This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2209) JMIR Theme Issue: COVID-19 Special Issue (2392) Public (e)Health, Digital Epidemiology and Public Health Informatics (641) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1013) Vaccination and Immunization in the Digital Age (346) Infodemiology and Infoveillance (1274) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1482)

Published on in Vol 6, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35754, first published .
Mandatory Vaccination Against COVID-19: Twitter Poll Analysis on Public Health Opinion

Mandatory Vaccination Against COVID-19: Twitter Poll Analysis on Public Health Opinion

Mandatory Vaccination Against COVID-19: Twitter Poll Analysis on Public Health Opinion

Authors of this article:

Valentin Ritschl1, 2 Author Orcid Image ;   Fabian Eibensteiner3, 4 Author Orcid Image ;   Erika Mosor1, 2 Author Orcid Image ;   Maisa Omara1, 2 Author Orcid Image ;   Lisa Sperl1, 2 Author Orcid Image ;   Faisal A Nawaz5 Author Orcid Image ;   Chandragiri Siva Sai6 Author Orcid Image ;   Merisa Cenanovic7 Author Orcid Image ;   Hari Prasad Devkota8, 9 Author Orcid Image ;   Mojca Hribersek4 Author Orcid Image ;   Ronita De10 Author Orcid Image ;   Elisabeth Klager4 Author Orcid Image ;   Eva Schaden4, 11 Author Orcid Image ;   Maria Kletecka-Pulker4, 12 Author Orcid Image ;   Sabine Völkl-Kernstock4, 13 Author Orcid Image ;   Harald Willschke4, 12 Author Orcid Image ;   Christoph Aufricht3 Author Orcid Image ;   Atanas G Atanasov4, 14 Author Orcid Image ;   Tanja Stamm1, 2 Author Orcid Image
Article Authors Cited by (1) Tweetations (24) Metrics

    Original Paper

    1Section for Outcomes Research, Medical University of Vienna, Vienna, Austria

    2Ludwig Boltzmann Institute for Arthritis and Rehabilitation, Vienna, Austria

    3Division of Pediatric Nephrology and Gastroenterology, Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria

    4Ludwig Boltzmann Institute for Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria

    5College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates

    6Amity Institute of Pharmacy, Amity University, Uttar Pradesh, India

    7Sarajevo, Bosnia and Herzegovina

    8Graduate School of Pharmaceutical Sciences, Kumamoto University, Kumamoto, Japan

    9Program for Leading Graduate Schools, Kumamoto University, Kumamoto, Japan

    10Indian Council of Medical Research-National Institute of Cholera and Enteric Diseases, West Bengal, India

    11Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Medical University of Vienna, Vienna, Austria

    12Institute for Ethics and Law in Medicine, University of Vienna, Vienna, Austria

    13Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria

    14Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, Jastrzebiec, Poland

    *these authors contributed equally

    Corresponding Author:

    Tanja Stamm, PhD

    Section for Outcomes Research

    Medical University of Vienna

    Spitalgasse 23

    Vienna, 1190

    Austria

    Phone: 43 140400 ext 16370

    Email: tanja.stamm@meduniwien.ac.at


    Background: On January 30, 2020, the World Health Organization Emergency Committee declared the rapid worldwide spread of COVID-19 a global health emergency. By December 2020, the safety and efficacy of the first COVID-19 vaccines had been demonstrated. However, international vaccination coverage rates have remained below expectations (in Europe at the time of manuscript submission). Controversial mandatory vaccination is currently being discussed and has already been introduced in some countries (Austria, Greece, and Italy). We used the Twitter survey system as a viable method to quickly and comprehensively gather international public health insights on mandatory vaccination against COVID-19.

    Objective: The purpose of this study was to better understand the public’s perception of mandatory COVID-19 vaccination in real time using Twitter polls.

    Methods: Two Twitter polls were developed (in the English language) to seek the public’s opinion on the possibility of mandatory vaccination. The polls were pinned to the Digital Health and Patient Safety Platform’s (based in Vienna, Austria) Twitter timeline for 1 week in mid-November 2021, 3 days after the official public announcement of mandatory COVID-19 vaccination in Austria. Twitter users were asked to participate and retweet the polls to reach the largest possible audience.

    Results: Our Twitter polls revealed two extremes on the topic of mandatory vaccination against COVID-19. Almost half of the 2545 respondents (n=1246, 49%) favor mandatory vaccination, at least in certain areas. This attitude contrasts with the 45.7% (n=1162) who categorically reject mandatory vaccination. Over one-quarter (n=621, 26.3%) of participating Twitter users said they would never get vaccinated, as reflected by the current Western European and North American vaccination coverage rate. Concatenating interpretation of these two polls should be done cautiously as participating populations might substantially differ.

    Conclusions: Mandatory vaccination against COVID-19 (in at least certain areas) is favored by less than 50%, whereas it is opposed by almost half of the surveyed Twitter users. Since (social) media strongly influences public perceptions and views, and social media discussions and surveys are specifically susceptible to the “echo chamber effect,” the results should be interpreted as a momentary snapshot. Therefore, the results of this study need to be complemented by long-term surveys to maintain their validity.

    JMIR Form Res 2022;6(6):e35754

    doi:10.2196/35754

    Keywords

    COVID-19; SARS-CoV-2; vaccine; vaccination; Twitter; survey; mandatory vaccination; vaccination hesitancy; coronavirus; hesitancy; social media; questionnaire; mandatory; support; poll; opinion; public health; perception 


    Many mitigation measurements, mostly nonpharmaceutical interventions, have been undertaken on local, national, and international levels to reduce the transmission of COVID-19 since the beginning of this pandemic [1-6]. As Sridhar and Gurdasani [7] discussed in January 2021, immunity can be boosted safely through vaccination in many infectious diseases, while achievement of herd immunity through SARS-CoV-2 infection is not a strategy worth considering due to little guarantee of success while putting a high toll on morbidity and mortality. Therefore, the return to prepandemic normality may rely on the success of vaccine-induced immunity to prevent severe disease and limit dissemination [8]. Although the first COVID-19 vaccines were quickly proven safe and efficacious, and were approved by regulatory authorities in December 2020 [9-12], global vaccination coverage has not been achieved for several reasons. Vaccination coverage rates largely depend on a country’s wealth and other factors that influence the vaccination behavior of a country’s citizens. As a result, SARS-CoV-2 variants continue to emerge, triggering disease episodes and slowing or even reversing the reopening of societies and economies [13].

