Expressions of pandemic fatigue on digital platforms: a thematic analysis of sentiment and narratives for infodemic insights.

BACKGROUND: The infodemic accompanying the COVID-19 pandemic has led to an overwhelming amount of information, including questions, concerns and misinformation. Pandemic fatigue has been identified as a concern from early in the pandemic. With new and ongoing health emergencies in 2022, it is important to understand how pandemic fatigue is being discussed and expressed by users on digital channels. This study aims to explore and report on key narrative themes associated with expressions of pandemic fatigue by users on digital platforms. METHODS: This paper describes the collection of publicly available data over a 3-month period from multiple online sources using the Meltwater and CrowdTangle platforms to source data from Twitter, Facebook, Instagram, YouTube, TikTok, Pinterest, Product Reviews, Twitch, blogs & forums. A comprehensive search strategy was developed and tested. A total of 1,484,042 social media posts were identified during the time-period that included the defined search terms for pandemic fatigue. These data were initially sorted by highest levels of engagement and from this dataset, analysts reviewed the identified posts to isolate and remove irrelevant content and identify dominant narratives. A thematic analysis was carried out on these narratives to identify themes related to expression of pandemic fatigue. Two researchers reviewed the data and themes. RESULTS: The thematic analysis of narratives identified six main themes relating to expression of pandemic fatigue, and one theme of counter narratives against pandemic fatigue. Data volume increased concurrent with the time of the mpox emergency announcement. Emergent themes showed the different ways users expressed pandemic fatigue and how it was interlaced with issues of trust, preventative measure acceptance and uptake, misinformation, and being overwhelmed with multiple or sustained emergencies. CONCLUSIONS: This paper has identified the different ways users express pandemic fatigue on digital channels over a 3-month period. Better understanding the implications of the information environment on user's perceptions, questions, and concerns regarding pandemic and more broadly emergency fatigue is vital in identifying relevant interventions and, in the longer term, strengthening the global architecture for health emergency preparedness, prevention, readiness and resilience, as evidenced in this paper. There are clear pathways for further research, including incorporating additional languages and reviewing these themes over longer time periods.

Building a Chatbot in a Pandemic.

Easy access to evidence-based information on COVID-19 within an infodemic has been a challenging task. Chatbots have been introduced in times of emergency, when human resources are stretched thin and individuals need a user-centered resource. The World Health Organization Regional Office for Europe and UNICEF (United Nations Children's Fund) Europe and Central Asia came together to build a chatbot, HealthBuddy+, to assist country populations in the region to access accurate COVID-19 information in the local languages, adapted to the country context. Working in close collaboration with thematic technical experts, colleagues and counterparts at the country level allowed the project to be tailored to a diverse range of subtopics. To ensure that HealthBuddy+ was relevant and useful in countries across the region, the 2 regional offices worked closely with their counterparts in country offices, which were essential in partnering with national authorities, engaging communities, promoting the tool, and identifying the most relevant communication channels in which to embed HealthBuddy+. Over the past 2 years, the project has expanded from a web-based chatbot in 7 languages to a multistream, multifunction chatbot available in 16 regional languages, and HealthBuddy+ continues to expand and adjust to meet emerging health emergency needs.

Expansion of the 'Antibiotic Guardian' one health behavioural campaign across Europe to tackle antibiotic resistance: pilot phase and analysis of AMR knowledge.

Antimicrobial resistance (AMR) is a major public health threat. The UK Antibiotic Guardian (AG) behavioural change campaign developed to tackle AMR was expanded across Europe through translation into Russian, Dutch and French. Demographics and knowledge of AGs were analyzed between 01 November 2016 and 31 December 2016. A total of 367 pledges were received with the majority from the public and health care professionals. The pilot has significantly increased the proportion of pledges from Europe (excluding UK) (χ2 = 108.7, P < 0.001). AMR knowledge was greater in AGs (including the public) compared to the EU Eurobarometer survey. Further promotion across Europe is required to measure an impact on tackling AMR.

How to increase COVID-19 vaccination among a population with persistently suboptimal vaccine uptake? Evidence from the North Macedonia mobile vaccination and public health advice caravan.

