Ivermectin for COVID-19: real-time meta analysis of 82 studies

https://ivmmeta.com/

•Statistically significant improvements are seen for mortality, ventilation, ICU admission, hospitalization, recovery, cases, and viral clearance. All remain significant after exclusions. 53 studies from 48 independent teams in 22 different countries show statistically significant improvements in isolation (39 primary outcome, 36 most serious outcome).

•Meta analysis using the most serious outcome shows 63% [53‑72%] and 83% [74‑89%] improvement for early treatment and prophylaxis, with similar results after exclusion based sensitivity analysis, for primary outcomes, for peer-reviewed studies, and for RCTs.

•Results are very robust — in worst case exclusion sensitivity analysis 54 of 82 studies must be excluded to avoid finding statistically significant efficacy.

•While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. Only 24% of ivermectin studies show zero events in the treatment arm. Multiple treatments are typically used in combination, which may be significantly more effective.

•No treatment, vaccine, or intervention is 100% available and effective for all variants. All practical, effective, and safe means should be used. Denying the efficacy of treatments increases mortality, morbidity, collateral damage, and endemic risk.

•Over 20 countries have adopted ivermectin for COVID-19. The evidence base is much larger and has much lower conflict of interest than typically used to approve drugs.

•All data to reproduce this paper and sources are in the appendix. See [Bryant, Hariyanto, Kory, Lawrie, Nardelli] for other meta analyses with similar results confirming efficacy.

Global adoption: 43%

Evidence base used for other COVID-19 approvals
Medication	Studies	Patients	Improvement
Molnupiravir (UK)	1	775	50%
Budesonide (UK)	1	1,779	17%
Remdesivir (USA EUA)	1	1,063	31%
Casirivimab/i.. (USA EUA)	1	799	66%
Ivermectin evidence	82	129,808	64% [56‑71%]

Highlights

Ivermectin reduces risk for COVID-19 with very high confidence for mortality, ventilation, ICU admission, hospitalization, progression, recovery, cases, viral clearance, and in pooled analysis.

We show traditional outcome specific analyses and combined evidence from all studies, incorporating treatment delay, a primary confounding factor in COVID-19 studies.

Real-time updates and corrections, transparent analysis with all results in the same format, consistent protocol for 40 treatments.

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Figure 1. A. Random effects meta-analysis excluding late treatment. This plot shows pooled effects, analysis for individual outcomes is below, and more details on pooled effects can be found in the heterogeneity section. Effect extraction is pre-specified, using the most serious outcome reported. Simplified dosages are shown for comparison, these are the total dose in the first four days for treatment, and the monthly dose for prophylaxis, for a 70kg person. For details of effect extraction and full dosage information see the appendix. B. Scatter plot showing the distribution of effects reported in early treatment studies and in all studies. C and D. Chronological history of all reported effects, with the probability that the observed or greater frequency of positive results were generated by an ineffective treatment.

Introduction

We analyze all significant studies concerning the use of ivermectin for COVID-19. Search methods, inclusion criteria, effect extraction criteria (more serious outcomes have priority), all individual study data, PRISMA answers, and statistical methods are detailed in Appendix 1. We present random effects meta-analysis results for all studies, studies within each treatment stage, specific outcomes, peer-reviewed studies, Randomized Controlled Trials (RCTs), and after exclusions.

We also perform a simple analysis of the distribution of study effects. If treatment was not effective, the observed effects would be randomly distributed (or more likely to be negative if treatment is harmful). We can compute the probability that the observed percentage of positive results (or higher) could occur due to chance with an ineffective treatment (the probability of >= k heads in n coin tosses, or the one-sided sign test / binomial test). Analysis of publication bias is important and adjustments may be needed if there is a bias toward publishing positive results.

Figure 2 shows stages of possible treatment for COVID-19. Prophylaxis refers to regularly taking medication before becoming sick, in order to prevent or minimize infection. Early Treatment refers to treatment immediately or soon after symptoms appear, while Late Treatment refers to more delayed treatment.

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Figure 2. Treatment stages.

Results

Figure 3 shows a visual overview of the results. Figure 4, 5, and 6 show results by treatment stage. Figure 7, 8, 9, 10, 11, 12, 13, and 14 show forest plots for a random effects meta-analysis of all studies with pooled effects, and for studies reporting mortality results, ICU admission, mechanical ventilation, hospitalization, recovery, COVID-19 cases, and viral clearance results only. Figure 15 shows results for peer reviewed trials only, and the supplementary data contains peer reviewed and individual outcome results after exclusions. Table 1 and Table 2 summarize the results.

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Figure 3. Overview of results.

Treatment time	Number of studies reporting positive effects	Total number of studies	Percentage of studies reporting positive effects	Probability of an equal or greater percentage of positive results from an ineffective treatment	Random effects meta-analysis results
Early treatment	27	32	84.4%	1 in 18 thousand	63% improvement RR 0.37 [0.28‑0.47] p < 0.0001
Late treatment	28	34	82.4%	1 in 10 thousand	40% improvement RR 0.60 [0.46‑0.76] p < 0.0001
Prophylaxis	16	16	100%	1 in 66 thousand	83% improvement RR 0.17 [0.11‑0.26] p < 0.0001
All studies	71	82	86.6%	1 in 294 billion	64% improvement RR 0.36 [0.29‑0.44] p < 0.0001

Table 1. Results by treatment stage.

	Studies	Prophylaxis	Early treatment	Late treatment	Patients	Authors
All studies	82	83% [74‑89%]	63% [53‑72%]	40% [24‑54%]	129,808	815
Peer-reviewedPeer-reviewed	62	83% [73‑90%]	62% [50‑72%]	41% [18‑58%]	119,455	664
After exclusionsw/exclusions	55	82% [68‑89%]	70% [62‑76%]	56% [35‑70%]	114,959	595
Randomized Controlled TrialsRCTs	33	84% [25‑96%]	60% [43‑72%]	23% [-1‑41%]	7,107	420
RCTs after exclusionsRCTs w/exc.	27	84% [25‑96%]	67% [55‑75%]	29% [4‑48%]	4,985	333

Table 2. Results by treatment stage for all studies and with different exclusions.

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Figure 4. Results by treatment stage.

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Figure 5. Chronological history of early and late treatment results, with the probability that the observed or greater frequency of positive results were generated by an ineffective treatment.

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Figure 6. Chronological history of prophylaxis results.

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Figure 8. Random effects meta-analysis for mortality.

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Figure 9. Random effects meta-analysis for mechanical ventilation.

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Figure 10. Random effects meta-analysis for ICU admission.

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Figure 11. Random effects meta-analysis for hospitalization.

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Figure 12. Random effects meta-analysis for recovery results only.

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Figure 13. Random effects meta-analysis for COVID-19 case results.

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Figure 14. Random effects meta-analysis for viral clearance.

Randomized Controlled Trials (RCTs)

Results restricted to Randomized Controlled Trials (RCTs) are shown in Figure 16, 17, 18, 19, and 20, and Table 3. The supplementary data contains RCT results after exclusions.

RCTs help to make study groups more similar, however they are subject to many biases, including age bias, treatment delay bias, severity of illness bias, regulation bias, recruitment bias, trial design bias, followup time bias, selective reporting bias, fraud bias, hidden agenda bias, vested interest bias, publication bias, and publication delay bias [Jadad], all of which have been observed with COVID-19 RCTs.

RCTs have a bias against finding an effect for interventions that are widely available — patients that believe they need the intervention are more likely to decline participation and take the intervention. This is illustrated with the extreme example of an RCT showing no significant differences for use of a parachute when jumping from a plane [Yeh]. RCTs for ivermectin are more likely to enroll low-risk participants that do not need treatment to recover, making the results less applicable to clinical practice. This bias is likely to be greater for widely known treatments such as ivermectin. The bias may also be greater in locations where ivermectin is more easily obtained. Note that this bias does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable.

Evidence shows that non-RCT trials can also provide reliable results. [Concato] find that well-designed observational studies do not systematically overestimate the magnitude of the effects of treatment compared to RCTs. [Anglemyer] summarized reviews comparing RCTs to observational studies and found little evidence for significant differences in effect estimates. [Lee] shows that only 14% of the guidelines of the Infectious Diseases Society of America were based on RCTs. Evaluation of studies relies on an understanding of the study and potential biases. Limitations in an RCT can outweigh the benefits, for example excessive dosages, excessive treatment delays, or Internet survey bias could have a greater effect on results. Ethical issues may also prevent running RCTs for known effective treatments. For more on issues with RCTs see [Deaton, Nichol].

In summary, we need to evaluate each trial on its own merits. RCTs for a given medication and disease may be more reliable, however they may also be less reliable. For example, consider trials for an off-patent medication, very high conflict of interest trials may be more likely to be RCTs (and more likely to be large trials that dominate meta analyses).

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Figure 16. Randomized Controlled Trials. The distribution of results for RCTs is similar to the distribution for all other studies.

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Figure 18. RCTs excluding late treatment.

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Figure 19. Random effects meta-analysis for RCT mortality results.

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Figure 20. Random effects meta-analysis for RCT viral clearance results.

Treatment time	Number of studies reporting positive effects	Total number of studies	Percentage of studies reporting positive effects	Probability of an equal or greater percentage of positive results from an ineffective treatment	Random effects meta-analysis results
Randomized Controlled Trials	27	33	81.8%	1 in 6 thousand	56% improvement RR 0.44 [0.32‑0.61] p < 0.0001
Randomized Controlled Trials (excluding late treatment)	18	22	81.8%	1 in 460	67% improvement RR 0.33 [0.21‑0.51] p < 0.0001

Table 3. Summary of RCT results.

Exclusions

To avoid bias in the selection of studies, we analyze all non-retracted studies. Here we show the results after excluding studies with critical issues likely to alter results, non-standard studies, and studies where very minimal detail is currently available. Our bias evaluation is based on analysis of each study and identifying when there is a significant chance that limitations will substantially change the outcome of the study. We believe this can be more valuable than checklist-based approaches such as Cochrane GRADE, which may underemphasize serious issues not captured in the checklists, overemphasize issues unlikely to alter outcomes in specific cases (for example, lack of blinding for an objective mortality outcome, or certain specifics of randomization with a very large effect size), or be subject to bias. However, they can also be very high quality [Bryant].

A team of researchers has analyzed the data in ivermectin studies and identified several studies with concerns. Retracted studies are not in this analysis. All other studies that the team has identified are excluded here. For more details see the response section.

Detailed description of issues with [López-Medina] can be found in the study notes section.

[Soto-Becerra] is a database analysis covering anyone with ICD-10 COVID-19 codes, which includes asymptomatic PCR+ patients. Therefore many patients in the control group are likely asymptomatic with regards to SARS-CoV-2, but in the hospital for another reason. For those that had symptomatic COVID-19, there is also likely significant confounding by indication. KM curves show that the treatment groups were in more serious condition, with more than the total excess mortality at 30 days occurring on day 1. All treatments are worse than the control group at 30 days, while at the latest followup all treatments show lower mortality than control. The machine learning system used also appears over-parameterized and likely to result in significant overfitting and inaccurate results. There is also no real control group in this study - patients receiving the treatments after 48 hours were put in the control group. Authors also state that outcomes within 24 hours were excluded, however the KM curves show significant mortality at day 1 (only for the treatment groups). Several protocol violations have also been reported in this study [Yim]. Note that this study provides both 30 day mortality and weighted KM curves up to day 43 for ivermectin, we use the day 43 results as per our protocol. [IVERCOR PREP] reports prophylaxis results, however only very minimal details are currently available in a news report. [Hellwig] analyze African countries and COVID-19 cases in October 2020 as a function of whether widespread prophylactic use of ivermectin is used for parasitic infections. [Tanioka] perform a similar analysis for COVID-19 mortality in January 2021. These studies are excluded because they are not clinical trials. [Shahbaznejad] had only one death that occurred in a patient that was critically ill at the time of admission and died within the first 24 hours. [Galan] perform an RCT comparing ivermectin and other treatments with very late stage severe condition hospitalized patients, not showing significant differences between the treatments. Authors were unable to add a control arm due to ethical issues. The closest control comparison we could find is [Baqui], which shows 43% hospital mortality in the northern region of Brazil where the study was performed, from which we can estimate the mortality with ivermectin in this study as 47% lower, RR 0.53. Further, the study is restricted to more severe cases, hence the expected mortality, and therefore the benefit of treatment, may be higher. [Kishoria] restrict inclusion to patients that did not respond to standard treatment, provide no details on the time of the discharge status, and there are very large unadjusted differences in the groups, with over twice as many patients in the ivermectin group with age >40, and all patients over 60 in the ivermectin group.

Summarizing, the studies excluded are as follows, and the resulting forest plot is shown in Figure 21. The supplementary data shows results after restrictions and exclusions.

[Abbas], very minimal patient information, three different results for the recovery outcome, selective omission of the statistically significant recovery p-value, and other inconsistencies.

[Ahsan], unadjusted results with no group details.

[Beltran Gonzalez], major inconsistencies reported and the data is no longer available [Chamie], although the authors state that it is available, and have shared it with an anti-treatment group.

[Borody], preliminary report with minimal details.

[Buonfrate], significant unadjusted group differences, with 3 times as many patients in the ivermectin arms having the baseline visit in a hospital setting, and arm C having large differences in baseline gender, weight, cough, pyrexia, and anosmia, excessive dose for arm C.

[Cadegiani], control group retrospectively obtained from untreated patients in the same population.

[Carvallo], concern about potential data issues.

[Carvallo (B)], concern about potential data issues.

[Carvallo (C)], minimal details of groups provided.

[de Jesús Ascencio-Montiel], unadjusted results with alternate outcome adjusted results showing significant changes with adjustments. Excluded results: death, mechanical ventilation, hospitalization, progression.

[Elavarasi], unadjusted results with no group details.

[Ferreira], unadjusted results with no group details, substantial unadjusted confounding by indication likely.

[Hazan], study uses a synthetic control arm.

[Hellwig], not a typical trial, analysis of African countries that used or did not use ivermectin prophylaxis for parasitic infections.

[IVERCOR PREP], minimal details provided.

[Kishoria], excessive unadjusted differences between groups.

[López-Medina], strong evidence of patients in the control group self-medicating, ivermectin widely used in the population at that time, and the study drug identity was concealed by using the name D11AX22.

[Mustafa], unadjusted results with no group details.

[Ravikirti], exclusion of patients in less severe condition, data/analysis concerns.

[Reis], multiple anomalies as per detailed analysis.

[Roy], no serious outcomes reported and fast recovery in treatment and control groups, there is little room for a treatment to improve results.

[Samajdar], minimal details provided, unadjusted results with no group details, results may be significantly affected by survey bias.

[Soto], substantial unadjusted confounding by indication likely, substantial confounding by time possible due to significant changes in SOC and treatment propensity near the start of the pandemic.

[Soto-Becerra], substantial unadjusted confounding by indication likely, includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons.

[Szente Fonseca], result is likely affected by collinearity across treatments in the model.

[Tanioka], not a typical trial, analysis of African countries that used or did not use ivermectin prophylaxis for parasitic infections.

[Thairu], significant confounding by time possible due to separation of groups in different time periods.

[Zubair], substantial unadjusted confounding by indication likely, unadjusted results with no group details.

Heterogeneity

Heterogeneity in COVID-19 studies arises from many factors including:

Treatment delay.

The time between infection or the onset of symptoms and treatment may critically affect how well a treatment works. For example an antiviral may be very effective when used early but may not be effective in late stage disease, and may even be harmful. Oseltamivir, for example, is generally only considered effective for influenza when used within 0-36 or 0-48 hours [McLean, Treanor]. Figure 22 shows a mixed-effects meta-regression for efficacy as a function of treatment delay in COVID-19 studies from 40 treatments, showing that efficacy declines rapidly with treatment delay. Early treatment is critical for COVID-19.

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Figure 22. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 40 treatments. Early treatment is critical.

Patient demographics.

Details of the patient population including age and comorbidities may critically affect how well a treatment works. For example, many COVID-19 studies with relatively young low-comorbidity patients show all patients recovering quickly with or without treatment. In such cases, there is little room for an effective treatment to improve results (as in [López-Medina]).

Effect measured.

Efficacy may differ significantly depending on the effect measured, for example a treatment may be very effective at reducing mortality, but less effective at minimizing cases or hospitalization. Or a treatment may have no effect on viral clearance while still being effective at reducing mortality.

Variants.

There are many different variants of SARS-CoV-2 and efficacy may depend critically on the distribution of variants encountered by the patients in a study. For example, the Gamma variant shows significantly different characteristics [Faria, Karita, Nonaka, Zavascki]. Different mechanisms of action may be more or less effective depending on variants, for example the viral entry process for the omicron variant has moved towards TMPRSS2-independent fusion, suggesting that TMPRSS2 inhibitors may be less effective [Peacock, Willett].

Regimen.

Effectiveness may depend strongly on the dosage and treatment regimen. Higher dosages have been found to be more successful for ivermectin [Babalola]. Method of administration may also be critical. [Guzzo] show that the plasma concentration of ivermectin is much higher when administered with food (Figure 23: geometric mean AUC 2.6 times higher). Many ivermectin studies specify fasting, or they do not specify administration. Fasting administration is expected to reduce effectiveness for COVID-19 due to lower plasma and tissue concentrations. Note that this is different to anthelmintic use in the gastrointestinal tract where fasting is recommended.

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Figure 23. Mean plasma concentration (ng/ml) profiles of ivermectin following single oral doses of 30mg (fed and fasted administration), from [Guzzo].

Treatments.

The use of other treatments may significantly affect outcomes, including anything from supplements, other medications, or other kinds of treatment such as prone positioning.

The distribution of studies will alter the outcome of a meta analysis. Consider a simplified example where everything is equal except for the treatment delay, and effectiveness decreases to zero or below with increasing delay. If there are many studies using very late treatment, the outcome may be negative, even though the treatment may be very effective when used earlier.

In general, by combining heterogeneous studies, as all meta analyses do, we run the risk of obscuring an effect by including studies where the treatment is less effective, not effective, or harmful.

When including studies where a treatment is less effective we expect the estimated effect size to be lower than that for the optimal case. We do not a priori expect that pooling all studies will create a positive result for an effective treatment. Looking at all studies is valuable for providing an overview of all research, important to avoid cherry-picking, and informative when a positive result is found despite combining less-optimal situations. However, the resulting estimate does not apply to specific cases such as early treatment in high-risk populations.

Ivermectin studies vary widely in all the factors above, which makes the consistently positive results even more remarkable. A failure to detect an association after combining heterogeneous studies does not mean the treatment is not effective (it may only work in certain cases), however the reverse is not true — an identified association is valid, although the magnitude of the effect may be larger for more optimal cases, and lower for less optimal cases. As above, the probability that an ineffective treatment generated results as positive as the 82 studies to date is estimated to be 1 in 294 billion. This result benefits from the fact that ivermectin shows some degree of efficacy for COVID-19 in a wide variety of cases. It also likely benefits from the fact that relatively few ivermectin trials to date have been designed in a way that favors poor results. However, more trials designed in this way are expected, for example the TOGETHER trial is testing ivermectin in locations known to have a high degree of self-medication and using low doses compared to current clinical recommendations as updated for current variants. As with a companion trial, this trial may also include very low-risk patients, include relatively late treatment while identifying as an early treatment trial, and use an active placebo (vitamin C). While we present results for all studies in this paper, the individual outcome and treatment time analyses are more relevant for specific use cases.

Discussion

Publication bias.

Publishing is often biased towards positive results, which we would need to adjust for when analyzing the percentage of positive results. For ivermectin, there is currently not enough data to evaluate publication bias with high confidence. One method to evaluate bias is to compare prospective vs. retrospective studies. Prospective studies are likely to be published regardless of the result, while retrospective studies are more likely to exhibit bias. For example, researchers may perform preliminary analysis with minimal effort and the results may influence their decision to continue. Retrospective studies also provide more opportunities for the specifics of data extraction and adjustments to influence results. Figure 24 shows a scatter plot of results for prospective and retrospective studies. The median effect size for prospective studies is 69% improvement, compared to 70% for retrospective studies, showing no significant difference. [Bryant] also perform a funnel plot analysis, which they found did not suggest evidence of publication bias. Ivermectin has one of the most closely watched and closely examined evidence bases in history. Negative studies are submitted to us by multiple people immediately on publication. On the other hand, there is substantial evidence that journals are rejecting and delaying the publication of positive studies, for example by accepting a paper for review, holding it for some time, and then rejecting it without review [Jerusalem Post, Kory (B)]. One group performed prophylaxis and early treatment trials, with only the less positive study being formally published to date [IVERCOR PREP, Vallejos], suggesting a negative publication bias. Dr. Eli Schwartz's [Biber] double blind RCT has been rejected without review by The Lancet and Clinical Infectious Diseases [Fox]. Authors of [Efimenko] do not plan to submit the very positive results to a journal, providing further evidence of a negative publication bias. Trials with pending and possibly delayed publication often involve researchers that may be restricted due to politics — publishing positive results may be incompatible with continued employment, whereas negative results can receive priority treatment at certain well-known journals, support the positions of employers or funding organizations, and receive substantial press.

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Figure 24. Prospective vs. retrospective studies.

News coverage of ivermectin studies is extremely biased. Only two studies to date have received significant press coverage in western media [López-Medina, Reis], both of which have multiple critical issues as discussed below.

Funnel plot analysis.

Funnel plots have traditionally been used for analyzing publication bias. This is invalid for COVID-19 acute treatment trials — the underlying assumptions are invalid, which we can demonstrate with a simple example. Consider a set of hypothetical perfect trials with no bias. Figure 25 plot A shows a funnel plot for a simulation of 80 perfect trials, with random group sizes, and each patient's outcome randomly sampled (10% control event probability, and a 30% effect size for treatment). Analysis shows no asymmetry (p > 0.05). In plot B, we add a single typical variation in COVID-19 treatment trials — treatment delay. Consider that efficacy varies from 90% for treatment within 24 hours, reducing to 10% when treatment is delayed 3 days. In plot B, each trial's treatment delay is randomly selected. Analysis now shows highly significant asymmetry, p < 0.0001, with six variants of Egger's test all showing p < 0.05 [Egger, Harbord, Macaskill, Moreno, Peters, Rothstein, Rücker, Stanley]. Note that these tests fail even though treatment delay is uniformly distributed. In reality treatment delay is more complex — each trial has a different distribution of delays across patients, and the distribution across trials may be biased (e.g., late treatment trials may be more common). Similarly, many other variations in trials may produce asymmetry, including dose, administration, duration of treatment, differences in SOC, comorbidities, age, variants, and bias in design, implementation, analysis, and reporting.

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Figure 25. Example funnel plot analysis for simulated perfect trials.

In Vitro evidence on required concentration.

Some people claim that [Caly] shows that therapeutic concentrations are not easily reached in humans. This is incorrect. The authors explain why their in vitro study cannot be used to determine the effective dose in vivo, and state that the concentration required is very unlikely to be an issue [Wagstaff]. The study used monkey kidney cells (the only choice at the time of the experiments), which lack adaptive immune responses and do not produce interferon. Authors also note that ivermectin accumulates in lung and other tissues, that subsequent experiments with lung cells show many times greater concentrations, and that the average lung concentration shown in modeling studies exceeds the effective level shown in their research. Authors note that ivermectin works with the immune system and a 1:1 ratio of drug to virus is unlikely to be required. In [Bray], author reply that "ivermectin's key direct target in mammalian cells is a not a viral component, but a host protein important in intracellular transport; the fact that it is a host-directed agent (HDA) is almost certainly the basis of its broad-spectrum activity against a number of different RNA viruses in vitro. The way a HDA can reduce viral load is by inhibiting a key cellular process that the virus hijacks to enhance infection by suppressing the host antiviral response. Reducing viral load by even a modest amount by using a HDA at low dose early in infection can be the key to enabling the body's immune system to begin to mount the full antiviral response before the infection takes control." In further research, authors note that they find efficacy for prophylactic use, and that smaller repeated doses are more efffective than a single larger dose [Wagstaff].

Strongyloides.

One theory for the beneficial effect of ivermectin for COVID-19 is related to strongyloides and the use of steroids — control group patients with strongyloides may be at risk due to steroid use, while ivermectin patients are protected. While this mechanism may contribute to efficacy in some cases, it is inconsistent with the data. If this was the case, we would expect to see greater benefit in late stage trials where steroids are used more often, and we would expect to see greater benefit for outcomes that occur after steroids are used. However, we see a very strong opposite effect for treatment time, and we see comparable or stronger efficacy for earlier outcomes.