    Widespread public acceptance of vaccines continues to be a challenging endeavor requiring accountancy of complex socioeconomic factors on the level of international policy makers, national and local public health officials, and professional and community organizations [14]. A large study from four metropolitan areas of the United States found more than 20% of participants reluctant to vaccinate. Participants expressed concerns on efficacy and safety while also questioning the severity of a COVID-19 infection [15]. In a Canadian study, participants who did not plan to get vaccinated were also less likely to retain mitigation measures such as wearing face masks and practicing physical distancing [16].

    Outreach to the public providing necessary information regarding COVID-19 has been achieved over several communication channels, such as traditional media and different social media platforms [17]. Public health implications of social media platforms such as Twitter have been studied before and with increasing intensity during the COVID-19 pandemic. Examples include public perception of antibiotic use and misuse, human papillomavirus vaccination on Twitter and analysis of boosted vaccination hesitancy, and the re-emergence of measles in the United States after its elimination [18-20]. During the COVID-19 pandemic, substantial effort has also been drawn to study symptoms for COVID-19 screening, dissemination of medical information and misinformation, the emergence of conspiracy theories, and discussions and emotions associated with COVID-19 on Twitter [21-25]. Longitudinal sentiment analysis of Twitter discussions around COVID-19 revealed a peak of percentages of tweets expressing fear in mid-March 2020 after the initial declaration of the pandemic, with the lowest point in early November 2020 when the first COVID-19 vaccines were announced. With the increasing perspective of promising vaccine results, the percentage of tweets expressing trust increased while fear declined [26]. With Twitter hosting about 353 million monthly active users and incorporating an inbuilt anonymous polling tool, it allows for potential insights into pressing public health topics on an international level with real-time feedback [27,28]. In a previous Twitter poll study on the public’s perceptions of the currently available COVID-19 vaccines, Eibensteiner et al [29] detected a high willingness to get vaccinated despite high levels of uncertainty regarding the available vaccine’s safety in February 2021. A later published study analyzing 4 million tweets since the beginning of the pandemic added that Twitter bots or political activists partly generated vaccine opposition content.

    In contrast, positive content on COVID-19 vaccination was produced mainly by well-known individuals and organizations [30]. A recent study by Germani and Biller-Andorno [31] also shows that those against vaccination increasingly participate in discussions on Twitter and disseminate their content from a pool of strong influencers such as political activists, authors, or artists. Donald Trump, a previous president of the United States, was the most influential disseminator of antivaccination content on Twitter (before his account was suspended). At this point, it should be emphasized that, of course, not only social media such as Twitter but also other factors can lead to vaccination hesitancy. Truong et al [32] mentioned in their review, for example, demographic factors (ethnicity, age, gender, pregnancy, education, and employment), personal responsibility and risk perception, trust in health authorities, and the (perceived) safety and efficacy of a new vaccine, as well as a lack of information or incorrect information about vaccines.

    Mandatory vaccination against COVID-19 for the public or health care workers has been a recent focus of attention in many European countries, including Austria, Germany, and the United Kingdom [33-35]. In Austria (general public 18 years or older) and Germany (employees in hospitals and care facilities), mandatory vaccination is scheduled for spring 2022. Recently, Italy approved mandated vaccines for everyone over 50 years of age and Greece for people older than 60 years [34-36]. A survey in Germany on 20,000 households in early summer 2020 revealed that about 50% of Germany’s residents would favor mandatory vaccination [37].

    With the recent announcement of mandatory COVID-19 vaccination in some western democracies (eg, Austria or Germany), our study aims to survey the public’s attitude on this matter. As has already been shown before, the fast-paced dynamic of this pandemic requires online survey tools to gain immediate large-scale international public health insights [23,26,29,38]. Therefore, we used the Twitter polling tool to rapidly collect and analyze the public’s opinion on mandatory COVID-19 vaccination to understand endorsement and refusal, possibly aiding policy makers on this highly relevant and timely topic. This study aimed to better understand public perceptions of mandatory COVID-19 vaccination in real time using Twitter polls.


    Overview

    To meet the objective of this study and better understand public perceptions of mandatory COVID-19 vaccination, we conducted two Twitter polls. For this purpose, we used the Twitter account of the Digital Health and Patient Safety Platform (DHPSP; Twitter handle @DHPSP) [39]. The DHPSP was founded by the Ludwig Boltzmann Institute for Digital Health and Patient Safety, established in Austria in 2019 [29].

    For this study, we distributed two Twitter polls online via the Twitter account @DHPSP between November 22 and 29, 2021. The polls were developed within the project expert team and evaluated in multiple rounds to ensure the best possible readability and comprehensibility. Poll 1 addressed whether participants had already been vaccinated (“Have you been vaccinated against COVID-19?”), whereas poll 2 asked about opinions about a possible mandatory vaccination for COVID-19 (“Do you support mandatory vaccination against COVID-19?”). Both polls were linked (poll 2 was posted as a comment under poll 1) and pinned to the top of the DHPSP Twitter timeline during the poll period. Pinning a tweet permanently places it at the top of a Twitter user’s account so that any new visitors will see this tweet at the top of the visited user’s timeline. The poll questions, including relevant hashtags for categorization, are limited to 280 characters on Twitter. Twitter allows up to four responses with a limit of 25 characters including spaces for each poll. Therefore, both polls had four responses ranging from complete agreement (“Yes, twice or more” and “Yes, definitely”) to complete disagreement (“I never will” and “I am clearly against it”) in the manner of a four-point response scale. Both surveys were categorized with the following hashtags to increase visibility and facilitate analysis: #MandatoryVaccination, #COVID19vaccines, and #DHPSP. Figure 1 shows the detailed structure of the two polls as they were distributed on Twitter.

