Background As a number of vaccines for COVID-19 are given emergency use authorization by local health agencies and are being administered in multiple countries, it is crucial to gain public trust in these vaccines to ensure herd immunity through vaccination. One way to gauge public sentiment regarding vaccines for the goal of increasing vaccination rates is by analyzing social media such as Twitter. Objective The goal of this research was to understand public sentiment toward COVID-19 vaccines by analyzing discussions about the vaccines on social media for a period of 60 days when the vaccines were started in the United States. Using the combination of topic detection and sentiment analysis, we identified different types of concerns regarding vaccines that were expressed by different groups of the public on social media. Methods To better understand public sentiment, we collected tweets for exactly 60 days starting from December 16, 2020 that contained hashtags or keywords related to COVID-19 vaccines. We detected and analyzed different topics of discussion of these tweets as well as their emotional content. Vaccine topics were identified by nonnegative matrix factorization, and emotional content was identified using the Valence Aware Dictionary and sEntiment Reasoner sentiment analysis library as well as by using sentence bidirectional encoder representations from transformer embeddings and comparing the embedding to different emotions using cosine similarity. Results After removing all duplicates and retweets, 7,948,886 tweets were collected during the 60-day time period. Topic modeling resulted in 50 topics; of those, we selected 12 topics with the highest volume of tweets for analysis. Administration and access to vaccines were some of the major concerns of the public. Additionally, we classified the tweets in each topic into 1 of the 5 emotions and found fear to be the leading emotion in the tweets, followed by joy. Conclusions This research focused not only on negative emotions that may have led to vaccine hesitancy but also on positive emotions toward the vaccine. By identifying both positive and negative emotions, we were able to identify the public's response to the vaccines overall and to news events related to the vaccines. These results are useful for developing plans for disseminating authoritative health information and for better communication to build understanding and trust.
more »
« less
Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method
The COVID-19 pandemic has been sweeping across the United States of America since early 2020. The whole world was waiting for vaccination to end this pandemic. Since the approval of the first vaccine by the U.S. CDC on 9 November 2020, nearly 67.5% of the US population have been fully vaccinated by 10 July 2022. While quite successful in controlling the spreading of COVID-19, there were voices against vaccines. Therefore, this research utilizes geo-tweets and Bayesian-based method to investigate public opinions towards vaccines based on (1) the spatiotemporal changes in public engagement and public sentiment; (2) how the public engagement and sentiment react to different vaccine-related topics; (3) how various races behave differently. We connected the phenomenon observed to real-time and historical events. We found that in general the public is positive towards COVID-19 vaccines. Public sentiment positivity went up as more people were vaccinated. Public sentiment on specific topics varied in different periods. African Americans’ sentiment toward vaccines was relatively lower than other races.
more »
« less
- NSF-PAR ID:
- 10396189
- Date Published:
- Journal Name:
- Vaccines
- Volume:
- 10
- Issue:
- 9
- ISSN:
- 2076-393X
- Page Range / eLocation ID:
- 1486
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
A novel coronavirus emerged in December of 2019 (COVID-19), causing a pandemic that inflicted unprecedented public health and economic burden in all nooks and corners of the world. Although the control of COVID-19 largely focused on the use of basic public health measures (primarily based on using non-pharmaceutical interventions, such as quarantine, isolation, social-distancing, face mask usage, and community lockdowns) initially, three safe and highly-effective vaccines (by AstraZeneca Inc., Moderna Inc., and Pfizer Inc.), were approved for use in humans in December 2020. We present a new mathematical model for assessing the population-level impact of these vaccines on curtailing the burden of COVID-19. The model stratifies the total population into two subgroups, based on whether or not they habitually wear face mask in public. The resulting multigroup model, which takes the form of a deterministic system of nonlinear differential equations, is fitted and parameterized using COVID-19 cumulative mortality data for the third wave of the COVID-19 pandemic in the United States. Conditions for the asymptotic stability of the associated disease-free equilibrium, as well as an expression for the vaccine-derived herd immunity threshold, are rigorously derived. Numerical simulations of the model show that the size of the initial proportion of individuals in the mask-wearing group, together with positive change in behavior from the non-mask wearing group (as well as those in the mask-wearing group, who do not abandon their mask-wearing habit) play a crucial role in effectively curtailing the COVID-19 pandemic in the United States. This study further shows that the prospect of achieving vaccine-derived herd immunity (required for COVID-19 elimination) in the U.S., using the Pfizer or Moderna vaccine, is quite promising. In particular, our study shows that herd immunity can be achieved in the U.S. if at least 60% of the population are fully vaccinated. Furthermore, the prospect of eliminating the pandemic in the U.S. in the year 2021 is significantly enhanced if the vaccination program is complemented with non-pharmaceutical interventions at moderate increased levels of compliance (in relation to their baseline compliance). The study further suggests that, while the waning of natural and vaccine-derived immunity against COVID-19 induces only a marginal increase in the burden and projected time-to-elimination of the pandemic, adding the impacts of therapeutic benefits of the vaccines into the model resulted in a dramatic reduction in the burden and time-to-elimination of the pandemic.more » « less
