prevention topics on Twitter over time., Objective: The primary objective of this study was to investigate temporal trends in the frequency of tweets about different HIV prevention topics on Twitter between 2014 and 2019., Methods: We used the Twitter application programming interface to obtain English-language tweets employing #HIVPrevention between January 1, 2014, and December 31, 2019 (n=69,197, globally). Using iterative qualitative content analysis on samples of tweets, we developed a keyword list to categorize the tweets into 10 prevention topics (eg, condom use, preexposure prophylaxis [PrEP]) and compared the frequency of tweets mentioning each topic over time. We assessed the overall change in the proportions of #HIVPrevention tweets mentioning each prevention topic in 2019 as compared with 2014 using chi-square and Fisher exact tests. We also conducted descriptive analyses to identify the accounts posting the most original tweets, the accounts retweeted most frequently, the most frequently used word pairings, and the spatial distribution of tweets in the United States compared with the number of state-level HIV cases., Results: PrEP (13,895 tweets; 20.08% of all included tweets) and HIV testing (7688, 11.11%) were the most frequently mentioned topics, whereas condom use (2941, 4.25%) and postexposure prophylaxis (PEP; 823, 1.19%) were mentioned relatively less frequently. The proportions of tweets mentioning PrEP (327/2251, 14.53%, in 2014, 5067/12,971, 39.1%, in 2019; P≤.001), HIV testing (208/2251, 9.24%, in 2014, 2193/12,971, 16.91% in 2019; P≤.001), and PEP (25/2251, 1.11%, in 2014, 342/12,971, 2.64%, in 2019; P≤.001) were higher in 2019 compared with 2014, whereas the proportions of tweets mentioning abstinence, condom use, circumcision, harm reduction, and gender inequity were lower in 2019 compared with 2014. The top retweeted accounts were mostly UN-affiliated entities; celebrities and HIV advocates were also represented. Geotagged #HIVPrevention tweets in the United States between 2014 and 2019 (n=514) were positively correlated with the number of state-level HIV cases in 2019 (r=0.81, P≤.01)., Conclusions: Twitter may be a useful source for identifying HIV prevention trends. During our evaluation period (2014-2019), the most frequently mentioned prevention topics were PrEP and HIV testing in tweets using #HIVPrevention. Strategic responses to these tweets that provide information about where to get tested or how to obtain PrEP may be potential approaches to reduce HIV incidence., (©Raquel Burgess, Josemari T Feliciano, Leonardo Lizbinski, Yusuf Ransome. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 11.08.2022.)

Objectives: The COVID-19 pandemic has influenced people's concerns regarding infectious diseases and their preventive measures. However, the magnitude of the impact and the difference between countries are unclear. This study aimed to assess the magnitude of the impact of COVID-19 on public interest and people's behaviours globally in preventing infectious diseases while comparing international trends and sustainability., Design: An infodemiology and infoveillance study., Setting: The study employed a web-based data collection to delineate public interest regarding COVID-19 preventive measures using Google Trends., Primary and Secondary Outcome Measures: A relative search volume was assigned to a keyword, standardising it from 0 to 100, with 100 representing the highest share of the term searches. The search terms "coronavirus", "wash hand", "social distancing", "hand sanitizer" and "mask" were investigated across 196 different countries and regions from July 2018 to October 2021 and weekly reports of the relative search volume were obtained. Persistence of interest was assessed by comparing the first 20 weeks with the last 20 weeks of the study period., Results: Although the relative search volume of "coronavirus" increased and was sustained at a significantly higher level (p<0.05) than before the pandemic declaration, globally, the trends and sustainability of the interest in preventable measures against COVID-19 varied between countries and regions., Conclusions: Sustained interest in preventive measures differed globally, with regional differences noted among Asia, Europe, Africa and the Americas. The global differences should be considered for implementing effective interventions against COVID-19. The increased interest in preventive behaviours against COVID-19 may be related to overall infectious disease prevention., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The COVID-19 pandemic caused a critical public health crisis worldwide, and policymakers are using lockdowns to control the virus. However, there has been a noticeable increase in aggressive social behaviors that threaten social stability. Lockdown measures might negatively affect mental health and lead to an increase in aggressive emotions. Discovering the relationship between lockdown and increased aggression is crucial for formulating appropriate policies that address these adverse societal effects. We applied natural language processing (NLP) technology to internet data, so as to investigate the social and emotional impacts of lockdowns., Objective: This research aimed to understand the relationship between lockdown and increased aggression using NLP technology to analyze the following 3 kinds of aggressive emotions: anger, offensive language, and hate speech, in spatiotemporal ranges of tweets in the United States., Methods: We conducted a longitudinal internet study of 11,455 Twitter users by analyzing aggressive emotions in 1,281,362 tweets they posted from 2019 to 2020. We selected 3 common aggressive emotions (anger, offensive language, and hate speech) on the internet as the subject of analysis. To detect the emotions in the tweets, we trained a Bidirectional Encoder Representations from Transformers (BERT) model to analyze the percentage of aggressive tweets in every state and every week. Then, we used the difference-in-differences estimation to measure the impact of lockdown status on increasing aggressive tweets. Since most other independent factors that might affect the results, such as seasonal and regional factors, have been ruled out by time and state fixed effects, a significant result in this difference-in-differences analysis can not only indicate a concrete positive correlation but also point to a causal relationship., Results: In the first 6 months of lockdown in 2020, aggression levels in all users increased compared to the same period in 2019. Notably, users under lockdown demonstrated greater levels of aggression than those not under lockdown. Our difference-in-differences estimation discovered a statistically significant positive correlation between lockdown and increased aggression (anger: P=.002, offensive language: P<.001, hate speech: P=.005). It can be inferred from such results that there exist causal relations., Conclusions: Understanding the relationship between lockdown and aggression can help policymakers address the personal and societal impacts of lockdown. Applying NLP technology and using big data on social media can provide crucial and timely information for this effort., (©Jerome Tze-Hou Hsu, Richard Tzong-Han Tsai. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 09.08.2022.)

Background: Automated conversational agents, or chatbots, have a role in reinforcing evidence-based guidance delivered through other media and offer an accessible, individually tailored channel for public engagement. In early-to-mid 2021, young adults and minority populations disproportionately affected by COVID-19 in the United States were more likely to be hesitant toward COVID-19 vaccines, citing concerns regarding vaccine safety and effectiveness. Successful chatbot communication requires purposive understanding of user needs., Objective: We aimed to review the acceptability of messages to be delivered by a chatbot named VIRA from Johns Hopkins University. The study investigated which message styles were preferred by young, urban-dwelling Americans as well as public health workers, since we anticipated that the chatbot would be used by the latter as a job aid., Methods: We conducted 4 web-based focus groups with 20 racially and ethnically diverse young adults aged 18-28 years and public health workers aged 25-61 years living in or near eastern-US cities. We tested 6 message styles, asking participants to select a preferred response style for a chatbot answering common questions about COVID-19 vaccines. We transcribed, coded, and categorized emerging themes within the discussions of message content, style, and framing., Results: Participants preferred messages that began with an empathetic reflection of a user concern and concluded with a straightforward, fact-supported response. Most participants disapproved of moralistic or reasoning-based appeals to get vaccinated, although public health workers felt that such strong statements appealing to communal responsibility were warranted. Responses tested with humor and testimonials did not appeal to the participants., Conclusions: To foster credibility, chatbots targeting young people with vaccine-related messaging should aim to build rapport with users by deploying empathic, reflective statements, followed by direct and comprehensive responses to user queries. Further studies are needed to inform the appropriate use of user-customized testimonials and humor in the context of chatbot communication., (©Rose Weeks, Lyra Cooper, Pooja Sangha, João Sedoc, Sydney White, Assaf Toledo, Shai Gretz, Dan Lahav, Nina Martin, Alexandra Michel, Jae Hyoung Lee, Noam Slonim, Naor Bar-Zeev. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.07.2022.)

