Vaccines | Free Full-Text | Incidence and Nature of Short-Term Adverse Events following COVID-19 Second Boosters: Insights from Taiwan’s Universal Vaccination Strategy
2. Materials and Methods
2.1. Taiwan’s Vaccination Program for Booster Vaccines
Taiwan’s booster vaccine program, distinguished by its high vaccination rates (first dose coverage at 93.8%, second at 89.06%, third at 76.9%, and fourth at 25% on 25 December 2023), adopts a comprehensive and inclusive approach. The government’s policy encourages staggered booster vaccinations for the entire population, a contrast to the strategies of other countries that focus primarily on high-risk groups. Integral to this program is a mix-and-match strategy, especially for booster doses, recommending mRNA or subunit vaccines following initial viral vector vaccines to enhance immune response. This strategy adapts to the availability of vaccines, exemplified by the predominant use of the Moderna BA.1 variant vaccine during the fourth dose rollout, due to its availability and the depletion of other brands. The decision for administering the second booster is informed by immunological evidence, allowing for its administration three months after the first booster. A significant focus of the research is the prevalent use of the mRNA1273 (Moderna COVID-19 vaccine, Spikevax (Cambridge, MA, USA)) vaccine in the booster program, particularly notable during the administration of the second booster that included the bivalent version of the Moderna COVID-19 vaccine (vaccine against original strain and BA.4/5 variant, mRNA-1273.214 in Taiwan). This scenario offers a unique opportunity providing insights into the occurrence of adverse events in a real-world context.
2.2. Vaccine Adverse Event Reporting System (VAERS) in Taipei Veterans General Hospital
A key aspect of this approach is the mandatory reporting of any symptoms by all vaccine recipients, regardless of whether they experience any. This inclusive reporting system guarantees a detailed accumulation of data regarding post-vaccination effects, thereby enhancing the precision and dependability of the study.
2.3. Study Design
This cross-sectional study investigated the vaccination status and associated adverse events reported over a three-month period at the end of 2022 at the vaccination site of Taipei Veterans General Hospital. The adverse events were categorized as severe and non-severe by the researchers. The study data included basic demographic information of the participants, vaccination details, and descriptions of any adverse event. The analysis aimed to explore the correlation between vaccine recipients who experienced adverse events and those who did not, examining potential influencing factors.
2.4. Data Sources
Data collection spanned from the announcement of the second booster (fourth dose)’s availability to citizens and foreign residents over 18 years old on 27 October 2022 until 19 January 2023. Patients receiving vaccines underwent thorough medical examinations, including checks for allergic reactions, acute infection symptoms, and major vaccine-related adverse events. Post-vaccination, patients were provided with a Chinese-language Google Form questionnaire, accessible via a QR code, to report any adverse events within seven days of vaccination. The questionnaire included demographics, vaccine brand choice for the second booster, and any adverse event experienced. To ensure privacy, gender was not included in the questionnaire. The information was anonymized upon submission, with each respondent limited to one submission. This study, approved by the IRB of Taipei Veterans General Hospital (IRB 2022-12-005AC#1), ensured comprehensive data collection while maintaining participant confidentiality.
2.5. Study Population
2.6. Basic Demographic Information and Vaccination History
Basic information, including respondents’ age and vaccination history, including the brand and time of each dose of vaccine, were extracted from the VAERS. First boosters and second boosters with the same brand of boosters were considered as homologous, and were otherwise classified as heterologous. Vaccines were further divided into two groups of “mRNA1273 (Moderna)” and “others” because of the high share of mRNA1273 vaccines.
2.7. Classification of AEs, Serious Adverse Events (SAEs), and Non-Serious Adverse Events (NSAEs)
Adverse event reports were self-submitted by participants with settled options in the questionnaire and also their own descriptions. Regardless of primary doses, only AEs after the first booster were considered. The responses were categorized by Lin, C.H. and Chen, Y.C. based on the questionnaire’s design. Symptoms potentially related to the cardiovascular system (like chest tightness or difficulty breathing) were classified as Serious Adverse Events (SAEs). Other symptoms, including localized reactions at the injection site, flu-like symptoms, rapid heartbeat, gastrointestinal issues, and muscle aches, were categorized as Non-Serious Adverse Events (NSAEs). This classification was utilized to analyze the correlations and potential influencing factors between vaccine recipients who experienced adverse events (both SAEs and NSAEs) and those who did not report any adverse events.
