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Background: With the outbreak of the SARS-CoV-2 pandemic, the uncertainty about the real impact of coinfection with other viruses, and the increased risk of mortality in the case of coinfection with the influenza virus, health authorities recommended an increase in influenza vaccination coverage among at-risk groups to minimize the possible impact on individuals and the healthcare system. Recommendations for influenza vaccination during the 2020-2021 campaign in Catalonia were focused on increasing vaccination coverage, especially for social and healthcare workers, elderly people and at-risk individuals of any age. The objectives for the 2020-2021 season in Catalonia were to reach 75 % for the elderly and for social and healthcare workers, and 60 % for pregnant women and at-risk groups. In the case of healthcare professionals and those over 65 years of age, the target was not met. Vaccination coverage reached 65.58 % and 66.44 %, respectively (in the 2019-2020 campaign it was 39.08 %).Analysing and following up on the background and context in which health professionals accept influenza vaccination will help develop strategies for long-term influenza vaccination campaigns. The present study looks at healthcare professionals in a specific territory where the reasons for acceptance or refusal of the influenza vaccine during the 2021-2022 vaccination campaign, as well as the reasons for acceptance or refusal of the COVID-19 vaccine, were analysed by means of an online survey. Methods: Calculations suggested that a random sample of 290 individuals would be sufficient to estimate, with 95% confidence and a precision of +/- 5 percentage units, a population percentage that was expected to be around 30%. The required replacement rate was 10%.The R statistical software (version 3.6.3) was used for the statistical analysis. Confidence intervals were 95 % and contrasts with a p-value of < 0.05 were considered significant. Findings: Of the 1921 professionals to whom the survey was sent, 586 (30.5%) responded to all the questions. 95.2% of respondents were vaccinated against COVID-19 and 66.2% against influenza.It was observed that the relationship between sociodemographic characteristics and the decision to get vaccinated was different for influenza and COVID-19. The reasons for accepting the COVID-19 vaccine with the highest percentage were firstly protecting family (82.2%), self-protection (74.9%) and also protecting patients (57.8%). Otherwise, other reasons not described in the survey (50%) and mistrust (42.3%) were the reasons for rejecting the COVID-19 vaccine.Regarding influenza, the most relevant reasons for which professionals got vaccinated were self-protection (70.7%), protecting family (69.7%) and protecting patients (58.4%). Reasons for refusing the influenza vaccine were reasons not mentioned in the survey (29.1%) and the low probability of suffering complications (27.4%). Interpretation: Analysing the context, territory, sector, and the reasons for both accepting and refusing a vaccine will help develop effective strategies. Although vaccination coverage against COVID-19 was very high throughout Spain, a marked increase in influenza vaccination in the context of COVID-19 was observed among healthcare professionals in the Central Catalonia region compared to the previous pre-pandemic campaign.
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BACKGROUND: The popularity of the magnetic vaccine conspiracy theory and other conspiracy theories of a similar nature creates challenges to promoting vaccines and disseminating accurate health information. OBJECTIVE: Health conspiracy theories are gaining in popularity. This study's objective was to evaluate the Twitter social media network related to the magnetic vaccine conspiracy theory and apply social capital theory to analyze the unique social structures of influential users. As a strategy for web-based public health surveillance, we conducted a social network analysis to identify the important opinion leaders sharing the conspiracy, the key websites, and the narratives. METHODS: A total of 18,706 tweets were retrieved and analyzed by using social network analysis. Data were retrieved from June 1 to June 13, 2021, using the keyword vaccine magnetic. Tweets were retrieved via a dedicated Twitter application programming interface. More specifically, the Academic Track application programming interface was used, and the data were analyzed by using NodeXL Pro (Social Media Research Foundation) and Gephi. RESULTS: There were a total of 22,762 connections between Twitter users within the data set. This study found that the most influential user within the network consisted of a news account that was reporting on the magnetic vaccine conspiracy. There were also several other users that became influential, such as an epidemiologist, a health economist, and a retired sports athlete who exerted their social capital within the network. CONCLUSIONS: Our study found that influential users were effective broadcasters against the conspiracy, and their reach extended beyond their own networks of Twitter followers. We emphasize the need for trust in influential users with regard to health information, particularly in the context of the widespread social uncertainty resulting from the COVID-19 pandemic, when public sentiment on social media may be unpredictable. This study highlights the potential of influential users to disrupt information flows of conspiracy theories via their unique social capital.
