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1. On the relationship between conspiracy theory beliefs, misinformation, and vaccine hesitancy

   https://doi.org/10.1371/journal.pone.0276082  

   Enders, Adam M. ; Uscinski, Joseph ; Klofstad, Casey ; Stoler, Justin ( October 2022 , PLOS ONE)

   Jonason, Peter Karl (Ed.)

   At the time of writing, nearly one hundred published studies demonstrate that beliefs in COVID-19 conspiracy theories and misinformation are negatively associated with COVID-19 preventive behaviors. These correlational findings are often interpreted as evidence that beliefs in conspiracy theories and misinformation are exogenous factors that shape human behavior, such as forgoing vaccination. This interpretation has motivated researchers to develop methods for “prebunking,” “debunking,” or otherwise limiting the spread of conspiracy theories and misinformation online. However, the robust literatures on conspiracy theory beliefs, health behaviors, and media effects lead us to question whether beliefs in conspiracy theories and misinformation should be treated as exogenous to vaccine hesitancy and refusal. Employing U.S. survey data (n = 2,065) from July 2021, we show that beliefs in COVID-19 conspiracy theories and misinformation are not only related to COVID-19 vaccine hesitancy and refusal, but also strongly associated with the same psychological, social, and political motivations theorized to drive COVID-19 vaccine hesitancy and refusal. These findings suggest that beliefs in conspiracy theories and misinformation might not always be an exogenous cause, but rather a manifestation of the same factors that lead to vaccine hesitancy and refusal. We conclude by encouraging researchers to carefully consider modeling choices and imploring practitioners to refocus on the worldviews, personality traits, and political orientations that underlie both health-related behaviors and beliefs in conspiracy theories and misinformation. 

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2. COVID-19 risk perception and vaccine acceptance in individuals with self-reported chronic respiratory or autoimmune conditions

   https://doi.org/10.1186/s13223-023-00791-6  

   Smith, Brianna A. ; Ricotta, Emily E. ; Kwan, Jennifer L. ; Evans, Nicholas G. ( May 2023 , Allergy, Asthma & Clinical Immunology)

   COVID-19 disproportionately affects those with preexisting conditions, but little research has determined whether those with chronic diseases view the pandemic itself differently - and whether there are differences between chronic diseases. We theorized that while individuals with respiratory disease or autoimmune disorders would perceive greater threat from COVID-19 and be more supportive of non-pharmaceutical interventions (NPIs), those with autoimmune disorders would be less likely to support vaccination-based interventions.

   We conducted a two-wave online survey conducted in February and November 2021 asking respondents their beliefs about COVID-19 risk perception, adoption and support of interventions, willingness to be vaccinated against COVID-19, and reasons for vaccination. Regression analysis was conducted to assess the relationship of respondents reporting a chronic disease and COVID-19 behaviors and attitudes, compared to healthy respondents adjusting for demographic and political factors.

   In the initial survey, individuals reporting a chronic disease had both stronger feelings of risk from COVID-19 as well as preferences for NPIs than healthy controls. The only NPI that was still practiced significantly more compared to healthy controls in the resample was limiting trips outside of the home. Support for community-level NPIs was higher among individuals reporting a chronic disease than healthy controls and remained high among those with respiratory diseases in sample 2. Vaccine acceptance produced more divergent results: those reporting chronic respiratory diseases were 6% more willing to be vaccinated than healthy controls, while we found no significant difference between individuals with autoimmune diseases and healthy controls. Respondents with chronic respiratory disease and those with autoimmune diseases were more likely to want to be vaccinated to protect themselves from COVID-19, and those with an autoimmune disease were more likely to report fear of a bad vaccine reaction as the reason for vaccine hesitancy. In the resample, neither those with respiratory diseases nor autoimmune diseases reported being more willing to receive a booster vaccine than healthy controls.

   It is not enough to recognize the importance of health in determining attitudes: nuanced differences between conditions must also be recognized.