The theory has gained renewed interest based on a new analysis [Bitterman]. However, this analysis is confounded by treatment delay, dose, conflicts of interest, and other factors, and the effect disappears when analyzing all studies, all RCTs, or all mortality results, as shown in Figure 26.

Although the first author has responded to the confounders on Twitter, we do not see mention of them in the paper. Author is also aware that the larger sets of all trials, all RCTs, or all mortality results do not show the effect, however we also do not see this mentioned in the paper. These omissions suggest investigator bias. Author claims they could not discuss these issues due to publication delays, however the paper was accepted Jan 31, 2022, and author was aware of the issues months before, for example discussing treatment delay and dose in Nov 2021. These confounders are also basic and not really possible to miss.

The meta analysis for [Hashim] includes critical patients, however these patients were always allocated to the treatment arm for ethical reasons, therefore including them is not logical and introduces substantial bias. According to the author response, this appears to have been known, suggesting investigator bias. Authors include [Shahbaznejad] where the only death was a critical patient that died within 24 hours of admission.

Although authors note following PRISMA guidelines, we do not see registration of the protocol or discussion thereof. We note that the current protocol is the result of multiple changes to the original methodology as posted on Twitter: from 3 groups to 2 groups, altering the included studies, and switching from using one source for prevalence estimates to selecting estimate sources on a per study basis, which allows potential bias in the selection. Notably, this resulted in moving the Together Trial (Brazil) into the low prevalence category.

Author's results rely on trials with a very small number of mortality events — the high stronglyoides prevalance group has trials with 1, 3, 4, and 13 events. Authors do mention limitations due to the small number of events and the reliability of strongyloides estimates.

Authors indicate no conflicts of interest, however the first author has been an investigator on a Pfizer trial, which may be NCT04092452, showing completion in January 2022 [clinicaltrials.gov, openpaymentsdata.cms.gov].

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Figure 26. Mixed-effects meta-regression showing efficacy as a function of strongyloides prevalence for all studies, all RCTs, and all mortality results.

The following refers to the first author's analysis posted earlier on Twitter. The author selected 10 of the 82 studies, with 3 in a high strongyloides prevalence group where a greater benefit is seen. This was used to draw strong conclusions about the mechanism of ivermectin efficacy.

There are several limitations to this analysis. One of the 3 studies does not mention steroids in the list of SOC medications, while a second reports 6% usage for the control group. Author has added a fourth paper in a revised grouping with 11 studies.

We perfomed a similar analysis for all studies (except the 2 ecological studies), which shows no significant effect, with the high prevalence group actually showing lower improvement (52% [36‑64%] vs. 70% [62‑76%] for the low prevalence group). Details can be found in the supplementary data. Results are similar when restricting to mortality results or when restricting to RCTs.

Why does the smaller analysis with 11 studies show a greater benefit in high strongyloides prevalence regions? The effect is based on relatively few events - 1, 3, 4, and 13 respectively for the high prevalence group. More importantly, the result is confounded by treatment delay and dose.

Treatment delay. All meta analyses combine heterogeneous studies which results in limitations. For example in pooled analysis we combine hospitalization and mortality. In terms of evaluating efficacy for COVID-19 treatments, reduction in hospitalization reasonably leads to reduction in mortality for high-risk populations. Both are indicators of efficacy, and both are valuable. In the largest series of COVID-19 treatment trials, hospitalization and mortality estimates are very similar. The same does not apply to treatment delay for antivirals. A trial showing efficacy with early treatment provides no information on late treatment, and a trial showing no efficacy with late treatment provides no information on early treatment. Ivermectin, as with many COVID-19 treatments, shows a strong treatment delay relationship — early treatment shows significantly higher efficacy.

The high prevalence group in the 11 study analysis has more early treatment trials, and the low prevalence group has more late treatment trials. The result is confounded by treatment delay, and reflects the greater efficacy of early treatment.

Only one trial in the high prevalence group is classified as late treatment, I-TECH, which was very close to the cutoff. Moreover, of all trials in the 11 trial analysis, this one uses the the highest dose.

Dose. The average dosage used in the high prevalence group is about twice the dose in the low prevalence group, and would be close to three times higher if the Together Trial was not moved to the low prevalence group. The result is confounded by dose, and reflects the greater efficacy of higher dosages.

Variants. Efficacy may vary based on variants. Notably, the Gamma variant was most common for one trial in the low prevalance group. This variant shows dramatically different characteristics [Zavascki], and clinicians report that significantly higher dosage and/or earlier treatment is required, as may be expected for variants where the peak viral load is significantly higher and/or reached earlier [Faria, Nonaka].

Conflicts of interest. Two trials have very high (>$US1B) negative conflicts of interest which may introduce bias towards null effects. The trial in the low prevalance group shows a lower effect size. The trial in the high prevalence group also shows a lower effect size for the primary outcome. This trial shows a larger mortality effect, however with only one event this has very low significance.

Summary. In summary, the greater benefit in high strongyloides prevalence regions is only seen with the small subset of 11 trials and is not seen with all trials, or after restriction to mortality results, or restriction to RCTs. Within the 11 trial sample, all trials except one in the low prevalence group have confounding due to treatment delay and/or low dosage, where a lower effect size is expected. The only remaining trial in the group is unpublished, has an unknown treatment delay (a significant percentage of patients may have been treated very late), has very high negative conflicts of interest, and the Gamma variant was most common, in addition to other issues.

Conflicts of interest.

Pharmaceutical drug trials often have conflicts of interest whereby sponsors or trial staff have a financial interest in the outcome being positive. Ivermectin for COVID-19 lacks this because it is off-patent, has many manufacturers, and is very low cost. In contrast, most COVID-19 ivermectin trials have been run by physicians on the front lines with the primary interest of finding the best methods to save human lives and minimize the collateral damage caused by COVID-19. While pharmaceutical companies are careful to run trials under optimal conditions (for example, restricting patients to those most likely to benefit, only including patients that can be treated soon after onset when necessary, ensuring accurate dosing), many ivermectin trials do not represent the optimal conditions for efficacy.

Two ivermectin trials to date involve very large financial conflicts of interest [López-Medina, Reis] — companies closely involved with the trial or organizers stand to lose billions of dollars if ivermectin efficacy becomes more widely known. The design of these trials favors producing a null outcome as detailed in [López-Medina, Reis]. Note that biasing an RCT to produce a false positive result is difficult (suppressing adverse events is relatively easy [Evans]), but biasing a trial to produce a false negative result is very easy — for example, in a trial of an antiviral that works within the first 24 hours of symptom onset, trial organizers only need to avoid treating people within the first 24 hours; or with a disease like COVID-19, organizers only need to select a low-risk population where most people recover quickly without treatment. We note that, even under the very suboptimal designs, these trials produced positive results, although without statistical significance.

Designed to fail.

Additional upcoming trials including ACTIV-6, COVID-OUT, and PRINCIPLE have been designed in a way that favors finding no effect, with a number of methods including late treatment, selecting low-risk patients, fasting administration, very high conflict of interest medication sourcing, and dosing below current clinical practice. For discussion see [Goodkin].

COVID-OUT is enrolling relatively low risk patients (median age 46, 0.45 mean comorbidities), includes asymptomatic patients, and has a long delay between symptoms and treatment based on the sample collection delay in [Bramante].

PRINCIPLE paused enrollment in December 2021, claiming there was a supply issue [Henderson], however the manufacturer supplying the trial reported that they were not experiencing any supply issues. As of January 27, 2022, the trial was paused without explanation. As of February 11, 2022, the trial was open intermittently (twice daily between Sunday and Thursday), which would further decrease the chances of participants receiving relatively early treatment.

One patient reported their experience with one of the remote outpatient ivermectin/fluvoxamine trials: they were offered enrollment 7 days after symptoms (receipt of medication would be even later), were offered $400 to participate, and reportedly target healthy people [twitter.com]. ACTIV-6 also reportedly does not ship study medications on the weekend, adding additional delays [twitter.com (B)].

If these trials provide results for high-risk patients stratified by treatment delay, including patients treated within 1, 2, and 3 days of symptom onset (including any shipping delay), they may be informative even with limited dosing.

Early/late vs. mild/moderate/severe.

Some analyses classify treatment based on early/late administration (as we do here), while others distinguish between mild/moderate/severe cases. We note that viral load does not indicate degree of symptoms — for example patients may have a high viral load while being asymptomatic. With regard to treatments that have antiviral properties, timing of treatment is critical — late administration may be less helpful regardless of severity.

Notes.

The 82 studies are from 74 independent research teams. 4 studies compare against other treatments rather than placebo. Currently ivermectin shows better results than these other treatments, however ivermectin may show greater improvement when compared to placebo. 17 of 82 studies combine treatments, for example ivermectin + doxycycline. The results of ivermectin alone may differ. 4 of 33 RCTs use combined treatment, three with doxycycline, and one with iota-carrageenan. 1 of 82 studies currently has minimal published details available.

Meta analyses.

Typical meta analyses involve subjective selection criteria, effect extraction rules, and study bias evaluation, which can be used to bias results towards a specific outcome. In order to avoid bias we include all studies and use a pre-specified method to extract results from all studies (we also present results after exclusions). The results to date are overwhelmingly positive, very consistent, and very insensitive to potential selection criteria, effect extraction rules, and/or bias evaluation. Additional meta analyses confirming the effectiveness of ivermectin can be found in [Bryant, Kory, Lawrie]. Figure 27 shows a comparison of mortality results across meta analyses. [Kory] also review epidemiological data and provide suggested treatment regimens.

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Figure 27. Comparison of mortality results from different meta analyses. OR converted to RR for [Kory, Nardelli]. OR displayed for [WHO]. WHO provides two results, one based on 5 studies and one based on 7, with no explanation for the difference. The result based on 7 studies is shown here, for which the details required to calculate the RR are not provided.

Evidence base.

The evidence supporting ivermectin for COVID-19 far exceeds the typical amount of evidence used for the approval of treatments. [Lee] shows that only 14% of the guidelines of the Infectious Diseases Society of America were based on RCTs. Table 4 and Table 5 compare the amount of evidence for ivermectin compared to that used for other COVID-19 approvals, and that used by WHO for the approval of ivermectin for scabies and strongyloidiasis. Table 6 compares US CDC recommendations for ibuprofen and ivermectin.

Indication	Studies	Patients	Status
Strongyloidiasis [Kory (C)]	5	591	Approved
Scabies [Kory (C)]	10	852	Approved
COVID‑19	82	129,808	Pending
COVID‑19 RCTs	33	7,107	Pending

Table 4. WHO ivermectin approval status.

Medication	Studies	Patients	Improvement	Status
Molnupiravir (UK)	1	775	50%	Approved
Budesonide (UK)	1	1,779	17%	Approved
Remdesivir (USA EUA)	1	1,063	31%	Approved
Casiri/imdevimab (USA EUA)	1	799	66%	Approved
Ivermectin evidence	82	129,808	64% [56‑71%]	Pending

Table 5. Evidence base used for other COVID-19 approvals compared with the ivermectin evidence base.

	Ibuprofen	Ivermectin (for scabies)	Ivermectin (for COVID-19)
Lives saved	0	0	>500,000
Deaths per year	~450	<1	<1
CDC recommended	Yes	Yes	No
Based on	0 RCTs	10 RCTs 852 patients	33 RCTs 7,107 patients

Table 6. Comparison of CDC recommendations [Kory (C)].

WHO, Merck, FDA

WHO Analysis.

WHO updated their treatment recommendations on 3/30/2021 [WHO]. For ivermectin they reported a mortality odds ratio of 0.19 [0.09-0.36] based on 7 studies with 1,419 patients. They do not specify which trials they included. The report is inconsistent, with a forest plot that only shows 4 studies with mortality results. WHO's recommendation has not been updated for days.

Despite this extremely positive result, they recommended only using ivermectin in clinical trials. The analysis contains many flaws [Kory (D)]:

•Of the 82 studies (33 RCTs), they only included 16.

•They excluded all 16 prophylaxis studies (3 RCTs).

•There was no protocol for data exclusion.

•Trials included in the original UNITAID search protocol were excluded.

•They excluded all epidemiological evidence, although WHO has considered such evidence in the past.

•They combine early treatment and late treatment studies and do not provide heterogeneity information. As above, early treatment is more successful, so pooling late treatment studies will obscure the effectiveness of early treatment. They chose not to do subgroup analysis by disease severity across trials, although treatment delay is clearly a critical factor in COVID-19 treatment, the analysis is easily done (as above), and it is well known that the studies for ivermectin and many other treatments clearly show greater effectiveness for early treatment.

•WHO downgraded the quality of trials compared to the UNITAID systematic review team and a separate international expert guideline group that has long worked with the WHO [Bryant].

•They disregarded their own guidelines that stipulate quality assessments should be upgraded when there is evidence of a large magnitude effect (which there is), and when there is evidence of a dose-response relationship (which there is). They claim there is no dose-response relationship, while the UNITAID systematic review team found a clear relationship, along with individual studies [Babalola].

•Their risk of bias assessments do not match the actual risk of bias in studies. For example they classify [López-Medina] as low risk of bias, however this study has many issues making the results unreliable [Covid Analysis], even prompting an open letter from over 170 physicians concluding that the study is fatally flawed [Open Letter]. [Beltran Gonzalez] is also classified as low risk of bias, but is a study with very late stage severe condition high-comorbidity patients. There is a clear treatment delay-response relationship and very late stage treatment is not expected to be as effective as early treatment. Conversely, much higher quality studies were classified as high risk of bias.

•Although WHO's analysis is called a "living guideline", it is rarely updated and very out of date. As of May 14, 2021, four of the missing RCTs are known to WHO and labeled "RCTs pending data extraction" [COVID-NMA]. We added these 4, 4, 2, and one month earlier.

•A single person served as Methods Chair, member of the Guidance Support Collaboraton Committee, and member of the Living Systematic Review/NMA team.

•Public statements from people involved in the analysis suggest substantial bias. For example, a co-chair reportedly said that "the data available was sparse and likely based on chance" [Reuters]. As above, the data is comprehensive, and we estimate the probability that an ineffective treatment generated results as positive as observed to be 1 in 294 billion. The clinical team lead refers to their analysis of ivermectin as "fighting this overuse of unproven therapies ... without evidence of efficacy" [Reuters], despite the extensive evidence of efficacy from the 82 studies by 815 scientists with 129,808 patients. People involved may be more favorable to late stage treatment of COVID-19, for example the co-chair recommended treating severe COVID-19 with remdesivir [Rochwerg].

In summary, although WHO's analysis predicts that over 2 million fewer people would be dead if ivermectin was used from early in the pandemic, they recommend against use outside trials. This appears to be based primarily on excluding the majority of the evidence, and by assigning bias estimates that do not match the actual risk of bias in studies.

Use early in the pandemic was proposed by Kitasato University including the co-discoverer of ivermectin, Dr. Satoshi Ōmura. They requested Merck conduct clinical trials of ivermectin for COVID-19 in Japan, because Merck has priority to submit an application for an expansion of ivermectinʼs indications. Merck declined [Yagisawa].

Merck Analysis.

Merck has recommended against ivermectin [Merck], however this recommendation has not been updated for days.

They stated that there is "no scientific basis for a potential therapeutic effect against COVID-19 from pre-clinical studies". This is contradicted by many papers and studies, including [Arévalo, Bello, Choudhury, de Melo, DiNicolantonio, DiNicolantonio (B), Errecalde, Eweas, Francés-Monerris, Heidary, Jans, Jeffreys, Kalfas, Kory, Lehrer, Li, Mody, Mountain Valley MD, Qureshi, Saha, Surnar, Udofia, Wehbe, Yesilbag, Zaidi, Zatloukal].

They state that there is "no meaningful evidence for clinical activity or clinical efficacy in patients with COVID-19 disease". This is contradicted by numerous studies including [Alam, Aref, Babalola, Baguma, Behera, Behera (B), Bernigaud, Budhiraja, Bukhari, Chaccour, Chahla, Chahla (B), Chowdhury, de Jesús Ascencio-Montiel, Elalfy, Espitia-Hernandez, Faisal, Ghauri, Hashim, Huvemek, Kerr, Khan, Lima-Morales, Loue, Mahmud, Manomaipiboon, Mayer, Merino, Mohan, Mondal, Morgenstern, Mourya, Okumuş, Ravikirti (B), Seet, Shimizu].

They also claim that there is "a concerning lack of safety data in the majority of studies". Safety analysis is found in [Descotes, Errecalde, Guzzo, Kory, Madrid], and safety data can be found in most studies, including [Abd-Elsalam, Ahmed, Aref, Babalola, Behera (B), Bhattacharya, Biber, Bukhari, Camprubí, Carvallo (C), Chaccour, Chahla (B), Chowdhury, Elalfy, Espitia-Hernandez, Ghauri, Gorial, Hazan, Huvemek, Khan, Kishoria, Krolewiecki, Lima-Morales, Loue, López-Medina, Mahmud, Mohan, Morgenstern, Mourya, Okumuş, Pott-Junior, Seet, Shahbaznejad, Shouman, Spoorthi, Szente Fonseca, Vallejos, Zubair].

Merck has a number of conflicts of interest:

•Merck has committed to give ivermectin away for free "as much as needed, for as long as needed" in the Mectizan® Donation Program [Merck (B)], to help eliminate river blindness.

•Merck has their own new COVID-19 treatments MK-7110 (formerly CD24Fc) [Adams] and Molnupiravir (MK-4482) [Jayk Bernal, Wikipedia]. Merck has a ~$US1.2B agreement to supply molnupiravir to the US government, if it receives EUA or approval [Khan (B)]. Over $US10B in near-term orders are expected if approved [Genetic Engineering and Biotechnology News].

•Ivermectin is off-patent, there are many manufacturers, and Merck is unlikely to be able to compete with low cost manufacturers.

•Promoting the use of low cost off-patent medications compared to new products may be undesirable to some shareholders.

•Japan requested Merck conduct clinical trials early in the pandemic and they declined. Merck may be reluctant to admit this mistake [Yagisawa].

For other concerns regarding Merck's statement and prior actions related to Vioxx, see [Scheim].

FDA Analysis.

The US FDA recommended against ivermectin on March 5, 2021, however they stated that "The FDA has not reviewed data to support use of ivermectin in COVID-19 patients to treat or to prevent COVID-19". There is still no indication that the FDA has reviewed the clinical trials days later.

The FDA notes that they "received multiple reports of patients who have required medical support and been hospitalized after self-medicating with ivermectin intended for horses". The number of reports was 4 [Pfeiffer]. For comparison, acetaminophen overdose results in ~33,000 yearly hospitalizations in the USA (~12,000 unintentional) [Charilaou]. The FDA's recommendation may increase cases of self-medication with animal ivermectin, because it reduces the percentage of prescribing physicians.

They state that "Ivermectin is not an anti-viral", however many studies contradict this [Ahmed, Aref, Babalola, Biber, Bukhari, Buonfrate, Caly, Chowdhury, Elalfy, Espitia-Hernandez, Khan, Mahmud, Mohan, Mourya, Okumuş, Rezk, Thairu], including 10 RCTs.

They note that "some initial research is underway", however there had been many studies completed and published prior to the FDA recommendation [Ahmed, Alam, Babalola, Behera, Beltran Gonzalez, Bernigaud, Biber, Budhiraja, Bukhari, Cadegiani, Camprubí, Carvallo (C), Chaccour, Chachar, Chahla (B), Chowdhury, Elalfy, Espitia-Hernandez, Ghauri, Gorial, Hashim, Hellwig, Khan, Lima-Morales, López-Medina, Mahmud, Mohan, Okumuş, Podder, Rajter, Ravikirti (B), Shouman, Spoorthi], including 17 RCTs.

Sep 3, 2021: The FDA revised their statement slightly. They removed the false claim that invermectin is not an antiviral, and they removed the statement that they have not reviewed the data. However, there is still nothing to indicate that they have reviewed the clinical trials. Indeed, they state "currently available data do not show ivermectin is effective against COVID-19" and "ivermectin has not been shown to be safe or effective for these indications", which are both false.

Conclusion

Ivermectin is an effective treatment for COVID-19. Treatment is more effective when used early. Meta analysis using the most serious outcome shows 63% [53‑72%] and 83% [74‑89%] improvement for early treatment and prophylaxis, with similar results after exclusion based sensitivity analysis, for primary outcomes, for peer-reviewed studies, and for RCTs. Statistically significant improvements are seen for mortality, ventilation, ICU admission, hospitalization, recovery, cases, and viral clearance. All remain significant after exclusions. 53 studies from 48 independent teams in 22 different countries show statistically significant improvements in isolation (39 for primary outcomes, and 36 for the most serious outcome). Results are very robust — in worst case exclusion sensitivity analysis 54 of 82 studies must be excluded to avoid finding statistically significant efficacy.

Responses

Inconclusive meta analyses.

[Popp, Roman] provide meta analyses that show positive effects without reaching statistical significance. The primary methods used that result in a lack of statistical significance are the exclusion of the majority of the evidence base, and division of the remaining subset. For more details see the study notes.

Primary outcome analysis.

We use fixed pre-specified effect extraction to avoid bias and to focus on the most clinically relevant results. For comparison, we have also performed analysis using the primary outcome of studies (shown in the supplementary data), with results showing similar effect sizes. Prophylaxis results are very similar with 100% (16 of 16) positive effects. Early treatment shows 97% (31 of 32) positive effects, improved due to the very small event count negative serious outcomes in Krolewiecki, Vallejos, and Buonfrate no longer having priority. Late treatment shows 71% (24 of 34) positive effects, reduced slightly, primarily due to viral clearance results being the primary outcome in some studies, and viral clearance being less successful with late treatment. Overall, the primary outcome analysis shows 87% (71 of 82) positive effects, which is currently identical to the results of the main protocol analysis.

Meta analysis should not combine heterogeneous studies.

All meta analyses combine heterogeneous studies, because all studies differ in one or more ways, including patient demographics, treatment delay distribution, effect measured, SARS-CoV-2 variants, and treatment regimens (note that this is different to heterogeneity caused by bias). Combining heterogeneous studies may obscure efficacy - for example if treatment within 24 hours is twice as effective as treatment within 48 hours and we include studies with later treatment; or if a treatment is effective at reducing mortality but has no effect on viral clearance and we include viral clearance studies. Including studies that are further from the optimal treatment situation will reduce the observed effect size. This can be seen in the treatment delay analysis - late treatment is less effective and including late treatment studies lowers the effect size. For any negative meta analysis, we must consider if the treatment is effective but only in a subset of the situations covered by the studies (or a situation not covered by any study, for example few treatments have studies with a treatment delay <= 24 hours).

BBC response.

Update: authors indicated that their data would be available "soon" as of Sep 14, 2021, however it has not been released six months later.

A BBC article raises questions due to data issues in some studies, based on an analysis from a team of researchers. One of the researchers reports that data in some trials could have been manipulated, while noting that human error can not be ruled out. Others in the team directly accuse authors of malfeasance. Regardless of the cause, concern over these studies is valid. Currently, 2 studies have been retracted, one was withdrawn by a preprint server, and another has been reported as pending retraction, although the journal reports that no retraction is pending. None of these studies are in our analysis.

Existence of some lower quality studies is typical in large evidence bases. The percentage of studies with issues is not greater than reported averages, and is not close to removing evidence of efficacy (and may actually improve evidence as detailed below). We performed an absolute worst case sensitivity analysis, where positive studies are excluded in order of the effect size, with the largest effect first. 66%, or 54 of 82 studies must be excluded to avoid finding statistically significant efficacy (this is in addition to the four papers not in this analysis).

The summary statistics from meta analysis necessarily obscure most of the information in the evidence base. For those that have read all of the research, knowledge of efficacy is supported by extensive additional information, including for example relationships between outcomes within a study, dose-response relationships within and across studies, treatment delay-efficacy relationships within and across studies, variant-efficacy relationships, etc. Notably, removal of Elgazzar, Samaha, and Niaee improve the treatment delay-efficacy and dose-response relationships and may further increase confidence when considering all information.

Concerns about [Cadegiani, Carvallo, Carvallo (B), Carvallo (C)] have also been reported. All of these studies are excluded in our exclusion analysis.

