Predictors of Seasonal Influenza Vaccination Willingness among High-Risk Populations Three Years after the Onset of the COVID-19 Pandemic

A Live Attenuated H1N1 Influenza Vaccine Based on the Mutated M Gene

The influenza vaccines currently approved for clinical use mainly include inactivated influenza virus vaccines and live attenuated influenza vaccines (LAIVs). LAIVs have multiple advantages, such as ease of use and strong immunogenicity, and can provide cross-protection. In this study, the M gene of the PR8 virus was mutated as follows (G11T, C79G, G82C, C85G, and C1016A), and a live attenuated influenza virus containing the mutated M gene was rescued and obtained using reverse genetic technology as a vaccine candidate. The replication ability of the rescued virus was significantly weakened in both MDCK cells and mice with attenuated virulence. Studies on immunogenicity found that 1000 TCID50 of mutated PR8 (mPR8) can prime strong humoral and cellular immune responses. Single-dose immunization of 1000 TCID50 mPR8 was not only able to counter the challenge of the homologous PR8 virus but also provided cross-protection against the heterologous H9N2 virus.

Impact of COVID-19 on Influenza and Pneumococcal Vaccination of Psoriatic Patients in Germany: Results from Vac-Pso

BACKGROUND

Suboptimal influenza and pneumococcal vaccination rates have been reported before the COVID-19 pandemics in certain populations at risk for severe infection. The aim of this longitudinal cohort study was to investigate changes in influenza and pneumococcal vaccination rates and patient perceptions in patients with psoriasis (PsO) before and during the pandemic.

METHODS

Data on vaccination, patient and disease characteristics, comorbidity, and patient perceptions were collected with questionnaires before and during the pandemic approximately one year later.

RESULTS

Over the whole cohort who participated in the follow-up visit (n = 287; 59.2% male; mean age: 56.3 years), both influenza and pneumococcal lifetime vaccination prevalences increased significantly from 50.5% to 66.2% and from 16.0% to 41.5%, respectively. A total of 88.5% of PsO patients were interested in a COVID-19 vaccination or had already received it. The reasons for and against vaccinations changed significantly before and during the pandemic.

CONCLUSIONS

Despite a promising increase in the vaccination prevalence in our PsO cohort, it remains important that awareness for vaccinations is encouraged and closely monitored in future research, particularly in populations at risk.

Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study

Background

Influenza A virus have a distinctive ability to exacerbate SARS-CoV-2 infection proven by in vitro studies. Furthermore, clinical evidence suggests that co-infection with COVID-19 and influenza not only increases mortality but also prolongs the hospitalization of patients. COVID-19 is in a small-scale recurrent epidemic, increasing the likelihood of co-epidemic with seasonal influenza. The impact of co-infection with influenza virus and SARS-CoV-2 on the population remains unstudied.

Method

Here, we developed an age-specific compartmental model to simulate the co-circulation of COVID-19 and influenza and estimate the number of co-infected patients under different scenarios of prevalent virus type and vaccine coverage. To decrease the risk of the population developing severity, we investigated the minimum coverage required for the COVID-19 vaccine in conjunction with the influenza vaccine, particularly during co-epidemic seasons.

Result

Compared to the single epidemic, the transmission of the SARS-CoV-2 exhibits a lower trend and a delayed peak when co-epidemic with influenza. Number of co-infection cases is higher when SARS-CoV-2 co-epidemic with Influenza A virus than that with Influenza B virus. The number of co-infected cases increases as SARS-CoV-2 becomes more transmissible. As the proportion of individuals vaccinated with the COVID-19 vaccine and influenza vaccines increases, the peak number of co-infected severe illnesses and the number of severe illness cases decreases and the peak time is delayed, especially for those >60 years old.

Conclusion

To minimize the number of severe illnesses arising from co-infection of influenza and COVID-19, in conjunction vaccinations in the population are important, especially priority for the elderly.

The Uptake of Pneumococcal and Seasonal Influenza Vaccinations Based on Perceptions and Attitudes Toward the COVID-19 Vaccine Among Patients With Diabetes

Objective In this study, we aimed to assess the rates of pneumococcal and seasonal influenza vaccinations among elderly and nonelderly diabetes patients and examine their perceptions and attitudes toward the coronavirus disease 2019 (COVID-19) vaccine. Methods A single-center study was conducted among patients with diabetes, employing a structured survey encompassing sociodemographic data, vaccination records, and the COVID-19 vaccine perception and attitude scale. Results Among the 280 diabetes patients in our study, the vaccination rates for COVID-19, seasonal influenza, and pneumococcal vaccines were 96.1%, 16.8%, and 17.5%, respectively. A higher cumulative dosage of the COVID-19 vaccine was associated with older age (r = 0.463; p<0.001), increased safety score (r = 0.479; p<0.001), and lower conspiracy theory score (r = -0.336; p<0.001). Participants who had received COVID-19 and influenza vaccines were observed to have significantly higher safety scores related to COVID-19 vaccines (p<0.001; d = 2.381 and p = 0.008; d = 0.525, respectively). Notably, vaccination rates for influenza and pneumococcus were significantly different between nonelderly and elderly patients (8.7% vs. 29.6%; p<0.001 and 13.4% vs. 24.1%; p = 0.022). Elderly patients with diabetes were 3.3 times more likely to receive the influenza vaccine than nonelderly participants [odds ratio (OR) = 3.319; 95% confidence interval (CI) = 1.592 - 6.920; p = 0.001] and had a higher safety score related to COVID-19 vaccines (OR = 1.076; 95% CI = 1.011 - 1.146; p = 0.021). Conclusions Both influenza and pneumococcal vaccination rates were below the desired targets in this study. The vaccination rates among the nonelderly diabetes population suggest that this group may be more likely to neglect to receive vaccination compared to the elderly diabetes population. The association between vaccination rates and post-pandemic safety perceptions highlights the critical need to implement public health strategies specifically designed to address and improve safety-related information dissemination.