    Once the polls were launched, the first accounts to see them in their Twitter timelines were DHPSP Twitter followers. Twitter polls are anonymous and do not allow respondents’ characteristics (eg, gender) to be assessed. Therefore, to obtain the characteristics of the audience that were first exposed to the polls, we attempted to analyze the characteristics of @DHPSP’s followers via the online tool Followerwonk [40] on December 1, 2021. In total, the Twitter account @DHPSP had 943 followers at the time of the analysis. Of these, 206 (21.8%) were male, 133 (14.1%) were female, and 604 (64.1%) did not indicate their gender on Twitter. Overall, 137 (14.5%) DHPSP followers had more than 5000 followers on their own, 320 (33.9%) had between 500 and 5000 followers, and 486 (51.5%) had less than 500 followers. The geographical distribution of the @DHPSP follower network can be seen in Figure 2. In addition, the DHPSP network includes 225 people on the mailing list, 306 people on LinkedIn, and 1757 Facebook followers.

    ‎
    Figure 1. Structure of the two Twitter polls. DHPSP: Digital Health and Patient Safety Platform.
    View this figure
    ‎
    Figure 2. Main locations of the Digital Health and Patient Safety Platform's (DHPSP) Twitter followers (note: these data cover only the fraction of the DHPSP's followers who indicated their location in their account information on Twitter).
    View this figure

    The text of the polls asked for retweets and discussion (“Retweets and comments/opinions are appreciated”; Figure 1), and with each new retweet, the polls gained an additional audience (consisting of the followers of the retweeting accounts). To gain extra visibility, members and subscribers to the DHPSP platform email list [39] were asked to support the polls by voting, retweeting, and sharing them through various additional networking approaches via emails or direct messages on social media. Various social media accounts of DHPSP members were also used to post hyperlinks to the Twitter polls. In addition, information about the polls was disseminated through DHPSP’s Facebook [41] and LinkedIn accounts [42].

    To characterize the user population that retweeted the polls under study, we conducted a hashtag analysis using the Symplur Signals online tool [43]. We analyzed (in terms of the number of retweets, users, locations, and languages) all tweets that contained the unique combination of the hashtags #MandatoryVaccination, #COVID19vaccines, and #DHPSP at the end of the poll period on November 29, 2021. To ensure accuracy and limit interference from other Twitter discussions on this topic, a Twitter search was conducted before the start of the surveys on November 21, 2021, which confirmed that this hashtag combination had never been used before. Symplur Signals was also used for sentiment analysis of all tweets containing this unique combination of hashtags. For additional analysis of the gender and age distribution of direct retweets, the tool Tweepsmap was applied using its “Tweet Reach” feature (quote tweets not included due to the specifics of the used tool).

    Ethical Considerations

    No ethical approval was required for this study as it does not fall within the scope of the Austrian Medical Ethics Act. Individual votes, retweets, and comments of any kind were anonymized using Symplur Signals. All data presented in this manuscript are anonymous. Thus, the data collected do not fall within the scope of the General Data Protection Regulation [44]. As follow-up information, the voting counts are immediately revealed to users as soon as they vote through their Twitter account. The parameters analyzed beyond the survey results, such as the number of followers and retweets, are based on online publicly available data.


    Both Twitter polls were pinned to the timeline of the DHPSP’s Twitter account (Twitter handle @DHPSP; Table 1) for 7 days, beginning on November 22, 2021. The gender and age distribution of the Twitter accounts that directly retweeted both polls (poll 1, n=178; poll 2, n=189) are depicted in Table 2. Sentiment analysis of all tweets featuring the polls demonstrated 45% (32 primary tweets with a sentiment score range from –0.5894 to –0.062) negative sentiment and 55% (50 primary tweets with a sentiment score range from 0.9338 to 0.7536) positive sentiment of the analyzed tweets (Figure 3).

    Poll 1 (“Have you been vaccinated against COVID-19?”) received a total of 2365 votes (199,902 views), whereas poll 2 (“Do you support mandatory vaccination against COVID-19?”) received a total of 2545 votes (200,939 views). Upon analysis of the polls’ retweets that contained the unique combination of the hashtags #MandatoryVaccination, #COVID19vaccines, and #DHPSP, a total of 2073 tweets from 442 users (one retweet: n=272, 61.5%; two retweets: n=100 users, 22.6%; three or more retweets: n=70, 15.8%) were identified. The polls, including all retweets, summed up to a total of 32,594,283 views on Twitter. The top locations of Twitter users retweeting the polls were the United States (n=59, 6.3%), Canada (n=41, 4.5%), and the United Kingdom (n=17, 1.5%). However, most of the users did not indicate their location. A summary of these details is given in Table 3.

    Of the Twitter users who responded to poll 1 (“Have you been vaccinated against COVID-19?”), 63.4% (1499/2365) agreed with “Yes, twice or more”; therefore, almost two-thirds of users who answered this question reported to be fully vaccinated. More than one-quarter (621/2365, 26.3%) of Twitter users expressed that they will never get vaccinated against COVID-19 (they voted “I never will”). Together, these two groups represent the extremes regarding vaccination and represent 89.6% (2120/2365) of all answers to this question. Of the 2365 respondents, 111 (4.7%) reported that they have not yet been vaccinated but do not rule out the possibility of getting vaccinated (“Not yet.”). The remaining 5.7% (n=134) of Twitter users had been vaccinated but have not yet received a second vaccine dose (“Yes, vaccinated once”).

    Poll 2 examined Twitter users’ attitudes toward possible mandatory vaccination (“Do you support mandatory vaccination against COVID-19?”). In this poll, 40.2% (1022/2545) of all respondents indicated (“Yes, definitely”) that they would support mandatory vaccination against COVID-19. In addition, 8.8% (224/2545) indicated that they would support mandatory vaccination in certain areas (eg, for certain professions; “Yes, in some areas”). In contrast to the vaccine supporters, almost half of the respondents (1162/2545, 45.7%) are strictly against mandatory vaccination (“I am clearly against it”). A small percentage of 5.4% (137/2545) of Twitter users stated that they do not yet have an opinion on mandatory vaccination against COVID-19 (“I am not sure”). A detailed summary of the responses to both polls is given in Figure 4.

