c19early.org COVID-19 treatment researchChlorhexidineChlorhexidine (more..)
Budesonide Meta
Colchicine Meta Nigella Sativa Meta
Conv. Plasma Meta Nitazoxanide Meta
Curcumin Meta PPIs Meta
Fluvoxamine Meta Quercetin Meta
Hydroxychlor.. Meta
Ivermectin Meta
Thermotherapy Meta
Melatonin Meta
Metformin Meta

Loading...
 
More
 

Chlorhexidine reduces COVID-19 risk: real-time meta analysis of 5 studies

@CovidAnalysis, May 2025, Version 5V5
Serious Outcome Risk
Hospital Icon Control
Chlorhexidine
0 0.5 1 1.5+ All studies 71% 5 722 Improvement, Studies, Patients Relative Risk Progression 74% 2 336 Cases 57% 1 76 Viral clearance 69% 3 386 RCTs 75% 3 630 Prophylaxis 61% 1 76 Early 73% 3 352 Late 75% 1 294 Chlorhexidine for COVID-19 c19early.org May 2025 Favorschlorhexidine Favorscontrol
Abstract
Significantly lower risk is seen for progression, cases, and viral clearance. 5 studies from 5 independent teams in 5 countries show significant benefit.
Meta analysis using the most serious outcome reported shows 71% [57‑80%] lower risk. Results are similar for Randomized Controlled Trials.
Serious Outcome Risk
Hospital Icon Control
Chlorhexidine
0 0.5 1 1.5+ All studies 71% 5 722 Improvement, Studies, Patients Relative Risk Progression 74% 2 336 Cases 57% 1 76 Viral clearance 69% 3 386 RCTs 75% 3 630 Prophylaxis 61% 1 76 Early 73% 3 352 Late 75% 1 294 Chlorhexidine for COVID-19 c19early.org May 2025 Favorschlorhexidine Favorscontrol
Currently there is limited data, with only 722 patients in trials to date.
4 RCTs with 512 patients have not reported results (up to 3 years late).
No treatment is 100% effective. Protocols combine safe and effective options with individual risk/benefit analysis and monitoring. Chlorhexidine may be detrimental to the natural microbiome, raising concern for side effects, especially with prolonged or excessive use. All data and sources to reproduce this analysis are in the appendix.
Evolution of COVID-19 clinical evidence Meta analysis results over time Chlorhexidine p=0.00000000075 Acetaminophen p=0.00000029 2020 2021 2022 2023 2024 2025 Lowerrisk Higherrisk c19early.org May 2025 100% 50% 0% -50%
Chlorhexidine for COVID-19 — Highlights
Chlorhexidine reduces risk with very high confidence for viral clearance and in pooled analysis, and low confidence for progression and cases.
50th treatment shown effective in November 2023, now with p = 0.00000000075 from 5 studies.
Real-time updates and corrections with a consistent protocol for 161 treatments. Outcome specific analysis and combined evidence from all studies including treatment delay, a primary confounding factor.
