NIH COVID-19 treatment analysis

• NIH reviewed very few RCTs for low-cost treatments, while claiming insufficient evidence
• Only three high-profit drugs from top lobbying companies were found beneficial

Authority review was extremely slow and overlooked most research Official treatment recommendations were often made based on a small fraction of the evidence, with substantial bias in the selection of studies. Just as 78% of experts polled regarding the origin of COVID-19 were not familiar with the DEFUSE protocol4, experts on COVID-19 treatments were not familiar with much of the key evidence. In some cases, recommendations were made without reviewing any clinical evidence, for example the US FDA recommended against ivermectin in an article that stated "The FDA has not reviewed data to support use of ivermectin in COVID-19"5. In cases where the people involved in recommendations are known, they were often busy professionals that could not realistically have time to carefully review all evidence6.

NIH reviewed only 2.9% of the 1,207 studies for these treatments

reviewednot reviewed
TreatmentReviewedStudiesPercent reviewed
Recommended against
Ivermectin1110610%
Insufficient evidence
Vitamin D51383.6%
Metformin41143.5%
Vitamin C6728.3%
Zinc3407.5%
Not analyzed
HCQ04260%
Diet0300%
PVP-I0210%
Sleep0170%
CPC040%

Analysis of NIH COVID-19 treatment guidelines. NIH added a second reference list with 21 extra ivermectin studies, but no summary, comments, or evidence that they were reviewed. The studies NIH selected are not higher quality—many of the lowest quality and most flawed studies are included.

Table 1. The NIH did not review most evidence for low-cost treatments. The studies they did review include very low-quality studies.
With 500+ therapeutic targets and 12,000+ proposed treatments, what is the probability that only 3 high-profit drugs from companies with strong US lobbying are beneficial?
NIH reviews NIH treatment reviews were done by a panel of 40+ external experts with extensive conflicts of interest towards high-profit treatments6,7. Out of 12,250 proposed treatments8, they found only three high-profit drugs from top lobbying companies to be beneficial for early treatment(a). Most others received either "insufficient evidence" or no review at all, despite extensive unreviewed evidence.
Across all low-cost treatments (within the 227 we cover), the NIH only referenced 2% of the studies. For vitamin D, the NIH claims "insufficient evidence ... to recommend either for or against"9. No authors are listed, they provide only a brief narrative review, and they reference only 5 of the 138 controlled studies (41 RCTs). The state is similar or worse for other treatments (Table 1). The NIH provides no quantitative analysis for any of the treatments listed.
Considering RCTs for vitamin D, the NIH references only 410-13 of 41 (Figure 114). The NIH selection does not have above average relevance or quality, for example including two very late treatment studies using bolus doses of cholecalciferol11,12—a trifecta of poor design and low relevance compared to recommended use: early treatment is better, continuous dosing is more effective than bolus doses, and calcifediol, calcitriol, or analogs avoid long delays in conversion. They include none of the early treatment RCTs. We provide similar analysis for vitamin C15 and zinc16.
Some NIH treatment guideline panel members have been revealed by FOIA requests17-19. Many members have major conflicts of interest as summarized in the following table.

Conflicts of interest - NIH COVID-19 treatment guidelines

November 2026

9 of 9 authors have conflicts: 43 relationships with 13 entities.