	Studies	Prophylaxis	Early treatment	Late treatment	Patients	Authors
With GMK/BBC exclusionsw/GMK/BBC exclusions	55	82% [68‑89%]	70% [62‑76%]	56% [35‑70%]	114,959	595
RCTs w/GMK/BBC exc.RCTs w/GMK/BBC exc.	27	84% [25‑96%]	67% [55‑75%]	29% [4‑48%]	4,985	333
Percentage improvement with ivermectin treatment after exclusion of all studies reported by this team

We note that, while malfeasance cannot be ruled out, reported concerns may also be caused by typos, data collection errors not affecting analyzed outcomes, and expected results from multiple tests. Authors, without any prior registration or statistical analysis plan, perform thousands of statistical tests across data in the studies and report results without correcting for multiple tests. For example, reporting the occurrence of a 1 in 1,000 event as evidence of randomization failure, while performing more than this number of tests across studies.

This group often dismisses studies based on an arbitrary statistical significance threshold for a specific outcome, a misunderstanding of statistics [Amrhein], and indefensible as a pre-filter in meta analysis.

This group has made many claims unsupported by the data. For Niaee, one author claimed the study "made a HUGE difference". It has no effect on early treatment or prophylaxis. For late treatment, which is not recommended, the change was relatively minor. For Elgazzar, the author claimed that it could be "the most consequential medical fraud ever committed". There was almost no difference in our analysis after removing this paper (excluding 1 of 85 studies has very little effect, and the exclusion actually improves the treatment delay-response relationship).

Statements by the group suggest significant bias. The main author first referred to ivermectin as "something else to debunk" in December 2020, and later as a "horse dewormer". Another group member has called for charging scientists that recommend vitamin D with "crimes against humanity".

The group has made claims about all ivermectin evidence based on the existence of some studies with issues. It is inappropriate to generalize about the entire group of 815 scientists and researchers based on the mistakes or actions of a few individuals.

This group has focused on finding issues in papers reporting large positive effects, which introduces a significant bias. Notably, the few studies that contribute most to minimizing the effects in meta analysis include studies with very high conflicts of interest and many reported protocol violations and data issues, however this group disregards all of these issues.

The article claims "The largest and highest quality ivermectin study published so far is the Together trial" which "found no benefit", however this study has not been published, is one of the lowest quality trials with many documented design, execution, and analysis issues, has extremely high conflicts of interest, there is a history of inaccurate reporting prior to publication for a previous treatment in the same trial, and the trial actually reported 18% lower mortality (not statistically significant).

The article reports that 26 studies were examined, however there are 85 studies, authors have not reported their results for all 26, and authors have not provided their data after repeated requests. Currently they have not even provided a list of the 26 studies.

The group has an excessive focus on RCTs, which have a fundamental bias against finding an effect for interventions like ivermectin that are widely known and easily available — patients that believe they need treatment are more likely to decline participation and take the treatment [Yeh] (this does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable and unfamiliar).

The main author of the group is also against vitamin D. Of the 73 vitamin D COVID-19 treatment studies, author suggests only one trial is worth looking at [Murai]. This gives us a simple case to examine potential bias. [Murai] is a small trial providing no statistically significant effects (mortality p = 0.43, other outcomes are positive while also not significant). Author acknowledges that the trial is too small for a conclusion. More importantly, this trial provides no information about whether vitamin D reduces the risk of a serious COVID-19 case, because the patients in this trial already had a serious COVID-19 case (90% already on oxygen treatment at baseline). Author does not mention this. The trial also has poorly matched arms in terms of gender, ethnicity, hypertension, diabetes, and baseline ventilation, all favoring the control group. Further, this study uses an inappropriate form of vitamin D — cholecalciferol. In reality physicians would use calcifediol or calcitriol with late stage treatment, because they avoid a very long delay for conversion. We are unaware of a reason to use cholecalciferol in this case (other than to produce a null result). In summary, author's chosen study is the study providing the least useful information from the 73 vitamin D treatment studies to date, suggesting biased analysis.

We fully support this team's effort to clean up the evidence base. This is extremely valuable and improves the integrity of the evidence base (and the accuracy if done equally for all studies). We hope this or other teams can do the same for all treatments. However the analysis plan should be published, details of all tests should be provided, results should be corrected for multiple testing, results for all studies and tests should be provided, and equal attention should be given to studies with non-statistically significant results, especially those with major reported data issues that have been disregarded by this team (for example data suggesting substantial protocol violations including confounding by time in [Reis] and control arm use of treatments in [López-Medina]).

For coverage of other errors in the BBC article, and illumination of the stark contrast between Dr. Lawrie's response to the BBC before publication and what they chose to report, see [BiRD Group, Campbell, Elijah, Lawrie (B)].

More details can be found in the following response regarding the main author of this group.

GMK response.

An influential anti-treatment Twitter personality, journalist, and epidemiologist has made a number of incorrect, misleading, hyperbolic, and unsupported statements. Author is notable as the only known researcher that reports having read a majority of the 85 (including retracted) studies, but does not find the evidence to be positive. However, their opinion appears to have been formed before reading the studies — they first referred to ivermectin as "something else to debunk". We note that the author has made very valuable contributions identifying significant issues with some studies, which has helped to improve the quality of the ivermectin evidence base, and has improved the dose-response and treatment delay-response relationships.

Analysis with GMK's recommended exclusions can be found in the supplementary data, which shows 47% [31‑59%] improvement, p = 0.0000035.

Author has been paid for writing anti-treatment articles, and has also referred to ivermectin as a "horse dewormer". Author has experienced personal tragedy with multiple family members having died of COVID-19, which may introduce a bias against acknowledging errors in treatment advice. If the author continues to deny the efficacy of treatments like ivermectin or vitamin D, we encourage them to at at least direct readers to government-approved treatments, for which there are several in the author's country, and many more in other countries (including ivermectin). While approved treatments in a specific country may not be as effective (or as inexpensive) as current evidence-based protocols combining multiple treatments, they are better than no recommendation.

Author's attempt to discredit ivermectin research centers on the fundamentally false assertion that excluding a small number of lower quality trials results in a negative outcome. It should be clear from the forest plot that this is not possible, but we can be more specific. We perform a worst case sensitivity analysis, where positive studies are excluded in order of the effect size, with the largest effect first. How many studies do we need to exclude before the meta analysis RR has a confidence interval exceeding 1.0? 66%, or 54 of 82 studies must be excluded to avoid finding statistically significant efficacy. As with all data in this paper, this analysis will automatically update as the evidence base evolves. Also note that this is after exclusion of withdrawn papers - one has never been in this analysis, the second was removed on the same day it was withdrawn, and the other two were removed in advance of retraction based on author's notification that retraction is pending (only one has been retracted, the journal for Niaee et al. has reported that no retraction is pending).

Author claims that we include several papers that are already excluded in the 10 exclusion analyses.

Author claims that there is a greater percentage of low quality studies for ivermectin and COVID-19 compared to other treatments. This is unsupported for such a large evidence base, and does not match previous studies.

Author often makes a basic error by equating positive effects that are not statistically significant at a specific level with "no effect", a misunderstanding of statistics [Amrhein]. For example, if a study reports 50% improvement with a p value of 0.1, we cannot say that the study shows the treatment is ineffective, or in the words of the author shows "no benefit at all". Author repeatedly makes false claims in this way.

On Sep 14, 2021, author indicated that their team had reviewed about 30 ivermectin studies and their data would be available soon, however it has not been released six months later.

Author appears to favor pharmaceutical company affiliated/operated trials. For example, the author has no problem with the lack of IPD for many pharmaceutical affiliated COVID-19 trials that support the author's treatment positions, yet considers the lack of IPD in a positive ivermectin trial to be problematic. Author believes the pharmaceutical affiliated Together Trial is the highest quality trial so far, yet not only is there no IPD currently available, there is no preprint, the trial has many documented design, execution, and analysis issues, has extremely high conflicts of interest, and there is a history of inaccurate reporting prior to publication for a previous treatment in the same trial.

Author disregards treatment delay in analysis, which results in incorrect conclusions. For example, author claims that the RECOVERY trial proved that another treatment is not effective, and would provide definitive data if the same was done for ivermectin. The trial provided valuable data on very late use (9 days after symptoms) with an excessively high dose and very late stage patients. However, it did not provide information on early treatment. Oseltamivir, for example, is generally only considered effective for influenza when used within 0-36 or 0-48 hours [McLean, Treanor]. Paxlovid was tested with a maximum of 3 days from symptom onset (the mean delay is unknown). For ivermectin, author believes the PRINCIPLE trial will provide strong data on efficacy, however this trial includes low risk patients less than 15 days from symptom onset, and may only provide information on late treatment in a low risk population. Figure 28 shows a mixed-effects meta-regression for efficacy as a function of treatment delay in COVID-19 studies from 40 treatments. Efficacy declines rapidly with treatment delay.

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Late treatment results
are not representative

Figure 28. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 40 treatments.

Author has an unwarranted focus on a specific outcome (mortality) and a specific subset of trials (RCTs). This would be reasonable in many cases when sufficient high-quality data is available, however this is not the case for off-patent COVID-19 treatment trials, where RCTs often involve delayed treatment, low-risk patients where mortality is rare, or very high conflicts of interest. Widely accepted and effective (for specific variants) treatments like casirivimab/imdevimab, bamlanivimab, and sotrovimab were all approved without statistically significant mortality benefits. Other outcomes are also important — accelerating viral clearance, and reducing cases, hospitalization, ICU admission, ventilation, etc. are all very valuable, for example reducing serious "long COVID" problems, reducing transmission of the virus, and reducing the burden on the healthcare system. These outcomes are also likely to correlate with reduced mortality among larger or higher-risk populations. We note that there is extensive evidence for the mortality outcome when not restricting to RCTs. RCTs have mostly been run with relatively low risk populations where mortality is low, leading to limited statistical significance. However RCTs are inherently biased towards low mortality and towards not finding an effect in this case — ivermectin is well-known to be beneficial for COVID-19 and is easily available, therefore participants that believe they may be at serious risk are more likely to decline participation in the RCT and take the recommended medications. Patients that do choose to participate are also more likely to have low adherence. This bias of RCTs is likely to be even larger in locations where ivermectin is widely used in the community and very easily obtained, which correlates with the observed RCT results.

Author suggests that we have chosen the wrong outcome in some cases. While mistakes are possible, for example we corrected errors with Espitia-Hernandez et al. and Jain et al., the claims made suggest that the author has not read the studies and/or our protocol carefully. Details are below. We note that the author disregards the existence of the individual outcome analyses and the primary outcome analysis.

Most errors have not been corrected over eight months later. Many false, misleading, and defamatory statements continue to be available, highly-ranked in search results, and highly influential. Other errors include:

•that excluding Elgazzar et al. completely changes the results and could be "the most consequential medical fraud ever committed". Excluding 1 of 85 studies has very little effect, and the exclusion improves the treatment delay-response relationship.

•that Niaee et al. "made a HUGE difference". It has no effect on early treatment or prophylaxis. For late treatment, which is not recommended, the change was relatively minor, and the exclusion improves the treatment delay-response relationship.

•making basic errors suggesting very superficial reading of studies, for example claiming the RR in Szente Fonseca is the risk of being treated.

•making basic errors suggesting very superficial reading of this paper, for example claiming that a result for prophylaxis studies is based on the number of patients from all studies.

•equating a high degree of COVID-19 in a country partially adopting a treatment with a lack of efficacy, disregarding obvious confounding such as heavily affected areas being more likely to adopt treatment (analysis of results in regions or time periods adopting treatment, while not equivalent to controlled studies, is more informative and shows efficacy [Chamie-Quintero, Chamie-Quintero (B), Merino, Ontai]).

•confusing heterogeneity due to dose, treatment delay, etc. and due to bias.

•disregarding treatment delay to dilute or obscure effects by including late treatment (author has also used this method with other treatments).

•disregarding the existence of specific outcome analyses, RCT analysis, and exclusion-based sensitivity analysis.

•suggesting that efficacy over longer periods is not possible because ivermectin has a half-life of "about a day". Author disregards known efficacy for other conditions over much longer periods, and mischaracterizes the half-life. Antiparasitic efficacy can persist for several months after a single dose [Canga]. Plasma half-life is longer in some studies, and significant plasma concentration can persist for over 2 weeks in some patients [Muñoz]. More importantly, ivermectin is highly lipophilic and may accumulate in the lung and other tissues where concentrations may be many times higher [Chaccour (B), Chiu].

•misunderstanding funnel plot analysis and explanations other than selective reporting (and providing no evidence of unreported negative studies, while there is substantial evidence of difficulty publishing positive studies [Jerusalem Post, Kory (B)]).

•suggesting that it is impossible to combine evidence from mortality and hospitalization (for example), but combining late treatment and early treatment in order to obscure efficacy (if a treatment reduces disease severity requiring hospitalization, reduced mortality in at-risk populations logically follows, whereas lack of efficacy several days after onset can not be extrapolated to early treatment — treatments for a viral infection are often less effective when delayed).

•making serious claims about individual studies without contacting authors (for example claiming patients were excluded for reaching the endpoint too quickly in one study, whereas authors report exclusions due to baseline negative status).

•author is unaware of different variants, suggesting that results should be identical for treatment at a given delay, even when the predominant variants have markedly different peak viral load, time to peak viral load [Faria, Karita, Nonaka], and mortality (for example Gamma vs. non-Gamma aHR 4.73 [1.15-19.41] [Zavascki]).

The cases where author suggests we have chosen the wrong outcome indicate that the author has not read the studies and/or our protocol carefully:

•suggesting that the risk of a good outcome should be selectively used instead of the risk of a bad outcome (author would like to do this when it reduces the effect size). This is similar to using the risk of surviving instead of the risk of death. 99% survival may only be a 4% improvement over 95% survival, but most people would appreciate the 80% lower risk of death.

•suggesting that hospitalization time should be used for symptomatic recovery in a study where discharge is based on viral clearance (and only tested weekly).

•suggesting that a specific symptom such as cough should be used (author would prefer a less positive result for the study).

•suggesting that viral load is more important than symptomatic results.

•suggesting that mortality should be used in populations with zero mortality (for low-risk populations with no mortality, reduction in mortality is not possible, this does not mean a reduction in hospitalization, for example, is not valuable).

•suggesting that unadjusted results should be used in a study where the adjustments clearly make a significant difference (author wants to cherry-pick unadjusted cough results).

•suggesting that, for example, in a study of viral load where all patients recover, it is not valuable if treated patients recover faster (or are less likely to transmit the virus to others).

•suggesting that study selected outcomes should have priority rather than using a consistent pre-specified protocol, disregarding the added bias and the fact that this actually improves results for ivermectin (for example the very small event count negative serious outcomes in Krolewiecki, Vallejos, and Buonfrate would no longer have priority).

•suggesting that cough is a more important symptom than low SpO₂ or fever. Cough can persist for a long time after more serious symptoms resolve, and persistent cough may be caused by many conditions.

•suggesting that combined low dose treatment results should be used in a study that had a combined ivermectin/doxycycline arm (single dose ivermectin, 5 days doxycline) and an ivermectin arm with treatment for 5 days.

We note that this personality has an extensive history of incorrect advice, including for example:

•claiming that flu is more dangerous than COVID-19

•claiming that SARS-CoV-2 is not airborne

•claiming that it's impossible to improve immune system functioning

•even believing and propagating a made up story that claimed ivermectin overdose was causing gunshot victims to wait at an ER

Author has taken a public position against early treatments for COVID-19 since at least July 2020. Given this longstanding and influential negative position, they may tend to view information with a negative filter and confirmation bias, and may be reluctant to admit errors. They acknowledge not having read all of the studies (and appear to have very superficially read others). They submitted zero feedback to us, suggesting that they know their comments are incorrect or that they have a motivation other than correcting errors. Author claims that they could not contact us, however there are over 50 feedback links throughout this article. We also note that the author is not open to critical feedback and routinely blocks Twitter users correcting mistakes or expressing anything critical on their feed. Reports suggest that the author also pre-emptively blocks people that have not even interacted with them, but are connected to other users reporting on their errors. Author ackowledges using a tool called MegaBlock that blocks all people that liked a specific tweet.

The author is also against vitamin D. Of the 73 vitamin D COVID-19 treatment studies, author suggests only one trial is worth looking at [Murai]. This gives us a simple case to examine potential bias. [Murai] is a small trial providing no statistically significant effects (mortality p = 0.43, other outcomes are positive while also not significant). Author acknowledges that the trial is too small for a conclusion. More importantly, this trial provides no information about whether vitamin D reduces the risk of a serious COVID-19 case, because the patients in this trial already had a serious COVID-19 case (90% already on oxygen treatment at baseline). Author does not mention this. The trial also has poorly matched arms in terms of gender, ethnicity, hypertension, diabetes, and baseline ventilation, all favoring the control group. Further, this study uses an inappropriate form of vitamin D — cholecalciferol. In reality physicians would use calcifediol or calcitriol with late stage treatment, because they avoid a very long delay for conversion. We are unaware of a reason to use cholecalciferol in this case (other than to produce a null result). In summary, author's chosen study is the study providing the least useful information from the 73 studies to date, suggesting biased analysis.

Based on many comments, author appears to focus on superficial criteria such as typesetting and quality of writing. While many of the studies have been performed by non-native English speakers with minimal budgets, this does not imply the researchers are less reliable. Indeed, the author is highly critical of the program used to create a graph, for example, but is unable to see flaws in high budget high conflict of interest trials, even when they prompt >100 scientists to write an open letter requesting retraction [Open Letter].

Eight months later, the author has still not contacted us, making content-free comments on Twitter such as calling us "sh*tty". Other individuals pointing out errors with detailed and careful feedback get similar treatment, such as being called a "d*ckhead" and being blocked.

More details can be found in the BBC response.

SSC response.

We note a few limitations and apparent biases in the SSC ivermectin analysis.

Analysis with SSC's recommended exclusions can be found in the supplementary data.

Author appears to be against all treatments, labeling them all "unorthodox" and "controversial", even those approved by western health authorities, including casirivimab/imdevimab, bamlanivimab, sotrovimab, and paxlovid. Update: author's original article still refers to all treatments we follow as unorthodox and controversial, however they report that they actually recommend fluvoxamine, paxlovid, casirivimab/imdevimab, bamlanivimab/etesevimab, and sotrovimab, and suggest that they support all western health authority approved treatments which additionally includes remdesivir, budesonide, bebtelovimab, tixagevimab/cilgavimab, and molnupiravir. Author also has positive comments for zinc (but reports there is no proof). i.e., author appears to actually support at least 11 of the 40 treatments we follow. We note that the methodology is the same for all treatments.

We encourage the author to at least direct readers to government approved treatments, for which there are several in the author's country, and many more in other countries (including ivermectin). While approved treatments in a specific country may not be as effective (or as inexpensive) as current evidence-based protocols combining multiple treatments, they are better than dismissing everything as "unorthodox". Elimination of COVID-19 is a race against viral evolution. No treatment, vaccine, or intervention is 100% available and effective for all variants — we need to embrace all safe and effective means.

The third-party analysis that author references for the strongyloides theory is confounded by treatment delay and dosage — the high prevalence group has more early treatment trials and a higher average dose, i.e., the analysis reflects the greater efficacy of early treatment and the greater efficacy of higher dosage. More details can be found in the strongyloides section.

Author refers to studies with positive but not statistically significant results as "negative" [Mohan], or "[the] original outcome would also have shown ivermectin not working" [López-Medina], which are incorrect conclusions [Amrhein]. Update: author believes this means we abandon statistical significance. We do not know where this comes from — all of our results report confidence intervals, and the first two words of this paper are "statistically significant". What is incorrect is making a negative conclusion based on an insignificant result. For example, if one study reports 50% lower mortality without reaching statistical signifiance, this does not mean that the treatment is useless. Consider if there are 10 studies all reporting ~50% lower mortality, the combined evidence may be strong even if each individual result is not statistically significant.

Author notes that: "if you say anything in favor of ivermectin you will be cast out of civilization and thrown into the circle of social hell reserved for Klan members and 1/6 insurrectionists", suggesting an environment that may bias the information that the author sees, and could unconsciously bias analysis. We note that similar environments influence the design, operation, and publication of some existing (and many upcoming) ivermectin trials.

Author looks at 29 of the 82 studies, which we note is much better than most commenters, but still ignores the majority of studies, including the prophylaxis studies.

The author finds efficacy at p = 0.04 in their analysis of 11 of the 29 studies they looked at. We note that simply looking at the other 53 studies will result in much higher confidence in efficacy. We also note that even at p = 0.04 with 11 independent studies, a rational risk-benefit analysis results in immediate adoption into protocols (pending stronger data with other combinations of treatments), and immediate collection of more data from sources without conflicts of interest.

However, ultimately the author at least partially supports the two prevailing theories that are commonly used by those against treatment. These theories require disregarding extensive contradictory evidence:

The steps required to accept the no-significant-effect outcome are extreme — one needs to find a reason to exclude most of the studies, disregard the strong treatment-delay response relationship, and disregard all prophylaxis studies. Even after this, the result is still positive, just not statistically signficant. This does not support a negative recommendation. Widely accepted and effective (subject to dependence on viral variants) treatments like casirivimab/imdevimab, bamlanivimab, and sotrovimab were all approved without statistically significant mortality benefits.

The steps required to accept the strongyloides-mechanism-only conclusion are also extreme - we need to disregard the majority of outcomes occuring before steroid use, and disregard the strong treatment-delay response relationship which is contradictory. Figure 26 shows analysis by strongyloides prevalence. The third-party analysis referenced by the author is confounded by treatment delay and dosage.

Author seems biased against believing any large effect size. We note that large effect sizes have been seen in several COVID-19 treatments approved by western health authorities, including paxlovid which the author is very positive about, and also that better results may be expected when studies combine multiple effective treaments with complementary mechanisms of action (as physicians that treat COVID-19 early typically do). Update: author confirms this bias but appears to disregard it for paxlovid.

Author is suspicious about a study based on the country of the researchers, and also appears biased against non-native speakers, with comments such as "unreadable" for one paper, compared to "written up very nicely in real English" for another. Update: author confirms being biased against certain countries.

Author calls a physician that has reported zero deaths and 5 hospitalizations with 2,400 COVID-19 patients "a crazy person" that "put his patients on every weird medication he could think of".

Author disregards the dramatically higher mortality for Gamma vs non-Gamma variants (aHR 4.73 [1.15-19.41] [Zavascki]), instead concluding that higher mortality indicates fraud in one instance, while in another instance assuming that the related confounding by time in the Together Trial is not significant.

Author's review of the 29 studies appears relatively cursory, for example author appears unaware that the ivermectin dosage is very different in the ivermectin + doxycycline arm of [Ahmed].

Author appears to accept the analysis and accusations of GMK as correct, however that author is often incorrect.

Author is concerned that we detail problems with [López-Medina], while correctly noting that the outcomes in this trial are actually positive and in favor of ivermectin (while not statistically significant in isolation).

Author is concerned that we specifically comment on [López-Medina, Reis]. We note that it has been others that have focused on these trials — we comment on them because they have received special attention, including being held up as sole evidence overriding all other trials, despite having major issues.

Author claims that nobody can find issues with [Vallejos], which suggests that they have not read the study, or our analysis.

AT response.

A technology blog published an article with incorrect and unsupported claims. The article refers to c19ivermectin.com (which is only a database of ivermectin research), but makes comments about this analysis. Most of the comments in this article are already addressed above.

Author correctly notes that the majority of results are positive and that no matter how you slice the data, the results are positive, but appears to dismiss the obvious reason without examining the evidence.

Author believes that because other effective treatments exist, and because we have also covered those, there must be a positive bias. For ivermectin though, we find evidence of a negative publication bias, and despite enormous worlwide attention, there is no evidence of missing negative trials, while there is substantial evidence of positive trials being delayed by editors(journals fast track null results, while holding positive trials and later returning them without review). We also note that many of the effective treatments are adopted by governments worldwide, including several in the author's country. Appoved treatments include sotrovimab, casirivimab, imdevimab, bamlanivimab, etesevimab, budesonide, favipiravir, and convalescent plasma (although not showing efficacy in our analysis), others have already been purchased pending approval or are not yet available (molnupiravir, proxalutamide), and others are widely accepted to be helpful, including in the author's country, despite gaining minimal attention from authorities (vitamin D, vitamin C) [Miller].