Over three years since the first COVID-19 vaccine was approved, many countries still have suboptimal vaccination rates despite holding great amounts of vaccines. Overall, there is little evidence on which policies are more effective to encourage vaccination, particularly in countries where a large share of the population remains unvaccinated. In this study, we examine the effectiveness of a community-based intervention carried out in March 2022 in North Macedonia, a country with a large and persistent share of the population that remains unvaccinated. The intervention, spearheaded by the Ministry of Health and supported by the World Health Organization and UNICEF, consisted of a mobile caravan offering vaccination and public health advice to different locations across the country on different days. Results from our staggered difference-in-difference model show that the mobile vaccination caravan increased daily vaccination rates by 7.7 vaccines per 100,000 inhabitants during the three weeks after the day of the caravan visit. This corresponds to a 35 % increase with respect to pre-intervention vaccination rates. We estimate a cost-effectiveness of 25.4 US dollars (USD) per additional vaccination induced. These results point to mobile caravan vaccines as an effective and cost-effective strategy to increase COVID-19 vaccination rates, even in a context of persistently suboptimal uptake.

Using Machine Learning Technology (Early Artificial Intelligence-Supported Response With Social Listening Platform) to Enhance Digital Social Understanding for the COVID-19 Infodemic: Development and Implementation Study.

BACKGROUND: Amid the COVID-19 pandemic, there has been a need for rapid social understanding to inform infodemic management and response. Although social media analysis platforms have traditionally been designed for commercial brands for marketing and sales purposes, they have been underused and adapted for a comprehensive understanding of social dynamics in areas such as public health. Traditional systems have challenges for public health use, and new tools and innovative methods are required. The World Health Organization Early Artificial Intelligence-Supported Response with Social Listening (EARS) platform was developed to overcome some of these challenges. OBJECTIVE: This paper describes the development of the EARS platform, including data sourcing, development, and validation of a machine learning categorization approach, as well as the results from the pilot study. METHODS: Data for EARS are collected daily from web-based conversations in publicly available sources in 9 languages. Public health and social media experts developed a taxonomy to categorize COVID-19 narratives into 5 relevant main categories and 41 subcategories. We developed a semisupervised machine learning algorithm to categorize social media posts into categories and various filters. To validate the results obtained by the machine learning-based approach, we compared it to a search-filter approach, applying Boolean queries with the same amount of information and measured the recall and precision. Hotelling T2 was used to determine the effect of the classification method on the combined variables. RESULTS: The EARS platform was developed, validated, and applied to characterize conversations regarding COVID-19 since December 2020. A total of 215,469,045 social posts were collected for processing from December 2020 to February 2022. The machine learning algorithm outperformed the Boolean search filters method for precision and recall in both English and Spanish languages (P<.001). Demographic and other filters provided useful insights on data, and the gender split of users in the platform was largely consistent with population-level data on social media use. CONCLUSIONS: The EARS platform was developed to address the changing needs of public health analysts during the COVID-19 pandemic. The application of public health taxonomy and artificial intelligence technology to a user-friendly social listening platform, accessible directly by analysts, is a significant step in better enabling understanding of global narratives. The platform was designed for scalability; iterations and new countries and languages have been added. This research has shown that a machine learning approach is more accurate than using only keywords and has the benefit of categorizing and understanding large amounts of digital social data during an infodemic. Further technical developments are needed and planned for continuous improvements, to meet the challenges in the generation of infodemic insights from social media for infodemic managers and public health professionals.

Risk Communication and Community Engagement in Action During Ukraine's War.

In the light of recent emergencies in Europe and around the globe-including COVID-19 and the war in Ukraine-the spotlight has shifted towards the scarcity of Risk Communication and Community Engagement (RCCE) research applied to health emergencies. RCCE nurtures the sense of empowerment among communities since it ensures that individuals and communities are part of the solution creation, thus they take informed decisions to protect their health and in turn, contribute to emergency control. Therefore, RCCE can play an important role as core public health intervention across health emergency preparedness and response. However, its tremendous impact, is still underestimated and not widely common. This viewpoint showcases the RCCE measures applied to the Ukrainian emergency to ensure that Ukrainian refugees access health services in host countries, based on their needs and concerns.

Ten considerations for effectively managing the COVID-19 transition.

Governments around the world have implemented measures to manage the transmission of coronavirus disease 2019 (COVID-19). While the majority of these measures are proving effective, they have a high social and economic cost, and response strategies are being adjusted. The World Health Organization (WHO) recommends that communities should have a voice, be informed and engaged, and participate in this transition phase. We propose ten considerations to support this principle: (1) implement a phased approach to a 'new normal'; (2) balance individual rights with the social good; (3) prioritise people at highest risk of negative consequences; (4) provide special support for healthcare workers and care staff; (5) build, strengthen and maintain trust; (6) enlist existing social norms and foster healthy new norms; (7) increase resilience and self-efficacy; (8) use clear and positive language; (9) anticipate and manage misinformation; and (10) engage with media outlets. The transition phase should also be informed by real-time data according to which governmental responses should be updated.