    Table 1. Digital Health and Patient Safety Platform’s Twitter follower characteristics.

    		Followers (n=943), n (%)
    Gender

    		Male206 (21.8)

    		Female133 (14.1)

    		Not stated604 (64.1)
    Follower counts

    		<500486 (51.5)

    		500-5000320 (33.9)

    		>5000137 (14.5)
    Account ages (years)

    		<186 (9.1)

    		1-5325 (34.5)

    		>5532 (56.4)
    Languages

    		English586 (62.1)

    		Spanish46 (4.9)

    		Other301 (31.9)
    Table 2. Gender and age distribution of Twitter accounts that retweeted the polls.

    		Twitter accounts, n (%)
    Poll 1 (n=178)

    		Distribution by gender poll 1: direct retweets


    		Male102 (57.3)


    		Female61 (34.4)


    		Businesses/groups15 (8.3)

    		Distribution by age poll 1: direct retweets


    		10-23 years20 (11.4)


    		24-64 years142 (80.0)


    		≥65 years16 (8.6)
    Poll 2 (n=189)

    		Distribution by gender poll 2: direct retweets


    		Male112 (59.6)


    		Female69 (36.4)


    		Businesses/groups8 (4)

    		Distribution by age poll 2: direct retweets


    		10-23 years28 (14.8)


    		24-64 years154 (81.5)


    		≥65 years7 (3.7)
    ‎
    Figure 3. Sentiment analysis of the poll's retweets containing the unique combination of the following hashtags: #MandatoryVaccination, #COVID19vaccines, and #DHPSP (Digital Health and Patient Safety Platform). The upper panel indicates sentiment over time and the overall sentiment scores (45% negative and 55% positive), and the lower panel displays sentiment word frequencies.
    View this figure
    Table 3. Analysis of the poll’s retweets containing the unique combination of the following hashtags: #MandatoryVaccination, #COVID19vaccines, and #DHPSP (Digital Health and Patient Safety Platform).

    		Twitter users (n=943), n (%)
    Top locations of Twitter usersa229 (24.3)

    		United States59 (6.3)

    		Canada41 (4.5)

    		United Kingdom17 (1.5)
    Number of users that retweetedb442 (46.9)

    		One retweet272 (61.5)

    		Two retweetsc100 (22.6)

    		Three or more retweetsc70 (15.8)
    Top languagesd

    		English1969 (95.0)

    		Other languages 104 (5.0)

    aDetermined based on data derived just from the users who indicated their location in their account information on Twitter. While interpreting the data, the readers should be aware that 75.7% of the 943 users did not provide location information on their profiles.

    bThe total number of retweets was 2073.

    cIncluding “regular” retweets, retweets with comments, and “quote retweets” (whereby a hyperlink to the original tweet is inserted in the newly composed tweet).

    dThe most used languages are indicated. All other tweet languages accounted for less than 0.5% each.

    ‎
    Figure 4. Twitter users' answers to poll 1 ("Have you been vaccinated against COVID-19?"; respondents n=2365) and poll 2 ("Do you support mandatory vaccination against COVID-19?"; respondents n=2545).
    View this figure

    Our Twitter polls showed two extremes on the issue of compulsory vaccination against COVID-19. Almost half of the respondents favor compulsory vaccination, at least for certain professional groups. However, this is in contrast to nearly as many people who categorically reject compulsory vaccination, indicating that a proportion of vaccinated people voted against mandating vaccination. In line with recent works building the methodological basis and outlining the possible benefits of Twitter polling to gain quick insights into the public’s attitudes on timely matters [28,29], we aimed to explore the public’s opinion on mandatory COVID-19 vaccination by using Twitter polls. This topic is currently of high interest as recently mandatory COVID-19 vaccination has been scheduled for spring 2022 in Austria and Germany [34,35]. This timely and important Twitter survey reveals that mandatory vaccination against COVID-19 (in at least certain areas) is supported by less than 50%, whereas it is opposed by almost half of the surveyed Twitter users.

    We used an established Twitter network (the DHPSP’s Twitter account) to pin our Twitter polls to generate high outreach and a high number of respondents in this study. This work complements our initial Twitter survey on the perceived safety of the available COVID-19 vaccines and participants’ confidence or hesitancy to get vaccinated [29]. In February 2021, 83% of Twitter users participating in polls posted back then stated that they would definitely get vaccinated against COVID-19. About 70% of participants indicated that they received at least their first dose in the current poll. The percentage of participants expressing their reluctance to get vaccinated increased from 8% to 26%. This data is in line with the current vaccination rates in Western European countries (United Kingdom, Germany, Austria, France, Spain, and Italy) and the United States, with 71% to 83% of people being at least partly vaccinated [45], and above the world average of 55% [45]. A direct comparison of these two Twitter polls can be carefully made, considering that the initial Twitter network was the same, even though participating users might substantially differ. Interpretability is further limited by the DHPSP’s follower base consisting mainly of younger educated individuals with scientific backgrounds, mainly due to the selective science-based content that attracted such followers and their interest in science. This concern is in line with several studies associating COVID-19 vaccine hesitancy with lower educational levels [46-49]. Comparability of other studies with our study is not straightforward, as the logic and infrastructure of Twitter surveys make the retrospective characterization of the sample difficult. Available information about Twitter users is limited (eg, in terms of location and language). Despite the composition of the original sample of “younger, educated people,” we reached a total of 26.3% (621/2365) of convinced nonvaxxers in our survey, which is in line with the results reported in other studies, such as the one by Hacquin and colleagues [49]. We explain this phenomenon by the fact that while the original sample was indeed enriched with younger, (better formally) educated individuals, each new retweet immediately adds the followers of each new retweeting account as an audience for the surveys. In this way, we seem to have achieved an equilibrium consistent with opinion patterns among Twitter users, which may explain why the proportion of nonvaxxers in our study was similar to that observed in previous work.