Author finds the heterogeneity in dosage, treatment time, etc. concerning. This heterogeneity is beneficial and gives us much more information on the situations where treatment is effective, and the optimal dosage. Results from a single study only apply to the conditions of that study and cannot be extrapolated to other conditions — author makes this mistake claiming another treatment is ineffective based on definitive evidence, but that evidence only applies to very late treatment in a very sick population with excessive dosage — not the optimal use of an antiviral for COVID-19. While we cannot use the larger evidence base to predict a specific situation, e.g., mortality in high risk patients with specific treatment delay and dosing, we can use the larger evidence base as evidence for/against efficacy, and many subgroup analyses have sufficient evidence for more specific cases.

Author refers to the withdrawn Elgazzar study (removed from this analysis on the same day) as a major development, however there was no significant change. Excluding 1 of 85 studies has very little effect, and the exclusion actually improves the treatment delay-response relationship. 54 of 82 studies need to be excluded to avoid finding statistically significant efficacy in a worst case sensitivity analysis.

Author is concerned that some studies use combined treatment, however 65 do not use combined treatment, and most of the additions are treatments independently known to not have significant efficacy alone.

We also note that the author has never contacted us.

How should the result be interpreted when pooling effects?

In the pooled analysis, the result is a weighted average of the improvement in the most serious outcome reported. The specific analyses should be used for specific outcomes. Note that a reduction in mortality logically follows from a reduction in hospitalization, which follows from a reduction in symptomatic cases, etc. Note that we have to consider all information to create the most accurate prediction of efficacy. While there are more sophisticated ways to combine all of the information, the advantage of the method used here is simplicity and transparency. Note that the highly significant results observed are without incorporating additional information that would further increase confidence, such as the treatment delay-response relationship.

Elgazzar.

This study was withdrawn and was removed from this analysis on the same day. There was no significant change (excluding 1 of 85 studies has very little effect, and the exclusion actually improves the treatment delay-response relationship).

Samaha.

This study was removed from this analysis within an hour of notification that it was pending retraction. There was no significant change in the results, and the exclusion improves the dose-response relationship.

Carvallo.

Concerns have been raised about [Carvallo]. There appears to be some valid concerns with potential data issues, and this study is excluded in the exclusion analysis. There is no significant change in results, with only a minor reduction in prophylaxis efficacy to 82% [68‑89%]. However, it is difficult to trust information from the personality reporting the concerns. The author suggests that the study may not have happened at all, claiming for example that the team could not have afforded the medications without funding, and that a busy clinician would not have enough time. However, with just basic checks, the author would know that a drug company has confirmed donating the medications, that they confirmed authorization for the study was received, that the main hospital for the study requested additional supplies, and that the hospital confirmed ethics committee approval. For additional details see [O'Reilly]. We also note that the combined treatment in this study has been independently shown to be effective, and the complementary mechanisms of action support improved efficacy of the combination [Figueroa].

Study Notes

For discussion of all studies see c19ivermectin.com. A few studies have received special attention, with some considering them to be very strong evidence overriding the other 81 studies. We note limitations of these studies here.

Together Trial.

"There is a clear signal that IVM works in COVID patients.. that would be significant if more patients were added.. you will hear me retract previous statements where I had been previously negative" — Ed Mills, Together Trial co-principal investigator [stevekirsch.substack.com]

"..the question of whether this study was stopped too early in light of the political ramifications of needing to demonstrate that the efficacy is really unimpressive.. really could be raised.." — Frank Harrell, "I totally agree with Frank" — Ed Mills [vimeo.com]

Submit Updates or Corrections

Many basic inconsistencies and protocol violations. There are many major issues with the protocol and data as detailed below.

Apr 5: The paper was updated, with no indication or explanation of the changes. Changes include: age range, placebo description, per-protocol count, and death counts (details below). Apr 9: Authors have still not responded to the data request. There is still no explanation for the Apr 5 changes. Data in this trial appears to be unreliable.

Data issues: unexplained delay no response to data request 3 different death counts patient count mismatch conflicting placebo arm counts (recently updated) unknown onset results dramatically better low active arm side-effects incorrect conclusion conflicting comorbidity counts unclear screening to treatment delay missing age information vaccination status unclear large change from previously reported results mean delay likely excluding unknown onset two different per-protocol counts 3-dose placebo much more effective dominated by Gamma variant, no discussion

Delayed >6 months. The paper was delayed over 6 months with no explanation. The companion fluvoxamine arm, completed at the same time, was published Aug 23, 2021.

No response to data request. Authors have not responded to a request for the data (requests can be sent to thetogethertrial@gmail.com, let us know the outcome). The trial registration states that data was to be available at termination and upon request [clinicaltrials.gov (B)].

Three different death counts. In the original paper, Table 3 shows 21 and 24 deaths, while Table S6 shows 20 and 25 [twitter.com (C)]. In Table 3, death and grade 5 events showed the same 21/24 numbers, but different effect sizes, with 0.81 being closer to the 20/25 counts and the previously reported number. This is consistent with one death being moved between arms after manuscript generation, but not updated in Table S6 or the Table 3 AE RR. This cannot be explained by the safety population excluding patients with zero doses because the AE control deaths are higher. In email, a co-principal investigator suggested that the discrepancy was due to one being COVID-19 deaths and the other being all-cause deaths [stevekirsch.substack.com]. That explanation does not fit the data because one arm increases while the other arm decreases. Both co-principal investigators report in the paper that "they had full access to all the trial data and vouch for the accuracy and completeness of the data and for the fidelity of the trial to the protocol." A third set of death counts, 20 and 24, with RR 0.84, was presented by a co-principal investigator on Mar 18, 2022 [vimeo.com (B)]. In total, 4 different death relative risks have been presented: Mar 18, 2022 presentation: 0.84, March 30 paper: 0.88 (T3), 0.81 (T3 AE), and 0.80 (TS6, presented as 20 and 25 only without group sizes). 6 days after publication, the paper was updated, with no information given on what was changed. In this version, a "respiratory, thoracic and mediastinal disorders" death was removed from the control arm and an "infections and infestations" death was added to the ivermectin arm. The paper still indicates RR 0.81 for death AE. JAMA's policy indicates that a correction notice summarizing errors and corrections should be provided [jamanetwork.com].

Trial was not blind. Ivermectin/placebo blinding was done by assigning a letter to each group that was only known to the pharmacist. If a patient received a 3-dose treatment, investigators immediately know that the patient is more likely to be in the treatment group than the control group, because 3-dose placebo was relatively rare. If a patient received non-3-day treatment, investigators immediately know that the patient is not an ivermectin treatment patient. Moreover, by observing the frequency of allocations, investigators can easily determine which letter corresponds to active ivermectin 3-day treatment, thereby removing all blinding. Note that we only know about this blinding failure because the journal required the authors to restrict to the 3-day placebo group. Also note that this may apply to all arms of the Together Trial, and that it would have been trivial to avoid if desired.

Patient counts do not match previously released enrollment graph. Authors claim the ivermectin and control patients were all from on or after March 23, 2021, however independent analyses of the enrollment graph (contained in this presentation [dcricollab.dcri.duke.edu]) require including patients prior to this date to reach the reported numbers [doyourownresearch.substack.com, longhaulwiki.com].

Funding conflict. The paper does not include the Bill and Melinda Gates Foundation or Unitaid as funders, however the Mar 25, 2021 protocol shows the Gates Foundation [static1.squarespace.com], and the web site shows Unitaid [togethertrial.com].

DSMC not independent. Reviewer 1 of the protocol notes that the DSMC is not independent [gatesopenresearch.org]. Prof. Thorlund is Vice President of the contract research organisation (CRO, Cytel), professor at the sponsoring university, and an author of the protocol. Dr. Haggstrom is an employee of the CRO. [doyourownresearch.substack.com, twitter.com (D)] reveals many other conflicts. Thorlund has written >100 papers with Mills. Singh has written 29 papers with Mills. Orbinski has written 9 papers with Mills. The first version of the web site showed Mills and Thorlund as joint leads. Emails pointed to a company MTEK Sciences, founded by Mills and Thorlund (MTEK is hypothesized to stand for Mills, Thorlund, Edward, Kristian). MTEK received grants from the Gates Foundation. MTEK also employed Haggstrom. MTEK was acquired by Cytel in 2019. The DSMC chair has published a paper with members of a well known anti-ivermectin research group [Thorlund].

Unequal randomization, significant confounding by time. The trial reports 1:1:1:1 randomization, however independent analysis shows much higher enrollment in the ivermectin treatment arm towards the start of the trial [c19ivermectin.com, longhaulwiki.com]. This introduces very significant confounding by time due to the major change in the distribution of variants, [Zavascki] show dramatically higher mortality for Gamma vs non-Gamma variants (28 day mortality from symptom onset aHR 4.73 [1.15-19.41]). Many more patients were randomized to ivermectin vs. placebo in the first few weeks, for example the first week shows 82 ivermectin vs. 28 placebo patients, 2.9x higher. The period of excess ivermectin enrollment coincides closely with a period of significantly higher deaths and CFR in Brazil.

Missing time from onset patients show statistically significant efficacy. For the known time since onset subgroups, both groups show worse results than the overall results [twitter.com (E)], with the missing 317 patients showing significant efficacy RR 0.51, p = 0.02 (compared to 1.00 and 1.14 for known patients).

Unknown onset patients were enrolled, subgroup results opposite of previous trials. After imputation, the percentage of patients in the late treatment subgroup went from 46% to 56%. 87% of the unknown patients were predicted to be in the late group. This is reasonable and expected — patients that do not recall when the onset was are more likely to have had onset further in the past. What is not clear is how these patients could be enrolled in the trial, how many of these patients had onset >7 days, how this very late 317 patient subgroup could show much greater efficacy as above, and why authors did not report this result, analyze this in greater detail, or recommend further research.

Side effect profile consistent with many treatment patients not receiving authentic ivermectin and/or control patients receiving ivermectin. The side effects (e.g., gastrointestinal side effects were lower in the ivermectin arm) suggest that many ivermectin patients may not have received authentic ivermectin, or that placebo patients may have taken ivermectin. For comparison, there was a 3.6 times greater incidence of diarrhea in the treatment arm in [Lim].

A local Brazilian investigator reports that, at the time of the trial, there was only one likely placebo manufacturer, and they reportedly did not receive a request to produce identical placebo tablets. They also report that compounded ivermectin in Brazil is considered unreliable.

Incorrect conclusion. The conclusion states that ivermectin "did not result in a lower incidence of [hospitalization] or of [ER observation >6hr]". This is incorrect, hospitalization was 17% lower (just not statistically significant).

Ivermectin use widespread in the community. Recent ivermectin use was not in the exclusion criteria. Ivermectin was available OTC, was recommended by the government for COVID-19, and had nine times higher sales [twitter.com (F)]. Authors claim they ensured patients did not use ivermectin via "extensive screening", but do not explain why this was not an exclusion criterion, or how this unwritten exclusion was ensured even though there is extensive missing data related to written exclusion criteria. Similar unwritten exclusions were not mentioned for other arms [twitter.com (G)], a primary investigator previously stated such an exclusion should not be an issue [twitter.com (H)], and it is not mentioned in the interview sheets [osf.io]. After publication, a co-principal investigator reportedly wrote that "even if some patients did access IVM, the fact that it is blinded should still maintain balance", which is incorrect, placebo patients taking ivermectin are expected to improve, treatment patients that already having significant tissue distributions may have positive, neutral, or negative responses to additional treatment.

Single-dose recruiting continued after change. The trial had requested moving to 3-dose treatment by Feb 15/19, when only 19 patients had been recruited, however the trial continued recruiting an additional 59 patients to single dose treatment [twitter.com (I)].

Per-protocol population different to the contemporary fluvoxamine arm. Table 2 per-protocol numbers show 92% per-protocol patients for ivermectin and only 42% for control. This appears to be a post-hoc change selecting only 3-day placebo patients, while similar selection does not appear to have been done for the companion fluvoxamine trial (showing 74% and 82% per-protocol patients for fluvoxamine and control) [Reis (B)].

Time of onset, required for inclusion, missing for 317 patients. For the companion fluvoxamine arm, 24% of patients had an unknown time from onset, including 179 of the control patients [Reis (B)]. In this trial, 0 patients have an unspecified time from onset in Table 1, due to imputation. However, Figure 2 reveals that the time from onset is unknown for 317 patients, similar to the fluvoxamine paper. However, time from onset is required for the inclusion criteria. According to Figure 2, age and BMI also show missing values.

Conflicting comorbidity counts. The companion fluvoxamine arm ran from Jan 20 to Aug 5, 2021, while this trial ran from March 23 to Aug 6, 2021 — most control patients should be shared, with an additional 10% for fluvoxamine from the earlier start. The fluvoxamine control arm shows 16/756 control patients with asthma. The ivermectin control arm has a subset of these patients (679), but shows a much higher prevalence of asthma (60 patients). This might be possible if there was a very high percentage of missing data. Figure 2 shows 282 in the ivermectin arm with cardiovascular disease, which is greater than the sum of every comorbidity in Table 1, even if there was no overlap between comorbidities.

Conflicting placebo arm counts across IVM/FLV arms. The IVM placebo arm has 679 patients and the FLV arm has 756. The 679 should be shared between the arms, with 77 extra patients for FLV.

For FLV, there were 34 patients requiring mechanical ventilation, for IVM there was only 25. The 77 extra patients for FLV need to have had 3.2x greater incidence of ventilation, however ventilation and mortality should have been lower in this period due to the distribution of variants. Death probability was lower for that period.

For FLV, there were 11 grade 1 AEs, for IVM there were 12, with 77 less patients.

For FLV, there were 50 grade 3 AEs, for IVM there were also 50, meaning the 77 extra patients had 0% grade 3 AEs vs. an expected 7.4%

For FLV, there were 54 CKD patients according to Figure 3 and Figure S1 (2 according to Table 2). For IVM there was 5.

Conflicting target enrollment. There are conflicting target enrollment numbers. The protocol showed 800 patients per arm as of Mar 21, 2021 (after the trial started) [static1.squarespace.com, twitter.com (J)], the co-principal investigator reported 800 per arm in an interview published June 14, 2021 [halifaxexaminer.ca], and the protocol changed to 681 on June 22 [static1.squarespace.com (B)]. However, the trial record from Jan indicates 2724 (681*4) patients [clinicaltrials.govz], suggesting that the 800 goal was later, and was kept for fluvoxamine but reverted for ivermectin. The fluvoxamine arm which started two months earlier was terminated at the same time, and was terminated due to superiority [Reis (B)] after 741/756 patients. Note that Gamma was declining significantly around the termination point, which likely favors improved efficacy if the trial continued, given the late treatment and dosage used.

Reportedly terminated for futility although futility threshold not reached. The trial was reportedly terminated due to futility [twitter.com (K)], however the futility thresholds were 20%, 40% and 60%, and all published probabilities are >60% (ITT 79.4%). Additionally, the fluvoxamine arm did not have the higher 60% threshold, only using 40%. Note the DSMC was not independent as below.

Screening to treatment delay. Table 2, schedule of study activities, shows treatment administration one day after screening, baseline, and randomization in the original protocol [drive.google.com], indicating an additional day delay in already late treatment for most patients. The protocol attached to this paper has changed, now stating that the treatment should be administered on the same day of randomization, however there is no explanation of when this change was made, how this change was implemented (there are many tasks in the screening and baseline visits), and no reporting for how many patients received treatment on the same day. The form for the first treatment visit asks if there were clinical events including >6hr ER visits since the baseline visit, which would not be possible if this visit was immediately after randomization. Time of first treatment was recorded [osf.io], but no information has been reported.

Mean delay. The reported mean number of days from symptoms to randomization likely only includes known onset patients and therefore is likely to significantly underestimate the actual average, in addition to not including the time between randomization and treatment.

Viral load not reported. The protocol has change in viral load as an outcome, however only viral clearance is reported, and without any details (for example, using a high Ct value would have limited relevance).

Incorrect dose reporting, many patients at higher risk due to BMI may have received lower per kg doses, and show lower efficacy. The paper reports 400μg/kg for 3 days, however the protocol indicates that this was only up to 90kg, meaning that the dose received for higher-risk high BMI patients was even further reduced from dosage which is already far below clinician recommendations for the dominant variant [twitter.com (L)]. 50% of patients had BMI ≥30. Much greater efficacy was seen in the low BMI subgroup (RR 0.77 vs 0.98).

Plasma concentration below known effective value. [Krolewiecki] show an antiviral effect only with plasma concentrations above 160ng/mL. Figure S5 shows that the authors expected the mean concentration to be well below this level [twitter.com (M)]. Dosage requirements are likely to vary significantly depending on many factors including the variant encountered, time of administration, mode of administration, patient genetics, concomitant medications, SOC, and the distribution of the infection in different tissues. However, the dose used is far below what is recommended by clinicians for post-infection treatment with the Gamma variant — about 2.5 - 6.5x lower, depending on the recommendation and which estimate of fasting/fed administration is used. Moreover Dr. Craig Rayner, a senior investigator on the trial, previously published research indicating that a higer dose is required [sciencedirect.com], raising the question of why the dose and fasting administration was chosen, especially for the initial single dose regimen.

Primary outcome easy to game, selected after ivermectin one dose arm. The subjective "emergency room visit for >6 hours" criterion shows higher risk (RR 1.16), while hospitalization is lower (RR 0.84 in the appendix or RR 0.83 in the paper). The primary outcome results were set on March 21, 2021, after the single dose ivermectin arm. Given the known public biases of some investigators, this may have been specifically chosen to reduce efficacy. Authors claim that the 6hr threshold did not include waiting time, however the emergency visit form has no mention of waiting time, only recording presentation and discharge times [osf.io].

Including contraindicated chronic kidney disease patients. "Stage IV chronic kidney disease or on dialysis" was an inclusion criterion, however ivermectin is contraindicated with kidney disease [Arise, en.wikipedia.org, Nunes] (not always recognized, and may be less critical with very low dose use for other conditions). According to Table 1 there were only 7 CKD patients, however two conflicting numbers are provided in the fluvoxamine paper [Reis (B)]: Table 1 reports 2 CKD placebo patients - it's not clear how CKD was imputed for 3 more patients in the smaller IVM group. Moreover, Figure 3 shows 54 placebo CKD patients for FLV.

Antigen test requirement. The protocol indicates that patients with a negative test may be included if they become positive a few days later, potentially resulting in a long unreported delay between randomization and treatment, depending on how investigators interpreted the protocol. The requirement for a positive antigen test excludes the possibility of early treatment in many cases - tests have very high false negative rates in the early stages of infection, and symptoms may appear before the test becomes positive.

Missing analysis. Authors do not provide time from onset analysis for either mortality or hospitalization, only the combined measure including the ER visits where anomalous results are seen.

Missing PP, mITT mortality, hospitalization results. Authors do not provide per-protocol or mITT results for mortality or hospitalization. Per-protocol mortality results were provided for the companion fluvoxamine trial.

Missing outcomes. Many outcomes specified in the protocol appear to be missing, including the co-primary outcome of COVID-19 mortality (only all-cause mortality is provided, specific AE details not provided), time to clinical failure, days with respiratory symptoms, mortality due to pulmonary complications, cardiovascular mortality, COVID-19 symptom scale assessment, WHO clinical worsening scale assessment, and 14 day mortality.

Missing age information. According to Figure 2, 98 patients are missing age information [twitter.com (N)].

Mid-trial protocol changes. There were several mid-trial protocol changes on July 5, 2021 [clinicaltrials.gov (C)]. The number of patients for viral load analysis was reduced, only for the ivermectin arm. All-cause, cardiovascular, and respiratory death outcomes were deleted. Exclusions were modified to allow enrolling patients vaccinated within the last 14 days. Inclusion criteria were modified to allow enrolling healthy young people — the criterion "fever >38C at baseline" was added, allowing enrollment independent of increased risk.

Vaccine status unclear. The trial appears to have switched to allowing vaccinated patients at some point, however details of any change, and results by vaccination status are not reported [twitter.com (O)].

Large change in results from previously released data. The published results are very different from the previously released results, for example 100/679 vs. 86/677 for the primary outcome ivermectin events. The mortality RR changed from 0.82 to [0.88/0.81/0.80] for [Table 2/Table 2 AE/Table S6].

Statistical analysis plan dated after trial start. The statistical analysis plan appears to be dated after the trial started [twitter.com (P)].

Per-protocol placebo results very different. The 3-dose placebo appears to have been much more effective [twitter.com (Q)].

Imputation protocol violation. The protocol specifies multiple imputation with up to 20% of missing data, however imputation was done with time from symptom onset, which has >23% missing data [twitter.com (R)].

Two different per-protocol counts. Figure 1 shows 228 per-protocol for the control arm, while Table 2 shows 288.

Possibly the largest financial conflict of interest of any trial to date. Disclosed conflicts of interest include: Pfizer, Merck, Bill & Melinda Gates Foundation, Australian Government, Rainwater Charitable Foundation, Fast Grants, Medicines Development for Global Health, Novaquest, Regeneron, Astrazeneca, Daichi Sankyo, Commonwealth Science and Research Organization, and Card Research. Many conflicts of interest appear unreported. For example, Unitaid is a sponsor [Harper, togethertrial.com].

Analysis done by a company that receives payment from and works closely with Pfizer. All analyses were done by Cytel. Cytel is a statistical modelling company that helps pharmaceutical companies get approval — they work very closely with Pfizer [cytel.com]. Cytel's software and services are used by the top 30 pharmaceutical companies [cytel.com (B)].

A co-principal investigator works for Cytel and the Gates Foundation [empendium.com]: "The majority of the time I work for a company called Cytel, where I design clinical trials, predominantly for the Bill & Melinda Gates Foundation".

The Gates Foundation is a founding partner of GAVI, which took out Google ads telling people not to use ivermectin [twitter.com (S)], and a major funder of Unitaid, which may have modified the results of the Hill meta analysis in a way that prevented adoption [c19ivermectin.com (B), c19ivermectin.com (C), twitter.com (T)].

Associated with MMS Holdings. The trial is associated with MMS Holdings [dcricollab.dcri.duke.edu], whose mission includes helping pharmaceutical companies get approval and designing scientific studies that help them get approval. One of their clients is Pfizer [mmsholdings.com].

Certara. One of the senior investigators was Dr. Craig Rayner, President of Integrated Drug Development at Certara - another company with a similar mission to MMS Holdings. They state on their website that: "Since 2014, our customers have received over 90% of new drug and biologic approvals by the FDA." One of their clients is Pfizer [certara.com].

Local variant shows very different characteristics. The trial took place in an area of Brazil where the Gamma variant was prominent. Brazilian clinicians report that this variant is much more virulent, and that significantly higher dosage and/or earlier treatment is required, as may be expected for variants where the peak viral load is significantly higher and/or reached earlier [Faria, Nonaka].

Single dose arm results missing. Results for the single dose ivermectin arm have not been reported.

Anomalous results from the same region. A local Brazilian investigator reports that the study was conducted in almost the same time and location as the Brazilian component of the molnupiravir trial. Notably, molnupiravir's EUA relied on the unusually higher efficacy observed in Brazil.

Designed by Cytel. The trial was designed by Cytel, a company that helps pharmaceutical companies get approval and that works very closely with Pfizer [cytel.com, cytel.com (C)]. Cytel's software and services are used by the top 30 pharmaceutical companies [cytel.com (B)].

Placebo unspecified. The placebo appears to be unspecified in the paper and protocol. The initial trial announcement indicated the placebo was vitamin C [cytel.com (C)], which would be an active treatment according to the results of 42 studies (mortality RR 0.75 [0.61-0.91]).

There are two previous published protocols, both are called "version 1", we refer to them as 1A (3/11/21 [drive.google.com] ) and 1B (8/5/21 [gatesopenresearch.org]. 1B deletes subgroup analysis by treatment delay, and deletes a statement requiring prior approval for amendments. 1B adds the statement: "we hypothesize that younger patients will benefit more than older patients."

Patients 50 years old were assigned to different groups in Table 1 and Figure 2 (≤50 vs. <50).

Greater efficacy was seen for patients >50 (RR 0.77) vs. patients ≤50 (RR 1.01).

The following comments are prior to the publication. We note that authors claim they have not included patients prior to the time period for the 3 dose ivermectin patients, however this does not appear to match the previously released recruitment over time graph according to an independent analysis [reddit.com].