Subject(s)
COVID-19 , Social Media , Vaccines , Humans , Pandemics , Social Network Analysis , Magnetic PhenomenaABSTRACT
BACKGROUND: COVID-19 pandemic has revealed the weaknesses of most health systems around the world, collapsing them and depleting their available health care resources. Fortunately, the development and enforcement of specific public health policies, such as vaccination, mask wearing, and social distancing, among others, has reduced the prevalence and complications associated with COVID-19 in its acute phase. However, the aftermath of the global pandemic has called for an efficient approach to manage patients with long COVID-19. This is a great opportunity to leverage on innovative digital health solutions to provide exhausted health care systems with the most cost-effective and efficient tools available to support the clinical management of this population. In this context, the SENSING-AI project is focused on the research toward the implementation of an artificial intelligence-driven digital health solution that supports both the adaptive self-management of people living with long COVID-19 and the health care staff in charge of the management and follow-up of this population. OBJECTIVE: The objective of this protocol is the prospective collection of psychometric and biometric data from 10 patients for training algorithms and prediction models to complement the SENSING-AI cohort. METHODS: Publicly available health and lifestyle data registries will be consulted and complemented with a retrospective cohort of anonymized data collected from clinical information of patients diagnosed with long COVID-19. Furthermore, a prospective patient-generated data set will be captured using wearable devices and validated patient-reported outcomes questionnaires to complement the retrospective cohort. Finally, the 'Findability, Accessibility, Interoperability, and Reuse' guiding principles for scientific data management and stewardship will be applied to the resulting data set to encourage the continuous process of discovery, evaluation, and reuse of information for the research community at large. RESULTS: The SENSING-AI cohort is expected to be completed during 2022. It is expected that sufficient data will be obtained to generate artificial intelligence models based on behavior change and mental well-being techniques to improve patients' self-management, while providing useful and timely clinical decision support services to health care professionals based on risk stratification models and early detection of exacerbations. CONCLUSIONS: SENSING-AI focuses on obtaining high-quality data of patients with long COVID-19 during their daily life. Supporting these patients is of paramount importance in the current pandemic situation, including supporting their health care professionals in a cost-effective and efficient management of long COVID-19. TRIAL REGISTRATION: Clinicaltrials.gov NCT05204615; https://clinicaltrials.gov/ct2/show/NCT05204615. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37704.
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BACKGROUND: Vaccination is one of the most successful public health interventions for the prevention of COVID-19. Toward the end of April 2021, UNICEF (United Nations International Children's Emergency Fund), alongside other organizations, were promoting the hashtag #VaccinesWork. OBJECTIVE: The aim of this paper is to analyze the #VaccinesWork hashtag on Twitter in the context of the COVID-19 pandemic, analyzing the main messages shared and the organizations involved. METHODS: The data set used in this study consists of 11,085 tweets containing the #VaccinesWork hashtag from the 29th to the 30th of April 2021. The data set includes tweets that may not have the hashtag but were replies or mentions in those tweets. The data were retrieved using NodeXL, and the network graph was laid out using the Harel-Koren fast multiscale layout algorithm. RESULTS: The study found that organizations such as the World Health Organization, UNICEF, and Gavi were the key opinion leaders and had a big influence on the spread of information among users. Furthermore, the most shared URLs belonged to academic journals with a high impact factor. Provaccination users had other vaccination-promoting hashtags in common, not only in the COVID-19 scenario. CONCLUSIONS: This study investigated the discussions surrounding the #VaccinesWork hashtag. Social media networks containing conspiracy theories tend to contain dubious accounts leading the discussions and are often linked to unverified information. This kind of analysis can be useful to detect the optimal moment for launching health campaigns on Twitter.
