scholarly journals Infodemic Signals Detection in the COVID-19 Pandemic: A Methodology for Identifying Potential Information Voids in Online Conversations (Preprint)

2021 ◽  
Author(s):  
Tina D Purnat ◽  
Paolo Vacca ◽  
Christine Czerniak ◽  
Sarah Ball ◽  
Stefano Burzo ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Public Health Response ◽  
Effective Response ◽  
Aggregated Data ◽  
Health Response ◽  
Online Conversations ◽  
Social Media Platforms ◽  
Over Time ◽  
Social Listening

BACKGROUND The COVID-19 pandemic has been accompanied by an information epidemic or “infodemic”: too much information including false or misleading information in digital and physical environments during an acute public health event, which leads to confusion, risk-taking and behaviors that can harm health, and lead to mistrust in health authorities and public health response. The analytical method described is part of the WHO work to develop tools for an evidence-based response to the infodemic, enabling prioritization of health response activities. OBJECTIVE The aim of this work was to develop a practical, structured approach to identifying narratives in public online conversations on social media platforms where concerns or confusion exist or where narratives are gaining traction, and to provide actionable data to help WHO prioritize its risk communications efforts where it is most critical in addressing the COVID-19 infodemic. METHODS We developed a taxonomy to filter global COVID-19 public online conversations in social media content in English and French into five themes, with 35 sub themes. The taxonomy and its implementation were validated for retrieval precision and retrieval recall, and reviewed and adapted as the linguistic expression about the pandemic in online conversations changed over time. The aggregated data were analyzed for each sub themes by volume, velocity and the presence of questions, on a weekly basis, to detect signals of information voids where there was potential for confusion or for mis- or dis-information to thrive. A human analyst reviewed the themes for potential information voids and used quantitative data to provide context and insight on narratives, influencers and public reactions. RESULTS A COVID-19 public health social listening taxonomy was developed and applied. A weekly analysis of public online conversations since 23 March 2020 has enabled the quantification of shifts of public interest in public health-related topics concerning the pandemic and has demonstrated the frequent resumption of information voids with verified health information. This approach therefore focuses on infodemic signal detection for actionable intelligence to rapidly inform decision-making for a more effective response, including adapting risk communication. CONCLUSIONS This approach been successfully applied during the COVID-19 pandemic to identify and take action on information voids based on analysis of infodemic signals. More broadly, the results have demonstrated the importance of ongoing monitoring and analysis of public online conversations, as information voids frequently resume and narratives shift over time. The approach is already being piloted in individual countries and WHO regions to generate localized insights and actions, while a pilot of an AI social listening platform is using this taxonomy to aggregate and compare online conversations across 20 countries. Looking beyond the COVID-19 pandemic, the taxonomy and methodology have the potential to be adapted for fast deployment in future public health events.

scholarly journals Infodemic Signal Detection During the COVID-19 Pandemic: Development of a Methodology for Identifying Potential Information Voids in Online Conversations

10.2196/30971 ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. e30971
Author(s):  
Tina D Purnat ◽  
Paolo Vacca ◽  
Christine Czerniak ◽  
Sarah Ball ◽  
Stefano Burzo ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
World Health ◽  
Aggregated Data ◽  
Response Planning ◽  
Online Conversations ◽  
Social Media Platforms ◽  
Health Organization ◽  
Over Time ◽  
Social Listening