Exploring Perceptions and Practices Regarding Adult Vaccination against Seasonal Influenza, Tetanus, Pneumococcal Disease, Herpes Zoster and COVID-19: A Mixed-Methods Study in Greece

We aimed to document vaccination coverage for five vaccines, predictors of each vaccine's uptake and attitudes regarding adult vaccination. Adults visiting four pharmacies were randomly invited to participate during summer 2022. Among 395 participants (mean age 51.2 years, range 19-96), vaccination rates were 78.1% for influenza and 25.8% for herpes zoster (≥60 years old), 64.3% for pneumococcal disease (≥65 years old), 33.1% for tetanus, while 11.4% had received two and 74.8% ≥3 COVID-19 vaccine doses. Half of participants (50.1%) voiced some degree of hesitancy, and 1.3% were refusers. The strongest predictor of each vaccine's uptake was doctor's recommendation (OR range 11.33-37.66, p < 0.001) and pharmacist's recommendation (4.01-19.52, p < 0.05), except for the COVID-19 vaccine, where the Attitude Towards Adult VACcination (ATAVAC) value of adult vaccination subscale's score was the only predictor (OR: 5.75, p < 0.001). Regarding insufficient coverage, thematic content analysis revealed seven main themes. Insufficient knowledge, the absence of health professionals' recommendation, perception of low susceptibility to disease, negligence and dispute of vaccine effectiveness were universal themes, whereas safety concerns and distrust in authorities were reported solely for COVID-19 vaccination. Designing public interventions aiming to increase trust in adult vaccination is essential in the aftermath of the COVID-19 pandemic. Health professionals' role in recommending strongly adult vaccination is crucial.

Comparison of Impressions of COVID-19 Vaccination and Influenza Vaccination in Japan by Analyzing Social Media Using Text Mining

The aim of this study was to compare impressions of COVID-19 vaccination and influenza vaccination in Japan by analyzing social media (Twitter®) using a text-mining method. We obtained 10,000 tweets using the keywords "corona vaccine" and "influenza vaccine" on 15 December 2022 and 19 February 2023. We then counted the number of times the words were used and listed frequency of these words by a text-mining method called KH Coder. We also investigated concepts in the data using groups of words that often appeared together or groups of documents that contained the same words using multi-dimensional scaling (MDS). "Death" in relation to corona vaccine and "severe disease" for influenza vaccine were frequently used on 15 December 2022. The number of times the word "death" was used decreased, "after effect" was newly recognized for corona vaccine, and "severe disease" was not used in relation to influenza vaccine. Through this comprehensive analysis of social media data, we observed distinct variations in public perceptions of corona vaccination and influenza vaccination in Japan. These findings provide valuable insights for public health authorities and policymakers to better understand public sentiment and tailor their communication strategies accordingly.

Examining the Negative Sentiments Related to Influenza Vaccination from 2017 to 2022: An Unsupervised Deep Learning Analysis of 261,613 Twitter Posts

Several countries are witnessing significant increases in influenza cases and severity. Despite the availability, effectiveness and safety of influenza vaccination, vaccination coverage remains suboptimal globally. In this study, we examined the prevailing negative sentiments related to influenza vaccination via a deep learning analysis of public Twitter posts over the past five years. We extracted original tweets containing the terms 'flu jab', '#flujab', 'flu vaccine', '#fluvaccine', 'influenza vaccine', '#influenzavaccine', 'influenza jab', or '#influenzajab', and posted in English from 1 January 2017 to 1 November 2022. We then identified tweets with negative sentiment from individuals, and this was followed by topic modelling using machine learning models and qualitative thematic analysis performed independently by the study investigators. A total of 261,613 tweets were analyzed. Topic modelling and thematic analysis produced five topics grouped under two major themes: (1) criticisms of governmental policies related to influenza vaccination and (2) misinformation related to influenza vaccination. A significant majority of the tweets were centered around perceived influenza vaccine mandates or coercion to vaccinate. Our analysis of temporal trends also showed an increase in the prevalence of negative sentiments related to influenza vaccination from the year 2020 onwards, which possibly coincides with misinformation related to COVID-19 policies and vaccination. There was a typology of misperceptions and misinformation underlying the negative sentiments related to influenza vaccination. Public health communications should be mindful of these findings.