    

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3. COVID‐19 vaccination and decreased death rates: A county‐level study in Pennsylvania

   https://doi.org/10.1002/jmv.28883  

   Ramunno, Maria ; Savitz, Ryan ( July 2023 , Journal of Medical Virology)

   In this paper we examine the relationship between vaccination against COVID‐19 and both the death rate from COVID‐19 and the rate of COVID‐19 spread. Our goal is determine if vaccination is associated with reduced death and/or spread of disease at the local level. This analysis was conducted at the county level in the state of Pennsylvania, United States of America, with data that were collected during the first half of 2022 from the state of Pennsylvania's Covid Dashboard (COVID‐19 Data for Pennsylvania (pa.gov). This study finds the vaccines to be highly effective in preventing death from Corona virus, even at a time when there was a mismatch between the vaccines and the prevalent variants. Specifically, a 1% increase in vaccination rate was found to correspond to a 0.751% decrease in death rate (95% confidence interval [0.236%, 1.266%]). Given that, during this time period, the vaccines being used were not geared specifically toward the common variants at that time, we found no statistically significant relationship between disease spread and vaccination rate at the county level. These results support previous findings from across the world that Covid vaccination is highly efficacious in preventing death from the disease. Even during a time when vaccine design was not optimally matched with the prevailing strains, vaccination was found to reduce death rate. Hence, improving global vaccine availability is vitally important, to achieve necessary outcomes.

    

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4. Topics and Sentiments of Public Concerns Regarding COVID-19 Vaccines: Social Media Trend Analysis

   https://doi.org/10.2196/30765  

   Monselise, Michal ; Chang, Chia-Hsuan ; Ferreira, Gustavo ; Yang, Rita ; Yang, Christopher C ( January 2021 , Journal of Medical Internet Research)

   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. 

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5. Promoting data harmonization to evaluate vaccine hesitancy in LMICs: approach and applications

   https://doi.org/10.1186/s12874-023-02088-z  

   Rego, Ryan T. ; Zhukov, Yuri ; Reneau, Kyrani A. ; Pienta, Amy ; Rice, Kristina L. ; Brady, Patrick ; Siwo, Geoffrey H. ; Wachira, Peninah Wanjiku ; Abubakar, Amina ; Kollman, Ken ; et al ( December 2023 , BMC Medical Research Methodology)

   Factors influencing the health of populations are subjects of interdisciplinary study. However, datasets relevant to public health often lack interdisciplinary breath. It is difficult to combine data on health outcomes with datasets on potentially important contextual factors, like political violence or development, due to incompatible levels of geographic support; differing data formats and structures; differences in sampling procedures and wording; and the stability of temporal trends. We present a computational package to combine spatially misaligned datasets, and provide an illustrative analysis of multi-dimensional factors in health outcomes.

   We rely on a new software toolkit, Sub-National Geospatial Data Archive (SUNGEO), to combine data across disciplinary domains and demonstrate a use case on vaccine hesitancy in Low and Middle-Income Countries (LMICs). We use data from the World Bank’s High Frequency Phone Surveys (HFPS) from Kenya, Indonesia, and Malawi. We curate and combine these surveys with data on political violence, elections, economic development, and other contextual factors, using SUNGEO. We then develop a stochastic model to analyze the integrated data and evaluate 1) the stability of vaccination preferences in all three countries over time, and 2) the association between local contextual factors and vaccination preferences.

   In all three countries, vaccine-acceptance is more persistent than vaccine-hesitancy from round to round: the long-run probability of staying vaccine-acceptant (hesitant) was 0.96 (0.65) in Indonesia, 0.89 (0.21) in Kenya, and 0.76 (0.40) in Malawi. However, vaccine acceptance was significantly less durable in areas exposed to political violence, with percentage point differences (ppd) in vaccine acceptance of -10 (Indonesia), -5 (Kenya), and -64 (Malawi). In Indonesia and Kenya, although not Malawi, vaccine acceptance was also significantly less durable in locations without competitive elections (-19 and -6 ppd, respectively) and in locations with more limited transportation infrastructure (-11 and -8 ppd).

   With SUNGEO, researchers can combine spatially misaligned and incompatible datasets. As an illustrative example, we find that vaccination hesitancy is correlated with political violence, electoral uncompetitiveness and limited access to public goods, consistent with past results that vaccination hesitancy is associated with government distrust.

    

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