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COVID-19 , Social Media , Child , Humans , Pandemics , Social Networking , Public HealthABSTRACT
Aim: To review the available evidence on asynchronous communication models between primary care professionals and patients in different countries around the world in order to analyse the added value that this model brings to patients and professionals. Design: A rapid literature review was conducted using the World Health Organisation guidance to include a variety of studies on the concept of asynchronous communications between primary care and patients in different countries. Data sources: The search for articles was carried out in PubMed and Google Academics and with the contribution of telemedicine experts from the Catalan Institute of Health. Selection of studies: The review included 271 articles. The inclusion criteria were: publications from 2010 onwards, in English, Spanish or Catalan, focused on asynchronous communications between primary care professionals and patients to improve patient management. After discarding duplicates and applying the exclusion criteria (255 articles), 16 were included for further review. Data extraction: The rapid literature review was conducted by an evaluator; detecting 5 main general themes: reduction of face-to-face visits, available services and most frequent uses, characteristics and perceptions of primary care professionals, characteristics and perceptions of users, and barriers and facilitators for the implementation of asynchronous teleconsultation. Results: A total of sixteen studies were included, including seven quantitative studies, seven qualitative studies and two mixed studies. Conclusions: The high degree of satisfaction of both users and professionals, the outbreak of COVID-19 and the effectiveness and efficiency of asynchronous remote communications are key factors for the implementation and improvement in the management of the different healthcare systems across the world.
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Influenza vaccination is the main measure of prevention against epidemic flu. Although recommended, vaccination coverage remains low. The lack of knowledge about the evolution of influenza in the context of the SARS-CoV-2 coronavirus pandemic led to the recommendation of influenza vaccination to people at risk and professionals to avoid a greater burden than the one already posed by SARS-CoV-2. The aim of the study is to determine health professionals' intention to vaccinate against seasonal flu in the 2020-2021 campaign, in the context of the SARS-CoV-2 pandemic, and to analyse the factors that influence it. Cross-sectional study through a structured survey aimed at Primary Care professionals in Central Catalonia. A total of 610 participants responded to the survey, 65.7% of whom intended to get vaccinated against influenza in this campaign, and 11.1% did not know or did not answer. The intention to get vaccinated is associated with the professional category and the number of years of professional practice. The profile of the professionals who intend to get vaccinated against flu includes professionals with a history of vaccination, who participate in on-call duties and perceive that their dependents were at risk of becoming ill. During the SARS-CoV-2 pandemic, although almost two-thirds of the respondents showed a clear intention to get vaccinated against influenza, 11% were doubtful. To improve influenza vaccination uptake among health professionals, strategies need to be devised to target those professionals who are hesitant or reluctant to vaccinate.
Subject(s)
COVID-19 , Influenza Vaccines , Influenza, Human , COVID-19/prevention & control , Cross-Sectional Studies , Humans , Influenza, Human/epidemiology , Influenza, Human/prevention & control , Intention , Primary Health Care , SARS-CoV-2 , Spain , VaccinationABSTRACT
Our purpose was to identify the reasons why members of the population, aged 18-60 years, are vaccinated against COVID-19 at the mass vaccination point in Bages, Spain. This is 1 of 42 provisional spaces outside of health centres which have been set up in Catalonia in the context of the COVID-19 pandemic, and where people from all over Catalonia could go to be vaccinated by appointment. METHODOLOGY: We performed a cross-sectional study of users attending mass vaccination points in Bages during the months of July, August, and September 2021. RESULTS: A total of 1361 questionnaires were statistically analysed. The most common reasons for vaccination were fear of infecting family (49.52%) and fear of self-infection (39.45%), followed by socialising (31.00%) and travel (30.56%). However, by applying a logistic regression model to each reason for vaccination, it was possible to estimate the associations regarding age, sex, marital status, educational level, production sector, mass vaccination point, previous COVID-19 infection, and COVID-19 infection of a family member. RELEVANCE: The data generated will inform decisions and formulations of appropriate campaigns that will promote vaccination in specific population groups.