Board or advisory rolePaymentsResearch fundingStock or equityAffiliation
AuthorConflicts
Prof. Adaora Adimora
  • Merckadvisory board1
  • Merckconsultant1
  • Merckresearch support2
  • Gileadconsultant; institution received research funding. “Aadimora AA has received consulting fees from Viiv, and Gilead and her institution has received funding from Gilead for her research.”3
  • Gileadresearch support4
  • MerckOpen Payments, $62,0005
  • GileadOpen Payments, $88,0005
Prof. Roger Bedimo
  • Merckadvisory board1
  • Gileadhonoraria4
  • MerckOpen Payments, $149,0006
  • SanofiOpen Payments, $76,0006
  • GileadOpen Payments, $23,0006
Prof. Rajesh Gandhi
  • Gileadgrants. “Dr. Gandhi reports grants and personal fees from Gilead, personal fees from Merck, grants and personal fees from Theratechnologies, grants from ViiV, grants from Janssen.”7
  • Gileadadvisory board and personal fees8
  • Merckadvisory board and personal fees4
  • Janssengrants7
  • MerckOpen Payments, $45,0009
  • GileadOpen Payments, $10,0009
Prof. David Glidden
  • Merckadvisory board2
  • Gileadconsultant4
Prof. Roy Gulick
  • Merckgrants; principal investigator of ACTG A5391, funded in part by Merck. “Roy M. Gulick, MD, MPH, has disclosed that he has received grants for clinical research from Abbott, Boehringer Ingelheim, Merck, Pfizer, Schering, and Tibotec, and has received grants for educational activities from Gilead and Monogram. Dr. Gulick has also disclosed that he has served as an ad-hoc advisor or consultant to Abbott, Boehringer Ingelheim, Bristol-Myers Squibb, Gilead, GlaxoSmithKline, Pfizer, Schering, and Tibotec.”10
  • Pfizergrants and ad-hoc advisor or consultant10 (deleted from current version11)
  • Gileadgrants and ad-hoc advisor or consultant10 (deleted from current version11)
  • GlaxoSmithKlinead-hoc advisor or consultant10 (deleted from current version11)
  • NIAID/NIHgrants12
Prof. Susanna Naggie
  • Gileadgrants and travel or meeting support8
  • AbbViegrants8
  • NIHgrants8
  • Vir Biotechnologyadvisory board1
  • Vir Biotechnologystockholder1
  • Ivermectin trial$155 million grant after the insufficient-evidence recommendation2
  • AbbVieOpen Payments, $2.4 million13
  • GileadOpen Payments, $1.2 million13
  • JanssenOpen Payments, $34,00013
  • MerckOpen Payments, $19,00013
Prof. Andrew Pavia
  • Merckconsultant4
  • Genentechconsultant4
  • GlaxoSmithKlineconsultant8
  • PfizerOpen Payments, $14,00014
  • MerckOpen Payments, $5,00014
  • JanssenOpen Payments, $4,00014
Dr. Stephen Cantrill
  • Gileadfaculty/primary author for Gilead-funded COVID-19 education released March 11, 2025 (NIH guidelines have not been updated since 2023)15
Dr. Timothy Uyeki
  • CDC/HHSCDC employee and Chief Medical Officer of the Influenza Division during COVID-19 guideline development; government institutional affiliation16
  1. NIH panel financial disclosure
  2. TrialSite News
  3. Adimora et al., International Journal of Maternal and Child Health and AIDS
  4. NIH guidelines archive, 27 Aug 2020
  5. Open Payments
  6. Open Payments