-
Public sentiment toward the COVID-19 vaccine as expressed on social media can interfere with communication by public health agencies on the importance of getting vaccinated. We investigated Twitter data to understand differences in sentiment, moral values, and language use between political ideologies on the COVID-19 vaccine. We estimated political ideology, conducted a sentiment analysis, and guided by the tenets of moral foundations theory (MFT), we analyzed 262,267 English language tweets from the United States containing COVID-19 vaccine-related keywords between May 2020 and October 2021. We applied the Moral Foundations Dictionary and used topic modeling and Word2Vec to understand moral values and the context of words central to the discussion of the vaccine debate. A quadratic trend showed that extreme ideologies of both Liberals and Conservatives expressed a higher negative sentiment than Moderates, with Conservatives expressing more negative sentiment than Liberals. Compared to Conservative tweets, we found the expression of Liberal tweets to be rooted in a wider set of moral values, associated with moral foundations of care (getting the vaccine for protection), fairness (having access to the vaccine), liberty (related to the vaccine mandate), and authority (trusting the vaccine mandate imposed by the government). Conservative tweets were found to be associated with harm (around safety of the vaccine) and oppression (around the government mandate). Furthermore, political ideology was associated with the expression of different meanings for the same words, e.g. “science” and “death.” Our results inform public health outreach communication strategies to best tailor vaccine information to different groups.more » « less
-
Since the start of the COVID-19 pandemic, disruptions have been experienced in many supply chains, particularly in personal protective equipment, testing kits, and even essential household goods. Effective vaccines to protect against COVID-19 were approved for emergency use in the United States in late 2020, which led to one of the most extensive vaccination campaigns in history. We continuously collect data on vaccine allocation, shipment and distribution, administration, and inventory in the United States, covering the entire vaccination campaign. In this article, we describe some data sets that we collaborated to obtain. We are publishing the data and making them freely available to researchers, media organizations, and other stakeholders so that others may use the data to develop insights about the distribution and wastage of vaccines during the current pandemic or to provide an informed future pandemic response. This article gives an overview of vaccine distribution logistics in the United States, describes the data we obtain, outlines how they may be accessed and used by others, and describes some high-level analyses demonstrating some aspects of the data (for data collected during January 1, 2021–March 31, 2021). This article also provides directions for future research using the collected data. Our goal is two-fold: (i) We would like the data to be used in many creative ways to inform the current and future pandemic response. (ii) We also want to inspire other researchers to make their data publicly available in a timely manner.more » « less
-
null (Ed.)Several COVID-19 vaccines have been on the market since early 2021 and may vary in their effectiveness and safety. This study characterizes hesitancy about accepting COVID-19 vaccines among parents in Shanghai, China, and identifies how sensitive they are to changes in vaccine safety and effectiveness profiles. Schools in each township of Minhang District, Shanghai, were sampled, and parents in the WeChat group of each school were asked to participate in this cross-sectional Internet-based survey. Parents responded to questions about hesitancy and were given information about five different COVID-19 vaccine candidates, the effectiveness of which varied between 50 and 95% and which had a risk of fever as a side effect between 5 and 20%. Overall, 3673 parents responded to the survey. Almost 90% would accept a vaccine for themselves (89.7%), for their child (87.5%) or for an elderly parent (88.5%) with the most ideal attributes (95% effectiveness with 5% risk of fever). But with the least ideal attributes (50% effectiveness and a 20% risk of fever) these numbers dropped to 33.5%, 31.3%, and 31.8%, respectively. Vaccine hesitancy, age at first child’s birth, and relative income were all significantly related to sensitivity to vaccine safety and effectiveness. Parents showed a substantial shift in attitudes towards a vaccine based on its safety and effectiveness profile. These findings indicate that COVID-19 vaccine acceptance may be heavily influenced by how effective the vaccine actually is and could be impeded or enhanced based on vaccines already on the market.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/vaccines10091486