The trial randomization chart does not match the protocol, suggesting major problems and indicating substantial confounding by time. For example, trial week 43, the first week for 3 dose ivermectin, shows ~3x patients assigned to ivermectin vs. placebo [reddit.com]. Treatment efficacy can vary significantly over time, for example due to overall improvement in protocols, changes in the distribution of variants, or changes in public awareness and treatment delays. [Zavascki] show dramatically higher mortality for Gamma vs non-Gamma variants (28 day mortality from symptom onset aHR 4.73 [1.15-19.41]), and the prevalence of the Gamma variant varied dramatically throughout the trial [ourworldindata.org]. This introduces confounding by time, which is common in COVID-19 retrospective studies and has often obscured efficacy (many retrospectives have more patients in the treatment group earlier in time when overall treatment protocols were significantly worse).

According to this analysis [reddit.com], the total number of patients for the ivermectin and placebo groups do not appear to match the totals in the presentation (the numbers for the fluvoxamine arm match) — reaching the number reported for ivermectin would require including some of the patients assigned to single dose ivermectin. Reaching the placebo number requires including placebo patients from the much earlier ivermectin single dose period, and from the early two week period when zero ivermectin patients were assigned. If these earlier participants were accidently included in the control group, this would dramatically change the results in favor of the control group according to the changes in Gamma variant prevalence.

An investigator from Brazil notes that the gamma variant became prevailing in the state of Minas Gerais later than in the rest of the country, with the time when gamma prevailed for the trial locations being more closely aligned with the start of the ivermectin arm [ufmg.br]. Due to the substantial differences in disease course and risk between the variants, authors need to consider only patients recruited during the same time period.

Treatment delay is currently unknown, however the protocol allows very late inclusion and a companion trial reported mostly late treatment. Overall mortality is high for 18+ outpatients. Results may be impacted by late treatment, poor SOC, and may be specific to local variants [Faria, Nonaka, Sabino]. Treatment was administered on an empty stomach, greatly reducing expected tissue concentration [Guzzo] and making the effective dose about 1/5th of current clinical practice. The trial was conducted in Minas Gerais, Brazil which had substantial community use of ivermectin [otempo.com.br], and prior use of ivermectin is not listed in the excluson criteria.

Time from symptom onset to randomization is specified as within 7 days. However the schedule of study activities specifies treatment administration only one day after randomization, suggesting that treatment was delayed an additional day for all patients.

This trial uses a soft primary outcome, easily subject to bias and event inflation in both arms (e.g., observe >6 hours independent of indication). There is also an unusual inclusion criteria: "patients with expected hospital stays of <= 5 days". This is similar to "patients less likely to need treatment beyond SOC to recover", and would make it very easy to reduce the effect seen. This is not in either of the published protocols.

RCTs have a fundamental bias against finding an effect for interventions that are widely available — patients that believe they need treatment are more likely to decline participation and take the intervention [Yeh], i.e. RCTs are more likely to enroll low-risk participants that do not need treatment to recover (this does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable). This trial was run in a community where ivermectin is widely known and used.

The same trial's results for a previous treatment were initially reported as RR 1.0 [0.45-2.21] [ajtmh.org], while the final paper reported something very different — HR 0.76 [0.30-1.88] [jamanetwork.com (B)].

Trial design, analysis, and presentation, along with previous public and private statements suggest investigator bias. Design: including very late treatment, additional day before administration, operation in a region with high community use, specifying administration on an empty stomach, limiting treatment to 3 days, using soft inclusion criterion and a soft primary outcome, easily subject to bias. Analysis: authors perform analysis excluding events very shortly after randomization for fluvoxamine but not ivermectin, and report viral load results for fluvoxamine but not ivermectin. Presentation: falsely describing positive but not statistically significant effects as "no effect, what so ever" [Amrhein, odysee.com]. Prior statements: [odysee.com].

The local Brazilian investigator also reports that nitazoxanide was tested in the same location, however very few patients reportedly experienced urine discoloration, while 100% are expected to experience this side effect; and that 6-hour observation is a poor choice because it is almost impossible to stay less than 6 hours in Brazil.

For additional issues see: [covid19criticalcare.com, doyourownresearch.substack.com (B), longhaulwiki.com, trialsitenews.com, twitter.com (U), twitter.com (V), twitter.com (W), twitter.com (X)].

NCT04727424.

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López-Medina et al.

An open letter, signed by >100 physicians, concluding this study is fatally flawed can be found at [jamaletter.com].

This is a phone survey based RCT with low risk patients, 200 ivermectin and 198 control, showing lower mortality, lower disease progression, lower treatment escalation, and faster resolution of symptoms with treatment, without reaching statistical significance. Authors find the results of this trial alone do not support the use of ivermectin. However the effects are all positive, especially for serious outcomes which are unable to reach statistical significance with the very small number of events in the low risk population.

RCTs have a fundamental bias against finding an effect for interventions that are widely available — patients that believe they need treatment are more likely to decline participation and take the intervention [Yeh], i.e., RCTs are more likely to enroll low-risk participants that do not need treatment to recover (this does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable). This trial was run in a community where ivermectin was available OTC and very widely known and used.

With the low risk patient population, there is little room for improvement with an effective treatment - 59/57% (IVM/control) recovered within the first 2 days to either "no symptoms" or "not hospitalized and no limitation of activities"; 73/69% within 5 days. Less than 3% of all patients ever deteriorated.

The primary outcome was changed mid-trial, it was originally clinical deterioration, which is more meaningful, and shows greater benefit. The new outcome of resolution of symptoms includes "not hospitalized and no limitation of activities" as a negative outcome and is not very meaningful in terms of assessing how much treatment reduces serious outcomes. Using this measure could completely invalidate results - for example a treatment that eliminates all COVID-19 symptoms but has a temporary minor adverse event could be seen as worse.

Authors state that "preliminary reports of other randomized trials of ivermectin as treatment for COVID-19 with positive results have not yet been published in peer-reviewed journals", however there were 8 peer-reviewed RCTs with positive effects published prior to this paper(and 19 total peer-reviewed studies with positive effects).

Authors advised taking ivermectin on an empty stomach, reducing lung tissue concentration by ~2.5x [Guzzo].

76 patients were excluded due to control patients receiving ivermectin. However, there was a similar percentage of adverse events like diarrhea, nausea, and abdominal pain in both treatment and control groups. These are potential non-serious side effects of treatment and suggest that it is possible that many more control patients received some kind of treatment.

Ivermectin was widely used in the population and available OTC at the time of the study. The study protocol only excluded patients with previous ivermectin use within 5 days, however other trials often monitor effects 10+ days after the last dose [osf.io (B)].

This study reportedly has an ethical issue whereby participants were told the study drug was "D11AX22" [trialsitenews.com (B)]. The editor-in-chief of JAMA initially offered to help with this issue, but later indicated that "JAMA does not review consent forms", however the lead author reportedly confirmed the issue [francesoir.fr, , trialsitenews.com (D)].

The study protocol specifically allows "the use of other treatments outside of clinical trials". The paper provides no information on what other treatments were used, but other treatments were commonly used at the time. Additionally, the control group did about 5x better than anticipated for deterioration, also suggesting that the control patients used some kind of treatment. Patients that enroll in such a study may be more likely to learn about and use other treatments, especially since they do not know if they are receiving the study medication.

The study protocol was amended 4 times. Amendments 2-4 are provided but amendment 1 is missing. Amendment 2 increased the inclusion criteria to within 7 days of onset, including more later stage patients and reducing the expected effectiveness. The trial protocol lists “the duration of supplemental oxygen” as an outcome but the results for this outcome are missing.

Grants and/or personal fees, including in some cases during the conduct of the study, were provided by Sanofi Pasteur, GlaxoSmithKline, Janssen, Merck, and Gilead. For more details see [trialsitenews.com (E)].

For other confounding issues see [osf.io (C)] and additional issues can be found in the comments of the article [jamanetwork.com (C)]. Re-analysis of the raw data has been reported to show a significant positive effect [twitter.com (Y)].

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Vallejos et al.

With only 7% hospitalization, this trial is underpowered. The trial primarily includes low-risk patients that recover quickly without treatment, leaving minimal room for improvement with treatment. 74 patients had symptoms for >= 7 days and more than 25% of patients were hospitalized within 1 day (Figure S2). Among the 7 patients requiring ventilation, authors note that the earlier requirement in the ivermectin group may be due to those patients having higher severity at baseline. However, authors know the answer to this - it is unclear why it is not reported. There were more adverse events in the placebo group than the ivermectin group, suggesting a possible issue with dispensing or non-trial medication usage.

The companion prophylaxis trial [IVERCOR PREP], which reported more positive results, has not yet been formally published, suggesting a negative publication bias.

Authors pre-specify multivariate analysis but do not present it, however multivariate analysis could significantly change the results. Consider for example if just a few extra patients in the ivermectin group were in severe condition based on baseline SpO2. The lower mean SpO2 in the ivermectin group, and the shorter time to ventilation, are consistent with this being the case. Additionally, there are 14% more male patients in the ivermectin group.

An extremely large percentage of patients (55%) were excluded based on ivermectin use in the last 7 days. However, ivermectin may retain efficacy much longer (for example antiparasitic activity may persist for months [Canga]). A significant number of patients may also misrepresent their prior and future usage — the population is clearly aware of ivermectin, and patients with progressing disease may be motivated to take it, knowing that they may be in the control group. Another report states that 12,000 patients were excluded for recent use of ivermectin [scidev.net]).

RCTs have a fundamental bias against finding an effect for interventions that are widely available — patients that believe they need treatment are more likely to decline participation and take the intervention [Yeh], i.e., RCTs are more likely to enroll low-risk participants that do not need treatment to recover (this does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable). This trial was run in a community where ivermectin was very widely known and used.

For other issues see [trialsitenews.com (F)].

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Beltrangonzalez et al.

Another study reports results on a larger group of patients in the same hospital, showing ivermectin mortality RR 0.81 [0.53-1.24] [Guzman].

Questions have been raised about this study and the early termination of the study and discontinuation of treatments, because the hospital statistics show a dramatically lower (~75%) case fatality rate during the period of the study [web.archive.org] (data from [gob.mx]).

Date	Cases	Deaths	CFR
3/2020	2	1	50%
4/2020	4	1	25%
5/2020	13	1	8%
6/2020	37	2	5%
7/2020	65	5	8%
8/2020	79	23	29%
9/2020	54	12	22%
10/2020	62	21	34%
11/2020	80	26	33%
12/2020	41	13	32%

Several other inconsistencies have been reported [Chamie].

Although the data from this study is reported to be available and has been shared with an anti-treatment group, independent researchers have been unable to obtain the data for verification [Chamie, twitter.com (Z)].

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Popp et al.

This meta analysis is designed to exclude most studies. Authors select a small subset of studies, with a majority of results based on only 1 or 2 studies. Authors split up studies which dilutes the effects and results in a lack of statistical significance for most outcomes. Authors perform 16+ meta analyses with very few studies in each analysis, and do not combine the evidence from all studies. However, we can consider the probability of the observed results across all outcomes.

Authors find positive results for 11 of 12 primary efficacy outcomes with events, or 16 of 18 including secondary outcomes. One of the primary outcomes and two of the secondary outcomes show statistically significant improvements in isolation. If we assume independence, the probability that 11+ of 12 primary efficacy outcomes were positive for an ineffective treatment is p = 0.003. For 16+ of 18 outcomes we get p = 0.0007. This simple analysis does not take into account the magnitude of positive effects, or the dependence due to some studies contributing multiple outcomes, however observation suggests that a full analysis of the combined evidence is likely to show efficacy.

The study is entirely retrospective in the current version. The protocol is dated April 20, 2021, and the most recent study included is from March 9, 2021. The protocol was modified after publication in order to include a close to null result (Beltran Gonzalez et al. "patients discharged without respiratory deterioration or death at 28 days"), so the current protocol is dated July 28, 2021.

Authors excluded many studies by requiring results at a specific time, for example mortality, ventilation, etc. required results at exactly 28 days. Authors excluded all prophylaxis studies by requiring results at exactly 14 days.

Studies comparing with other medications were excluded, however these studies confirm efficacy of ivermectin. The only case where they could overstate the efficacy of ivermectin is if the other medication was harmful. There is some evidence of this for excessive dosage/very late stage use, however that does not apply to any of the studies here.

Studies using combined treatment were excluded, even when it is known that the other components have minimal or no effect. 3 of 4 RCTs with combined treatment use doxycycline in addition [Butler]. Other studies were excluded by requiring PCR confirmation.

Authors are inconsistent regarding active comparators. They state that hydroxychloroquine “does not work”, yet excluded trials comparing ivermectin to a drug they hold to be inactive. On the other hand, remdesivir was an acceptable comparator, although it is considered to be effective standard of care in some locations [Fordham].

Authors fail to recognize that Risk of Bias (RoB) domains such as blinding are far less important for the objective outcome of mortality.

[Fordham] summarizes several problems:

•unsupported assertions of adverse reactions to ivermectin, and the outdated claim that unsafe dosing would be needed to be effective;

•a demand for PCR or antigen testing, without analysis of reliability and not universally available even in developed countries at the start of the pandemic;

•contradictions in the exclusion criteria, including placebo and approved SoC comparators, but rejecting hydroxychloroquine, though held to be ineffective (and an approved SoC in some jurisdictions);

•inclusion of “deemed active” comparators whilst excluding “potentially active” ones;

•exclusion of combination therapies, though the norm among practising clinicians;

•the rejection of other than RCTs when the objective is a “complete evidence profile”;

•arbitrary time-points for outcome measures, excluding non-compliant trials;

•fragmentation of data by location of care under varying hospitalisation criteria;

•the resulting focus on a small fraction of the available clinical evidence, with most comparisons based on single studies with no meta-analysis possible;

•a resulting inpatient mortality comparison with fewer patients than a June 2020 confounder-matched study;

•no conclusion on the headline mortality outcome, when multiple lines of evidence from elsewhere (including the WHO) point to significant mortality advantage.

Cochrane was reputable in the past, but is now controlled by pharmaceutical interests. For example, see the news related to the expulsion of founder Dr. Gøtzsche and the associated mass resignation of board members in protest [blogs.bmj.com, bmj.com, en.x-mol.com]. For another example of bias see [ebm.bmj.com].

The BiRD group gave the following early comment: "Yesterday’s Cochrane review surprisingly doesn’t take a pragmatic approach comparing ivermectin versus no ivermectin, like in the majority of other existing reviews. It uses a granular approach similar to WHO’s and the flawed Roman et al paper, splitting studies up and thereby diluting effects. Consequently, the uncertain conclusions add nothing to the evidence base. A further obfuscation of the evidence on ivermectin and an example of research waste. Funding conflicts of interests of the authors and of the journal concerned should be examined."

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Roman et al.

This is a severely flawed meta analysis. An open letter signed by 40 physicians detailing errors and flaws, and requesting retraction, can be found at [trialsitenews.com (G)]. See also [bird-group.org].

Authors cherry-pick to include only 4 studies reporting non-zero mortality and they initially claimed a mortality RR of 1.11 [0.16-7.65]. However, they reported incorrect values for Niaee et al., claiming an RR of 6.51 [2.18-19.45], when the correct RR for Niaee et al. is 0.18 [0.06-0.55]. After correction, their cherry-picked studies show >60% mortality reduction, however authors did not correct the conclusion.

Similarly, for viral clearance and NCT04392713, they report 20/41 treatment, 18/45 control, whereas the correct day 7 clearance numbers are 37/41 and 20/45 (sum of clearance @72hrs and @7 days), or 17/41 and 2/45 @72 hrs.

The duration of hospital stay for Niaee et al. is also incorrectly reported, showing a lower duration for the control group.

All of the errors are in one direction - incorrectly reporting lower than actual efficacy for ivermectin. Authors claim to include all RCTs excluding prophylaxis, however they only include 10 of the 24 non-prophylaxis RCTs (28 including prophylaxis at the time of publication). Authors actually reference meta analyses that do include the missing RCTs, so they should be aware of the missing RCTs.

The PubMed search strategy provided is syntactically incorrect. For additional errors, see [pubpeer.com]. Also see [roundingtheearth.substack.com].

The authors state that they have no conflicts of interest on medRxiv, however Dr. Pasupuleti’s affiliation is Cello Health, whose website [cellohealth.com] notes that they provide services such as “brand and portfolio commercial strategy for biotech and pharma”, and that their clients are "24 of the top 25 pharmaceutical companies”.

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Revisions

Please submit updates and corrections at the bottom of this page.Please submit updates and corrections at https://ivmmeta.com/.

4/9: We updated the Together Trial analysis.

4/8: We added [Ravikirti].

4/5: We added preprint discussion based on [Zeraatkar], and updated the Together Trial analysis.

4/2: We updated the Together Trial analysis.

3/30: We updated [Reis] to the journal version.

3/21: Strongyloides discussion updates.

3/3: We updated [Beltran Gonzalez] to the journal version.

3/2: We added [Soto].

2/28: We added [Efimenko].

2/25: We added [Thairu].

2/23: We updated [Mayer] to the journal version.

2/18: We updated [Lim] to the journal version.

2/2: We added [Manomaipiboon].

1/28: We added [de Jesús Ascencio-Montiel].

1/21: We added [Zubair].

1/17: We added an explanation of why funnel plot analysis is not valid in this case.

1/16: We added RCT viral clearance analysis and corrected missing symptomatic case results in the case analysis.

1/15: We updated [Kerr] to the journal version.

1/15: We corrected hospitalization group sizes in [Buonfrate].

1/13: We added [Abbas, Baguma].

1/11: We updated [Kerr] to the latest results, and added discussion of [Beltran Gonzalez].

1/7: We updated [Buonfrate] to the journal version, and we updated [Kerr] to the latest results.

12/31: We added [Shimizu].

12/29: We added [Mustafa].

12/26: We updated [Kerr] to the revised version of the paper.

12/16: We added [Jamir].

12/11: We added [Kerr].

12/8: We added analysis of the number of independent research groups reporting statistically significant positive results.

12/5: We added [Ferreira].

12/5: We added [Rezk].

12/3: A note on Bernigaud: continuity correction uses the reciprocal of the contrasting arm [Sweeting], as detailed in the appendix. We previously limited the size of the control group when showing the total number of patients, however this was confusing for people that did not read the details, as discussed below. The full group size has always been used when computing the RR.

12/1: Strongyloides discussion updates.

11/30: We corrected [Ghauri] to use the event counts.

11/24: We added [Ozer].

11/24: SSC discussion updates.

11/21: Strongyloides discussion updates.

11/20: Strongyloides discussion updates.

11/19: We added analysis by strongyloides prevalence, and updated it to match the revised classification used in the comparable analysis.

11/19: We added additional exclusion analyses in the supplementary data.

11/18: We incorrectly included [López-Medina] as a study not reporting use of steroids, however they report 6% usage in the control group.

11/18: We added [Samajdar].

11/17: SSC response.

11/16: Discussion updates.

11/12: We now show the number of studies reporting statistically significant results for any outcome, primary outcomes, and the most serious outcome.

11/9: Discussion updates.

11/5: We added discussion of strongyloides, comparison with the recent molnupiravir approval, and notes on recruitment for remote outpatient delayed treatment trials.

11/3: We added [Lim].

11/3: Discussion updates.

10/29: Discussion updates including GMK vitamin D analysis.

10/28: Discussion updates.

10/26: We updated the GMK response.

10/24: We added additional exclusion analyses for individual outcomes.

10/21: We added [Borody].

10/19: Discussion updates.

10/18: [Ghauri] was updated to the journal version.

10/16: We added a summary plot for all results.

10/13: We added primary outcome analysis and additional exclusion analyses. Niaee et al. has been reported as pending retraction and has been removed. 10/27 update: the journal has reported that this is incorrect — no retraction is pending.

10/11: Discussion updates. Niaee et al. exclusion. Updates to the study notes including discussion of Vallejos et al. and additional issues in the Together Trial. Discussion of inherent bias in RCTs for widely available interventions.

10/8: Discussion updates.

10/7: Samaha et al. has been reported as pending retraction and has been removed. There was no significant change in the results.

10/4: Merck discussion updates.

9/29: We corrected a display error causing a few points to be missing in Figure 4.

9/27: We added [Mayer].

9/24: We added a graph of variants over time for the Together Trial discussion and corrected outcome discussion for Popp et al.

9/22: Discussion updates.

9/20: Discussion updates.

9/18: We added [Buonfrate], and updated discussion of the Together Trial.

9/17: We added study notes.

9/15: Discussion updates.

9/14: FDA discussion updates.

9/9: We added sensitivity analysis to compute the minimum number of studies that need to be excluded in order to avoid showing efficacy. Discussion updates.

9/7: Discussion updates.

9/6: We corrected [Espitia-Hernandez] to use the reported recovery time and added missing recovery and viral clearance results.

9/3: We updated discussion and excluded Carvallo et al. in the exclusion analysis.

8/27: We updated [Morgenstern (B)] with the journal version of the article.

8/26: We updated [Mohan] with the journal version of the article.

8/16: We updated [Reis] with event counts.

8/15: We updated discussion and made the abstract more concise.

8/12: We added [Elavarasi, Reis].

8/8: We updated discussion in the responses.

8/6: We updated [Behera (B)] with the journal version of the article.

8/5: We added [Mondal].

8/4: We added discussion of the FDA recommendation.

8/3: We added discussion in the responses section.

8/2: We added analysis restricted to serious outcomes and analysis restricted to recovery, and we added discussion in the responses section.

7/31: We added discussion in the responses section related to in vitro evidence and therapeutic concentrations.

7/29: We added discussion in the responses section.

7/20: We updated [Hashim] with the journal version of the article.

7/16: We updated [Ravikirti (B)] with the journal version of the article.

7/15: Elgazzar et al. was withdrawn by the preprint server and has been removed.

7/9: We added [Hazan].

7/8: We updated [Cadegiani] to the journal version.

7/6: We previously limited the size of the control group for [Bernigaud] when calculating the total number of patients, however this was confusing for many people that did not read the details. We now show the original counts and note the larger size of the control group in the text.

7/3: We added [Vallejos].

7/2: We updated Niaee et al. to the journal version.

6/21: We added more information to the abstract.

6/19: We updated [Bryant] to the journal version.

6/19: [Beltran Gonzalez] was incorrectly included in the peer-reviewed analysis.

6/18: We added [Krolewiecki].

6/15: We added [Aref].

6/7: We added [Hariyanto].

6/5: We added [Ahsan].

6/2: We added [Abd-Elsalam].

5/31: [Biber] was updated to the preprint.

5/26: Samaha et al. was updated to the journal version.

5/18: We added analysis of Merck's recommendation.

5/17: We added [Szente Fonseca].

5/15: We updated the discussion of the WHO analysis.

5/13: We updated [Mahmud] to the journal version.

5/10: We added [Faisal].

5/10: We added additional information in the abstract.

5/8: We added [Merino].

5/7: We updated [Shahbaznejad] to the journal version, which includes additional outcomes not reported earlier.

5/6: We updated [Chahla] to the Research Square preprint.

5/6: We added a comparison of CDC recommendations.

5/6: We added mechanical ventilation and ICU admission analysis.

5/6: We updated discussion based on peer review including discussion of heterogeneity, exclusion based sensitivity analysis, and search criteria.

5/5: We updated [Okumuş] to the journal paper.

5/5: We previously limited the size of the control group in [Bernigaud] to be the same as the treatment group for calculation of the total number of patients. This is now also reflected and noted in the forest plots.

5/4: We added [Loue].

4/30: We added analysis of the WHO meta analysis and updated [Kory] to the journal version.

4/28: We added the WHO meta analysis results for comparison.

4/27: We added analysis restricted to hospitalization results and a comparison with the evidence base used in the approval of other COVID-19 treatments.

4/26: We added notes on heterogeneity.

4/25: We updated [Biber] to the latest results reported at the International Ivermectin for Covid Conference.

4/18: We updated [Morgenstern] to the preprint.

4/16: We added [Morgenstern].

4/14: We added [Seet].

4/10: We added [Kishoria].

4/9: We corrected a duplicate entry for [Bukhari].

4/7: We identified studies where minimal detail is currently available in the forest plots.

4/5: We added [Mourya].

4/4: We added event counts to the forest plots.

3/31: We updated [Chahla (B)] to the preprint.

3/30: We added [Chahla].

3/28: We highlighted and added discussion for studies that use combined treatments.

3/26: We added [Tanioka].

3/25: We added [Huvemek].

3/17: We added [Nardelli].

3/12: We added [Bryant, Roy].

3/10: We added [Pott-Junior].

3/6: We added [Chowdhury] and we identify studies that compare with another treatment.

3/5: We added discussion of pooled effects (we show both pooled effects and individual outcome results).

3/4: We added [López-Medina], and we added more information in the abstract.

3/3: We updated the graphs to indicate the time period for the dosage column, now showing the dosage over one month for prophylaxis and over four days for other studies.

3/2: We updated [IVERCOR PREP] with the latest results [Vallejos (B)].

2/27: We added analysis restricted to peer reviewed studies.

2/24: We added a comparison of the evidence base and WHO approval status for the use of ivermectin with scabies and COVID-19. We updated [Okumuş] with the Research Square preprint.

2/23: We added [Beltran Gonzalez].

2/18: We updated [Babalola] to the journal version of the paper.

2/17: We added [Elalfy], and we added analysis restricted to viral clearance outcomes, and mortality results restricted to RCTs.

2/16: We updated [Behera] to the journal version of the paper.

2/15: We added [Behera (B)].

2/14: We added analysis restricted to COVID-19 case outcomes, and we added additional results in the abstract.

2/12: We added [Biber].

2/11: We added more details on the analysis of prospective vs. retrospective studies.

2/10: We added [Lima-Morales].

2/5: We updated [Bukhari] to the preprint.

2/2: We added [Mohan].

1/26: We updated [Shouman] with the journal version of the article.

1/25: We updated [IVERCOR PREP] with the recently released results.

1/19: We added [Shahbaznejad] and Samaha et al. [Chaccour] was updated to the journal version of the paper.

1/17: We added [Bukhari].

1/16: We moved the analysis with exclusions to the main text, and added additional commentary.

1/15: We added the effect measured for each study in the forest plots.

1/12: We added [Okumuş].

1/11: We added [Chahla (B)].

1/10: We put all prophylaxis studies in a single group.

1/9: We added [Ravikirti (B)]. Due to the much larger size of the control group in [Bernigaud], we limited the size of the control group to be the same as the treatment group for calculation of the total number of patients.

1/7: We added direct links to the study details in the chronological plots.

1/6: We added [Babalola].

1/5: We added direct links to the study details in the forest plots.

1/2/2021: We added dosage information and we added the number of patients to the forest plots.

12/31: We added additional details about the studies in the appendix.

12/29: We added meta analysis excluding late treatment.

12/27: We added the total number of authors and patients.

12/26: We added [Carvallo (B), IVERCOR PREP].

12/17: We added [Alam].

12/16: We added [Ghauri].

12/11: We added [Soto-Becerra].

12/7: We added [Chaccour].

12/2: We added [Ahmed].

11/26/2020: Initial revision.

Appendix 1. Methods and Study Results

We performed ongoing searches of PubMed, medRxiv, ClinicalTrials.gov, The Cochrane Library, Google Scholar, Collabovid, Research Square, ScienceDirect, Oxford University Press, the reference lists of other studies and meta-analyses, and submissions to the site c19ivermectin.com, which regularly receives submissions of studies upon publication. Search terms were ivermectin and COVID-19 or SARS-CoV-2, or simply ivermectin. Automated searches are performed every hour with notification of new matches. The broad search terms result in a large volume of new studies on a daily basis which are reviewed for inclusion. All studies regarding the use of ivermectin for COVID-19 that report a comparison with a control group are included in the main analysis. Sensitivity analysis is performed, excluding studies with major issues, epidemiological studies, and studies with minimal available information. This is a living analysis and is updated regularly.

We extracted effect sizes and associated data from all studies. If studies report multiple kinds of effects then the most serious outcome is used in pooled analysis, while other outcomes are included in the outcome specific analyses. For example, if effects for mortality and cases are both reported, the effect for mortality is used, this may be different to the effect that a study focused on. If symptomatic results are reported at multiple times, we used the latest time, for example if mortality results are provided at 14 days and 28 days, the results at 28 days are used. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms were not used (the next most serious outcome is used — no studies were excluded). For example, in low-risk populations with no mortality, a reduction in mortality with treatment is not possible, however a reduction in hospitalization, for example, is still valuable. Clinical outcome is considered more important than PCR testing status. When basically all patients recover in both treatment and control groups, preference for viral clearance and recovery is given to results mid-recovery where available (after most or all patients have recovered there is no room for an effective treatment to do better). If only individual symptom data is available, the most serious symptom has priority, for example difficulty breathing or low SpO₂ is more important than cough. When results provide an odds ratio, we computed the relative risk when possible, or converted to a relative risk according to [Zhang]. Reported confidence intervals and p-values were used when available, using adjusted values when provided. If multiple types of adjustments are reported including propensity score matching (PSM), the PSM results are used. Adjusted primary outcome results have preference over unadjusted results for a more serious outcome when the adjustments significantly alter results. When needed, conversion between reported p-values and confidence intervals followed [Altman, Altman (B)], and Fisher's exact test was used to calculate p-values for event data. If continuity correction for zero values is required, we use the reciprocal of the opposite arm with the sum of the correction factors equal to 1 [Sweeting]. Results are expressed with RR < 1.0 favoring treatment, and using the risk of a negative outcome when applicable (for example, the risk of death rather than the risk of survival). If studies only report relative continuous values such as relative times, the ratio of the time for the treatment group versus the time for the control group is used. Calculations are done in Python (3.9.12) with scipy (1.8.0), pythonmeta (1.26), numpy (1.22.2), statsmodels (0.14.0), and plotly (5.6.0).

Forest plots are computed using PythonMeta [Deng] with the DerSimonian and Laird random effects model (the fixed effect assumption is not plausible in this case) and inverse variance weighting. Mixed-effects meta-regression results are computed with R (4.1.2) using the metafor (3.0-2) and rms (6.2-0) packages, and using the most serious sufficiently powered outcome. Forest plots show simplified dosages for comparison, these are the total dose in the first four days for treatment, and the monthly dose for prophylaxis, for a 70kg person. For full dosage details see below.

We received no funding, this research is done in our spare time. We have no affiliations with any pharmaceutical companies or political parties.

We have classified studies as early treatment if most patients are not already at a severe stage at the time of treatment (for example based on oxygen status or lung involvement), and treatment started within 5 days of the onset of symptoms. If studies contain a mix of early treatment and late treatment patients, we consider the treatment time of patients contributing most to the events (for example, consider a study where most patients are treated early but late treatment patients are included, and all mortality events were observed with late treatment patients). We note that a shorter time may be preferable. Antivirals are typically only considered effective when used within a shorter timeframe, for example 0-36 or 0-48 hours for oseltamivir, with longer delays not being effective [McLean, Treanor].

Note that the size of the control group in [Bernigaud] is significantly larger than the treatment group. We previously limited the size to be the same as that of the treatment group for calculation of the number of patients, however this was confusing to many people that did not read the details.

A summary of study results is below. Please submit updates and corrections at the bottom of this page.

A summary of study results is below. Please submit updates and corrections at https://ivmmeta.com/.

Early treatment.

Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. Only the first (most serious) outcome is used in pooled analysis, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.

[Abbas], 12/31/2021, Double Blind Randomized Controlled Trial, placebo-controlled, China, Asia, peer-reviewed, 3 authors, dosage 300μg/kg days 1-5, excluded in exclusion analyses: very minimal patient information, three different results for the recovery outcome, selective omission of the statistically significant recovery p-value, and other inconsistencies. Submit Corrections or Updates.	risk of death, 4.0% higher, RR 1.04, p = 1.00, treatment 1 of 99 (1.0%), control 1 of 103 (1.0%).
	deterioration of 2 or more points, 40.5% lower, RR 0.59, p = 0.54, treatment 4 of 99 (4.0%), control 7 of 103 (6.8%), NNT 36.
	escalation of care, 14.9% lower, RR 0.85, p = 0.82, treatment 9 of 99 (9.1%), control 11 of 103 (10.7%), NNT 63.
	fever during study, 17.9% lower, RR 0.82, p = 0.58, treatment 15 of 99 (15.2%), control 19 of 103 (18.4%), NNT 30.
	risk of no recovery, 35.6% lower, RR 0.64, p = 0.04, treatment 26 of 99 (26.3%), control 42 of 103 (40.8%), NNT 6.9.
	recovery time, 30.8% lower, relative time 0.69, p = 0.08, treatment 99, control 103.
[Ahmed], 12/2/2020, Double Blind Randomized Controlled Trial, Bangladesh, South Asia, peer-reviewed, mean age 42.0, 15 authors, average treatment delay 3.83 days, dosage 12mg days 1-5, the ivermectin + doxycycline group took only a single dose of ivermectin. Submit Corrections or Updates.	risk of unresolved symptoms, 85.0% lower, RR 0.15, p = 0.09, treatment 0 of 17 (0.0%), control 3 of 19 (15.8%), NNT 6.3, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), day 7, fever, ivermectin (5 days).
	risk of unresolved symptoms, 62.7% lower, RR 0.37, p = 0.35, treatment 1 of 17 (5.9%), control 3 of 19 (15.8%), NNT 10, day 7, fever, ivermectin (1 day) + doxycycline.
	risk of no virological cure, 75.6% lower, HR 0.24, p = 0.03, treatment 11 of 22 (50.0%), control 20 of 23 (87.0%), NNT 2.7, adjusted per study, day 7, ivermectin (5 days).
	risk of no virological cure, 56.5% lower, HR 0.43, p = 0.22, treatment 16 of 23 (69.6%), control 20 of 23 (87.0%), NNT 5.8, adjusted per study, day 7, ivermectin (1 day) + doxycycline.
	risk of no virological cure, 63.0% lower, HR 0.37, p = 0.02, treatment 5 of 22 (22.7%), control 14 of 23 (60.9%), NNT 2.6, adjusted per study, day 14, ivermectin (5 days).
	risk of no virological cure, 41.2% lower, HR 0.59, p = 0.19, treatment 9 of 23 (39.1%), control 14 of 23 (60.9%), NNT 4.6, adjusted per study, day 14, ivermectin (1 day) + doxycycline.
	time to viral-, 23.6% lower, relative time 0.76, p = 0.02, treatment 22, control 23, ivermectin (5 days).
	time to viral-, 9.4% lower, relative time 0.91, p = 0.27, treatment 23, control 23, ivermectin (1 day) + doxycycline.
[Aref], 6/15/2021, Randomized Controlled Trial, Egypt, Africa, peer-reviewed, 7 authors, dosage not specified. Submit Corrections or Updates.	relative duration of fever, 63.2% lower, relative time 0.37, p < 0.001, treatment 57, control 57.
	relative duration of dyspnea, 56.4% lower, relative time 0.44, p < 0.001, treatment 57, control 57.
	relative duration of anosmia, 68.8% lower, relative time 0.31, p < 0.001, treatment 57, control 57.
	relative duration of cough, 64.3% lower, relative time 0.36, p < 0.001, treatment 57, control 57.
	risk of no virological cure, 78.6% lower, RR 0.21, p = 0.004, treatment 3 of 57 (5.3%), control 14 of 57 (24.6%), NNT 5.2.
	time to viral-, 35.7% lower, relative time 0.64, p < 0.001, treatment 57, control 57.
[Babalola], 1/6/2021, Double Blind Randomized Controlled Trial, Nigeria, Africa, peer-reviewed, baseline oxygen requirements 8.3%, 10 authors, dosage 12mg or 6mg q84h for two weeks, this trial compares with another treatment - results may be better when compared to placebo. Submit Corrections or Updates.	adjusted risk of viral+ at day 5, 63.9% lower, RR 0.36, p = 0.11, treatment 40, control 20, adjusted per study.
	relative ∆SpO₂ (unadjusted), 41.5% better, RR 0.59, p = 0.07, treatment 38, control 18, figure 3.
	risk of no virological cure, 58.0% lower, HR 0.42, p = 0.01, treatment 20, control 20, 12mg - Cox proportional hazard model.
	risk of no virological cure, 40.5% lower, HR 0.60, p = 0.12, treatment 20, control 20, 6mg - Cox proportional hazard model.
	time to viral-, 49.2% lower, relative time 0.51, p = 0.02, treatment 20, control 20, 12mg.
	time to viral-, 34.4% lower, relative time 0.66, p = 0.08, treatment 20, control 20, 6mg.
[Biber], 2/12/2021, Double Blind Randomized Controlled Trial, Israel, Middle East, preprint, 10 authors, average treatment delay 4.0 days, dosage 12mg days 1-3, 15mg for patients >= 70kg. Submit Corrections or Updates.	risk of hospitalization, 70.2% lower, RR 0.30, p = 0.34, treatment 1 of 47 (2.1%), control 3 of 42 (7.1%), NNT 20.
	risk of no virological cure, 44.8% lower, RR 0.55, p = 0.04, treatment 13 of 47 (27.7%), control 21 of 42 (50.0%), NNT 4.5, adjusted per study, odds ratio converted to relative risk, multivariable logistic regression, day 6, Ct>30.
	risk of no virological cure, 70.2% lower, RR 0.30, p = 0.14, treatment 2 of 47 (4.3%), control 6 of 42 (14.3%), NNT 10.0, day 10, non-infectious samples (Ct>30 or non-viable culture).
	risk of no virological cure, 82.1% lower, RR 0.18, p = 0.01, treatment 2 of 47 (4.3%), control 10 of 42 (23.8%), NNT 5.1, day 8, non-infectious samples (Ct>30 or non-viable culture).
	risk of no virological cure, 75.6% lower, RR 0.24, p = 0.02, treatment 3 of 47 (6.4%), control 11 of 42 (26.2%), NNT 5.0, day 6, non-infectious samples (Ct>30 or non-viable culture).
	risk of no virological cure, 65.1% lower, RR 0.35, p = 0.05, treatment 4 of 28 (14.3%), control 9 of 22 (40.9%), NNT 3.8, day 4, non-infectious samples (Ct>30 or non-viable culture).
	risk of no virological cure, 51.9% lower, RR 0.48, p = 0.08, treatment 7 of 47 (14.9%), control 13 of 42 (31.0%), NNT 6.2, day 10, Ct>30.
	risk of no virological cure, 57.9% lower, RR 0.42, p = 0.02, treatment 8 of 47 (17.0%), control 17 of 42 (40.5%), NNT 4.3, day 8, Ct>30.
	risk of no virological cure, 44.7% lower, RR 0.55, p = 0.049, treatment 13 of 47 (27.7%), control 21 of 42 (50.0%), NNT 4.5, day 6, Ct>30.
	risk of no virological cure, 31.9% lower, RR 0.68, p = 0.16, treatment 13 of 28 (46.4%), control 15 of 22 (68.2%), NNT 4.6, day 4, Ct>30.
[Borody], 10/19/2021, retrospective, Australia, Oceania, preprint, 2 authors, study period 1 June, 2021 - 30 September, 2021, dosage 24mg days 1-10, this trial uses multiple treatments in the treatment arm (combined with zinc and doxycycline) - results of individual treatments may vary, excluded in exclusion analyses: preliminary report with minimal details. Submit Corrections or Updates.	risk of death, 92.3% lower, RR 0.08, p = 0.03, treatment 0 of 600 (0.0%), control 6 of 600 (1.0%), NNT 100, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	risk of hospitalization, 92.9% lower, RR 0.07, p < 0.001, treatment 5 of 600 (0.8%), control 70 of 600 (11.7%), NNT 9.2.
[Bukhari], 1/16/2021, Randomized Controlled Trial, Pakistan, South Asia, preprint, 10 authors, dosage 12mg single dose. Submit Corrections or Updates.	risk of no virological cure, 82.4% lower, RR 0.18, p < 0.001, treatment 4 of 41 (9.8%), control 25 of 45 (55.6%), NNT 2.2, day 7.
	risk of no virological cure, 38.7% lower, RR 0.61, p < 0.001, treatment 24 of 41 (58.5%), control 43 of 45 (95.6%), NNT 2.7, day 3.
[Buonfrate], 9/6/2021, Double Blind Randomized Controlled Trial, Italy, Europe, peer-reviewed, 18 authors, average treatment delay 4.0 days, dosage 1200μg/kg days 1-5, arm B 600µg/kg, arm C 1200µg/kg, excluded in exclusion analyses: significant unadjusted group differences, with 3 times as many patients in the ivermectin arms having the baseline visit in a hospital setting, and arm C having large differences in baseline gender, weight, cough, pyrexia, and anosmia, excessive dose for arm C. Submit Corrections or Updates.	risk of hospitalization, 210.7% higher, RR 3.11, p = 0.47, treatment 1 of 28 (3.6%), control 0 of 31 (0.0%), continuity correction due to zero event (with reciprocal of the contrasting arm), arm B.
	risk of hospitalization, 610.0% higher, RR 7.10, p = 0.11, treatment 3 of 30 (10.0%), control 0 of 31 (0.0%), continuity correction due to zero event (with reciprocal of the contrasting arm), arm C, very high dose, poorly tolerated with low compliance.
	relative change in viral load, RR 0.80, p = 0.59, treatment mean 2.5 (±2.2) n=28, control mean 2.0 (±4.4) n=29, day 7, arm B.
	relative change in viral load, RR 0.69, p = 0.07, treatment mean 2.9 (±1.6) n=30, control mean 2.0 (±2.1) n=29, day 7, arm C.
[Cadegiani], 11/4/2020, prospective, Brazil, South America, peer-reviewed, 4 authors, average treatment delay 2.9 days, dosage 200μg/kg days 1-3, this trial uses multiple treatments in the treatment arm (combined with AZ, nitazoxanide (82), HCQ (22), spironolactone (66), dutasteride (4)) - results of individual treatments may vary, excluded in exclusion analyses: control group retrospectively obtained from untreated patients in the same population. Submit Corrections or Updates.	risk of death, 78.3% lower, RR 0.22, p = 0.50, treatment 0 of 110 (0.0%), control 2 of 137 (1.5%), NNT 68, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), control group 1.
	risk of mechanical ventilation, 94.2% lower, RR 0.06, p = 0.005, treatment 0 of 110 (0.0%), control 9 of 137 (6.6%), NNT 15, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), control group 1.
	risk of hospitalization, 98.0% lower, RR 0.02, p < 0.001, treatment 0 of 110 (0.0%), control 27 of 137 (19.7%), NNT 5.1, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), control group 1.
[Carvallo (C)], 9/15/2020, prospective, Argentina, South America, peer-reviewed, mean age 55.7, 3 authors, dosage 36mg days 1, 8, dose varied depending on patient condition - mild 24mg, moderate 36mg, severe 48mg, this trial uses multiple treatments in the treatment arm (combined with dexamethasone, enoxaparin, and aspirin) - results of individual treatments may vary, excluded in exclusion analyses: minimal details of groups provided. Submit Corrections or Updates.	risk of death, 85.4% lower, RR 0.15, p = 0.08, treatment 1 of 32 (3.1%), control 3 of 14 (21.4%), NNT 5.5, moderate/severe patients, the only treatment death was a patient already in the ICU before treatment.
[Chaccour], 12/7/2020, Double Blind Randomized Controlled Trial, Spain, Europe, peer-reviewed, 23 authors, average treatment delay 1.0 days, dosage 400μg/kg single dose. Submit Corrections or Updates.	risk of symptoms, 96.0% lower, OR 0.04, p < 0.05, treatment 12, control 12, logistic regression, chance of presenting any symptom, RR approximated with OR.
	viral load, 94.6% lower, relative load 0.05, p < 0.01, treatment 12, control 12, day 7 mid-recovery, average of gene E and gene N, data in supplementary appendix.
	risk of no virological cure, 8.0% lower, RR 0.92, p = 1.00, treatment 12, control 12.
[Chahla], 3/30/2021, Cluster Randomized Controlled Trial, Argentina, South America, preprint, 9 authors, dosage 24mg days 1, 8, 15, 22. Submit Corrections or Updates.	risk of no discharge, 86.9% lower, RR 0.13, p = 0.004, treatment 2 of 110 (1.8%), control 20 of 144 (13.9%), NNT 8.3, adjusted per study, odds ratio converted to relative risk, logistic regression.
[Chowdhury], 7/14/2020, Randomized Controlled Trial, Bangladesh, South Asia, peer-reviewed, 6 authors, dosage 200μg/kg single dose, this trial compares with another treatment - results may be better when compared to placebo, this trial uses multiple treatments in the treatment arm (combined with doxycycline) - results of individual treatments may vary. Submit Corrections or Updates.	risk of hospitalization, 80.6% lower, RR 0.19, p = 0.23, treatment 0 of 60 (0.0%), control 2 of 56 (3.6%), NNT 28, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	risk of no recovery, 46.4% lower, RR 0.54, p < 0.001, treatment 27 of 60 (45.0%), control 47 of 56 (83.9%), NNT 2.6, mid-recovery day 5.
	recovery time, 15.2% lower, relative time 0.85, p = 0.07, treatment 60, control 56.
	risk of no virological cure, 80.6% lower, RR 0.19, p = 0.23, treatment 0 of 60 (0.0%), control 2 of 56 (3.6%), NNT 28, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	time to viral-, 4.3% lower, relative time 0.96, p = 0.23, treatment 60, control 56.
[de Jesús Ascencio-Montiel], 1/24/2022, retrospective, Mexico, North America, peer-reviewed, 10 authors, dosage 6mg days 1-2, this trial uses multiple treatments in the treatment arm (combined with AZ, acetaminophen, aspirin) - results of individual treatments may vary. Submit Corrections or Updates.	risk of death/hospitalization, 59.0% lower, RR 0.41, p < 0.001, treatment 7,898, control 20,150, adjusted per study, multivariable.
	risk of death/hospitalization, 71.0% lower, RR 0.29, p < 0.001, treatment 5,557, control 12,526, adjusted per study, with phone call followup, multivariable.
	risk of death, 15.0% lower, RR 0.85, p = 0.16, treatment 101 of 7,898 (1.3%), control 303 of 20,150 (1.5%), NNT 445, unadjusted, excluded in exclusion analyses: unadjusted results with alternate outcome adjusted results showing significant changes with adjustments.
	risk of mechanical ventilation, 9.1% lower, RR 0.91, p = 0.51, treatment 77 of 7,898 (1.0%), control 216 of 20,150 (1.1%), NNT 1031, unadjusted, excluded in exclusion analyses: unadjusted results with alternate outcome adjusted results showing significant changes with adjustments.
	risk of hospitalization, 47.6% lower, RR 0.52, p < 0.001, treatment 485 of 7,898 (6.1%), control 2,360 of 20,150 (11.7%), NNT 18, unadjusted, excluded in exclusion analyses: unadjusted results with alternate outcome adjusted results showing significant changes with adjustments.
	risk of progression, 41.8% lower, RR 0.58, p < 0.001, treatment 435 of 7,898 (5.5%), control 1,906 of 20,150 (9.5%), NNT 25, unadjusted, ER, excluded in exclusion analyses: unadjusted results with alternate outcome adjusted results showing significant changes with adjustments.
[Elalfy], 2/16/2021, retrospective, Egypt, Africa, peer-reviewed, 15 authors, dosage 18mg days 1, 4, 7, 10, 13, <90kg 18mg, 90-120kg 24mg, >120kg 30mg, this trial uses multiple treatments in the treatment arm (combined with nitazoxanide, ribavirin, and zinc) - results of individual treatments may vary. Submit Corrections or Updates.	risk of no virological cure, 86.9% lower, RR 0.13, p < 0.001, treatment 7 of 62 (11.3%), control 44 of 51 (86.3%), NNT 1.3, day 15.
	risk of no virological cure, 58.1% lower, RR 0.42, p < 0.001, treatment 26 of 62 (41.9%), control 51 of 51 (100.0%), NNT 1.7, day 7.
[Espitia-Hernandez], 8/15/2020, retrospective, Mexico, North America, peer-reviewed, mean age 45.1, 5 authors, dosage 6mg days 1-2, 8-9, this trial uses multiple treatments in the treatment arm (combined with azithromycin and cholecalciferol) - results of individual treatments may vary. Submit Corrections or Updates.	recovery time, 70.0% lower, relative time 0.30, p < 0.001, treatment 28, control 7.
	risk of viral+ at day 10, 97.2% lower, RR 0.03, p < 0.001, treatment 0 of 28 (0.0%), control 7 of 7 (100.0%), NNT 1.0, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
[Faisal], 5/10/2021, Randomized Controlled Trial, Pakistan, South Asia, peer-reviewed, 3 authors, dosage 12mg days 1-5. Submit Corrections or Updates.	risk of no recovery, 68.4% lower, RR 0.32, p = 0.005, treatment 6 of 50 (12.0%), control 19 of 50 (38.0%), NNT 3.8, 6-8 days, mid-recovery.
	risk of no recovery, 27.3% lower, RR 0.73, p = 0.11, treatment 24 of 50 (48.0%), control 33 of 50 (66.0%), NNT 5.6, 3-5 days.
	risk of no recovery, 75.0% lower, RR 0.25, p = 0.09, treatment 2 of 50 (4.0%), control 8 of 50 (16.0%), NNT 8.3, 9-10 days.
[Ghauri], 12/15/2020, retrospective, Pakistan, South Asia, peer-reviewed, 6 authors, dosage 12mg days 1-6. Submit Corrections or Updates.	risk of fever, 92.2% lower, RR 0.08, p = 0.04, treatment 0 of 37 (0.0%), control 7 of 53 (13.2%), NNT 7.6, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), day 14.
	risk of fever, 86.4% lower, RR 0.14, p < 0.001, treatment 2 of 37 (5.4%), control 21 of 53 (39.6%), NNT 2.9, day 10.
	risk of fever, 55.7% lower, RR 0.44, p < 0.001, treatment 13 of 37 (35.1%), control 42 of 53 (79.2%), NNT 2.3, day 7.
	risk of fever, 42.2% lower, RR 0.58, p < 0.001, treatment 21 of 37 (56.8%), control 52 of 53 (98.1%), NNT 2.4, day 5.
[Krolewiecki], 6/18/2021, Randomized Controlled Trial, Argentina, South America, peer-reviewed, 23 authors, average treatment delay 3.5 days, dosage 600μg/kg days 1-5. Submit Corrections or Updates.	risk of mechanical ventilation, 151.9% higher, RR 2.52, p = 1.00, treatment 1 of 27 (3.7%), control 0 of 14 (0.0%), continuity correction due to zero event (with reciprocal of the contrasting arm).
	risk of progression, 3.7% higher, RR 1.04, p = 1.00, treatment 2 of 27 (7.4%), control 1 of 14 (7.1%).
	viral decay rate, 65.6% lower, RR 0.34, p = 0.09, treatment 20, control 14, relative mean viral decay rate (corrigendum table 2).
[Loue], 4/17/2021, retrospective quasi-randomized (patient choice), France, Europe, peer-reviewed, 2 authors, dosage 200μg/kg single dose. Submit Corrections or Updates.	risk of death, 70.0% lower, RR 0.30, p = 0.34, treatment 1 of 10 (10.0%), control 5 of 15 (33.3%), NNT 4.3.
	risk of severe case, 55.0% lower, RR 0.45, p = 0.11, treatment 3 of 10 (30.0%), control 10 of 15 (66.7%), NNT 2.7.
[López-Medina], 3/4/2021, Double Blind Randomized Controlled Trial, Colombia, South America, peer-reviewed, median age 37.0, 19 authors, average treatment delay 5.0 days, dosage 300μg/kg days 1-5, excluded in exclusion analyses: strong evidence of patients in the control group self-medicating, ivermectin widely used in the population at that time, and the study drug identity was concealed by using the name D11AX22. Submit Corrections or Updates.	risk of death, 66.8% lower, RR 0.33, p = 0.50, treatment 0 of 200 (0.0%), control 1 of 198 (0.5%), NNT 198, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	risk of escalation of care, 60.8% lower, RR 0.39, p = 0.11, treatment 4 of 200 (2.0%), control 10 of 198 (5.1%), NNT 33, odds ratio converted to relative risk.
	risk of escalation of care with post-hoc <12h exclusion, 34.3% lower, RR 0.66, p = 0.52, treatment 4 of 200 (2.0%), control 6 of 198 (3.0%), NNT 97, odds ratio converted to relative risk.
	risk of deterioration by >= 2 points on an 8-point scale, 43.1% lower, RR 0.57, p = 0.37, treatment 4 of 200 (2.0%), control 7 of 198 (3.5%), NNT 65, odds ratio converted to relative risk.
	risk of fever post randomization, 24.8% lower, RR 0.75, p = 0.38, treatment 16 of 200 (8.0%), control 21 of 198 (10.6%), NNT 38, odds ratio converted to relative risk.
	risk of unresolved symptoms at day 21, 15.3% lower, RR 0.85, p = 0.53, treatment 36 of 200 (18.0%), control 42 of 198 (21.2%), NNT 31, odds ratio converted to relative risk, Cox proportional-hazard model.
	lack of resolution of symptoms, 6.5% lower, HR 0.93, p = 0.53, treatment 200, control 198.
[Mahmud], 10/9/2020, Double Blind Randomized Controlled Trial, Bangladesh, South Asia, peer-reviewed, 15 authors, average treatment delay 4.0 days, dosage 12mg single dose, this trial uses multiple treatments in the treatment arm (combined with doxycycline) - results of individual treatments may vary. Submit Corrections or Updates.	risk of death, 85.7% lower, HR 0.14, p = 0.25, treatment 0 of 183 (0.0%), control 3 of 183 (1.6%), NNT 61, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	risk of progression, 57.0% lower, HR 0.43, p < 0.001, treatment 16 of 183 (8.7%), control 32 of 180 (17.8%), NNT 11, adjusted per study, Cox regression.
	risk of no recovery, 94.0% lower, HR 0.06, p < 0.001, treatment 72 of 183 (39.3%), control 100 of 180 (55.6%), NNT 6.2, adjusted per study, day 7, Cox regression.
	risk of no recovery, 38.5% lower, RR 0.61, p = 0.005, treatment 40 of 183 (21.9%), control 64 of 180 (35.6%), NNT 7.3, day 11.
	risk of no recovery, 96.0% lower, HR 0.04, p < 0.001, treatment 42 of 183 (23.0%), control 67 of 180 (37.2%), NNT 7.0, adjusted per study, day 12, Cox regression.
	time to recovery, 27.0% lower, HR 0.73, p = 0.003, treatment 183, control 180, Cox regression.
	risk of no virological cure, 39.0% lower, HR 0.61, p = 0.002, treatment 14 of 183 (7.7%), control 36 of 180 (20.0%), NNT 8.1, adjusted per study, Cox regression.
[Manomaipiboon], 2/2/2022, Double Blind Randomized Controlled Trial, placebo-controlled, Thailand, South Asia, preprint, 8 authors, dosage 12mg days 1-5. Submit Corrections or Updates.	risk of no recovery, 43.5% lower, RR 0.57, p = 0.26, treatment 3 of 36 (8.3%), control 6 of 36 (16.7%), NNT 12, adjusted per study, odds ratio converted to relative risk, resolution of symptoms, day 28.
	recovery time, 15.3% lower, RR 0.85, p = 0.57, treatment 36, control 36, time to resolution of symptoms.
	risk of no virological cure, 5.0% lower, RR 0.95, p = 1.00, treatment 19 of 36 (52.8%), control 20 of 36 (55.6%), NNT 36, day 14.
	risk of no virological cure, 3.3% lower, RR 0.97, p = 1.00, treatment 29 of 36 (80.6%), control 30 of 36 (83.3%), NNT 36, day 7.
[Mayer], 9/23/2021, retrospective, Argentina, South America, peer-reviewed, 14 authors, dosage 540μg/kg days 1-5, mean prescribed dose. Submit Corrections or Updates.	risk of death, 55.1% lower, RR 0.45, p < 0.001, treatment 3,266, control 17,966, adjusted per study, odds ratio converted to relative risk, Figure 3, multivariable.
	risk of ICU admission, 65.9% lower, RR 0.34, p < 0.001, treatment 3,266, control 17,966, adjusted per study, odds ratio converted to relative risk, Figure 3, multivariable.
	risk of death, 27.6% lower, RR 0.72, p = 0.03, treatment 3,266, control 17,966, odds ratio converted to relative risk, unadjusted.
	risk of ICU admission, 26.0% lower, RR 0.74, p = 0.13, treatment 3,266, control 17,966, odds ratio converted to relative risk, unadjusted.
[Merino], 5/3/2021, retrospective quasi-randomized (patients receiving kit), population-based cohort, Mexico, North America, preprint, 7 authors, dosage 6mg bid days 1-2. Submit Corrections or Updates.	risk of hospitalization, 74.4% lower, RR 0.26, p < 0.001, model 7, same time period, patients receiving kit.
	risk of hospitalization, 68.4% lower, RR 0.32, p < 0.001, model 1, different time periods, administrative rule.
[Mohan], 2/2/2021, Double Blind Randomized Controlled Trial, India, South Asia, peer-reviewed, 27 authors, dosage 400μg/kg single dose, 200μg/kg also tested. Submit Corrections or Updates.	risk of no discharge at day 14, 62.5% lower, RR 0.38, p = 0.27, treatment 2 of 40 (5.0%), control 6 of 45 (13.3%), NNT 12, ivermectin 24mg.
	risk of clinical worsening, 32.5% lower, RR 0.68, p = 0.72, treatment 3 of 40 (7.5%), control 5 of 45 (11.1%), NNT 28, ivermectin 24mg.
	risk of no virological cure, 23.8% lower, RR 0.76, p = 0.18, treatment 21 of 40 (52.5%), control 31 of 45 (68.9%), NNT 6.1, ivermectin 24mg, day 5.
	risk of no virological cure, 10.3% lower, RR 0.90, p = 0.65, treatment 20 of 36 (55.6%), control 26 of 42 (61.9%), NNT 16, ivermectin 24mg, day 7.
[Mourya], 4/1/2021, retrospective, India, South Asia, peer-reviewed, 5 authors, dosage 12mg days 1-7. Submit Corrections or Updates.	risk of no virological cure, 89.4% lower, RR 0.11, p < 0.001, treatment 5 of 50 (10.0%), control 47 of 50 (94.0%), NNT 1.2.
[Ravikirti (B)], 1/9/2021, Double Blind Randomized Controlled Trial, India, South Asia, peer-reviewed, 11 authors, average treatment delay 6.1 days, dosage 12mg days 1, 2. Submit Corrections or Updates.	risk of death, 88.7% lower, RR 0.11, p = 0.12, treatment 0 of 55 (0.0%), control 4 of 57 (7.0%), NNT 14, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	risk of mechanical ventilation, 79.3% lower, RR 0.21, p = 0.10, treatment 1 of 55 (1.8%), control 5 of 57 (8.8%), NNT 14.
	risk of ICU admission, 13.6% lower, RR 0.86, p = 0.80, treatment 5 of 55 (9.1%), control 6 of 57 (10.5%), NNT 70.
	risk of no hospital discharge, 88.7% lower, RR 0.11, p = 0.12, treatment 0 of 55 (0.0%), control 4 of 57 (7.0%), NNT 14, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	risk of no virological cure, 11.6% higher, RR 1.12, p = 0.35, treatment 42 of 55 (76.4%), control 39 of 57 (68.4%).
[Reis], 8/6/2021, Double Blind Randomized Controlled Trial, Brazil, South America, peer-reviewed, 27 authors, study period 23 March, 2021 - 6 August, 2021, dosage 400μg/kg days 1-3, excluded in exclusion analyses: multiple anomalies as per detailed analysis. Submit Corrections or Updates.	risk of death, 12.0% lower, RR 0.88, p = 0.68, treatment 21 of 679 (3.1%), control 24 of 679 (3.5%), NNT 226.
	risk of mechanical ventilation, 23.0% lower, RR 0.77, p = 0.38, treatment 19 of 679 (2.8%), control 25 of 679 (3.7%), NNT 113.
	risk of hospitalization, 17.0% lower, RR 0.83, p = 0.19, treatment 79 of 679 (11.6%), control 95 of 679 (14.0%), NNT 42.
	extended ER observation or hospitalization, 10.0% lower, RR 0.90, p = 0.42, treatment 100 of 679 (14.7%), control 111 of 679 (16.3%), NNT 62.
	risk of no virological cure, no change, RR 1.00, p = 1.00, treatment 106 of 142 (74.6%), control 123 of 165 (74.5%), day 7.
[Roy], 3/12/2021, retrospective, database analysis, India, South Asia, preprint, 5 authors, dosage not specified, this trial uses multiple treatments in the treatment arm (combined with doxycycline) - results of individual treatments may vary, excluded in exclusion analyses: no serious outcomes reported and fast recovery in treatment and control groups, there is little room for a treatment to improve results. Submit Corrections or Updates.	relative time to clinical response of wellbeing, 5.6% lower, relative time 0.94, p = 0.87, treatment 14, control 15.
[Szente Fonseca], 10/31/2020, retrospective, Brazil, South America, peer-reviewed, mean age 50.6, 10 authors, average treatment delay 4.6 days, dosage 12mg days 1-2, excluded in exclusion analyses: result is likely affected by collinearity across treatments in the model. Submit Corrections or Updates.	risk of hospitalization, 13.9% higher, RR 1.14, p = 0.53, treatment 340, control 377, adjusted per study, odds ratio converted to relative risk, control prevalence approximated with overall prevalence.
[Vallejos], 7/2/2021, Double Blind Randomized Controlled Trial, Argentina, South America, peer-reviewed, 29 authors, average treatment delay 4.0 days, dosage 12mg days 1-2, <80kg 12mg, 80-110kg 18mg, >110kg 24mg. Submit Corrections or Updates.	risk of death, 33.5% higher, RR 1.33, p = 0.70, treatment 4 of 250 (1.6%), control 3 of 251 (1.2%), odds ratio converted to relative risk.
	risk of mechanical ventilation, 33.5% higher, RR 1.33, p = 0.70, treatment 4 of 250 (1.6%), control 3 of 251 (1.2%), odds ratio converted to relative risk.
	risk of hospitalization, 33.0% lower, RR 0.67, p = 0.23, treatment 14 of 250 (5.6%), control 21 of 251 (8.4%), NNT 36, odds ratio converted to relative risk.
	risk of no virological cure, 5.0% higher, RR 1.05, p = 0.55, treatment 137 of 250 (54.8%), control 131 of 251 (52.2%), odds ratio converted to relative risk, day 3.
	risk of no virological cure, 26.8% higher, RR 1.27, p = 0.29, treatment 38 of 250 (15.2%), control 30 of 251 (12.0%), odds ratio converted to relative risk, day 12.

Late treatment.

[Abd-Elsalam], 6/2/2021, Randomized Controlled Trial, Egypt, Africa, peer-reviewed, 16 authors, dosage 12mg days 1-3. Submit Corrections or Updates.	risk of death, 25.0% lower, RR 0.75, p = 0.70, treatment 3 of 82 (3.7%), control 4 of 82 (4.9%), NNT 82, odds ratio converted to relative risk, logistic regression.
	risk of mechanical ventilation, no change, RR 1.00, p = 1.00, treatment 3 of 82 (3.7%), control 3 of 82 (3.7%).
	hospitalization time, 19.6% lower, relative time 0.80, p = 0.09, treatment 82, control 82.
[Ahsan], 4/29/2021, retrospective, Pakistan, South Asia, peer-reviewed, 10 authors, dosage 150μg/kg days 1-2, 150-200µg/kg, this trial uses multiple treatments in the treatment arm (combined with doxycycline) - results of individual treatments may vary, excluded in exclusion analyses: unadjusted results with no group details. Submit Corrections or Updates.	risk of death, 50.0% lower, RR 0.50, p = 0.03, treatment 17 of 110 (15.5%), control 17 of 55 (30.9%), NNT 6.5.
[Baguma], 12/28/2021, retrospective, Uganda, Africa, preprint, 16 authors, study period March 2020 - October 2021, dosage not specified. Submit Corrections or Updates.	risk of death, 96.8% lower, RR 0.03, p = 0.31, treatment 7, control 474, adjusted per study, odds ratio converted to relative risk, multivariable, control prevalance approximated with overall prevalence.
[Beltran Gonzalez], 2/23/2021, Double Blind Randomized Controlled Trial, Mexico, North America, peer-reviewed, mean age 53.8, 13 authors, average treatment delay 7.0 days, dosage 12mg single dose, 18mg for patients >80kg, excluded in exclusion analyses: major inconsistencies reported and the data is no longer available, although the authors state that it is available, and have shared it with an anti-treatment group. Submit Corrections or Updates.	risk of death, 14.4% lower, RR 0.86, p = 1.00, treatment 5 of 36 (13.9%), control 6 of 37 (16.2%), NNT 43.
	risk of respiratory deterioration or death, 8.6% lower, RR 0.91, p = 1.00, treatment 8 of 36 (22.2%), control 9 of 37 (24.3%), NNT 48.
	risk of no hospital discharge, 37.0% higher, RR 1.37, p = 0.71, treatment 4 of 36 (11.1%), control 3 of 37 (8.1%).
	hospitalization time, 20.0% higher, relative time 1.20, p = 0.43, treatment 36, control 37.
[Budhiraja], 11/18/2020, retrospective, India, South Asia, preprint, 12 authors, dosage not specified. Submit Corrections or Updates.	risk of death, 99.1% lower, RR 0.009, p = 0.04, treatment 0 of 34 (0.0%), control 103 of 942 (10.9%), NNT 9.1, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), unadjusted.
[Camprubí], 11/11/2020, retrospective, Spain, Europe, peer-reviewed, 9 authors, average treatment delay 12.0 days, dosage 200μg/kg single dose. Submit Corrections or Updates.	risk of mechanical ventilation, 40.0% lower, RR 0.60, p = 0.67, treatment 3 of 13 (23.1%), control 5 of 13 (38.5%), NNT 6.5.
	risk of ICU admission, 33.3% lower, RR 0.67, p = 1.00, treatment 2 of 13 (15.4%), control 3 of 13 (23.1%), NNT 13, ICU at day 8.
	risk of no improvement at day 8, 33.3% higher, RR 1.33, p = 1.00, treatment 4 of 13 (30.8%), control 3 of 13 (23.1%).
	risk of no virological cure, 25.0% higher, RR 1.25, p = 1.00, treatment 5 of 13 (38.5%), control 4 of 13 (30.8%), tests done between days 3-5.
[Chachar], 9/30/2020, Randomized Controlled Trial, India, South Asia, peer-reviewed, 6 authors, dosage 36mg, 12mg stat, 12mg after 12 hours, 12mg after 24 hours. Submit Corrections or Updates.	risk of no recovery at day 7, 10.0% lower, RR 0.90, p = 0.50, treatment 9 of 25 (36.0%), control 10 of 25 (40.0%), NNT 25.
[Efimenko], 2/28/2022, retrospective, propensity score matching, USA, North America, peer-reviewed, 6 authors, study period 1 January, 2020 - 11 July, 2021, dosage not specified, this trial compares with another treatment - results may be better when compared to placebo. Submit Corrections or Updates.	risk of death, 69.2% lower, OR 0.31, p < 0.001, treatment 1,072, control 40,536, propensity score matching, RR approximated with OR.
[Elavarasi], 8/12/2021, retrospective, India, South Asia, preprint, 26 authors, dosage not specified, excluded in exclusion analyses: unadjusted results with no group details. Submit Corrections or Updates.	risk of death, 19.6% lower, RR 0.80, p = 0.12, treatment 48 of 283 (17.0%), control 311 of 1,475 (21.1%), NNT 24, unadjusted.
[Ferreira], 11/26/2021, retrospective, Brazil, South America, peer-reviewed, 5 authors, study period 12 March, 2020 - 8 July, 2020, average treatment delay 7.0 days, dosage not specified, excluded in exclusion analyses: unadjusted results with no group details, substantial unadjusted confounding by indication likely. Submit Corrections or Updates.	risk of death, 5.0% higher, RR 1.05, p = 1.00, treatment 3 of 21 (14.3%), control 11 of 81 (13.6%).
	risk of death/intubation, 54.3% higher, RR 1.54, p = 0.37, treatment 6 of 21 (28.6%), control 15 of 81 (18.5%).
	risk of death/intubation/ICU, 62.4% higher, RR 1.62, p = 0.27, treatment 8 of 21 (38.1%), control 19 of 81 (23.5%).
[Gorial], 7/8/2020, retrospective, Iraq, Middle East, preprint, 9 authors, dosage 200μg/kg single dose. Submit Corrections or Updates.	risk of death, 71.0% lower, RR 0.29, p = 1.00, treatment 0 of 16 (0.0%), control 2 of 71 (2.8%), NNT 36, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	hospitalization time, 42.0% lower, relative time 0.58, p < 0.001, treatment 16, control 71.
	risk of no recovery, 71.0% lower, RR 0.29, p = 1.00, treatment 0 of 16 (0.0%), control 2 of 71 (2.8%), NNT 36, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
[Hashim], 10/26/2020, Single Blind Randomized Controlled Trial, Iraq, Middle East, peer-reviewed, 7 authors, dosage 200μg/kg days 1-2, some patients received a third dose on day 8, this trial uses multiple treatments in the treatment arm (combined with doxycycline) - results of individual treatments may vary. Submit Corrections or Updates.	risk of death, 91.7% lower, RR 0.08, p = 0.03, treatment 0 of 59 (0.0%), control 6 of 70 (8.6%), NNT 12, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), excluding non-randomized critical patients.
	risk of death, 67.1% lower, RR 0.33, p = 0.16, treatment 2 of 70 (2.9%), control 6 of 70 (8.6%), NNT 18, odds ratio converted to relative risk, including critical patients that were always allocated to treatment.
	risk of progression, 83.1% lower, RR 0.17, p = 0.07, treatment 1 of 59 (1.7%), control 7 of 70 (10.0%), NNT 12, excluding non-randomized critical patients.
	risk of progression, 57.4% lower, RR 0.43, p = 0.20, treatment 3 of 70 (4.3%), control 7 of 70 (10.0%), NNT 18, odds ratio converted to relative risk, including critical patients that were always allocated to treatment.
	recovery time, 40.7% lower, relative time 0.59, p < 0.001, treatment 70, control 70.
[Hazan], 7/7/2021, retrospective, USA, North America, preprint, 7 authors, average treatment delay 9.2 days, dosage 12mg days 1, 4, 8, this trial uses multiple treatments in the treatment arm (combined with doxycycline, zinc, vitamin D, vitamin C) - results of individual treatments may vary, excluded in exclusion analyses: study uses a synthetic control arm. Submit Corrections or Updates.	risk of death, 86.2% lower, RR 0.14, p = 0.04, NNT 6.9, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	risk of hospitalization, 93.5% lower, RR 0.07, p = 0.001, NNT 3.3, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
[Huvemek], 3/25/2021, Double Blind Randomized Controlled Trial, Bulgaria, Europe, preprint, 1 author, average treatment delay 7.0 days, dosage 400μg/kg days 1-3. Submit Corrections or Updates.	risk of no improvement, 31.6% lower, RR 0.68, p = 0.28, treatment 13 of 50 (26.0%), control 19 of 50 (38.0%), NNT 8.3, day 7, patients with improvement on WHO scale.
	risk of no improvement, 34.5% lower, RR 0.66, p = 0.07, treatment 19 of 50 (38.0%), control 29 of 50 (58.0%), NNT 5.0, day 4, patients with improvement on WHO scale.
[Jamir], 12/13/2021, retrospective, India, South Asia, peer-reviewed, 6 authors, study period June 2020 - October 2010, dosage not specified. Submit Corrections or Updates.	risk of death, 53.0% higher, RR 1.53, p = 0.13, treatment 32 of 76 (42.1%), control 69 of 190 (36.3%), adjusted per study, multivariable Cox regression.
[Khan], 9/24/2020, retrospective, Bangladesh, South Asia, preprint, median age 35.0, 8 authors, dosage 12mg single dose. Submit Corrections or Updates.	risk of death, 87.1% lower, RR 0.13, p = 0.02, treatment 1 of 115 (0.9%), control 9 of 133 (6.8%), NNT 17.
	risk of ICU admission, 89.5% lower, RR 0.11, p = 0.007, treatment 1 of 115 (0.9%), control 11 of 133 (8.3%), NNT 14.
	risk of progression, 83.5% lower, RR 0.17, p < 0.001, treatment 3 of 115 (2.6%), control 21 of 133 (15.8%), NNT 7.6.
	risk of no recovery, 87.1% lower, RR 0.13, p = 0.02, treatment 1 of 115 (0.9%), control 9 of 133 (6.8%), NNT 17.
	hospitalization time, 40.0% lower, relative time 0.60, p < 0.001, treatment 115, control 133.
	time to viral-, 73.3% lower, relative time 0.27, p < 0.001, treatment 115, control 133.
[Kishoria], 8/31/2020, Randomized Controlled Trial, India, South Asia, peer-reviewed, 7 authors, dosage 12mg single dose, excluded in exclusion analyses: excessive unadjusted differences between groups. Submit Corrections or Updates.	risk of no hospital discharge, 7.5% higher, RR 1.08, p = 1.00, treatment 11 of 19 (57.9%), control 7 of 13 (53.8%).
	risk of no virological cure, 7.5% higher, RR 1.08, p = 1.00, treatment 11 of 19 (57.9%), control 7 of 13 (53.8%), day 3.
	risk of no virological cure, 220.0% higher, RR 3.20, p = 0.45, treatment 1 of 5 (20.0%), control 0 of 6 (0.0%), continuity correction due to zero event (with reciprocal of the contrasting arm), day 5.
[Lim], 11/3/2021, Randomized Controlled Trial, Malaysia, Europe, peer-reviewed, 26 authors, study period 31 May, 2021 - 9 October, 2021, average treatment delay 5.1 days, dosage 400μg/kg days 1-5. Submit Corrections or Updates.	risk of death, 69.0% lower, RR 0.31, p = 0.09, treatment 3 of 241 (1.2%), control 10 of 249 (4.0%), NNT 36.
	risk of death, 75.2% lower, RR 0.25, p = 0.02, treatment 3 of 52 (5.8%), control 10 of 43 (23.3%), NNT 5.7, among patients progressing to severe cases (mostly before treatment ended).
	risk of mechanical ventilation, 59.0% lower, RR 0.41, p = 0.17, treatment 4 of 241 (1.7%), control 10 of 249 (4.0%), NNT 42.
	risk of ICU admission, 22.0% lower, RR 0.78, p = 0.79, treatment 6 of 241 (2.5%), control 8 of 249 (3.2%), NNT 138.
	risk of progression, 31.1% lower, RR 0.69, p = 0.29, treatment 14 of 241 (5.8%), control 21 of 249 (8.4%), NNT 38, death/IMV/NIV/high flow (WHO severe cases).
	risk of progression, 25.0% higher, RR 1.25, p = 0.25, treatment 52 of 241 (21.6%), control 43 of 249 (17.3%).
	hospitalization time, 5.5% higher, relative time 1.05, p = 0.38, treatment 241, control 249.
	risk of no recovery, 2.5% higher, RR 1.02, p = 0.86, treatment 116 of 241 (48.1%), control 116 of 247 (47.0%), day 5.
[Lima-Morales], 2/10/2021, prospective, Mexico, North America, peer-reviewed, 9 authors, average treatment delay 7.2 days, dosage 12mg single dose, this trial uses multiple treatments in the treatment arm (combined with azithromycin, montelukast, and aspirin) - results of individual treatments may vary. Submit Corrections or Updates.	risk of death, 77.7% lower, RR 0.22, p < 0.001, treatment 15 of 481 (3.1%), control 52 of 287 (18.1%), NNT 6.7, adjusted per study, odds ratio converted to relative risk, multivariate.
	risk of mechanical ventilation, 51.9% lower, RR 0.48, p = 0.15, treatment 8 of 434 (1.8%), control 11 of 287 (3.8%), NNT 50.
	risk of hospitalization, 67.4% lower, RR 0.33, p < 0.001, treatment 44 of 481 (9.1%), control 89 of 287 (31.0%), NNT 4.6, adjusted per study, odds ratio converted to relative risk, multivariate.
	risk of no recovery, 58.6% lower, RR 0.41, p < 0.001, treatment 75 of 481 (15.6%), control 118 of 287 (41.1%), NNT 3.9, adjusted per study, odds ratio converted to relative risk, recovery at day 14 after symptoms, multivariate.
[Mustafa], 12/29/2021, retrospective, Pakistan, South Asia, peer-reviewed, 7 authors, dosage varies, excluded in exclusion analyses: unadjusted results with no group details. Submit Corrections or Updates.	risk of death, 63.7% lower, RR 0.36, p = 0.09, treatment 3 of 73 (4.1%), control 42 of 371 (11.3%), NNT 14.
[Okumuş], 1/12/2021, Double Blind Randomized Controlled Trial, Turkey, Europe, peer-reviewed, 15 authors, dosage 200μg/kg days 1-5, 36-50kg - 9mg, 51-65kg - 12mg, 66-79kg - 15mg, >80kg 200μg/kg. Submit Corrections or Updates.	risk of death, 33.3% lower, RR 0.67, p = 0.55, treatment 6 of 30 (20.0%), control 9 of 30 (30.0%), NNT 10.
	risk of no improvement at day 10, 42.9% lower, RR 0.57, p = 0.18, treatment 8 of 30 (26.7%), control 14 of 30 (46.7%), NNT 5.0.
	risk of no improvement at day 5, 15.8% lower, RR 0.84, p = 0.60, treatment 16 of 30 (53.3%), control 19 of 30 (63.3%), NNT 10.
	risk of no virological cure, 80.0% lower, RR 0.20, p = 0.02, treatment 2 of 16 (12.5%), control 5 of 8 (62.5%), NNT 2.0, day 10.
[Ozer], 11/23/2021, prospective, USA, North America, peer-reviewed, 12 authors, dosage 200μg/kg days 1, 3. Submit Corrections or Updates.	risk of death, 75.0% lower, RR 0.25, p = 0.09, treatment 2 of 60 (3.3%), control 8 of 60 (13.3%), NNT 10.0, PSM.
	risk of mechanical ventilation, 12.6% lower, RR 0.87, p = 0.20, treatment 3 of 60 (5.0%), control 2 of 60 (3.3%), odds ratio converted to relative risk, PSM, multivariable.
	ventilation time, 83.3% lower, relative time 0.17, p = 0.002, treatment 60, control 60.
	risk of ICU admission, 48.7% lower, RR 0.51, p = 0.42, treatment 6 of 60 (10.0%), control 3 of 60 (5.0%), odds ratio converted to relative risk, PSM, multivariable.
	ICU time, 70.6% lower, relative time 0.29, p < 0.001, treatment 60, control 60.
	hospitalization time, 9.0% higher, relative time 1.09, p = 0.09, treatment 60, control 60, PSM, multivariable.
[Podder], 9/3/2020, Randomized Controlled Trial, Bangladesh, South Asia, peer-reviewed, 4 authors, average treatment delay 7.0 days, dosage 200μg/kg single dose. Submit Corrections or Updates.	recovery time from enrollment, 16.1% lower, relative time 0.84, p = 0.34, treatment 32, control 30.
[Pott-Junior], 3/9/2021, Randomized Controlled Trial, Brazil, South America, peer-reviewed, 10 authors, average treatment delay 8.0 days, dosage 200μg/kg single dose, dose varies in three arms 100, 200, 400μg/kg. Submit Corrections or Updates.	risk of mechanical ventilation, 85.2% lower, RR 0.15, p = 0.25, treatment 1 of 27 (3.7%), control 1 of 4 (25.0%), NNT 4.7.
	risk of ICU admission, 85.2% lower, RR 0.15, p = 0.25, treatment 1 of 27 (3.7%), control 1 of 4 (25.0%), NNT 4.7.
	relative improvement in Ct value, 0.8% better, RR 0.99, p = 1.00, treatment 27, control 3.
	risk of no virological cure, 11.1% higher, RR 1.11, p = 1.00, treatment 10 of 27 (37.0%), control 1 of 3 (33.3%).
[Rajter], 10/13/2020, retrospective, propensity score matching, USA, North America, peer-reviewed, 6 authors, dosage 200μg/kg single dose. Submit Corrections or Updates.	risk of death, 46.0% lower, RR 0.54, p = 0.045, treatment 13 of 98 (13.3%), control 24 of 98 (24.5%), NNT 8.9, adjusted per study, odds ratio converted to relative risk, PSM.
	risk of death, 66.9% lower, RR 0.33, p = 0.03, treatment 26 of 173 (15.0%), control 27 of 107 (25.2%), NNT 9.8, adjusted per study, odds ratio converted to relative risk, multivariate.
	risk of mechanical ventilation, 63.6% lower, RR 0.36, p = 0.10, treatment 4 of 98 (4.1%), control 11 of 98 (11.2%), NNT 14, matched cohort excluding intubated at baseline.
[Ravikirti], 4/6/2022, retrospective, India, South Asia, preprint, 7 authors, study period 1 April, 2021 - 15 May, 2021, dosage varies, excluded in exclusion analyses: exclusion of patients in less severe condition, data/analysis concerns. Submit Corrections or Updates.	risk of death, 2.8% lower, RR 0.97, p = 0.82, treatment 53 of 171 (31.0%), control 254 of 794 (32.0%), NNT 100, odds ratio converted to relative risk.
[Rezk], 10/30/2021, prospective, Egypt, Africa, peer-reviewed, 4 authors, dosage 36mg days 1, 3, 6. Submit Corrections or Updates.	risk of death, 80.0% lower, RR 0.20, p = 0.50, treatment 0 of 160 (0.0%), control 2 of 160 (1.2%), NNT 80, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	risk of progression, 55.6% lower, RR 0.44, p = 0.06, treatment 8 of 160 (5.0%), control 18 of 160 (11.2%), NNT 16, 2 weeks, including deaths.
	risk of no recovery, 33.4% lower, RR 0.67, p = 0.27, treatment 14 of 145 (9.7%), control 20 of 138 (14.5%), NNT 21, 4 weeks, more patients were lost to followup in the control group.
	time to viral-, 27.3% lower, relative time 0.73, p = 0.01, treatment 160, control 160.
[Shahbaznejad], 1/19/2021, Double Blind Randomized Controlled Trial, Iran, Middle East, peer-reviewed, 8 authors, average treatment delay 6.29 days, dosage 200μg/kg single dose. Submit Corrections or Updates.	risk of death, 197.1% higher, RR 2.97, p = 1.00, treatment 1 of 35 (2.9%), control 0 of 34 (0.0%), continuity correction due to zero event (with reciprocal of the contrasting arm), patient died within 24 hours of admission.
	risk of mechanical ventilation, 94.3% higher, RR 1.94, p = 1.00, treatment 2 of 35 (5.7%), control 1 of 34 (2.9%).
	recovery time, 31.6% lower, relative time 0.68, p = 0.048, treatment 35, control 34, duration of dsypnea.
	recovery time, 19.2% lower, relative time 0.81, p = 0.02, treatment 35, control 34, duration of all symptoms.
	hospitalization time, 15.5% lower, relative time 0.85, p = 0.02, treatment 35, control 34.
[Shimizu], 12/31/2021, retrospective, Japan, Asia, peer-reviewed, 11 authors, study period December 2020 - May 2021, dosage 200μg/kg days 1, 14. Submit Corrections or Updates.	risk of death, 99.9% lower, HR 0.001, p < 0.001, treatment 0 of 39 (0.0%), control 8 of 49 (16.3%), NNT 6.1, adjusted per study, Cox proportional hazard regression.
	ventilator free days, 47.9% lower, OR 0.52, p = 0.03, treatment 39, control 49, adjusted per study, proportional odds logistic regression, RR approximated with OR.
	ventilation time, 38.5% lower, relative time 0.62, p < 0.001, treatment 39, control 49.
	ICU free days, 42.8% lower, OR 0.57, p = 0.06, treatment 39, control 49, adjusted per study, proportional odds logistic regression, RR approximated with OR.
	ICU time, 37.5% lower, relative time 0.62, p < 0.001, treatment 39, control 49.
	GI complications while ventilated, 77.9% lower, RR 0.22, p = 0.03, treatment 39, control 49, adjusted per study, Cox proportional hazard regression.
[Soto], 3/2/2022, retrospective, Peru, South America, peer-reviewed, median age 58.0, 10 authors, study period April 2020 - August 2020, dosage not specified, excluded in exclusion analyses: substantial unadjusted confounding by indication likely, substantial confounding by time possible due to significant changes in SOC and treatment propensity near the start of the pandemic. Submit Corrections or Updates.	risk of death, 41.0% higher, HR 1.41, p = 0.001, treatment 280 of 484 (57.9%), control 374 of 934 (40.0%), adjusted per study, multivariable.
[Soto-Becerra], 10/8/2020, retrospective, database analysis, Peru, South America, preprint, median age 59.4, 4 authors, study period 1 April, 2020 - 19 July, 2020, dosage 200μg/kg single dose, excluded in exclusion analyses: substantial unadjusted confounding by indication likely, includes PCR+ patients that may be asymptomatic for COVID-19 but in hospital for other reasons. Submit Corrections or Updates.	risk of death, 17.1% lower, HR 0.83, p = 0.01, treatment 92 of 203 (45.3%), control 1,438 of 2,630 (54.7%), NNT 11, IVM vs. control day 43 (last day available) weighted KM from figure 3, per the pre-specified rules, the last available day mortality results have priority.
	risk of death, 39.0% higher, HR 1.39, p = 0.16, treatment 47 of 203 (23.2%), control 401 of 2,630 (15.2%), adjusted per study, day 30, Table 2, IVM wHR.
[Spoorthi], 11/14/2020, prospective, India, South Asia, peer-reviewed, 2 authors, dosage not specified, this trial uses multiple treatments in the treatment arm (combined with doxycycline) - results of individual treatments may vary. Submit Corrections or Updates.	recovery time, 21.1% lower, relative time 0.79, p = 0.03, treatment 50, control 50.
	hospitalization time, 15.5% lower, relative time 0.84, p = 0.01, treatment 50, control 50.
[Thairu], 2/25/2022, retrospective, Nigeria, Africa, preprint, 5 authors, study period April 2021 - November 2021, dosage 200μg/kg days 1-5, excluded in exclusion analyses: significant confounding by time possible due to separation of groups in different time periods. Submit Corrections or Updates.	risk of death, 87.9% lower, RR 0.12, p = 0.12, treatment 0 of 21 (0.0%), control 4 of 26 (15.4%), NNT 6.5, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), propensity score matching.
	risk of death, 93.0% lower, RR 0.07, p = 0.007, treatment 0 of 61 (0.0%), control 4 of 26 (15.4%), NNT 6.5, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), all patients.
	time to discharge, 54.6% lower, relative time 0.45, p < 0.001, treatment 61, control 26, propensity score matching.
	risk of no virological cure, 94.8% lower, RR 0.05, p = 0.001, treatment 0 of 21 (0.0%), control 10 of 26 (38.5%), NNT 2.6, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), propensity score matching, day 21.
	risk of no virological cure, 95.2% lower, RR 0.05, p < 0.001, treatment 1 of 21 (4.8%), control 26 of 26 (100.0%), NNT 1.1, propensity score matching, day 14.
	risk of no virological cure, 28.6% lower, RR 0.71, p = 0.005, treatment 15 of 21 (71.4%), control 26 of 26 (100.0%), NNT 3.5, propensity score matching, day 5.
[Zubair], 1/18/2022, retrospective, Pakistan, South Asia, peer-reviewed, 8 authors, study period October 2020 - February 2021, dosage 12mg single dose, excluded in exclusion analyses: substantial unadjusted confounding by indication likely, unadjusted results with no group details. Submit Corrections or Updates.	risk of death, 9.0% higher, RR 1.09, p = 1.00, treatment 5 of 90 (5.6%), control 5 of 98 (5.1%), unadjusted.
	hospitalization time, 8.0% higher, relative time 1.08, p = 0.40, treatment 90, control 98, unadjusted, Table 3, mean number of days.

Prophylaxis.

[Alam], 12/15/2020, prospective, Bangladesh, South Asia, peer-reviewed, 13 authors, dosage 12mg monthly. Submit Corrections or Updates.	risk of case, 90.6% lower, RR 0.09, p < 0.001, treatment 4 of 58 (6.9%), control 44 of 60 (73.3%), NNT 1.5.
[Behera (B)], 2/15/2021, prospective, India, South Asia, peer-reviewed, 14 authors, dosage 300μg/kg days 1, 4. Submit Corrections or Updates.	risk of case, 83.0% lower, RR 0.17, p < 0.001, treatment 45 of 2,199 (2.0%), control 133 of 1,147 (11.6%), NNT 10, two doses.
[Behera], 11/3/2020, retrospective, India, South Asia, peer-reviewed, 13 authors, dosage 300μg/kg days 1, 4. Submit Corrections or Updates.	risk of case, 53.8% lower, RR 0.46, p < 0.001, treatment 41 of 117 (35.0%), control 145 of 255 (56.9%), NNT 4.6, adjusted per study, odds ratio converted to relative risk, model 2 2+ doses conditional logistic regression.
[Bernigaud], 11/28/2020, retrospective, France, Europe, peer-reviewed, 12 authors, dosage 200μg/kg days 1, 8, 15, 400μg/kg days 1, 8, 15, two different dosages. Submit Corrections or Updates.	risk of death, 99.4% lower, RR 0.006, p = 0.08, treatment 0 of 69 (0.0%), control 150 of 3,062 (4.9%), NNT 20, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
	risk of case, 55.1% lower, RR 0.45, p = 0.01, treatment 7 of 69 (10.1%), control 692 of 3,062 (22.6%), NNT 8.0.
[Carvallo], 11/17/2020, prospective, Argentina, South America, peer-reviewed, 4 authors, dosage 12mg weekly, this trial uses multiple treatments in the treatment arm (combined with iota-carrageenan) - results of individual treatments may vary, excluded in exclusion analyses: concern about potential data issues. Submit Corrections or Updates.	risk of case, 99.9% lower, RR 0.001, p < 0.001, treatment 0 of 788 (0.0%), control 237 of 407 (58.2%), NNT 1.7, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
[Carvallo (B)], 10/19/2020, prospective, Argentina, South America, preprint, 1 author, dosage 1mg days 1-14, this trial uses multiple treatments in the treatment arm (combined with iota-carrageenan) - results of individual treatments may vary, excluded in exclusion analyses: concern about potential data issues. Submit Corrections or Updates.	risk of case, 96.3% lower, RR 0.04, p < 0.001, treatment 0 of 131 (0.0%), control 11 of 98 (11.2%), NNT 8.9, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
[Chahla (B)], 1/11/2021, Randomized Controlled Trial, Argentina, South America, peer-reviewed, 11 authors, dosage 12mg weekly, this trial uses multiple treatments in the treatment arm (combined with iota-carrageenan) - results of individual treatments may vary. Submit Corrections or Updates.	risk of moderate/severe case, 95.2% lower, RR 0.05, p = 0.002, treatment 0 of 117 (0.0%), control 10 of 117 (8.5%), NNT 12, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), moderate/severe COVID-19.
	risk of case, 84.0% lower, RR 0.16, p = 0.004, treatment 4 of 117 (3.4%), control 25 of 117 (21.4%), NNT 5.6, adjusted per study, odds ratio converted to relative risk, all cases.
[Hellwig], 11/28/2020, retrospective, ecological study, multiple countries, multiple regions, peer-reviewed, 2 authors, dosage 200μg/kg, dose varied, typically 150-200μg/kg, excluded in exclusion analyses: not a typical trial, analysis of African countries that used or did not use ivermectin prophylaxis for parasitic infections. Submit Corrections or Updates.	risk of case, 78.0% lower, RR 0.22, p < 0.02, African countries, PCTI vs. no PCT, relative cases per capita.
[IVERCOR PREP], 12/20/2020, retrospective, Argentina, South America, preprint, 1 author, dosage 12mg weekly, excluded in exclusion analyses: minimal details provided. Submit Corrections or Updates.	risk of case, 73.4% lower, RR 0.27, p < 0.001, treatment 13 of 389 (3.3%), control 61 of 486 (12.6%), NNT 11.
[Kerr], 12/11/2021, retrospective, propensity score matching, Brazil, South America, peer-reviewed, 9 authors, study period July 2020 - December 2020, dosage 200μg/kg days 1, 2, 16, 17, 0.2mg/kg/day for 2 days every 15 days. Submit Corrections or Updates.	risk of death, 70.0% lower, RR 0.30, p < 0.001, treatment 25 of 3,034 (0.8%), control 79 of 3,034 (2.6%), NNT 56, adjusted per study, multivariate linear regression, propensity score matching.
	risk of hospitalization, 67.0% lower, RR 0.33, p < 0.001, treatment 44 of 3,034 (1.5%), control 99 of 3,034 (3.3%), adjusted per study, multivariate linear regression, propensity score matching.
	risk of case, 44.5% lower, RR 0.56, p < 0.001, treatment 4,197 of 113,845 (3.7%), control 3,034 of 45,716 (6.6%), NNT 34.
[Mondal], 5/31/2021, retrospective, India, South Asia, peer-reviewed, 11 authors, dosage not specified. Submit Corrections or Updates.	risk of symptomatic case, 87.9% lower, RR 0.12, p = 0.006, treatment 128, control 1,342, adjusted per study, odds ratio converted to relative risk, control prevalence approximated with overall prevalence, multivariable.
[Morgenstern], 4/16/2021, retrospective, propensity score matching, Dominican Republic, Caribbean, peer-reviewed, 16 authors, dosage 200μg/kg weekly. Submit Corrections or Updates.	risk of hospitalization, 80.0% lower, RR 0.20, p = 0.50, treatment 0 of 271 (0.0%), control 2 of 271 (0.7%), NNT 136, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), PSM.
	risk of case, 74.0% lower, RR 0.26, p = 0.008, treatment 5 of 271 (1.8%), control 18 of 271 (6.6%), NNT 21, adjusted per study, PSM, multivariate Cox regression.
[Samajdar], 11/17/2021, retrospective, India, South Asia, peer-reviewed, 9 authors, study period 1 September, 2020 - 31 December, 2020, dosage not specified, excluded in exclusion analyses: minimal details provided, unadjusted results with no group details, results may be significantly affected by survey bias. Submit Corrections or Updates.	risk of case, 79.8% lower, RR 0.20, p < 0.001, treatment 12 of 164 (7.3%), control 29 of 81 (35.8%), NNT 3.5, odds ratio converted to relative risk, physician survey.
	risk of case, 48.6% lower, RR 0.51, p = 0.03, treatment 11 of 109 (10.1%), control 39 of 200 (19.5%), NNT 11, odds ratio converted to relative risk, combined ivermectin or HCQ in community.
[Seet], 4/14/2021, Cluster Randomized Controlled Trial, Singapore, Asia, peer-reviewed, 15 authors, dosage 12mg single dose, 200µg/kg, maximum 12mg, this trial compares with another treatment - results may be better when compared to placebo. Submit Corrections or Updates.	risk of symptomatic case, 49.8% lower, RR 0.50, p < 0.001, treatment 32 of 617 (5.2%), control 64 of 619 (10.3%), NNT 19.
	risk of case, 5.8% lower, RR 0.94, p = 0.61, treatment 398 of 617 (64.5%), control 433 of 619 (70.0%), NNT 18, adjusted per study, odds ratio converted to relative risk, model 6.
[Shouman], 8/28/2020, Randomized Controlled Trial, Egypt, Africa, peer-reviewed, 8 authors, dosage 18mg days 1, 3, dose varies depending on weight - 40-60kg: 15mg, 60-80kg: 18mg, >80kg: 24mg. Submit Corrections or Updates.	risk of symptomatic case, 91.3% lower, RR 0.09, p < 0.001, treatment 15 of 203 (7.4%), control 59 of 101 (58.4%), NNT 2.0, adjusted per study, multivariate.
	risk of severe case, 92.9% lower, RR 0.07, p = 0.002, treatment 1 of 203 (0.5%), control 7 of 101 (6.9%), NNT 16, unadjusted.
[Tanioka], 3/26/2021, retrospective, ecological study, multiple countries, multiple regions, preprint, 3 authors, dosage 200μg/kg, dose varied, typically 150-200μg/kg, excluded in exclusion analyses: not a typical trial, analysis of African countries that used or did not use ivermectin prophylaxis for parasitic infections. Submit Corrections or Updates.	risk of death, 88.2% lower, RR 0.12, p = 0.002, relative mean mortality per million.

Supplementary Data

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Please send us corrections, updates, or comments. Vaccines and treatments are both valuable and complementary. All practical, effective, and safe means should be used. No treatment, vaccine, or intervention is 100% available and effective for all current and future variants. Denying the efficacy of any method increases mortality, morbidity, collateral damage, and the risk of endemic status. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.

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Aspirin	(meta)	Melatonin	(meta)
Bamlaniv../e..	(meta)	Metformin	(meta)
Bebtelovimab	(meta)	Molnupiravir	(meta)
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