2.8. Definition of Repeated Adverse Events
Repeated adverse events (repeated AEs) refers to the occurrence of adverse events following each subsequent dose of the COVID-19 vaccine. This category is particularly focused on analyzing whether individuals who experienced AEs after one dose are more likely to experience similar events following subsequent doses. Cumulative risk of AEs (cumulative AEs) assesses whether the likelihood or severity of adverse events increases with each subsequent dose of the vaccine. This concept is crucial for evaluating the long-term safety of the vaccination, especially in a regime involving multiple booster doses. In the current study, we investigated incidence-dependent cumulative risk by evaluating whether the incidence of AEs increases with additional doses.
2.9. Statistical Analysis
To estimate the incidence rates of AEs, we employed point estimation using a binomial distribution to calculate the incidence rates (IRs) and 95% confidence interval (95% CI) of AEs for each category. We used the Fisher exact test to compare the effects of various factors and identify the factors associated with the occurrence of AEs after the second booster. Furthermore, Poisson regression analysis was used to identify factors associated with AEs following the second booster. Incidence rate ratios (IRRs) were used to evaluate the effect of association. To test repeated occurrences of AEs, the McNemar test was used to explore the association between first AEs and second AEs. We examined the IRs of first AEs and second AEs to evaluate the cumulative risk of AEs. All statistics were analyzed using R (R-4.3.2 for Windows); a p-value < 0.05 was considered statistically significant.
To address widespread public concerns about adverse events (AEs) due to repeated vaccinations, this study analyzed VAERS data from Taipei Veterans General Hospital to explore the AEs following the administration of the second COVID-19 booster dose. The incidence rates of adverse events (AEs) were relatively high, at 25.6% after the first booster and 24.9% after the second. Most notably, these AEs were predominantly non-serious, with symptoms such as injection site pain and fatigue being the most common. We observed the pattern of adverse events (AEs) following COVID-19 booster vaccinations to be repetitive rather than cumulative, where individuals who experienced an AE following the first booster were more likely to report AEs after the second booster. This finding underscores the importance of considering previous AEs, the brand of the second booster, and the booster combination in devising personalized vaccination strategies. These results are vital for health providers and enhancing the understanding of vaccine safety, particularly in the context of administering booster doses.
Cautions are needed for interpretation the current result. The reliance on self-reported data in our research might have led to an overestimation of the incidence rates of adverse events. This is particularly relevant as self-reported data can vary in accuracy and completeness, which may skew the true incidence of these events. It is important to note that our findings predominantly apply to common and minor adverse events, given that the number of cases reported was relatively small. Therefore, these results may not be generalizable to rare and severe adverse events. This limitation underscores the need for further studies with more robust data collection methods to accurately assess the incidence of both common and rare adverse events following COVID-19 booster vaccinations.
Moreover, there are still some limitations to the current study. First, a significant limitation of this study is reporting bias. The reliance on self-reported data means patients without adverse events may be less inclined to report their status, potentially leading to an overestimation of the incidence of adverse events. This bias can skew the results towards those who experienced more noticeable or bothersome symptoms. Moreover, a significant limitation of this study is the absence of gender data in the questionnaire. The lack of gender-specific information precludes analysis of gender differences in vaccine responses, this gap in data may impact the study’s relevance to diverse populations. Secondly, the study’s methodology is susceptible to recall bias. Since data collection is based on participants’ recollections of their symptoms and the timeline of these symptoms post-vaccination, participants may forget minor symptoms or misremember the severity and timing of their symptoms. Third, the intensity of discomfort or severity of adverse events in this study was subjectively evaluated by the participants themselves, rather than through objective assessment by medical experts. This subjective evaluation can lead to a variation in the reported intensity of symptoms. Fourth, the study’s findings may not be generalizable to the broader population due to the limited sample size and the specific demographic characteristics of the study participants. Larger and more diverse sample sizes are needed to validate these findings across different populations. Fifth, the study does not account for all possible confounding factors, such as underlying health conditions, concurrent medication use, or previous exposure to COVID-19, which can influence the occurrence and reporting of adverse events. Sixth, the reliance on online questionnaires for data collection may introduce a selection bias, as it excludes individuals without internet access or those who are less technologically inclined. Seventh, the study establishes a temporal association between vaccination and the occurrence of adverse events but does not prove causality. Further investigation is needed to establish a direct causal relationship. Furthermore, our study did not include data on participants’ prior infections with COVID-19, nor did it encompass information regarding their comorbidities, limiting our ability to analyze the impact of previous COVID-19 infections and existing health conditions on vaccine response and adverse events.
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