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Bonn 96% 0.04 [0.00-0.76] viral load 31 (n) 31 (n) Short term viral CT​1 Improvement, RR [CI] Treatment Control Jing (DB RCT) 79% 0.21 [0.11-0.39] OGD 10/120 56/140 OGD CT​1 Sulistyani 54% 0.46 [0.29-0.73] viral load 15 (n) 15 (n) Tau​2 = 0.30, I​2 = 66.4%, p = 0.002 Early treatment 73% 0.27 [0.12-0.62] 10/166 56/186 73% lower risk Huang (RCT) 75% 0.25 [0.19-0.34] viral+ 38/159 127/135 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Late treatment 75% 0.25 [0.19-0.34] 38/159 127/135 75% lower risk Karami (DB RCT) 61% 0.39 [0.16-0.97] symptoms 36 (n) 40 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.041 Prophylaxis 61% 0.39 [0.16-0.97] 36 (n) 40 (n) 61% lower risk All studies 71% 0.29 [0.20-0.43] 48/361 183/361 71% lower risk 5 chlorhexidine COVID-19 studies c19early.org May 2025 Tau​2 = 0.08, I​2 = 48.7%, p < 0.0001 Effect extraction pre-specified(most serious outcome, see appendix) 1 CT: study uses combined treatment Favors chlorhexidine Favors control
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Bonn 96% viral- Short term viral CT​1 Improvement Relative Risk [CI] Jing (DB RCT) 79% OGD OGD CT​1 Sulistyani 54% viral- Tau​2 = 0.30, I​2 = 66.4%, p = 0.002 Early treatment 73% 73% lower risk Huang (RCT) 75% viral- Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Late treatment 75% 75% lower risk Karami (DB RCT) 61% symptoms Tau​2 = 0.00, I​2 = 0.0%, p = 0.041 Prophylaxis 61% 61% lower risk All studies 71% 71% lower risk 5 chlorhexidine C19 studies c19early.org May 2025 Tau​2 = 0.08, I​2 = 48.7%, p < 0.0001 Protocol pre-specified/rotate for details1 CT: study uses combined treatment Favors chlorhexidine Favors control
B
-100% -50% 0% 50% 100% Timeline of COVID-19 chlorhexidine studies (pooled effects) 2020 2021 2022 2023 2024 2025 Favorschlorhexidine Favorscontrol c19early.org May 2025 November 2023: efficacy (pooled outcomes) January 2024: efficacy (RCT pooled) April 2025: efficacy (specific outcome)
Figure 1. A. Random effects meta-analysis. This plot shows pooled effects, see the specific outcome analyses for individual outcomes. Analysis validating pooled outcomes for COVID-19 can be found below. Effect extraction is pre-specified, using the most serious outcome reported. For details see the appendix. B. Timeline of results in chlorhexidine studies. The marked dates indicate the time when efficacy was known with a statistically significant improvement of ≥10% from ≥3 studies for pooled outcomes, one or more specific outcome, and pooled outcomes in RCTs. Efficacy based on RCTs only was delayed by 1.6 months, compared to using all studies. Efficacy based on specific outcomes was delayed by 17.3 months, compared to using pooled outcomes.
SARS-CoV-2 infection typically starts in the upper respiratory tract, and specifically the nasal respiratory epithelium. Entry via the eyes and gastrointestinal tract is possible, but less common, and entry via other routes is rare. Infection may progress to the lower respiratory tract, other tissues, and the nervous and cardiovascular systems. The primary initial route for entry into the central nervous system is thought to be the olfactory nerve in the nasal cavity1. Progression may lead to cytokine storm, pneumonia, ARDS, neurological injury2-14 and cognitive deficits5,10, cardiovascular complications15-19, organ failure, and death. Systemic treatments may be insufficient to prevent neurological damage9. Minimizing replication as early as possible is recommended.
Figure 2. SARS-CoV-2 virions attached to cilia of nasal epithelial cells, from Chien-Ting Wu20,21.
Logically, stopping replication in the upper respiratory tract should be simpler and more effective. Wu et al., using an airway organoid model incorporating many in vivo aspects, show that SARS-CoV-2 initially attaches to cilia — hair-like structures responsible for moving the mucus layer and where ACE2 is localized in nasal epithelial cells22. The mucus layer and the need for ciliary transport slow down infection, providing more time for localized treatments20,21. Early or prophylactic nasopharyngeal/oropharyngeal treatment may avoid the consequences of viral replication in other tissues, and avoid the requirement for systemic treatments with greater potential for side effects.
SARS-CoV-2 infection and replication involves the complex interplay of 100+ host and viral proteins and other factorsA,23-30, providing many therapeutic targets for which many existing compounds have known activity. Scientists have predicted that over 9,000 compounds may reduce COVID-19 risk31, either by directly minimizing infection or replication, by supporting immune system function, or by minimizing secondary complications.
Preclinical studies have shown efficacy with chlorhexidine for influenza A virus32 and respiratory syncytial virus32.
We analyze all significant controlled studies of chlorhexidine 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, individual outcomes, and Randomized Controlled Trials (RCTs).