Background The COVID-19 pandemic has been accompanied by an infodemic: excess information, including false or misleading information, in digital and physical environments during an acute public health event. This infodemic is leading to confusion and risk-taking behaviors that can be harmful to health, as well as to mistrust in health authorities and public health responses. The World Health Organization (WHO) is working to develop tools to provide an evidence-based response to the infodemic, enabling prioritization of health response activities. Objective In this work, we aimed to develop a practical, structured approach to identify narratives in public online conversations on social media platforms where concerns or confusion exist or where narratives are gaining traction, thus providing actionable data to help the WHO prioritize its response efforts to address the COVID-19 infodemic. Methods We developed a taxonomy to filter global public conversations in English and French related to COVID-19 on social media into 5 categories with 35 subcategories. The taxonomy and its implementation were validated for retrieval precision and recall, and they were reviewed and adapted as language about the pandemic in online conversations changed over time. The aggregated data for each subcategory were analyzed on a weekly basis by volume, velocity, and presence of questions to detect signals of information voids with potential for confusion or where mis- or disinformation may thrive. A human analyst reviewed and identified potential information voids and sources of confusion, and quantitative data were used to provide insights on emerging narratives, influencers, and public reactions to COVID-19–related topics. Results A COVID-19 public health social listening taxonomy was developed, validated, and applied to filter relevant content for more focused analysis. A weekly analysis of public online conversations since March 23, 2020, enabled quantification of shifting interests in public health–related topics concerning the pandemic, and the analysis demonstrated recurring voids of verified health information. This approach therefore focuses on the detection of infodemic signals to generate actionable insights to rapidly inform decision-making for a more targeted and adaptive response, including risk communication. Conclusions This approach has been successfully applied to identify and analyze infodemic signals, particularly information voids, to inform the COVID-19 pandemic response. More broadly, the results have demonstrated the importance of ongoing monitoring and analysis of public online conversations, as information voids frequently recur and narratives shift over time. The approach is being piloted in individual countries and WHO regions to generate localized insights and actions; meanwhile, a pilot of an artificial intelligence–based social listening platform is using this taxonomy to aggregate and compare online conversations across 20 countries. Beyond the COVID-19 pandemic, the taxonomy and methodology may be adapted for fast deployment in future public health events, and they could form the basis of a routine social listening program for health preparedness and response planning.

scholarly journals Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study (Preprint)

2020 ◽  
Author(s):  
Monika Pobiruchin ◽  
Richard Zowalla ◽  
Martin Wiesner
Keyword(s):  
Public Health ◽  
Social Media ◽  
Media Coverage ◽  
Relative Proportion ◽  
World Health ◽  
Shared Resources ◽  
Public Health Response ◽  
External Resources ◽  
Geographical Variations ◽  
Social Media Platforms

BACKGROUND The spread of the 2019 novel coronavirus disease, COVID-19, across Asia and Europe sparked a significant increase in public interest and media coverage, including on social media platforms such as Twitter. In this context, the origin of information plays a central role in the dissemination of evidence-based information about the SARS-CoV-2 virus and COVID-19. On February 2, 2020, the World Health Organization (WHO) constituted a “massive infodemic” and argued that this situation “makes it hard for people to find trustworthy sources and reliable guidance when they need it.” OBJECTIVE This <i>infoveillance</i> study, conducted during the early phase of the COVID-19 pandemic, focuses on the social media platform Twitter. It allows monitoring of the dynamic pandemic situation on a global scale for different aspects and topics, languages, as well as regions and even whole countries. Of particular interest are temporal and geographical variations of COVID-19–related tweets, the situation in Europe, and the categories and origin of shared external resources. METHODS Twitter’s Streaming application programming interface was used to filter tweets based on 16 prevalent hashtags related to the COVID-19 outbreak. Each tweet’s text and corresponding metadata as well as the user’s profile information were extracted and stored into a database. Metadata included links to external resources. A link categorization scheme—introduced in a study by Chew and Eysenbach in 2009—was applied onto the top 250 shared resources to analyze the relative proportion for each category. Moreover, temporal variations of global tweet volumes were analyzed and a specific analysis was conducted for the European region. RESULTS Between February 9 and April 11, 2020, a total of 21,755,802 distinct tweets were collected, posted by 4,809,842 distinct Twitter accounts. The volume of #covid19-related tweets increased after the WHO announced the name of the new disease on February 11, 2020, and stabilized at the end of March at a high level. For the regional analysis, a higher tweet volume was observed in the vicinity of major European capitals or in densely populated areas. The most frequently shared resources originated from various social media platforms (ranks 1-7). The most prevalent category in the top 50 was “Mainstream or Local News.” For the category “Government or Public Health,” only two information sources were found in the top 50: US Centers for Disease Control and Prevention at rank 25 and the WHO at rank 27. The first occurrence of a prevalent scientific source was Nature (rank 116). CONCLUSIONS The naming of the disease by the WHO was a major signal to address the public audience with public health response via social media platforms such as Twitter. Future studies should focus on the origin and trustworthiness of shared resources, as monitoring the spread of fake news during a pandemic situation is of particular importance. In addition, it would be beneficial to analyze and uncover bot networks spreading COVID-19–related misinformation.

