Ve čtvrtek 27. listopadu 2025 se v prostorách NEWTON Media uskutečnil odborný workshop pořádaný řešitelským týmem projektu Infoveillance – prevence proti in ...

Date Submitted: Aug 26, 2025. Open Peer Review Period: Sep 9, 2025 - Nov 4, 2025.

The complex interplay between sleep-related information—both accurate and misleading—and its impact on clinical public health is an emerging area of concern. Lack of awareness of the importance of sleep, and inadequate information related to sleep,…

This article traces the emergence of the research field “infodemiology” through the professional biography and influence of medical informatics scholar Gunther Eysenbach, from his 2002 coinage of the ...

This article traces the emergence of the research field “infodemiology” through the professional biography and influence of medical informatics scholar Gunther Eysenbach, from his 2002 coinage of the ...

This article traces the emergence of the research field “infodemiology” through the professional biography and influence of medical informatics scholar Gunther Eysenbach, from his 2002 coinage of the term “infodemiology” to the WHO’s framing of an “infodemic” during COVID-19. Methodologically grounded in an analogy between viruses and information, infodemiology examines the dynamics and public-health effects of (mis)information in digital media. Pursuing a historical-genealogical approach, I demonstrate how Eysenbach extended his early work on the “semantic web” into a broader program of “infoveillance,” increasingly oriented toward society-wide monitoring and intervention. I reconstruct crucial moments, including SARS (2003), H1N1 (2009), the rise of Web 2.0, and COVID-19, during which infodemiology became increasingly popularized. This genealogical study of infodemiology reflects a specific historical period in social media research, marked by comparatively permissive conditions for data scraping primarily using Twitter’s APIs. As Eysenbach and other infodemiologists continuously discussed and used digital contact tracing since the SARS-outbreak in 2003, this case study also analyzes infodemiology through the lens of Isin and Ruppert’s concept of “sensory power”. Deriving normative conclusions from my genealogical-historical findings, I argue that infodemiological approaches raise epistemological, political, and legal concerns since they take the analogy between viruses and information too far.

Digital infoveillance offers a complementary approach to early detection of zoonotic threats by analysing online signals, digital traces, and real-time data streams. However, current One Health sur...

Background Surveys are popular methods to measure public perceptions in emergencies but can be costly and time consuming. We suggest and evaluate a complementary “infoveillance” approach using Twitter during the 2009 H1N1 pandemic. Our study aimed to: 1) monitor the use of the terms “H1N1” versus “swine flu” over time; 2) conduct a content analysis of “tweets”; and 3) validate Twitter as a real-time content, sentiment, and public attention trend-tracking tool. Methodology/Principal Findings Between May 1 and December 31, 2009, we archived over 2 million Twitter posts containing keywords “swine flu,” “swineflu,” and/or “H1N1.” using Infovigil, an infoveillance system. Tweets using “H1N1” increased from 8.8% to 40.5% (R2 = .788; p<.001), indicating a gradual adoption of World Health Organization-recommended terminology. 5,395 tweets were randomly selected from 9 days, 4 weeks apart and coded using a tri-axial coding scheme. To track tweet content and to test the feasibility of automated coding, we created database queries for keywords and correlated these results with manual coding. Content analysis indicated resource-related posts were most commonly shared (52.6%). 4.5% of cases were identified as misinformation. News websites were the most popular sources (23.2%), while government and health agencies were linked only 1.5% of the time. 7/10 automated queries correlated with manual coding. Several Twitter activity peaks coincided with major news stories. Our results correlated well with H1N1 incidence data. Conclusions This study illustrates the potential of using social media to conduct “infodemiology” studies for public health. 2009 H1N1-related tweets were primarily used to disseminate information from credible sources, but were also a source of opinions and experiences. Tweets can be used for real-time content analysis and knowledge translation research, allowing health authorities to respond to public concerns.

Date Submitted: Apr 15, 2026. Open Peer Review Period: Apr 27, 2026 - Jun 22, 2026.

Date Submitted: Apr 15, 2026. Open Peer Review Period: Apr 27, 2026 - Jun 22, 2026.

... Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original ...