    Our findings agree with the previously reported percentage of 26% of participants stating that they will never get vaccinated against COVID-19, with about 5% remaining undecided. In the current literature, COVID-19 vaccine hesitancy is further evident among university students (14%), medical students (23%), and health care workers (28%) [50-52]. A large-scale survey in Ireland and the United Kingdom segmented the previously published high percentages of COVID-19 vaccination hesitancy/refusal (eg, 33% in the United States) to 25% to 26% vaccination hesitancy and 6% to 9% resistance [53]. Although we aimed to formulate our poll questions and answers clearly and discriminatively (eg, “I never will”), further interpretation of these results due to missing demographics and other indicators of socioeconomic status, health literacy, and political and religious views was not possible. In addition, the study published by Murphy et al [53] was conducted in Spring 2020, at a time when no COVID-19 vaccines were yet available. Vaccination refusal may not only affect the course of this pandemic but has also been the focus of discussion among the prevention of other vaccine-preventable and potentially deadly diseases such as measles [54].

    Our Twitter polls revealed high rates of being vaccinated against COVID-19 at least once, while 40% of participants supported mandatory vaccination for the public. Such concatenating interpretation of these two polls needs to be done cautiously, as the participating populations might substantially differ between both polls. Mandatory vaccination against COVID-19 is currently under rigorous discussion in many European countries and among health and home care workers [33,55,56]. Austria is currently the first western democracy, followed by Germany, to officially announce mandatory vaccination against COVID-19 for the public [34,35]. This would not be the first time mandatory vaccination has been enforced. For example, in England and Imperial Germany, between 1874 and 1975, vaccination against smallpox was compulsory, resulting in substantially reduced mortality rates [57]. However, ethical, medical, and philosophical reasons supporting and opposing mandatory vaccination involve complex socioeconomic and psychological perspectives [58-60] that are out of this paper’s scope and will not be further discussed.

    Several studies have assessed the public’s opinion on mandatory COVID-19 vaccination in German, French, Greek, Austrian, American, Pakistani, and Italian individuals. A broad range favored mandatory COVID-19 vaccination from 17% to 74% of survey participants. Five of these studies were conducted before COVID-19 vaccines were available and before the official public announcement of mandatory vaccination against COVID-19 for the public in Austria [37,61-66].

    Therefore, this is the first study analyzing the public’s attitude on mandatory COVID-19 vaccination immediately following (3 days) the official public announcement of the Austrian government, which is the first western democracy to mandate vaccination for its entire population [34]. This timely analysis on an international scale provides valuable insights into changes in the public’s attitude and general beliefs toward COVID-19 vaccine mandates that may aid policy makers in strategizing similar paths to Austria.

    The strengths of this study lay in the rapid and timely assessment on an international scale with clear and concise information on the publics’ attitude. As previously discussed in our prequel study, restrictions of word counts in Twitter polling might serve as a strength for concise and well-formulated surveys, possibly aiding a higher number of respondents in comparison to traditional surveys. On the other hand, it substantially limits the interpretability of results, as no additional information may be retrieved, and the formulation of more complex questions and clarification statements is hampered [29]. For example, it could be that the wording of the second answer of the second poll, “yes, in some areas” I am in favor of compulsory vaccination, may be understood by some respondents as “region,” “district,” or another geographical unit. In the original conception, however, the term “area” was meant rather as “branch” or “profession.” A misunderstanding cannot be ruled out and must be considered when interpreting the results. Distribution of the Twitter polls via a pre-existing network might also influence sample selection and cause bias further challenged by a lack of baseline characteristics of the survey participants. This is potentiated by the “echo chamber effect,” exposing social media users to curated content most likely aligning with their pre-existing beliefs based on their previous social media behavior [67,68]. This also includes the previous observation that individuals exposed to negative opinions on human papillomavirus vaccination were more likely to share these on Twitter, in contrast to those exposed to neutral or positive opinions [69]. An explicit limitation also lies in the extremely limited concatenating interpretation of the different Twitter polls, as the participating user populations might substantially differ between the two polls, and comparability cannot be achieved due to the polls’ anonymity. Thus, a direct transferability of the results to individual countries is impossible or only possible to a limited extent. In addition, poll manipulation by exploiting multiple users due to the polls’ anonymity needs to be kept in mind upon interpreting these results, as already mentioned by Vidal-Alaball et al [28]. We used Symplur Signals for sentiment analysis of all tweets. This automated text-mining tool helped us get an impression of the sentiment. Still, it has to be mentioned that this is not equal to classical qualitative data analysis.

    When interpreting the data, it is important to remember that the two surveys involved self-selected users of a popular social media platform who self-reported their COVID-19 vaccination status and their opinion on introducing such mandatory vaccination. Objective data, for example, on vaccination status, could not be collected in this study.

    In summary, mandatory vaccination against COVID-19 is supported by less than 50% of Twitter users and opposed by almost half of the Twitter users surveyed in this study. Refusal rates of COVID-19 vaccination are prevalent among 26% of surveyed Twitter users. These findings are reflected by the current vaccination coverage rates and align with the existing literature. Public perceptions and views on health issues are heavily influenced by social media, being specifically susceptible to the “echo chamber effect,” underscoring the importance of using social media surveys to understand the public’s views on health in real time to inform public health messages and communications efforts.

    Acknowledgments

    This research received no external funding.

    Data Availability

    Raw data are available upon reasonable request.

    Authors' Contributions

    VR, FE, AGA, and TS conceptualized and planned the study, including the preparation of the polls. VR, FE, CA, AGA, and TS wrote the first draft of the manuscript. CA, AGA, and TS reviewed the whole process. All other authors suggested and agreed upon the research questions, disseminated the polls via their networks, read the report prior to the manuscript, discussed the results, and contributed to the text. All authors approved the final version of the manuscript.

    Conflicts of Interest

    TS reports grants and personal fees from AbbVie, grants and personal fees from Roche, personal fees from Sanofi, personal fees from Takeda, and personal fees from Novartis, outside the submitted work. The other authors declare no conflicts of interest.