  7. NEJM disclosure supplement
  8. ICMJE disclosure form
  9. Open Payments
  10. Medscape disclosure, archived 2014
  11. Medscape disclosure, current version
  12. ACP Journals
  13. Open Payments
  14. Open Payments
  15. Clinical Care Options
  16. WHO, August 2023

Vitamin D RCTs missing in NIH analysis

November 2026
StudyImprovementRR · 95% CIOutcomeTreatmentControlRelative Risk
Early treatment31%0.69 · 0.53–0.9044/22861/22631% lower risk
Tau² = 0.00, I² = 0.0%, p = 0.0056
Entrenas Ca.. (RCT)85%0.15 · 0.01–2.93death0/502/26COVIDIOL< STUDY MISSING > Rastogi (RCT)53%0.47 · 0.24–0.92viral+6/1619/24SHADE< STUDY MISSING > Murai (DB RCT)−49%1.49 · 0.55–4.05death9/1196/118 Sabico (RCT)−192%2.92 · 0.12–69.43death1/380/35LD2< STUDY MISSING > Soliman (RCT)63%0.37 · 0.09–2.78death7/403/16< STUDY MISSING > Elamir (RCT)86%0.14 · 0.01–2.63death0/253/25 Maghbooli (DB RCT)40%0.60 · 0.15–2.38death3/535/53< STUDY MISSING > Leal-Martínez (RCT)86%0.14 · 0.03–0.80death1/407/40CT1< STUDY MISSING > Beigm.. (SB RCT)89%0.11 · 0.01–1.98death0/304/30ICU patients CT1< STUDY MISSING > Bishop (DB RCT)85%0.15 · 0.01–2.78progression0/653/69REsCue< STUDY MISSING > Cannata-An.. (RCT)−44%1.44 · 0.76–2.72death22/27415/269COVID-VIT-D< STUDY MISSING > Torres (SB RCT)−7%1.07 · 0.07–16.60death1/411/44LD2< STUDY MISSING > Mariani (DB RCT)−124%2.24 · 0.44–11.29death5/1152/103CARED Singh (DB RCT)45%0.55 · 0.30–1.01death11/4520/45Shade-S< STUDY MISSING > Karonova (RCT)86%0.14 · 0.01–2.66ICU0/563/54< STUDY MISSING > Cervero (SB RCT)−7%1.07 · 0.07–16.60death1/411/44LD2< STUDY MISSING > Zurita-C.. (SB RCT)79%0.21 · 0.03–1.59death1/206/25< STUDY MISSING > De Niet (DB RCT)65%0.35 · 0.04–3.10death1/213/22< STUDY MISSING > Lakkireddy (RCT)61%0.39 · 0.08–1.91death2/445/43see notes< STUDY MISSING > Sarhan (RCT)19%0.81 · 0.75–0.90death26/5830/58LD2< STUDY MISSING > Bychinin (DB RCT)27%0.73 · 0.47–1.14death19/5227/54COVID-VITICU patients< STUDY MISSING > Domazet B.. (RCT)21%0.79 · 0.55–1.13death30/7539/77ICU patients< STUDY MISSING > Jaun (DB RCT)50%0.50 · 0.04–4.53death1/392/39LD2< STUDY MISSING > Taslim (SB RCT)71%0.29 · 0.11–0.77oxygen4/3014/30LD2< STUDY MISSING > Salman (RCT)60%0.40 · 0.16–1.00death6/15015/150< STUDY MISSING > Seely (DB RCT)48%0.52 · 0.10–2.71progression2/424/44CT1< STUDY MISSING > Sanz (DB RCT)80%0.20 · 0.01–3.74death0/112/11< STUDY MISSING > Abdelhai (RCT)83%0.17 · 0.08–0.37death8/17022/80LD2< STUDY MISSING > Ganmaa (DB RCT)4%0.96 · 0.73–1.26misc.863 (n)884 (n)VIVID< STUDY MISSING >
Late treatment40%0.60 · 0.47–0.76167/2,623263/2,51240% lower risk
Tau² = 0.13, I² = 44.2%, p < 0.0001
Prophylaxis28%0.72 · 0.56–0.945/19,56017/21,04428% lower risk
Tau² = 0.00, I² = 0.0%, p = 0.015
All studies35%0.65 · 0.55–0.77216/22,411341/23,78235% lower risk
Tau² = 0.06, I² = 30.0%, p < 0.000100.511.52+
1 CT: study uses combined treatment
2 LD: comparison with low dose treatment
Rotate screen for more detailsIncrease width for more details
← Vitamin D
reduces risk
Increased
risk →
NIH ANALYSIS:
90% OF RCTs MISSING
Figure 1. NIH vitamin D analysis—37 RCTs missing.