scholarly journals Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19–Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study

10.2196/19629 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e19629
Author(s):  
Monika Pobiruchin ◽  
Richard Zowalla ◽  
Martin Wiesner
Keyword(s):  
Public Health ◽  
Social Media ◽  
Media Coverage ◽  
Relative Proportion ◽  
World Health ◽  
Shared Resources ◽  
Public Health Response ◽  
External Resources ◽  
Geographical Variations ◽  
Social Media Platforms

Background The spread of the 2019 novel coronavirus disease, COVID-19, across Asia and Europe sparked a significant increase in public interest and media coverage, including on social media platforms such as Twitter. In this context, the origin of information plays a central role in the dissemination of evidence-based information about the SARS-CoV-2 virus and COVID-19. On February 2, 2020, the World Health Organization (WHO) constituted a “massive infodemic” and argued that this situation “makes it hard for people to find trustworthy sources and reliable guidance when they need it.” Objective This infoveillance study, conducted during the early phase of the COVID-19 pandemic, focuses on the social media platform Twitter. It allows monitoring of the dynamic pandemic situation on a global scale for different aspects and topics, languages, as well as regions and even whole countries. Of particular interest are temporal and geographical variations of COVID-19–related tweets, the situation in Europe, and the categories and origin of shared external resources. Methods Twitter’s Streaming application programming interface was used to filter tweets based on 16 prevalent hashtags related to the COVID-19 outbreak. Each tweet’s text and corresponding metadata as well as the user’s profile information were extracted and stored into a database. Metadata included links to external resources. A link categorization scheme—introduced in a study by Chew and Eysenbach in 2009—was applied onto the top 250 shared resources to analyze the relative proportion for each category. Moreover, temporal variations of global tweet volumes were analyzed and a specific analysis was conducted for the European region. Results Between February 9 and April 11, 2020, a total of 21,755,802 distinct tweets were collected, posted by 4,809,842 distinct Twitter accounts. The volume of #covid19-related tweets increased after the WHO announced the name of the new disease on February 11, 2020, and stabilized at the end of March at a high level. For the regional analysis, a higher tweet volume was observed in the vicinity of major European capitals or in densely populated areas. The most frequently shared resources originated from various social media platforms (ranks 1-7). The most prevalent category in the top 50 was “Mainstream or Local News.” For the category “Government or Public Health,” only two information sources were found in the top 50: US Centers for Disease Control and Prevention at rank 25 and the WHO at rank 27. The first occurrence of a prevalent scientific source was Nature (rank 116). Conclusions The naming of the disease by the WHO was a major signal to address the public audience with public health response via social media platforms such as Twitter. Future studies should focus on the origin and trustworthiness of shared resources, as monitoring the spread of fake news during a pandemic situation is of particular importance. In addition, it would be beneficial to analyze and uncover bot networks spreading COVID-19–related misinformation.