    1. Anderson M, Mckee M, Mossialos E. Covid-19 exposes weaknesses in European response to outbreaks. BMJ 2020 Mar 18;368:m1075. [CrossRef] [Medline]
    2. Anderson RM, Heesterbeek H, Klinkenberg D, Hollingsworth TD. How will country-based mitigation measures influence the course of the COVID-19 epidemic? Lancet 2020 Mar 21;395(10228):931-934 [FREE Full text] [CrossRef] [Medline]
    3. Chu D, Akl EA, Duda S, Solo K, Yaacoub S, Schünemann HJ, COVID-19 Systematic Urgent Review Group Effort (SURGE) study authors. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. Lancet 2020 Jun 27;395(10242):1973-1987 [FREE Full text] [CrossRef] [Medline]
    4. Cowling B, Ali S, Ng T, Tsang T, Li J, Fong M, et al. Impact assessment of non-pharmaceutical interventions against coronavirus disease 2019 and influenza in Hong Kong: an observational study. Lancet Public Health 2020 May;5(5):e279-e288 [FREE Full text] [CrossRef] [Medline]
    5. Eibensteiner F, Ritschl V, Ariceta G, Jankauskiene A, Klaus G, Paglialonga F, European Pediatric Dialysis Working Group. Rapid response in the COVID-19 pandemic: a Delphi study from the European Pediatric Dialysis Working Group. Pediatr Nephrol 2020 Sep;35(9):1669-1678 [FREE Full text] [CrossRef] [Medline]
    6. Pan A, Liu L, Wang C, Guo H, Hao X, Wang Q, et al. Association of public health interventions with the epidemiology of the COVID-19 outbreak in Wuhan, China. JAMA 2020 May 19;323(19):1915-1923 [FREE Full text] [CrossRef] [Medline]
    7. Sridhar D, Gurdasani D. Herd immunity by infection is not an option. Science 2021 Jan 15;371(6526):230-231. [CrossRef] [Medline]
    8. Rubin EJ, Longo DL. SARS-CoV-2 vaccination - an ounce (actually, much less) of prevention. N Engl J Med 2020 Dec 31;383(27):2677-2678 [FREE Full text] [CrossRef] [Medline]
    9. Baden LR, El Sahly HM, Essink B, Kotloff K, Frey S, Novak R, COVE Study Group. Efficacy and safety of the mRNA-1273 SARS-CoV-2 vaccine. N Engl J Med 2021 Feb 04;384(5):403-416 [FREE Full text] [CrossRef] [Medline]
    10. Logunov D, Dolzhikova I, Shcheblyakov D, Tukhvatulin A, Zubkova O, Dzharullaeva A, Gam-COVID-Vac Vaccine Trial Group. Safety and efficacy of an rAd26 and rAd5 vector-based heterologous prime-boost COVID-19 vaccine: an interim analysis of a randomised controlled phase 3 trial in Russia. Lancet 2021 Feb 20;397(10275):671-681 [FREE Full text] [CrossRef] [Medline]
    11. Polack FP, Thomas SJ, Kitchin N, Absalon J, Gurtman A, Lockhart S, C4591001 Clinical Trial Group. Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine. N Engl J Med 2020 Dec 31;383(27):2603-2615 [FREE Full text] [CrossRef] [Medline]
    12. Voysey M, Clemens S, Madhi S, Weckx L, Folegatti P, Aley P, Oxford COVID Vaccine Trial Group. Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK. Lancet 2021 Jan 09;397(10269):99-111 [FREE Full text] [CrossRef] [Medline]
    13. Tregoning JS, Flight KE, Higham SL, Wang Z, Pierce BF. Progress of the COVID-19 vaccine effort: viruses, vaccines and variants versus efficacy, effectiveness and escape. Nat Rev Immunol 2021 Oct;21(10):626-636 [FREE Full text] [CrossRef] [Medline]
    14. Schoch-Spana M, Brunson EK, Long R, Ruth A, Ravi SJ, Trotochaud M, et al. The public's role in COVID-19 vaccination: human-centered recommendations to enhance pandemic vaccine awareness, access, and acceptance in the United States. Vaccine 2021 Sep 24;39(40):6004-6012 [FREE Full text] [CrossRef] [Medline]
    15. El-Mohandes A, White TM, Wyka K, Rauh L, Rabin K, Kimball SH, et al. COVID-19 vaccine acceptance among adults in four major US metropolitan areas and nationwide. Sci Rep 2021 Nov 04;11(1):21844. [CrossRef] [Medline]
    16. Muhajarine N, Adeyinka DA, McCutcheon J, Green KL, Fahlman M, Kallio N. COVID-19 vaccine hesitancy and refusal and associated factors in an adult population in Saskatchewan, Canada: Evidence from predictive modelling. PLoS One 2021;16(11):e0259513 [FREE Full text] [CrossRef] [Medline]
    17. Su Y. It doesn’t take a village to fall for misinformation: social media use, discussion heterogeneity preference, worry of the virus, faith in scientists, and COVID-19-related misinformation beliefs. Telematics Inform 2021 May;58:101547. [CrossRef]
    18. Hotez PJ, Nuzhath T, Colwell B. Combating vaccine hesitancy and other 21st century social determinants in the global fight against measles. Curr Opin Virol 2020 Apr;41:1-7. [CrossRef] [Medline]
    19. Kendra RL, Karki S, Eickholt JL, Gandy L. Characterizing the discussion of antibiotics in the Twittersphere: what is the bigger picture? J Med Internet Res 2015 Jun 19;17(6):e154 [FREE Full text] [CrossRef] [Medline]
    20. Massey PM, Leader A, Yom-Tov E, Budenz A, Fisher K, Klassen AC. Applying multiple data collection tools to quantify human papillomavirus vaccine communication on Twitter. J Med Internet Res 2016 Dec 05;18(12):e318 [FREE Full text] [CrossRef] [Medline]
    21. Ahmed W, Vidal-Alaball J, Downing J, López Seguí F. COVID-19 and the 5G conspiracy theory: social network analysis of Twitter data. J Med Internet Res 2020 May 06;22(5):e19458 [FREE Full text] [CrossRef] [Medline]
    22. Guo J, Radloff CL, Wawrzynski SE, Cloyes KG. Mining twitter to explore the emergence of COVID-19 symptoms. Public Health Nurs 2020 Nov;37(6):934-940 [FREE Full text] [CrossRef] [Medline]