Background: Societies worldwide have witnessed growing rifts separating advocates and opponents of vaccinations and other COVID-19 countermeasures. With the rollout of vaccination campaigns, the European German-speaking region (Germany, Austria, and Switzerland) initially exhibited a noticeably low vaccination uptake compared to other European regions. Later, uptake increased. It remains unclear which factors contributed to these changes. Objective: This study aimed to shed light on the intricacies of vaccine hesitancy among the German-speaking population and the possible dynamics between policy changes and public concerns using web discourse data. These insights are valuable for policymakers tasked with making far-reaching decisions—policies need to effectively curb the spread of the virus and at the same time respect fundamental civil liberties and minimize undesired consequences. Methods: This study drew on data from Twitter (subsequently rebranded X). We used a hybrid pipeline to detect and analyze 191,750 German-language vaccination-related tweets using a semiautomatic seed list generation approach, topic modeling, sentiment analysis, and a minimum of social scientific domain knowledge to evaluate the discourse about vaccinations in light of the COVID-19 pandemic. We further analyzed the evolution of public attention during different phases of the pandemic and in relation to policy changes to identify potential drivers of shifts in public attention. Results: The discourse concerning vaccinations was associated with more negative sentiments than the general discourse on German-speaking Twitter (47,159/191,750, 24.59% vs 1,758,776/12,297,163, 14.3% predominantly negative tweets, respectively). The relative frequencies of the discussed themes fluctuated heavily (eg, safety and side effects was the most dominant theme in wave 3 [1,611/9,179, 17.55%] but ranked 6th in wave 5 [428/4,865, 8.8%], and effectiveness of vaccinations ranked 7th in wave 3 [711/9,179, 7.75%] and 2nd in wave 5 [831/4,865, 17.08%]). In wave 3, vaccines were authorized, and vaccinations were suspended and resumed due to safety concerns. Later, policies were implemented that restricted the freedom of unvaccinated citizens. Change points in attention aligned better with policy actions than with pandemic phases. During the later phases, vaccination uptake increased (wave 2: 5.6%, wave 3: 47%, and wave 5: 74% compared to 30%, 62%, and 78%, respectively, in the United Kingdom), and so did the attention to freedom and civil liberties (wave 2: 1,139/6,595, 17.27%; wave 5: 1,403/4,865, 28.84%). Substantially increasing negative and stronger sentiments were expressed. Conclusions: Our analyses suggest potential interactions among policies, public attention to different topics, and associated sentiments. While vaccination uptake increased, our findings indicate that citizens’ doubts and concerns did not decrease and that, rather than being fully persuaded, they remained skeptical. This study showcases that monitoring web discourse can provide valuable insights for data-driven policymaking in highly dynamic contexts such as the COVID-19 pandemic.

Date Submitted: Aug 26, 2025. Open Peer Review Period: Sep 9, 2025 - Nov 4, 2025.

Background: The effect of the #COVID19 #coronavirus pandemic on the well-being of dental professionals and ##Patients has been difficult to track and quantify. X (formerly known as #Twitter) proved to be a useful infoveillance tool for tracing the impact of the #COVID19 #coronavirus pandemic worldwide. Objective: This #Study aims to investigate the use of X to track #COVID19 #coronavirus infections and deaths associated with dental practices. Methods: English #Tweets reporting infections or deaths associated with the dental practice were collected from January 1, 2020, to March 31, 2021. #Tweets were searched manually using the X Pro search engine (previously known as #TweetDeck [X Corp], #Twitter Inc, and #TweetDeck Ltd) and automatically using a #Tweet crawler on the X Academic #Research application programming interface. Queries included keywords on infection or death of dental staff and ##Patients caused by #COVID19 #coronavirus. #Tweets registering events on infection or death of dentists, dental staff, and ##Patients as part of their conversation were included. Results: A total of 5641 eligible #Tweets were retrieved. Of which 1583 (28.1%) were deemed relevant after applying the inclusion and exclusion criteria. Of the relevant #Tweets, 311 (19.6%) described infections at dental practices, where 1168 (86.9%) infection cases were reported among dentists, 134 (9.9%) dental staff, and 41 (3.1%) ##Patients. The majority of reported infections occurred in the United States, India, and Canada, affecting individuals aged 20-51 years. Among the 600 documented deaths, 253 (42.2%) were dentists, 22 (3.7%) were dental staff, and 7 (1.2%) were ##Patients. The countries with the highest number of deaths were the United States, Pakistan, and India, with an affected age range of 23-83 years. Conclusions: The data suggest that analyses of X information in populations of affected areas may provide useful information regarding the impact of a pandemic on the dental profession and demonstrate a correlation with suspected and confirmed infection or death cases. Platform X shows potential as an early predictor for #Disease spread. However, further #Research is required to confirm its validity.

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WhatsApp, COVID-19 Related Misinformation in Africa and the Need for Continuous Infoveillance By Chidindu C. Mmadu-Okoli, Nigeria Centre for Disease Control, Abuja, FCT, Nigeria Dr. Ifeanyi M. Nsofor, EpiAfric, Abuja, FCT, Nigeria Facebook Twitter LinkedIn Citation Mmadu-Okoli C, Nsofor Ifeanyi. WhatsApp, COVID-19 related misinformation in Africa and the need for continuous infoveillance. HPHR. 2021;39. 10.54111/0001/MM8 […]