Figure 3 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.
regular treatment to prevent or minimize infectionstreat immediately on symptoms or shortly thereafterlate stage after disease progressionexposed to virusEarly TreatmentProphylaxisTreatment delayLate Treatment
Figure 3. Treatment stages.
Table 1 summarizes the results for all stages combined, for Randomized Controlled Trials, and for specific outcomes. Table 2 shows results by treatment stage. Figure 4 plots individual results by treatment stage. Figure 5, 6, 7, and 8 show forest plots for random effects meta-analysis of all studies with pooled effects, progression, cases, and viral clearance.
Table 1. Random effects meta-analysis for all stages combined, for Randomized Controlled Trials, and for specific outcomes. Results show the percentage improvement with treatment and the 95% confidence interval. * p<0.05  ** p<0.01  **** p<0.0001.
Improvement Studies Patients Authors
All studies71% [57‑80%]
****
5 722 35
Randomized Controlled TrialsRCTs75% [67‑80%]
****
3 630 13
Viral69% [44‑83%]
***
3 386 24
Table 2. Random effects meta-analysis results by treatment stage. Results show the percentage improvement with treatment, the 95% confidence interval, and the number of studies for the stage.treatment and the 95% confidence interval. * p<0.05  ** p<0.01  **** p<0.0001.
Early treatment Late treatment Prophylaxis
All studies73% [38‑88%]
**
75% [66‑81%]
****
61% [3‑84%]
*
Randomized Controlled TrialsRCTs79% [61‑89%]
****
75% [66‑81%]
****
61% [3‑84%]
*
Viral78% [-91‑98%]75% [66‑81%]
****
0 0.25 0.5 0.75 1 1.25 1.5+ All studies Late treatment Early treatment Prophylaxis Efficacy in COVID-19 chlorhexidine studies (pooled effects) Favors chlorhexidine Favors control c19early.org May 2025
Figure 4. Scatter plot showing the most serious outcome in all studies, and for studies within each stage. Diamonds shows the results of random effects meta-analysis.
Loading..
Loading..
Figure 5. Random effects meta-analysis for all studies. This plot shows pooled effects, see the specific outcome analyses for individual outcomes. Analysis validating pooled outcomes for COVID-19 can be found below. Effect extraction is pre-specified, using the most serious outcome reported. For details see the appendix.
Loading..
Figure 6. Random effects meta-analysis for progression.
Loading..
Figure 7. Random effects meta-analysis for cases.
Loading..
Figure 8. Random effects meta-analysis for viral clearance.
Figure 9 shows a comparison of results for RCTs and non-RCT studies. Figure 10 shows a forest plot for random effects meta-analysis of all Randomized Controlled Trials. RCT results are included in Table 1 and Table 2.
Loading..
Figure 9. Results for RCTs and non-RCT studies.
Loading..
Figure 10. Random effects meta-analysis for all Randomized Controlled Trials. This plot shows pooled effects, see the specific outcome analyses for individual outcomes. Analysis validating pooled outcomes for COVID-19 can be found below. Effect extraction is pre-specified, using the most serious outcome reported. For details see the appendix.
RCTs help to make study groups more similar and can provide a higher level of evidence, however they are subject to many biases33, and analysis of double-blind RCTs has identified extreme levels of bias34. For COVID-19, the overhead may delay treatment, dramatically compromising efficacy; they may encourage monotherapy for simplicity at the cost of efficacy which may rely on combined or synergistic effects; the participants that sign up may not reflect real world usage or the population that benefits most in terms of age, comorbidities, severity of illness, or other factors; standard of care may be compromised and unable to evolve quickly based on emerging research for new diseases; errors may be made in randomization and medication delivery; and investigators may have hidden agendas or vested interests influencing design, operation, analysis, reporting, and the potential for fraud. All of these biases have been observed with COVID-19 RCTs. There is no guarantee that a specific RCT provides a higher level of evidence.
