Addressing vaccine hesitancy and misinformation amidst Japan’s self-amplifying mRNA COVID-19 vaccine rollout
Bibliographic record
Abstract
As of 1 October 2024, Japan implemented a revised coronavirus disease 2019 (COVID-19) vaccination strategy, shifting from a fully publicly funded model to one where costs are partially or fully borne by recipients. This new annual program targets individuals aged 65 and above, and those aged 60-64 at higher risk of severe illness, requiring them to cover some vaccination expenses. For others, the vaccine remains voluntary and self-funded. Notably, this program includes the world's first self-amplifying mRNA COVID-19 vaccine, zapomeran (Kostaive®, Meiji Seika Pharma Co., Ltd.) approved on 28 November 2023. This vaccine's innovative self-amplifying feature has ignited debates across media platforms, with widespread public division and confusion. The new vaccine encodes replicase proteins and the spike protein antigen, allowing for reduced doses of 5 µg compared to traditional mRNA vaccines that require 30 µg. However, concerns have been raised, primarily around four misconceptions: shedding, perpetual mRNA replication, integration into human DNA, and its non-approval situation outside Japan. Despite these scientifically unfounded concerns, they have fueled vaccine hesitancy, influenced by misleading information spreading rapidly on social media. Alarmingly, biased statements from an academic university and an academic society aggravate this hesitancy. Japan's history has experienced vaccine hesitancies in human papillomavirus and diphtheria-tetanus-pertussis vaccination cases. To prevent a public health crisis, it is crucial that governmental bodies and academic groups actively counter misinformation, advocating for evidence-based understanding and encouraging vaccination among those most at risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".