    23. Krittanawong C, Narasimhan B, Virk HUH, Narasimhan H, Hahn J, Wang Z, et al. Misinformation dissemination in Twitter in the COVID-19 era. Am J Med 2020 Dec;133(12):1367-1369 [FREE Full text] [CrossRef] [Medline]
    24. Rosenberg H, Syed S, Rezaie S. The Twitter pandemic: the critical role of Twitter in the dissemination of medical information and misinformation during the COVID-19 pandemic. CJEM 2020 Jul;22(4):418-421 [FREE Full text] [CrossRef] [Medline]
    25. Xue J, Chen J, Hu R, Chen C, Zheng C, Su Y, et al. Twitter discussions and emotions about the COVID-19 pandemic: machine learning approach. J Med Internet Res 2020 Nov 25;22(11):e20550 [FREE Full text] [CrossRef] [Medline]
    26. Lyu JC, Han EL, Luli GK. COVID-19 vaccine-related discussion on Twitter: topic modeling and sentiment analysis. J Med Internet Res 2021 Jun 29;23(6):e24435 [FREE Full text] [CrossRef] [Medline]
    27. Statista.   URL: https://de.statista.com/ [accessed 2021-03-04]
    28. Vidal-Alaball J, Fernandez-Luque L, Marin-Gomez FX, Ahmed W. A new tool for public health opinion to give insight into telemedicine: Twitter poll analysis. JMIR Form Res 2019 May 28;3(2):e13870 [FREE Full text] [CrossRef] [Medline]
    29. Eibensteiner F, Ritschl V, Nawaz FA, Fazel SS, Tsagkaris C, Kulnik ST, et al. People's willingness to vaccinate against COVID-19 despite their safety concerns: Twitter poll analysis. J Med Internet Res 2021 Apr 29;23(4):e28973 [FREE Full text] [CrossRef] [Medline]
    30. Yousefinaghani S, Dara R, Mubareka S, Papadopoulos A, Sharif S. An analysis of COVID-19 vaccine sentiments and opinions on Twitter. Int J Infect Dis 2021 Jul;108:256-262 [FREE Full text] [CrossRef] [Medline]
    31. Germani F, Biller-Andorno N. The anti-vaccination infodemic on social media: a behavioral analysis. PLoS One 2021;16(3):e0247642 [FREE Full text] [CrossRef] [Medline]
    32. Truong J, Bakshi S, Wasim A, Ahmad M, Majid U. What factors promote vaccine hesitancy or acceptance during pandemics? A systematic review and thematic analysis. Health Promot Int 2022 Feb 17;37(1):daab105. [CrossRef] [Medline]
    33. Rimmer A. Covid vaccination to be mandatory for NHS staff in England from spring 2022. BMJ 2021 Nov 10;375:n2733. [CrossRef] [Medline]
    34. Horowitz J, Eddy M. Austria announces covid vaccine mandate, crossing a threshold for Europe. The New York Times.   URL: https://www.nytimes.com/2021/11/19/world/europe/austria-covid-vaccine-mandate-lockdown.html [accessed 2021-11-22]
    35. Schuetze CF. Germany shuts unvaccinated people out of much of public life. The New York Times.   URL: https://www.nytimes.com/2021/12/02/world/europe/germany-unvaccinated-restrictions.html [accessed 2021-12-04]
    36. Semlitsch T, Blank W, Kopp I, Siering U, Siebenhofer A. Evaluating guidelines: a review of key quality criteria. Dtsch Arztebl Int 2015 Jul 06;112(27-28):471-478. [CrossRef] [Medline]
    37. Graeber D, Schmidt-Petri C, Schröder C. Attitudes on voluntary and mandatory vaccination against COVID-19: evidence from Germany. PLoS One 2021;16(5):e0248372 [FREE Full text] [CrossRef] [Medline]
    38. Spitale G, Merten S, Jafflin K, Schwind B, Kaiser-Grolimund A, Biller-Andorno N. A novel risk and crisis communication platform to bridge the gap between policy makers and the Public in the Context of the COVID-19 Crisis (PubliCo): protocol for a mixed methods study. JMIR Res Protoc 2021 Nov 01;10(11):e33653 [FREE Full text] [CrossRef] [Medline]
    39. Digital Health and Patient Safety Platform.   URL: https://digitalpatientsafety.com/ [accessed 2021-03-19]
    40. Followerwonk.   URL: https://followerwonk.com/ [accessed 2021-02-20]
    41. Digital Health and Patient Safety Platform. Facebook.   URL: https://www.facebook.com/DHPSP [accessed 2021-03-19]
    42. Ludwig Boltzmann Institute for Digital Health and Patient Safety. LinkedIn.   URL: https://at.linkedin.com/company/ludwig-boltzmann-institute-for-digital-health-and-patient-safety [accessed 2021-03-19]
    43. Symplur.   URL: https://www.symplur.com/ [accessed 2021-02-20]
    44. Crutzen R, Ygram Peters G, Mondschein C. Why and how we should care about the General Data Protection Regulation. Psychol Health 2019 Nov;34(11):1347-1357. [CrossRef] [Medline]
    45. Mathieu E, Ritchie H, Ortiz-Ospina E, Roser M, Hasell J, Appel C, et al. A global database of COVID-19 vaccinations. Nat Hum Behav 2021 Jul;5(7):947-953. [CrossRef] [Medline]
    46. Schwarzinger M, Watson V, Arwidson P, Alla F, Luchini S. COVID-19 vaccine hesitancy in a representative working-age population in France: a survey experiment based on vaccine characteristics. Lancet Public Health 2021 Apr;6(4):e210-e221 [FREE Full text] [CrossRef] [Medline]
    47. Rhodes A, Hoq M, Measey M, Danchin M. Intention to vaccinate against COVID-19 in Australia. Lancet Infect Dis 2021 May;21(5):e110 [FREE Full text] [CrossRef] [Medline]
    48. Lin C, Tu P, Beitsch LM. Confidence and receptivity for COVID-19 vaccines: a rapid systematic review. Vaccines (Basel) 2020 Dec 30;9(1):16 [FREE Full text] [CrossRef] [Medline]