RCTs are expensive and many RCTs are funded by pharmaceutical companies or interests closely aligned with pharmaceutical companies. For COVID-19, this creates an incentive to show efficacy for patented commercial products, and an incentive to show a lack of efficacy for inexpensive treatments. The bias is expected to be significant, for example Als-Nielsen et al. analyzed 370 RCTs from Cochrane reviews, showing that trials funded by for-profit organizations were 5 times more likely to recommend the experimental drug compared with those funded by nonprofit organizations. For COVID-19, some major philanthropic organizations are largely funded by investments with extreme conflicts of interest for and against specific COVID-19 interventions.
High quality RCTs for novel acute diseases are more challenging, with increased ethical issues due to the urgency of treatment, increased risk due to enrollment delays, and more difficult design with a rapidly evolving evidence base. For COVID-19, the most common site of initial infection is the upper respiratory tract. Immediate treatment is likely to be most successful and may prevent or slow progression to other parts of the body. For a non-prophylaxis RCT, it makes sense to provide treatment in advance and instruct patients to use it immediately on symptoms, just as some governments have done by providing medication kits in advance. Unfortunately, no RCTs have been done in this way. Every treatment RCT to date involves delayed treatment. Among the 161 treatments we have analyzed, 66% of RCTs involve very late treatment 5+ days after onset. No non-prophylaxis COVID-19 RCTs match the potential real-world use of early treatments. They may more accurately represent results for treatments that require visiting a medical facility, e.g., those requiring intravenous administration.
For COVID-19, observational study results do not systematically differ from RCTs, RR 1.00 [0.93‑1.07] across 161 treatments36.
Evidence shows that observational studies can also provide reliable results. Concato et al. found that well-designed observational studies do not systematically overestimate the magnitude of the effects of treatment compared to RCTs. Anglemyer et al. analyzed reviews comparing RCTs to observational studies and found little evidence for significant differences in effect estimates. We performed a similar analysis across the 161 treatments we cover, showing no significant difference in the results of RCTs compared to observational studies, RR 1.00 [0.93‑1.07]. Similar results are found for all low-cost treatments, RR 1.02 [0.93‑1.11]. High-cost treatments show a non-significant trend towards RCTs showing greater efficacy, RR 0.93 [0.83‑1.04]. Details can be found in the supplementary data. Lee (B) et al. showed 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 remote survey bias may have a greater effect on results. Ethical issues may also prevent running RCTs for known effective treatments. For more on issues with RCTs see40,41.
Currently, 53 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. Of these, 58% have been confirmed in RCTs, with a mean delay of 7.8 months (66% with 8.9 months delay for low-cost treatments). The remaining treatments either have no RCTs, or the point estimate is consistent.
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 off-patent medications, very high conflict of interest trials may be more likely to be RCTs, and more likely to be large trials that dominate meta analyses.
Figure 11. Optimal spray angle may increase nasopharyngeal drug delivery 100x for nasal sprays, adapted from Akash et al.
In addition to the dosage and frequency of administration, efficacy for nasopharyngeal/oropharyngeal treatments may depend on many other details. For example considering sprays, viscosity, mucoadhesion, sprayability, and application angle are important.
Akash et al. performed a computational fluid dynamics study of nasal spray administration showing 100x improvement in nasopharyngeal drug delivery using a new spray placement protocol, which involves holding the spay nozzle as horizontally as possible at the nostril, with a slight tilt towards the cheeks. The study also found the optimal droplet size range for nasopharyngeal deposition was ~7-17µm.
4 chlorhexidine RCTs have not reported results43-46. The trials report a total of 512 patients, with 3 trials having actual enrollment of 422, and the other estimated. The results are delayed from 2 years to over 3 years.
Heterogeneity in COVID-19 studies arises from many factors including:
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 hours47,48. Baloxavir marboxil studies for influenza also show that treatment delay is critical — Ikematsu et al. report an 86% reduction in cases for post-exposure prophylaxis, Hayden et al. show a 33 hour reduction in the time to alleviation of symptoms for treatment within 24 hours and a reduction of 13 hours for treatment within 24-48 hours, and Kumar et al. report only 2.5 hours improvement for inpatient treatment.