Purpose: The aim of the present study was to use Google Trends for evaluating the association between the internet searches of the term "conjunctivitis" and the daily new cases of COVID-19., Methods: The relative search volume (RSV) of conjunctivitis from January 1 to April 16, 2019 (control group), January 1 to April 16, 2020 (first wave), and October 1 to December 31, 2020 (second wave) was obtained using Google Trends in Italy, France, United Kingdom, and United States. The number of COVID-19 daily new cases in the same countries were retrieved from Worldometer. Lag time correlation analyses were performed to evaluate the relationship between RSV and daily new cases (Pearson's correlation coefficient)., Results: During the first wave, the lagged RSV of conjunctivitis was significantly correlated with the number of COVID-19 daily new cases in all investigated countries. The highest correlation coefficients were obtained with a lag of 16 days in Italy ( R  = 0.868), 18 days in France ( R  = 0.491), 15 days in United Kingdom ( R  = 0.883), and 14 days in United States ( R  = 0.484) (all p  < 0.001). Conversely, no significant correlations were found in the second wave and in the control group., Conclusion: Google Trends searches on conjunctivitis were significantly correlated with COVID-19 daily new cases during the first wave in Italy, France, United Kingdom, and United States, with a lag of 14-18 days. Repeating the analysis for the second wave, however, no significant correlations were found in any of the investigated countries.

Background: Patients and their caregivers, including clinicians and educators, use web-based search engines to access healthcare-related information from the internet. Online search behavior analysis has been used to obtain insights on health information demand., Objectives: We aimed to describe the online search behavior for autoimmune encephalitis, autoimmune seizures, and autoimmune encephalitis (AE) worldwide over time through the analysis of search volumes made on Google., Methods: In this infodemiological study, we retrieved search volume indices for the keyword "autoimmune encephalitis (search term)", "autoimmune seizures (search term)", and "autoimmune encephalitis (search term)" based on worldwide search data from January 01, 2004 to October 31, 2021, using Google Trends. We performed a descriptive analysis of search volume patterns, including related topics and queries., Results: There was a progressive increase in search volume numbers over time for the keyword "autoimmune encephalitis", "autoimmune seizures", and "autoimmune epilepsy" with no annual seasonal variation. Peak search volumes for these keywords were recorded in July 2018, February 2005, December 2012, respectively. The greatest search volume for "autoimmune encephalitis" was recorded in Singapore, followed by Australia, the United States of America, the Philippines, and New Zealand, whereas it was highest in the United States for "autoimmune seizures" and "autoimmune epilepsy". The most searched topics were related to definition, causes, symptoms, diagnosis, and treatment. All related topics and queries increased in volume by more than 5000-fold over time., Conclusions: This study showed an uptrend in the online search interest on autoimmune encephalitis, autoimmune seizures, and autoimmune epilepsy over time, which may reflect the increased awareness of the condition by the public and the medical community. Information on online health information-seeking behavior may be obtained from Google Trends data despite its limitations., Competing Interests: Declaration of competing interests None of the authors has any conflict of interest to disclose. We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: The COVID-19 pandemic has created environments with increased risk factors for household violence, such as unemployment and financial uncertainty. At the same time, it led to the introduction of policies to mitigate financial uncertainty. Further, it hindered traditional measurements of household violence., Objective: Using an infoveillance approach, our goal was to determine if there were excess Google searches related to exposure to child abuse, intimate partner violence (IPV), and child-witnessed IPV during the COVID-19 pandemic and if any excesses are temporally related to shelter-in-place and economic policies., Methods: Data on relative search volume for each violence measure was extracted using the Google Health Trends application programming interface for each week from 2017 to 2020 for the United States. Using linear regression with restricted cubic splines, we analyzed data from 2017 to 2019 to characterize the seasonal variation shared across prepandemic years. Parameters from prepandemic years were used to predict the expected number of Google searches and 95% prediction intervals (PI) for each week in 2020. Weeks with searches above the upper bound of the PI are in excess of the model's prediction., Results: Relative search volume for exposure to child abuse was greater than expected in 2020, with 19% (10/52) of the weeks falling above the upper bound of the PI. These excesses in searches began a month after the Pandemic Unemployment Compensation program ended. Relative search volume was also heightened in 2020 for child-witnessed IPV, with 33% (17/52) of the weeks falling above the upper bound of the PI. This increase occurred after the introduction of shelter-in-place policies., Conclusions: Social and financial disruptions, which are common consequences of major disasters such as the COVID-19 pandemic, may increase risks for child abuse and child-witnessed IPV., (©Corinne A Riddell, Krista Neumann, N Jeanie Santaularia, Kriszta Farkas, Jennifer Ahern, Susan M Mason. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.06.2022.)

Stagnating COVID-19 vaccination rates and vaccine hesitancy remain a threat to public health. Improved strategies for real-time tracking and estimation of population-level behavior regarding vaccinations are needed. The aim of this study was to evaluate whether online search trends for COIVD-19 and influenza mirror vaccination rates. State-level weekly fraction of online searches for top vaccination-related search terms and CDC vaccination data were obtained from June 1, 2020, to May 31, 2021. Next, trends in online search and vaccination data for COVID-19 and influenza were analyzed for visual and quantitative correlation patterns using Spearman's rank correlation analysis. Online searches in the US for COVID-19 vaccinations increased 2.71-fold (95% CI: 1.98-3.45) in the 4 weeks after the FDA emergency authorization compared to the precedent 4 weeks. In March-April 2021, US online searches reached a plateau that was followed by a decline of 83.3% (95% CI: 31.2%-135.3%) until May 31, 2021. The timing of peaks in online searches varied across US states. Online searches were strongly correlated with vaccination rates (r=0.71, 95% CI: 0.45 - 0.87), preceding actual reported vaccination rates in 44 of 51 states. Online search trends preceded vaccination trends by a median of 3.0 weeks (95% CI: 2.0-4.0 weeks) across all states. For influenza vaccination searches, seasonal peaks in September-October between 2016-2020 were noted. Influenza search trends highly correlated with the timing of actual vaccinations for the 2019-2020 (r=0.82, 95% CI: 0.64 - 0.93) and 2020-2021 season (r=0.91, 95% CI: 0.78 - 0.97). Search trends and real-world vaccination rates are highly correlated. Temporal alignment and correlation levels were higher for influenza vaccinations; however, only online searches for COVID-19 vaccination preceded vaccination trends. These findings indicate that US online search data can potentially guide public health efforts, including policy changes and identifying geographical areas to expand vaccination campaigns., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Berning, Huang, Razavi, Boakye, Osuji, Stokes, Martin, Ayers, Blaha and Dzaye.)

Objective: The goal was to assess public interest in a wide range of musculoskeletal symptoms and disorders during the coronavirus disease 2019 (COVID-19) pandemic., Methods: We searched Google Trends for 118 search queries within the United States. We compared two timeframes of 2020 (March 15-July 4 and July 5-October 31) to similar timeframes over the four prior years (2016-2019)., Results: In the early pandemic, March 15-July 4, a statistically significant decrease in relative search volume of the majority of queries (60%) was detected, with a significant increase in only 2 queries (i.e. myalgia and toe swelling). In the phase July through October, a statistically significant decrease was detected in only 22% of search queries; there was no difference for 60% of search queries between 2020 and 2016-2019 suggesting a return to their prior levels for most of search queries. Interestingly, the search volume of 18% of search queries (i.e. fatigue, joint pain, muscle pain, myalgia, spondylosis, radiculopathy, myelopathy, neck pain, neck strain, lower back strain, sciatica, shoulder pain, frozen shoulder, elbow pain, lateral epicondylitis, wrist pain, carpal tunnel, hand pain, finger pain, trigger finger, and Morton's neuroma) was significantly increased compared with the four prior years., Conclusion: Public interest focused on COVID-19 and sought online information for COVID-19 symptoms in the early pandemic. In the period July through October, there was an upward trend in musculoskeletal symptoms and some colloquial terms/well-known musculoskeletal conditions coupled with a downward trend in general musculoskeletal disorder terms and certain specific diagnoses. This information may help rheumatologists understand public interest in musculoskeletal symptoms and disorders and address the needs of patients to mitigate the negative impact of the pandemic on outcomes., (© 2021. Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Background: Per- and polyfluoroalkyl substances (PFAS) are environmental contaminants that have received significant public attention. PFAS are a large group of human-made chemicals that have been used in industry and consumer products worldwide since the 1950s. Human exposure to PFAS is a growing public health concern. Studies suggest that exposure to PFAS may increase the risk of some cancers and have negative health impacts on the endocrine, metabolic, and immune systems. Federal and state health partners are investigating the exposure to and possible health effects associated with PFAS. Government agencies can observe social media discourse on PFAS to better understand public concerns and develop targeted communication and outreach efforts., Objective: The primary objective of this study is to understand how social media is used to share, disseminate, and engage in public discussions of PFAS-related information in the United States., Methods: We investigated PFAS-related content across 2 social media platforms between May 1, 2017, and April 30, 2019, to identify how social media is used in the United States to seek and disseminate PFAS-related information. Our key variable of interest was posts that mentioned "PFAS," "PFOA," "PFOS," and their hashtag variations across social media platforms. Additional variables included post type, time, PFAS event, and geographic location. We examined term use and post type differences across platforms. We used descriptive statistics and regression analysis to assess the incidence of PFAS discussions and to identify the date, event, and geographic patterns. We qualitatively analyzed social media content to determine the most prevalent themes discussed on social media platforms., Results: Our analysis revealed that Twitter had a significantly greater volume of PFAS-related posts compared with Reddit (98,264 vs 3126 posts). PFAS-related social media posts increased by 670% over 2 years, indicating a marked increase in social media users' interest in and awareness of PFAS. Active engagement varied across platforms, with Reddit posts demonstrating more in-depth discussions compared with passive likes and reposts among Twitter users. Spikes in PFAS discussions were evident and connected to the discovery of contamination events, media coverage, and scientific publications. Thematic analysis revealed that social media users see PFAS as a significant public health concern and seek a trusted source of information about PFAS-related public health efforts., Conclusions: The analysis identified a prevalent theme-on social media, PFAS are perceived as an immediate public health concern, which demonstrates a growing sense of urgency to understand this emerging contaminant and its potential health impacts. Government agencies can continue using social media research to better understand the changing community sentiment on PFAS and disseminate targeted information and then use social media as a forum for dispelling misinformation, communicating scientific findings, and providing resources for relevant public health services., (©Hao Tian, Christy Gaines, Lori Launi, Ana Pomales, Germaine Vazquez, Amanda Goharian, Bradley Goodnight, Erica Haney, Christopher M Reh, Rachel D Rogers. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.03.2022.)

Background: The emergence and media coverage of COVID-19 may have affected influenza search patterns, possibly affecting influenza surveillance results using Google Trends., Objective: We aimed to investigate if the emergence of COVID-19 was associated with modifications in influenza search patterns in the United States., Methods: We retrieved US Google Trends data (relative number of searches for specified terms) for the topics influenza, Coronavirus disease 2019, and symptoms shared between influenza and COVID-19. We calculated the correlations between influenza and COVID-19 search data for a 1-year period after the first COVID-19 diagnosis in the United States (January 21, 2020 to January 20, 2021). We constructed a seasonal autoregressive integrated moving average model and compared predicted search volumes, using the 4 previous years, with Google Trends relative search volume data. We built a similar model for shared symptoms data. We also assessed correlations for the past 5 years between Google Trends influenza data, US Centers for Diseases Control and Prevention influenza-like illness data, and influenza media coverage data., Results: We observed a nonsignificant weak correlation (ρ= -0.171; P=0.23) between COVID-19 and influenza Google Trends data. Influenza search volumes for 2020-2021 distinctly deviated from values predicted by seasonal autoregressive integrated moving average models-for 6 weeks within the first 13 weeks after the first COVID-19 infection was confirmed in the United States, the observed volume of searches was higher than the upper bound of 95% confidence intervals for predicted values. Similar results were observed for shared symptoms with influenza and COVID-19 data. The correlation between Google Trends influenza data and CDC influenza-like-illness data decreased after the emergence of COVID-19 (2020-2021: ρ=0.643; 2019-2020: ρ=0.902), while the correlation between Google Trends influenza data and influenza media coverage volume remained stable (2020-2021: ρ=0.746; 2019-2020: ρ=0.707)., Conclusions: Relevant differences were observed between predicted and observed influenza Google Trends data the year after the onset of the COVID-19 pandemic in the United States. Such differences are possibly due to media coverage, suggesting limitations to the use of Google Trends as a flu surveillance tool., (©Owen Cai, Bernardo Sousa-Pinto. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 03.03.2022.)

Objective: To explore trends and patterns of laypeople's activity for seeking telephone number of emergency medical services (EMS) based on analysis of online search traffic, including changes of the search activity with onset of the coronavirus disease 2019 (COVID-19) outbreak, in five countries - the United States of America (USA), India, Brazil, the United Kingdom (UK) and Russia., Methods: Google Trends (GT) country-level data on weekly relative search volumes (RSV) for top queries to seek EMS number were examined for January 2018-October 2021, including a comparison of RSVs between pre-COVID-19 period (January 2018-October 2019) and COVID-19 period (January 2020-October 2021), and evaluation of temporal associations of RSVs with weekly numbers of new COVID-19 cases., Results: The countries demonstrated diverse patterns of the search activity with significantly different mean RSVs (the USA 1.76, India 10.20, Brazil 2.51, the UK 6.42, Russia 56.79; p < 0.001). For all countries excepting the USA mean RSVs of the COVID-19 period were significantly higher compared with the pre-COVID-19 ones (India +74%, Brazil +148%, the UK +22%, Russia +9%; p ≤ 0.034), and exhibited positive correlations with numbers of new COVID-19 cases, more pronounced for 2021 (India r S  = 0.538, Brazil 0.307, the UK 0.434, Russia 0.639; p ≤ 0.045)., Conclusion: Laypeople's activity for seeking EMS telephone number greatly varies between countries. It clearly responds to the spread of COVID-19 and could be reflective of public need for obtaining emergency help. Further studies are required to establish the role of GT for conducting real-time surveillance of population demand for EMS., Competing Interests: Declaration of Competing Interest The author declare no conflicts of interest., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Advances in automated data processing and machine learning (ML) models, together with the unprecedented growth in the number of social media users who publicly share and discuss health-related information, have made public health surveillance (PHS) one of the long-lasting social media applications. However, the existing PHS systems feeding on social media data have not been widely deployed in national surveillance systems, which appears to stem from the lack of practitioners and the public's trust in social media data. More robust and reliable data sets over which supervised ML models can be trained and tested reliably is a significant step toward overcoming this hurdle. The health implications of daily behaviors (physical activity, sedentary behavior, and sleep [PASS]), as an evergreen topic in PHS, are widely studied through traditional data sources such as surveillance surveys and administrative databases, which are often several months out-of-date by the time they are used, costly to collect, and thus limited in quantity and coverage., Objective: The main objective of this study is to present a large-scale, multicountry, longitudinal, and fully labeled data set to enable and support digital PASS surveillance research in PHS. To support high-quality surveillance research using our data set, we have conducted further analysis on the data set to supplement it with additional PHS-related metadata., Methods: We collected the data of this study from Twitter using the Twitter livestream application programming interface between November 28, 2018, and June 19, 2020. To obtain PASS-related tweets for manual annotation, we iteratively used regular expressions, unsupervised natural language processing, domain-specific ontologies, and linguistic analysis. We used Amazon Mechanical Turk to label the collected data to self-reported PASS categories and implemented a quality control pipeline to monitor and manage the validity of crowd-generated labels. Moreover, we used ML, latent semantic analysis, linguistic analysis, and label inference analysis to validate the different components of the data set., Results: LPHEADA (Labelled Digital Public Health Dataset) contains 366,405 crowd-generated labels (3 labels per tweet) for 122,135 PASS-related tweets that originated in Australia, Canada, the United Kingdom, or the United States, labeled by 708 unique annotators on Amazon Mechanical Turk. In addition to crowd-generated labels, LPHEADA provides details about the three critical components of any PHS system: place, time, and demographics (ie, gender and age range) associated with each tweet., Conclusions: Publicly available data sets for digital PASS surveillance are usually isolated and only provide labels for small subsets of the data. We believe that the novelty and comprehensiveness of the data set provided in this study will help develop, evaluate, and deploy digital PASS surveillance systems. LPHEADA will be an invaluable resource for both public health researchers and practitioners., (©Zahra Shakeri Hossein Abad, Gregory P Butler, Wendy Thompson, Joon Lee. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 14.02.2022.)

Background: The Ending the HIV Epidemic (EHE) plan aims to end the HIV epidemic in the United States by 2030. Having timely and accessible data to assess progress toward EHE goals at the local level is a critical resource to achieve this goal., Objective: The aim of this paper was to introduce America's HIV Epidemic Analysis Dashboard (AHEAD), a data visualization tool that displays relevant data on the 6 HIV indicators provided by the Centers for Disease Control and Prevention. AHEAD can be used to monitor progress toward ending the HIV epidemic in local communities across the United States. Its objective is to make data available to stakeholders, which can be used to measure national and local progress toward 2025 and 2030 EHE goals and to help jurisdictions make local decisions that are grounded in high-quality data., Methods: AHEAD displays data from public health data systems (eg, surveillance systems and census data), organized around the 6 EHE indicators (HIV incidence, knowledge of HIV status, HIV diagnoses, linkage to HIV medical care, viral HIV suppression, and preexposure prophylaxis coverage). Data are displayed for each of the EHE priority areas (48 counties in Washington, District of Columbia, and San Juan, Puerto Rico) which accounted for more than 50% of all US HIV diagnoses in 2016 and 2017 and 7 primarily southern states with high rates of HIV in rural communities. AHEAD also displays data for the 43 remaining states for which data are available. Data features prioritize interactive data visualization tools that allow users to compare indicator data stratified by sex at birth, race or ethnicity, age, and transmission category within a jurisdiction (when available) or compare data on EHE indicators between jurisdictions., Results: AHEAD was launched on August 14, 2020. In the 11 months since its launch, the Dashboard has been visited 26,591 times by 17,600 unique users. About one-quarter of all users returned to the Dashboard at least once. On average, users engaged with 2.4 pages during their visit to the Dashboard, indicating that the average user goes beyond the informational landing page to engage with 1 or more pages of data and content. The most frequently visited content pages are the jurisdiction webpages., Conclusions: The Ending the HIV Epidemic plan is described as a "whole of society" effort. Societal public health initiatives require objective indicators and require that all societal stakeholders have transparent access to indicator data at the level of the health jurisdictions responsible for meeting the goals of the plan. Data transparency empowers local stakeholders to track movement toward EHE goals, identify areas with needs for improvement, and make data-informed adjustments to deploy the expertise and resources required to locally tailor and implement strategies to end the HIV epidemic in their jurisdiction., (©Patrick Sean Sullivan, Cory R Woodyatt, Oskian Kouzouian, Kristen J Parrish, Jennifer Taussig, Chris Conlan, Harold Phillips. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 10.02.2022.)

Background: The WHO has used the term "infodemic" to describe the vast amount of false and true information that was making it difficult for people to find reliable information when they needed it. The infodemic spreads faster than COVID-19 itself. The main objective of the study was to characterize and analyze content about COVID-19 returned by Google during the pandemic and compare it between countries., Methods: The study was conducted between 30 March and 27 April 2020. The information was searched through local Google websites using the "COVID-19", "Coronavirus", "SARS-CoV-2" and "fake news" keywords. The search was conducted in Australia, France, Germany, Italy, Poland, Singapore, Spain, UK and the USA. The total number of the analyzed webpages was 685., Results: The most frequent types were News websites 47% (324/685) and Governmental 19% (131/685) while the least were Health portals 2% (17/685) and Scientific journals 5% (35/635), p < 0.001. United States and Australia had the highest share of Governmental websites. There was a positive correlation between the amount of preventive information and a number of SARS-CoV-2 infections in countries. The higher the number of tests performed, the higher was the amount of information about prevention available online., Conclusions: Online information is usually available on news and government websites and refers to prevention. There were differences between countries in types of information available online. The highest positioned (the first 20) websites for COVID-19, Coronavirus and SARS-CoV-2 keywords returned by Google include true information.

Background: Perceptions of tobacco, cannabis, and electronic nicotine delivery systems (ENDS) are continually evolving in the United States. Exploring these characteristics through user generated text sources may provide novel insights into product use behavior that are challenging to identify using survey-based methods. The objective of this study was to compare the topics frequently discussed among Reddit members in cannabis, tobacco, and ENDS-specific subreddits. Methods: We collected 643,070 posts on the social media site Reddit between January 2013 and December 2018. We developed and validated an annotation scheme, achieving a high level of agreement among annotators. We then manually coded a subset of 2,630 posts for their content with relation to experiences and use of the three products of interest, and further developed word cloud representations of the words contained in these posts. Finally, we applied Latent Dirichlet Allocation (LDA) topic modeling to the 643,070 posts to identify emerging themes related to cannabis, tobacco, and ENDS products being discussed on Reddit. Results: Our manual annotation process yielded 2,148 (81.6%) posts that contained a mention(s) of either cannabis, tobacco, or ENDS with 1,537 (71.5%) of these posts mentioning cannabis, 421 (19.5%) mentioning ENDS, and 264 (12.2%) mentioning tobacco. In cannabis-specific subreddits, personal experiences with cannabis, cannabis legislation, health effects of cannabis use, methods and forms of cannabis, and the cultivation of cannabis were commonly discussed topics. The discussion in tobacco-specific subreddits often focused on the discussion of brands and types of combustible tobacco, as well as smoking cessation experiences and advice. In ENDS-specific subreddits, topics often included ENDS accessories and parts, flavors and nicotine solutions, procurement of ENDS, and the use of ENDS for smoking cessation. Conclusion: Our findings highlight the posting and participation patterns of Reddit members in cannabis, tobacco, and ENDS-specific subreddits and provide novel insights into aspects of personal use regarding these products. These findings complement epidemiologic study designs and highlight the potential of using specific subreddits to explore personal experiences with cannabis, ENDS, and tobacco products., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Benson, Hu, Chen, Zhu and Conway.)

Objectives: Acute laryngitis is a common disease with self-limiting nature. Since the leading cause is attributed to viral infections and thus self-limiting, many affected individuals do not seek professional medical help. However, because the major symptom of hoarseness imposes a substantial burden in everyday life, it might be speculated that web-based search interest on this condition follows incidence rates, with highest peaks during winter months. The aim of this study was to evaluate global public health-information seeking behaviour on laryngitis-related search terms., Methods: We utilized Google Trends to assess country-specific, representative laryngitis-related search terms for English and non-English speaking countries of both hemispheres. Extracted time series data from Australia, Brazil, Canada, Germany, the United Kingdom, and the United States of America, covering a timeframe between 2004 and 2019 were first assessed for reliability, followed by seasonality analysis using the cosinor model., Results: Direct comparisons revealed different, representative laryngitis-related search terms for English- and non-English speaking countries. Extracted data showed a trend of higher reliability in countries with more inhabitants. Subsequent graphical analysis revealed winter peaks in all countries from both hemispheres. Cosinor analysis confirmed these seasonal variations to be significant (all P < 0.001)., Conclusion: Public interest in laryngitis-related, online health information displayed seasonal variations in countries from both hemispheres, with highest interest during winter months. These findings emphasize the importance to optimize the distribution of reliable, web-based health education in order to prevent the spread of misinformation and to improve health literacy among general populations., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The novel coronavirus pandemic continues to ravage communities across the United States. Opinion surveys identified the importance of political ideology in shaping perceptions of the pandemic and compliance with preventive measures.Objective: The aim of this study was to measure political partisanship and antiscience attitudes in the discussions about the pandemic on social media, as well as their geographic and temporal distributions.Methods: We analyzed a large set of tweets from Twitter related to the pandemic, collected between January and May 2020, and developed methods to classify the ideological alignment of users along the moderacy (hardline vs moderate), political (liberal vs conservative), and science (antiscience vs proscience) dimensions.Results: We found a significant correlation in polarized views along the science and political dimensions. Moreover, politically moderate users were more aligned with proscience views, while hardline users were more aligned with antiscience views. Contrary to expectations, we did not find that polarization grew over time; instead, we saw increasing activity by moderate proscience users. We also show that antiscience conservatives in the United States tended to tweet from the southern and northwestern states, while antiscience moderates tended to tweet from the western states. The proportion of antiscience conservatives was found to correlate with COVID-19 cases.Conclusions: Our findings shed light on the multidimensional nature of polarization and the feasibility of tracking polarized opinions about the pandemic across time and space through social media data. [ABSTRACT FROM AUTHOR]

Background: COVID-19 has continued to spread in the United States and globally. Closely monitoring public engagement and perceptions of COVID-19 and preventive measures using social media data could provide important information for understanding the progress of current interventions and planning future programs.Objective: The aim of this study is to measure the public's behaviors and perceptions regarding COVID-19 and its effects on daily life during 5 months of the pandemic.Methods: Natural language processing (NLP) algorithms were used to identify COVID-19-related and unrelated topics in over 300 million online data sources from June 15 to November 15, 2020. Posts in the sample were geotagged by NetBase, a third-party data provider, and sensitivity and positive predictive value were both calculated to validate the classification of posts. Each post may have included discussion of multiple topics. The prevalence of discussion regarding these topics was measured over this time period and compared to daily case rates in the United States.Results: The final sample size included 9,065,733 posts, 70% of which were sourced from the United States. In October and November, discussion including mentions of COVID-19 and related health behaviors did not increase as it had from June to September, despite an increase in COVID-19 daily cases in the United States beginning in October. Additionally, discussion was more focused on daily life topics (n=6,210,255, 69%), compared with COVID-19 in general (n=3,390,139, 37%) and COVID-19 public health measures (n=1,836,200, 20%).Conclusions: There was a decline in COVID-19-related social media discussion sourced mainly from the United States, even as COVID-19 cases in the United States increased to the highest rate since the beginning of the pandemic. Targeted public health messaging may be needed to ensure engagement in public health prevention measures as global vaccination efforts continue. [ABSTRACT FROM AUTHOR]

Background: The wide adoption of social media in daily life renders it a rich and effective resource for conducting near real-time assessments of consumers' perceptions of health services. However, its use in these assessments can be challenging because of the vast amount of data and the diversity of content in social media chatter.Objective: This study aims to develop and evaluate an automatic system involving natural language processing and machine learning to automatically characterize user-posted Twitter data about health services using Medicaid, the single largest source of health coverage in the United States, as an example.Methods: We collected data from Twitter in two ways: via the public streaming application programming interface using Medicaid-related keywords (Corpus 1) and by using the website's search option for tweets mentioning agency-specific handles (Corpus 2). We manually labeled a sample of tweets in 5 predetermined categories or other and artificially increased the number of training posts from specific low-frequency categories. Using the manually labeled data, we trained and evaluated several supervised learning algorithms, including support vector machine, random forest (RF), naïve Bayes, shallow neural network (NN), k-nearest neighbor, bidirectional long short-term memory, and bidirectional encoder representations from transformers (BERT). We then applied the best-performing classifier to the collected tweets for postclassification analyses to assess the utility of our methods.Results: We manually annotated 11,379 tweets (Corpus 1: 9179; Corpus 2: 2200) and used 7930 (69.7%) for training, 1449 (12.7%) for validation, and 2000 (17.6%) for testing. A classifier based on BERT obtained the highest accuracies (81.7%, Corpus 1; 80.7%, Corpus 2) and F1 scores on consumer feedback (0.58, Corpus 1; 0.90, Corpus 2), outperforming the second best classifiers in terms of accuracy (74.6%, RF on Corpus 1; 69.4%, RF on Corpus 2) and F1 score on consumer feedback (0.44, NN on Corpus 1; 0.82, RF on Corpus 2). Postclassification analyses revealed differing intercorpora distributions of tweet categories, with political (400778/628411, 63.78%) and consumer feedback (15073/27337, 55.14%) tweets being the most frequent for Corpus 1 and Corpus 2, respectively.Conclusions: The broad and variable content of Medicaid-related tweets necessitates automatic categorization to identify topic-relevant posts. Our proposed system presents a feasible solution for automatic categorization and can be deployed and generalized for health service programs other than Medicaid. Annotated data and methods are available for future studies. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has impacted people's lives at unprecedented speed and scale, including how they eat and work, what they are concerned about, how much they move, and how much they can earn. Traditional surveys in the area of public health can be expensive and time-consuming, and they can rapidly become outdated. The analysis of big data sets (such as electronic patient records and surveillance systems) is very complex. Google Trends is an alternative approach that has been used in the past to analyze health behaviors; however, most existing studies on COVID-19 using these data examine a single issue or a limited geographic area. This paper explores Google Trends as a proxy for what people are thinking, needing, and planning in real time across the United States.Objective: We aimed to use Google Trends to provide both insights into and potential indicators of important changes in information-seeking patterns during pandemics such as COVID-19. We asked four questions: (1) How has information seeking changed over time? (2) How does information seeking vary between regions and states? (3) Do states have particular and distinct patterns in information seeking? (4) Do search data correlate with-or precede-real-life events?Methods: We analyzed searches on 38 terms related to COVID-19, falling into six themes: social and travel; care seeking; government programs; health programs; news and influence; and outlook and concerns. We generated data sets at the national level (covering January 1, 2016, to April 15, 2020) and state level (covering January 1 to April 15, 2020). Methods used include trend analysis of US search data; geographic analyses of the differences in search popularity across US states from March 1 to April 15, 2020; and principal component analysis to extract search patterns across states.Results: The data showed high demand for information, corresponding with increasing searches for coronavirus linked to news sources regardless of the ideological leaning of the news source. Changes in information seeking often occurred well in advance of action by the federal government. The popularity of searches for unemployment claims predicted the actual spike in weekly claims. The increase in searches for information on COVID-19 care was paralleled by a decrease in searches related to other health behaviors, such as urgent care, doctor's appointments, health insurance, Medicare, and Medicaid. Finally, concerns varied across the country; some search terms were more popular in some regions than in others.Conclusions: COVID-19 is unlikely to be the last pandemic faced by the United States. Our research holds important lessons for both state and federal governments in a fast-evolving situation that requires a finger on the pulse of public sentiment. We suggest strategic shifts for policy makers to improve the precision and effectiveness of non-pharmaceutical interventions and recommend the development of a real-time dashboard as a decision-making tool. [ABSTRACT FROM AUTHOR]

Background: Psoriasis is an autoimmune disease estimated to affect more than 6 million adults in the United States. It poses a significant public health problem and contributes to rising health care costs, affecting people's quality of life and ability to work. Previous research showed that nontreatment and undertreatment of patients with psoriasis remain a significant problem. Perspectives of patients toward seeking psoriasis treatment are understudied. Social media offers a new data source of user-generated content. Researchers suggested that the social network Twitter may serve as a rich avenue for exploring how patients communicate about their health issues. Objective: The objective of this study is to conduct a content analysis of Twitter posts (in English) published by users in the United States between February 1, 2016, and October 31, 2018, to examine perspectives that potentially influence the treatment decision among patients with psoriasis. Methods: User-generated Twitter posts that include keywords related to psoriasis will be analyzed using text classifiers to identify themes related to the research questions. We will use Symplur Signals, a health care social media analytics platform, to access the Twitter data. We will use descriptive statistics to analyze the data and identify the most prevalent topics in the Twitter content among people with psoriasis. Results: This study is supported by the National Center for Advancing Translational Science through a Clinical and Translational Science Award award. Study approval was obtained from the institutional review board at the University of Southern California. Data extraction and cleaning are complete. For the time period from February 1, 2016, to October 31, 2018, we obtained 95,040 Twitter posts containing terms related to "psoriasis" from users in the United States published in English. After removing duplicates, retweets, and non-English tweets, we found that 75.51% (52,301/69,264) of the psoriasis-related posts were sent by commercial or bot-like accounts, while 16,963 posts were noncommercial and will be included in the analysis to assess the patient perspective. Analysis was completed in Summer 2020. Conclusions: This protocol paper provides a detailed description of a social media research project including the process of data extraction, cleaning, and analysis. It is our goal to contribute to the development of more transparent social media research efforts. Our findings will shed light on whether Twitter provides a promising data source for garnering patient perspective data about psoriasis treatment decisions. The data will also help to determine whether Twitter might serve as a potential outreach platform for raising awareness of psoriasis and treatment options among patients and implementing related health interventions. International Registered Report Identifier (IRRID): DERR1-10.2196/13731 JMIR Res Protoc 2021;10(2):e13731 doi:10.2196/13731 [ABSTRACT FROM AUTHOR]

Background: Health misinformation is a public health concern. Various stakeholders have called on health care professionals, such as nurses and physicians, to be more proactive in correcting health misinformation on social media., Objective: This study aims to identify US physicians' and nurses' motivations for correcting health misinformation on social media, the barriers they face in doing so, and their recommendations for overcoming such barriers., Methods: In-depth interviews were conducted with 30 participants, which comprised 15 (50%) registered nurses and 15 (50%) physicians. Qualitative data were analyzed by using thematic analysis., Results: Participants were personally (eg, personal choice) and professionally (eg, to fulfill the responsibility of a health care professional) motivated to correct health misinformation on social media. However, they also faced intrapersonal (eg, a lack of positive outcomes and time), interpersonal (eg, harassment and bullying), and institutional (eg, a lack of institutional support and social media training) barriers to correcting health misinformation on social media. To overcome these barriers, participants recommended that health care professionals should receive misinformation and social media training, including building their social media presence., Conclusions: US physicians and nurses are willing to correct health misinformation on social media despite several barriers. Nonetheless, this study provides recommendations that can be used to overcome such barriers. Overall, the findings can be used by health authorities and organizations to guide policies and activities aimed at encouraging more health care professionals to be present on social media to counteract health misinformation., (©John Robert Bautista, Yan Zhang, Jacek Gwizdka. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 01.09.2021.)

Background: It is now common to search for health information online. A 2013 Pew Research Center survey found that 77% of online health seekers began their query at a search engine. The widespread use of online health information seeking also applies to women's reproductive health. Despite online interest in birth control, not much is known about related interests and concerns reflected in the search terms in the United States., Objective: In this study, we identify the top search terms on Google related to birth control in Louisiana and Mississippi and compare those results to the broader United States, examining how Google searches on birth control have evolved over time and identifying regional variation within states., Methods: We accessed search data on birth control from 2014-2018 from 2 Google application programming interfaces (APIs), Google Trends and Google Health Trends. We selected Google as it is the most commonly used search engine. We focused our analysis on data from 2017 and compared with 2018 data as appropriate. To assess trends, we analyzed data from 2014 through 2018. To compare the relative search frequencies of the top queries across Louisiana, Mississippi, and the United States, we used the Google Health Trends API. Relative search volume by designated marketing area (DMA) gave us the rankings of search volume for each birth control method in each DMA as compared to one another., Results: Results showed that when people searched for "birth control" in Louisiana and the broader United States, they were searching for information on a diverse spectrum of methods. This differs from Mississippi, where the data indicated people were mainly searching for information related to birth control pills. Across all locations, searches for birth control pills were significantly higher than any other queries related to birth control in the United States, Louisiana, and Mississippi, and this trend remained constant from 2014 to 2018. Regional level analysis showed variations in search traffic for birth control across each state., Conclusions: The internet is a growing source of health information for many users, including information on birth control. Understanding popular Google search queries on birth control can inform in-person discussions initiated by family planning practitioners and broader birth control messaging campaigns., International Registered Report Identifier (irrid): RR2-10.2196/16543., (©Ndola Prata, Karen Weidert, Anne Zepecki, Elina Yon, Elizabeth Pleasants, Petrice Sams-Abiodun, Sylvia Guendelman. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.07.2021.)

Background: The COVID-19 pandemic led to unprecedented mitigation efforts that disrupted the daily lives of millions. Beyond the general health repercussions of the pandemic itself, these measures also present a challenge to the world's mental health and health care systems. Considering that traditional survey methods are time-consuming and expensive, we need timely and proactive data sources to respond to the rapidly evolving effects of health policy on our population's mental health. Many people in the United States now use social media platforms such as Twitter to express the most minute details of their daily lives and social relations. This behavior is expected to increase during the COVID-19 pandemic, rendering social media data a rich field to understand personal well-being.Objective: This study aims to answer three research questions: (1) What themes emerge from a corpus of US tweets about COVID-19? (2) To what extent did social media use increase during the onset of the COVID-19 pandemic? and (3) Does sentiment change in response to the COVID-19 pandemic?Methods: We analyzed 86,581,237 public domain English language US tweets collected from an open-access public repository in three steps. First, we characterized the evolution of hashtags over time using latent Dirichlet allocation (LDA) topic modeling. Second, we increased the granularity of this analysis by downloading Twitter timelines of a large cohort of individuals (n=354,738) in 20 major US cities to assess changes in social media use. Finally, using this timeline data, we examined collective shifts in public mood in relation to evolving pandemic news cycles by analyzing the average daily sentiment of all timeline tweets with the Valence Aware Dictionary and Sentiment Reasoner (VADER) tool.Results: LDA topics generated in the early months of the data set corresponded to major COVID-19-specific events. However, as state and municipal governments began issuing stay-at-home orders, latent themes shifted toward US-related lifestyle changes rather than global pandemic-related events. Social media volume also increased significantly, peaking during stay-at-home mandates. Finally, VADER sentiment analysis scores of user timelines were initially high and stable but decreased significantly, and continuously, by late March.Conclusions: Our findings underscore the negative effects of the pandemic on overall population sentiment. Increased use rates suggest that, for some, social media may be a coping mechanism to combat feelings of isolation related to long-term social distancing. However, in light of the documented negative effect of heavy social media use on mental health, social media may further exacerbate negative feelings in the long-term for many individuals. Thus, considering the overburdened US mental health care structure, these findings have important implications for ongoing mitigation efforts. [ABSTRACT FROM AUTHOR]

Background: The exposure and consumption of information during epidemic outbreaks may alter people's risk perception and trigger behavioral changes, which can ultimately affect the evolution of the disease. It is thus of utmost importance to map the dissemination of information by mainstream media outlets and the public response to this information. However, our understanding of this exposure-response dynamic during the COVID-19 pandemic is still limited.Objective: The goal of this study is to characterize the media coverage and collective internet response to the COVID-19 pandemic in four countries: Italy, the United Kingdom, the United States, and Canada.Methods: We collected a heterogeneous data set including 227,768 web-based news articles and 13,448 YouTube videos published by mainstream media outlets, 107,898 user posts and 3,829,309 comments on the social media platform Reddit, and 278,456,892 views of COVID-19-related Wikipedia pages. To analyze the relationship between media coverage, epidemic progression, and users' collective web-based response, we considered a linear regression model that predicts the public response for each country given the amount of news exposure. We also applied topic modelling to the data set using nonnegative matrix factorization.Results: Our results show that public attention, quantified as user activity on Reddit and active searches on Wikipedia pages, is mainly driven by media coverage; meanwhile, this activity declines rapidly while news exposure and COVID-19 incidence remain high. Furthermore, using an unsupervised, dynamic topic modeling approach, we show that while the levels of attention dedicated to different topics by media outlets and internet users are in good accordance, interesting deviations emerge in their temporal patterns.Conclusions: Overall, our findings offer an additional key to interpret public perception and response to the current global health emergency and raise questions about the effects of attention saturation on people's collective awareness and risk perception and thus on their tendencies toward behavioral change. [ABSTRACT FROM AUTHOR]

Background: The coronavirus disease (COVID-19) pandemic led to substantial public discussion. Understanding these discussions can help institutions, governments, and individuals navigate the pandemic.Objective: The aim of this study is to analyze discussions on Twitter related to COVID-19 and to investigate the sentiments toward COVID-19.Methods: This study applied machine learning methods in the field of artificial intelligence to analyze data collected from Twitter. Using tweets originating exclusively in the United States and written in English during the 1-month period from March 20 to April 19, 2020, the study examined COVID-19-related discussions. Social network and sentiment analyses were also conducted to determine the social network of dominant topics and whether the tweets expressed positive, neutral, or negative sentiments. Geographic analysis of the tweets was also conducted.Results: There were a total of 14,180,603 likes, 863,411 replies, 3,087,812 retweets, and 641,381 mentions in tweets during the study timeframe. Out of 902,138 tweets analyzed, sentiment analysis classified 434,254 (48.2%) tweets as having a positive sentiment, 187,042 (20.7%) as neutral, and 280,842 (31.1%) as negative. The study identified 5 dominant themes among COVID-19-related tweets: health care environment, emotional support, business economy, social change, and psychological stress. Alaska, Wyoming, New Mexico, Pennsylvania, and Florida were the states expressing the most negative sentiment while Vermont, North Dakota, Utah, Colorado, Tennessee, and North Carolina conveyed the most positive sentiment.Conclusions: This study identified 5 prevalent themes of COVID-19 discussion with sentiments ranging from positive to negative. These themes and sentiments can clarify the public's response to COVID-19 and help officials navigate the pandemic. [ABSTRACT FROM AUTHOR]

Background: The use of social big data is an important emerging concern in public health. Internet search volumes are useful data that can sensitively detect trends of the public's attention during a pandemic outbreak situation., Objective: Our study aimed to analyze the public's interest in COVID-19 proliferation, identify the correlation between the proliferation of COVID-19 and interest in immunity and products that have been reported to confer an enhancement of immunity, and suggest measures for interventions that should be implemented from a health and medical point of view., Methods: To assess the level of public interest in infectious diseases during the initial days of the COVID-19 outbreak, we extracted Google search data from January 20, 2020, onward and compared them to data from March 15, 2020, which was approximately 2 months after the COVID-19 outbreak began. In order to determine whether the public became interested in the immune system, we selected coronavirus, immune, and vitamin as our final search terms., Results: The increase in the cumulative number of confirmed COVID-19 cases that occurred after January 20, 2020, had a strong positive correlation with the search volumes for the terms coronavirus (R=0.786; P<.001), immune (R=0.745; P<.001), and vitamin (R=0.778; P<.001), and the correlations between variables were all mutually statistically significant. Moreover, these correlations were confirmed on a country basis when we restricted our analyses to the United States, the United Kingdom, Italy, and Korea. Our findings revealed that increases in search volumes for the terms coronavirus and immune preceded the actual occurrences of confirmed cases., Conclusions: Our study shows that during the initial phase of the COVID-19 crisis, the public's desire and actions of strengthening their own immune systems were enhanced. Further, in the early stage of a pandemic, social media platforms have a high potential for informing the public about potentially helpful measures to prevent the spread of an infectious disease and provide relevant information about immunity, thereby increasing the public's knowledge., (©Jinhee Lee, Yunna Kwan, Jun Young Lee, Jae Il Shin, Keum Hwa Lee, Sung Hwi Hong, Young Joo Han, Andreas Kronbichler, Lee Smith, Ai Koyanagi, Louis Jacob, SungWon Choi, Ramy Abou Ghayda, Myung-Bae Park. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 18.06.2021.)

Background: Compared with White Americans, Black Americans have higher colon cancer mortality rates but lower up-to-date screening rates. Chadwick Boseman was a prominent Black American actor who died of colon cancer on August 28, 2020. As announcements of celebrity diagnoses often result in increased awareness, Boseman's death may have resulted in greater interest in colon cancer on the internet, particularly among Black Americans., Objective: This study aims to quantify the impact of Chadwick Boseman's death on web-based search interest in colon cancer and determine whether there was an increase in interest in regions of the United States with a greater proportion of Black Americans., Methods: We conducted an infoveillance study using Google Trends (GT) and Wikipedia pageview analysis. Using an autoregressive integrated moving average algorithm, we forecasted the weekly relative search volume (RSV) for GT search topics and terms related to colon cancer that would have been expected had his death not occurred and compared it with observed RSV data. This analysis was also conducted for the number of page views on the Wikipedia page for colorectal cancer. We then delineated GT RSV data for the term colon cancer for states and metropolitan areas in the United States and determined how the RSV values for these regions correlated with the percentage of Black Americans in that region. Differences in these correlations before and after Boseman's death were compared to determine whether there was a shift in the racial demographics of the individuals conducting the searches., Results: The observed RSVs for the topics colorectal cancer and colon cancer screening increased by 598% and 707%, respectively, and were on average 121% (95% CI 72%-193%) and 256% (95% CI 35%-814%) greater than expected during the first 3 months following Boseman's death. Daily Wikipedia page view volume during the 2 months following Boseman's death was on average 1979% (95% CI 1375%-2894%) greater than expected, and it was estimated that this represented 547,354 (95% CI 497,708-585,167) excess Wikipedia page views. Before Boseman's death, there were negative correlations between the percentage of Black Americans living in a state or metropolitan area and the RSV for colon cancer in that area (r=-0.18 and r=-0.05, respectively). However, in the 2 weeks following his death, there were positive correlations between the RSV for colon cancer and the percentage of Black Americans per state and per metropolitan area (r=0.73 and r=0.33, respectively). These changes persisted for 4 months and were all statistically significant (P<.001)., Conclusions: There was a significant increase in web-based activity related to colon cancer following Chadwick Boseman's death, particularly in areas with a higher proportion of Black Americans. This reflects a heightened public awareness that can be leveraged to further educate the public., (©Hiten Naik, Maximilian Desmond Dimitri Johnson, Michael Roger Johnson. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 15.06.2021.)

Background: As policy makers continue to shape the national and local responses to the COVID-19 pandemic, the information they choose to share and how they frame their content provide key insights into the public and health care systems., Objective: We examined the language used by the members of the US House and Senate during the first 10 months of the COVID-19 pandemic and measured content and sentiment based on the tweets that they shared., Methods: We used Quorum (Quorum Analytics Inc) to access more than 300,000 tweets posted by US legislators from January 1 to October 10, 2020. We used differential language analyses to compare the content and sentiment of tweets posted by legislators based on their party affiliation., Results: We found that health care-related themes in Democratic legislators' tweets focused on racial disparities in care (odds ratio [OR] 2.24, 95% CI 2.22-2.27; P<.001), health care and insurance (OR 1.74, 95% CI 1.7-1.77; P<.001), COVID-19 testing (OR 1.15, 95% CI 1.12-1.19; P<.001), and public health guidelines (OR 1.25, 95% CI 1.22-1.29; P<.001). The dominant themes in the Republican legislators' discourse included vaccine development (OR 1.51, 95% CI 1.47-1.55; P<.001) and hospital resources and equipment (OR 1.22, 95% CI 1.18-1.25). Nonhealth care-related topics associated with a Democratic affiliation included protections for essential workers (OR 1.55, 95% CI 1.52-1.59), the 2020 election and voting (OR 1.31, 95% CI 1.27-1.35), unemployment and housing (OR 1.27, 95% CI 1.24-1.31), crime and racism (OR 1.22, 95% CI 1.18-1.26), public town halls (OR 1.2, 95% CI 1.16-1.23), the Trump Administration (OR 1.22, 95% CI 1.19-1.26), immigration (OR 1.16, 95% CI 1.12-1.19), and the loss of life (OR 1.38, 95% CI 1.35-1.42). The themes associated with the Republican affiliation included China (OR 1.89, 95% CI 1.85-1.92), small business assistance (OR 1.27, 95% CI 1.23-1.3), congressional relief bills (OR 1.23, 95% CI 1.2-1.27), press briefings (OR 1.22, 95% CI 1.19-1.26), and economic recovery (OR 1.2, 95% CI 1.16-1.23)., Conclusions: Divergent language use on social media corresponds to the partisan divide in the first several months of the course of the COVID-19 public health crisis., (©Sharath Chandra Guntuku, Jonathan Purtle, Zachary F Meisel, Raina M Merchant, Anish Agarwal. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 03.06.2021.)