Sexuality and public health

2021 ◽  
pp. 307-316
Author(s):  
Richard Parker ◽  
Jonathan Garcia ◽  
Miguel Muñoz-Laboy ◽  
Marni Sommer ◽  
Patrick Wilson
Keyword(s):  
Public Health ◽  
Sexual Health ◽  
Well Being ◽  
Hiv And Aids ◽  
Health It ◽  
Public Health Response ◽  
International Agencies ◽  
Health Response ◽  
Health And Well Being ◽  
Over Time

This chapter seeks to provide an overview of this rapidly growing body of work in public health. It describes the initial public health response to sexuality in the context of HIV and AIDS, as well as the ways in which that response has been gradually broadened over time in order to provide a more comprehensive approach to sexual health and well-being. It also focuses on both the local and the global dimensions of this work, in both developed and developing countries, and as much in the work of local communities struggling to respond to the needs of their own populations, as well as on the part of a range of international agencies that are increasingly seeking to address a range of challenges to sexual health.

Formulate Evaluation Questions (Step 2)

2019 ◽  
pp. 73-80
Author(s):  
Edmund M. Ricci ◽  
Ernesto A. Pretto ◽  
Knut Ole Sundnes
Keyword(s):  
Public Health ◽  
Disaster Response ◽  
Evaluation Study ◽  
Logic Model ◽  
Public Health Response ◽  
Evaluation Team ◽  
Medical Response ◽  
Model Following ◽  
Health Response ◽  
Over Time

In this chapter we define the five basic categories of evaluation, namely structure (resources), process (activities), outcomes, adequacy, and costs associated with the response(s). Structure refers to the equipment and personnel and the way in which these resources were organized for use in the medical response. Process refers to the activities carried out during the disaster response. Outcome assessment concerns the results of the care provided on the patients served, usually measured over time. Adequacy describes the extent to which the search-and-rescue, pre-hospital and hospital, and public health responses were able to meet the needs of the community during the disaster response. In general, these categories are consistent with the design of a typical logic model. Following the discussion of ‘evaluation categories’ we suggest questions that the evaluation team might consider for inclusion in the evaluation study. For each category we suggest questions which could be addressed in any disaster evaluation study which focuses on the medical and public health response. The stakeholder group should be fully involved in the selection of questions to be addressed by the evaluation team.

scholarly journals Social media in Ebola outbreak

2016 ◽  
Vol 144 (10) ◽  
pp. 2136-2143 ◽  
Author(s):  
L. HOSSAIN ◽  
D. KAM ◽  
F. KONG ◽  
R. T. WIGAND ◽  
T. BOSSOMAIER
Keyword(s):  
Public Health ◽  
Social Media ◽  
Ad Hoc ◽  
Media Use ◽  
Emerging Diseases ◽  
Public Health Response ◽  
Social Media Use ◽  
The Public ◽  
Health Response ◽  
Media Reports

SUMMARYThe West African 2014 Ebola outbreak has highlighted the need for a better information network. Hybrid information networks, an integration of both hierarchical and formalized command control-driven and community-based, orad hocemerging networks, could assist in improving public health responses. By filling the missing gaps with social media use, the public health response could be more proactive rather than reactive in responding to such an outbreak of global concern. This article provides a review of the current social media use specifically in this outbreak by systematically collecting data from ProQuest Newsstand, Dow Jones Factiva, Program for Monitoring Emerging Diseases (ProMED) as well as Google Trends. The period studied is from 19 March 2014 (first request for information on ProMED) to 15 October 2014, a total of 31 weeks. The term ‘Ebola’ was used in the search for media reports. The outcome of the review shows positive results for social media use in effective surveillance response mechanisms – for improving the detection, preparedness and response of the outbreak – as a complement to traditional, filed, work-based surveillance approach.

You're not alone: A public health response to immigrant/refugee distress in the current sociopolitical context.

2020 ◽  
Vol 17 (S1) ◽  
pp. 128-138 ◽  
Author(s):  
Rebecca E. Ford-Paz ◽  
Catherine DeCarlo Santiago ◽  
Claire A. Coyne ◽  
Claudio Rivera ◽  
Sisi Guo ◽  
...  
Keyword(s):  
Public Health ◽  
Public Health Response ◽  
Health Response ◽  
Sociopolitical Context
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