Vitamin C RCTs missing in NIH analysis

November 2026
StudyImprovementRR · 95% CIOutcomeTreatmentControlRelative Risk
Early treatment30%0.70 · 0.54–0.9070/21046/12530% lower risk
Tau² = 0.00, I² = 0.0%, p = 0.0059
Late treatment19%0.81 · 0.70–0.9588/2,309163/1,94119% lower risk
Tau² = 0.02, I² = 31.2%, p = 0.0073
All studies20%0.80 · 0.69–0.92158/2,519209/2,06620% lower risk
Tau² = 0.02, I² = 30.9%, p = 0.001600.511.52+
1 CT: study uses combined treatment
Rotate screen for more detailsIncrease width for more details
← Vitamin C
reduces risk
Vitamin C
increases risk →
NIH ANALYSIS:
70% OF RCTs MISSING
Figure 2. NIH vitamin C analysis—14 RCTs missing.

Zinc RCTs missing in NIH analysis

November 2026
StudyImprovementRR · 95% CIOutcomeTreatmentControlRelative Risk
Early treatment21%0.79 · 0.45–1.4120/28925/28921% lower risk
Tau² = 0.00, I² = 0.0%, p = 0.44
Late treatment35%0.65 · 0.24–1.805/1069/11235% lower risk
Tau² = 0.00, I² = 0.0%, p = 0.42
Prophylaxis50%0.50 · 0.33–0.7434/69367/67550% lower risk
Tau² = 0.00, I² = 0.0%, p = 0.0006
All studies42%0.58 · 0.43–0.8059/1,088101/1,07642% lower risk
Tau² = 0.00, I² = 0.0%, p = 0.0007800.511.52+
1 OT: comparison with other treatment
2 CT: study uses combined treatment
Rotate screen for more detailsIncrease width for more details
← Zinc
reduces risk
Zinc
increases risk →
NIH ANALYSIS:
75% OF RCTs MISSING
Figure 3. NIH zinc analysis—6 RCTs missing.
Waiting for RCTs costs lives While the NIH examined few of the RCTs, they dismissed almost all observational studies. RCTs can provide significant advantages, however they show no benefit for COVID-19 and they introduce significantly delay. For the 227 treatments analyzed, there is no difference in results between RCTs and observational studies, RR 0.97 [0.91‑1.03]20 (Figure 4). Observational studies do not systematically over- or underestimate efficacy, as found in previous research21,22, and they provided confirmation of efficacy 8+ months faster. RCTs aim to equalize study groups, but add their own biases. For acute diseases with strong benefits for earlier treatment, the typical increased treatment delay adds a major confounding factor. Both RCTs and observational studies span the bias spectrum, from minimal to extreme. Studies must be evaluated individually. While observational studies require greater expertise to analyze, the advantages in practicality, cost, time, and ethics are substantial.
Across 227 treatments
Low-cost0.98 0.90‑1.06
High-profit0.92 0.84‑1.02
All treatments0.97 0.91‑1.03
0 0.5 1 1.5 2
← RCTs show
higher efficacy
RCTs show →
lower efficacy
Figure 4. For COVID-19 there is no significant difference between the results of observational studies and RCTs20.
Waiting for specific outcomes costs lives While patented treatments may be approved with a single non-clinical result23, authorities often dismiss results for low-cost treatments where studies report different outcomes. To avoid delay and unnecessary mortality, we must use all available evidence. Logically, minimizing viral replication will minimize serious outcomes. Singh et al.24 confirm, showing improved viral clearance significantly associated with lower hospitalization/death. We confirm this across all 227 treatments—improved viral clearance is strongly associated with lower serious outcomes, p = 0.00000000015 (see the appendix for details). Authorities may not pool any outcomes, e.g., separating studies reporting mortality and studies reporting ICU admission, however data shows that—for COVID-19—it is valid to combine outcomes from viral clearance to mortality. 85% of treatments showing significant efficacy/harm with pooled effects have been confirmed without pooling, with a mean delay of 4.6 months.
Novel treatments are high risk, existing treatments have a critical safety advantage Existing treatments have a strong advantage with known pharmacokinetics and safety profiles. New agents are more risky. Long-term risks cannot be known, and known risks may not be acknowledged for some time. For example, molnupiravir's potential risks include the creation of dangerous variants25-29, mutagenicity, carcinogenicity, teratogenicity, and embryotoxicity30-44. While the risk always exceeded the benefits within the context of all treatments, and confirmation of harm continues to accumulate, the treatment is still used in 2026 in some locations. Novel treatments saw limited use during the pandemic45,46, partly due to prescription requirements, limited availability, high cost, and, for certain treatments, administration requirements and drug interactions.

Low-cost existing treatments

  • Can reduce risk
  • Known safety profile
  • More widely available
  • Available immediately
  • Can be distributed in advance for immediate treatment

High-profit novel treatments

  • Can reduce risk
  • Inherently risky—long-term and rare side effects unknown
  • High cost limits use
  • Limited production
  • High profit incentivizes unethical behavior
  • Substantial delay for development and testing
  • Delayed treatment due to access barriers
Contact.
Contact us on X at @CovidAnalysis.
Funding.
We have received no funding or compensation in any form, and do not accept donations. This is entirely volunteer work.
Conflicts of interest.
We have no conflicts of interest. We have no affiliation with any pharmaceutical companies, supplement companies, governments, political parties, or advocacy organizations.
AI.
We use AI models (Gemini, Grok, Claude, and ChatGPT) tasked with functioning as additional peer-reviewers to check for errors, suggest improvements, and review spelling and grammar. Any corrections are manually verified. Our preference for em dashes is independent of AI.
Updates.
Our COVID-19 meta-analyses involve the extraction of over 229,000 datapoints from thousands of papers for 227 treatments. We thank the thousands of scientists, physicians, and other contributors that have provided updates, suggestions, feedback, and corrections. These are all welcome and can be submitted below.
Dedication.
This work is dedicated to top evidence-based physicians that worked tirelessly to analyze evidence and greatly reduce mortality and morbidity during the pandemic. In alphabetical order: Dr. Thomas J. Borody, Dr. Mary Talley Bowden, Dr. Flavio Cadegiani, Dr. Shankara Chetty, Dr. Ryan Cole, Dr. George Fareed, Dr. Sabine Hazan, Dr. Pierre Kory, Dr. Tess Lawrie, Dr. Robert Malone, Dr. Paul Marik, Dr. Peter McCullough, Dr. Didier Raoult, Dr. Harvey Risch, Dr. Jackie Stone, Dr. Brian Tyson, Dr. Joseph Varon, and Dr. Vladimir Zelenko.
Public domain.
This is a public domain work distributed in accordance with the Creative Commons CC0 1.0 Universal license, which dedicates the work to the public domain by waiving all rights worldwide under copyright law. You can distribute, remix, adapt, and build upon this work in any medium or format, including for commercial purposes, without asking permission. Referenced material and third-party images retain any original copyrights or restrictions. See: https://creativecommons.org/publicdomain/zero/1.0/.
 
Monoclonal antibodies were also included in earlier versions. Other treatments such as dexamethasone, tocilizumab, and baricitinib were recommended for late stage hospitalized patients.
secure.medicalletter.org, secure.medicalletter.org/TML-article-1702e.