    49. Hacquin AS, Altay S, de Araujo E, Chevallier C, Mercier H. Sharp rise in vaccine hesitancy in a large and representative sample of the French population: reasons for vaccine hesitancy. PsyArXiv Preprint posted online on November 16, 2020. [FREE Full text] [CrossRef]
    50. Verger P, Scronias D, Dauby N, Adedzi K, Gobert C, Bergeat M, et al. Attitudes of healthcare workers towards COVID-19 vaccination: a survey in France and French-speaking parts of Belgium and Canada, 2020. Euro Surveill 2021 Jan;26(3):2002047 [FREE Full text] [CrossRef] [Medline]
    51. Kelekar AK, Lucia VC, Afonso NM, Mascarenhas AK. COVID-19 vaccine acceptance and hesitancy among dental and medical students. J Am Dent Assoc 2021 Aug;152(8):596-603 [FREE Full text] [CrossRef] [Medline]
    52. Barello S, Nania T, Dellafiore F, Graffigna G, Caruso R. 'Vaccine hesitancy' among university students in Italy during the COVID-19 pandemic. Eur J Epidemiol 2020 Aug;35(8):781-783 [FREE Full text] [CrossRef] [Medline]
    53. Murphy J, Vallières F, Bentall RP, Shevlin M, McBride O, Hartman TK, et al. Psychological characteristics associated with COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom. Nat Commun 2021 Jan 04;12(1):29. [CrossRef] [Medline]
    54. Tokish H, Solanto M. The problem of vaccination refusal: a review with guidance for pediatricians. Curr Opin Pediatr 2020 Oct;32(5):683-693. [CrossRef] [Medline]
    55. Hayes L, Pollock AM. Mandatory covid-19 vaccination for care home workers. BMJ 2021 Jul 07;374:n1684. [CrossRef] [Medline]
    56. Franco JVA. Should COVID-19 vaccination be mandatory? BMJ Evid Based Med 2021 Dec;26(6):269-270. [CrossRef] [Medline]
    57. Hennock EP. Vaccination policy against smallpox, 1835-1914: a comparison of England with Prussia and Imperial Germany. Soc Hist Med 1998 Apr;11(1):49-71. [CrossRef] [Medline]
    58. Vetrugno G, Cicconi M, Foti F, Spagnolo A, De-Giorgio F. Compulsory vaccination would exacerbate resistance. BMJ 2019 Jul 04;366:l4464. [CrossRef] [Medline]
    59. Salmon DA, Teret SP, MacIntyre CR, Salisbury D, Burgess MA, Halsey NA. Compulsory vaccination and conscientious or philosophical exemptions: past, present, and future. Lancet 2006 Feb 04;367(9508):436-442. [CrossRef] [Medline]
    60. Arie S. Compulsory vaccination and growing measles threat. BMJ 2017 Jul 20;358:j3429. [CrossRef] [Medline]
    61. Gagneux-Brunon A, Botelho-Nevers E, Bonneton M, Peretti-Watel P, Verger P, Launay O, et al. Public opinion on a mandatory COVID-19 vaccination policy in France: a cross-sectional survey. Clin Microbiol Infect 2022 Mar;28(3):433-439 [FREE Full text] [CrossRef] [Medline]
    62. Gallè F, Sabella EA, Roma P, Da Molin G, Diella G, Montagna MT, et al. Acceptance of COVID-19 vaccination in the elderly: a cross-sectional study in southern Italy. Vaccines (Basel) 2021 Oct 21;9(11):1222 [FREE Full text] [CrossRef] [Medline]
    63. Giannouchos TV, Steletou E, Saridi M, Souliotis K. Mandatory vaccination support and intentions to get vaccinated for COVID-19: results from a nationally representative general population survey in October 2020 in Greece. J Eval Clin Pract 2021 Aug;27(4):996-1003 [FREE Full text] [CrossRef] [Medline]
    64. Largent EA, Persad G, Sangenito S, Glickman A, Boyle C, Emanuel EJ. US public attitudes toward COVID-19 vaccine mandates. JAMA Netw Open 2020 Dec 01;3(12):e2033324 [FREE Full text] [CrossRef] [Medline]
    65. Paul KT, Eberl J, Partheymüller J. Policy-relevant attitudes toward COVID-19 vaccination: associations with demography, health risk, and social and political factors. Front Public Health 2021;9:671896. [CrossRef] [Medline]
    66. Tahir MJ, Saqlain M, Tariq W, Waheed S, Tan SHS, Nasir SI, et al. Population preferences and attitudes towards COVID-19 vaccination: a cross-sectional study from Pakistan. BMC Public Health 2021 Sep 26;21(1):1759 [FREE Full text] [CrossRef] [Medline]
    67. Chou WS, Oh A, Klein WMP. Addressing health-related misinformation on social media. JAMA 2018 Dec 18;320(23):2417-2418. [CrossRef] [Medline]
    68. Schmidt AL, Zollo F, Scala A, Betsch C, Quattrociocchi W. Polarization of the vaccination debate on Facebook. Vaccine 2018 Jun 14;36(25):3606-3612. [CrossRef] [Medline]
    69. Dunn AG, Leask J, Zhou X, Mandl KD, Coiera E. Associations between exposure to and expression of negative opinions about human papillomavirus vaccines on social media: an observational study. J Med Internet Res 2015 Jun 10;17(6):e144 [FREE Full text] [CrossRef] [Medline]

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    DHPSP: Digital Health and Patient Safety Platform

    Edited by A Mavragani; submitted 16.12.21; peer-reviewed by M Alfelali, G Spitale, G Kernohan, C Weerth; comments to author 08.01.22; revised version received 27.01.22; accepted 19.04.22; published 21.06.22

    Copyright

    ©Valentin Ritschl, Fabian Eibensteiner, Erika Mosor, Maisa Omara, Lisa Sperl, Faisal A Nawaz, Chandragiri Siva Sai, Merisa Cenanovic, Hari Prasad Devkota, Mojca Hribersek, Ronita De, Elisabeth Klager, Eva Schaden, Maria Kletecka-Pulker, Sabine Völkl-Kernstock, Harald Willschke, Christoph Aufricht, Atanas G Atanasov, Tanja Stamm. Originally published in JMIR Formative Research (https://formative.jmir.org), 21.06.2022.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.