Table 3. Studies of baloxavir marboxil for influenza show that early treatment is more effective.
Treatment delayResult
Post-exposure prophylaxis86% fewer cases49
<24 hours-33 hours symptoms50
24-48 hours-13 hours symptoms50
Inpatients-2.5 hours to improvement51
Figure 12 shows a mixed-effects meta-regression for efficacy as a function of treatment delay in COVID-19 studies from 161 treatments, showing that efficacy declines rapidly with treatment delay. Early treatment is critical for COVID-19.
Loading..
Figure 12. Early treatment is more effective. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 161 treatments.
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, for example as in López-Medina et al.
Efficacy may depend critically on the distribution of SARS-CoV-2 variants encountered by patients. Risk varies significantly across variants53, for example the Gamma variant shows significantly different characteristics54-57. Different mechanisms of action may be more or less effective depending on variants, for example the degree to which TMPRSS2 contributes to viral entry can differ across variants58,59.
Effectiveness may depend strongly on the dosage and treatment regimen.
The quality of medications may vary significantly between manufacturers and production batches, which may significantly affect efficacy and safety. Williams et al. analyze ivermectin from 11 different sources, showing highly variable antiparasitic efficacy across different manufacturers. Xu et al. analyze a treatment from two different manufacturers, showing 9 different impurities, with significantly different concentrations for each manufacturer.
The use of other treatments may significantly affect outcomes, including supplements, other medications, or other interventions such as prone positioning. Treatments may be synergistic62-78, therefore efficacy may depend strongly on combined treatments.
Across all studies there is a strong association between different outcomes, for example improved recovery is strongly associated with lower mortality. However, efficacy may differ depending on the effect measured, for example a treatment may be more effective against secondary complications and have minimal effect on viral clearance.
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 early treatment is very effective. All meta analyses combine heterogeneous studies, varying in population, variants, and potentially all factors above, and therefore may obscure efficacy by including studies where treatment is less effective. Generally, we expect the estimated effect size from meta analysis to be less than that for the optimal case. 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. While we present results for all studies, we also present treatment time and individual outcome analyses, which may be more informative for specific use cases.
This section validates the use of pooled effects for COVID-19, which enables earlier detection of efficacy, however pooled effects are no longer required for chlorhexidine as of April 2025. Efficacy is now known based on specific outcomes. Efficacy based on specific outcomes was delayed by 17.3 months compared to using pooled outcomes.
For COVID-19, delay in clinical results translates into additional death and morbidity, as well as additional economic and societal damage. Combining the results of studies reporting different outcomes is required. There may be no mortality in a trial with low-risk patients, however a reduction in severity or improved viral clearance may translate into lower mortality in a high-risk population. Different studies may report lower severity, improved recovery, and lower mortality, and the significance may be very high when combining the results. "The studies reported different outcomes" is not a good reason for disregarding results. Pooling the results of studies reporting different outcomes allows us to use more of the available information. Logically we should, and do, use additional information when evaluating treatments—for example dose-response and treatment delay-response relationships provide additional evidence of efficacy that is considered when reviewing the evidence for a treatment.
We present both specific outcome and pooled analyses. In order to combine the results of studies reporting different outcomes we use the most serious outcome reported in each study, based on the thesis that improvement in the most serious outcome provides comparable measures of efficacy for a treatment. A critical advantage of this approach is simplicity and transparency. There are many other ways to combine evidence for different outcomes, along with additional evidence such as dose-response relationships, however these increase complexity.
Trials with high-risk patients may be restricted due to ethics for treatments that are known or expected to be effective, and they increase difficulty for recruiting. Using less severe outcomes as a proxy for more serious outcomes allows faster and safer collection of evidence.
For many COVID-19 treatments, a reduction in mortality logically follows from a reduction in hospitalization, which follows from a reduction in symptomatic cases, which follows from a reduction in PCR positivity. We can directly test this for COVID-19.
Analysis of the the association between different outcomes across studies from all 161 treatments we cover confirms the validity of pooled outcome analysis for COVID-19. