Covid-19 vaccines and treatments: we must have raw data, now
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Data should be fully and immediately available for public scrutiny
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These study limitations all stem from the fact that the raw data from COVID-19 vaccine clinical trials are not publicly available.
“These study limitations all stem from the fact that the raw data from COVID-19 vaccine clinical trials are not publicly available. [45,46].”
From Serious adverse events of special interest following mRNA COVID-19 vaccination in randomized trials in adults (2022) · cites this paper as [46]
The section “Data should be fully and immediately available for public scrutiny” says that participant-level data underlying COVID-19 vaccine trials remain inaccessible to doctors, researchers, and the public. The paper does not establish that all of the citing study’s limitations stem from that lack of access. (LLM, conf=0.86)
Experimental — accuracy not yet measuredAs we approach 2 years after release of COVID-19 vaccines, participant-level data remain inaccessible.
“Unfortunately, as we approach 2 years after release of COVID-19 vaccines, participant level data remain inaccessible. [45,46].”
From Serious adverse events of special interest following mRNA COVID-19 vaccination in randomized trials in adults (2022) · cites this paper as [46]
The 'Data should be fully and immediately available for public scrutiny' section says anonymised participant-level trial data remained inaccessible despite the global vaccine rollout. The paper was published in 2022 and predicts that access may remain restricted for years, but it does not establish the data’s availability at the citing sentence’s nearly two-year mark. (LLM, conf=0.82)
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Cites
No references could be resolved yet.
Research works printed but not linked: 22
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Cited by
Sorted by citations
Fraiman, J., Erviti, J., Jones, M., Greenland, S., Whelan, P., Kaplan, R. M., & Doshi, P. (2022) · Vaccine · doi:10.1016/j.vaccine.2022.08.036 · Cited by 228 · see citing works
“[45,46].”
Self-citationLi, W., Liu, X., Zhang, Q., Shi, L., Zhang, J.-X., Zhang, X., Luan, J., Li, Y., Xu, T., Zhang, R., et al. (2026) · Accountability in Research · doi:10.1080/08989621.2025.2481943 · Cited by 1 · see citing works
- Authors
- Doshi, P., Godlee, F., & Abbasi, K.
- Affiliations
- BMJ Group (United Kingdom) (GB)
- Corresponding author
- Doshi, Peter
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2022-01-19
- Volume
- 376
- Pages
- o102
- ISSN
- 1756-1833 (ISSN-L)
- OpenAlex
- W4205793382
- Cited by
- 63
- References
- 0
- Citations by year
- 2025: 4 · 2024: 6 · 2023: 26 · 2022: 27
- FWCI
- 7.70
- Type
- journal article
- Language
- en
- Update notices
- correction (2022-01-24)
- Open access
- bronze
- doi.org
- Licence
- www.bmj.com/company/legal-information/terms-conditions/legal-information/tdm-licencepolicy (tdm)
- Locations
- BMJ (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Moderna
- Johnson and Johnson
- Health Canada
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Social Sciences › Decision Sciences › Information Systems and Management › Academic Publishing and Open Access
- Social Sciences › Health › Vaccine Coverage and Hesitancy
- Keywords
- COVID-19 vaccines, COVID-19 treatment, raw data availability, data transparency, public scrutiny, clinical trial data, open data
- MeSH terms
- Public Reporting of Healthcare Data, COVID-19, SARS-CoV-2, COVID-19 Vaccines, COVID-19 Drug Treatment, Humans
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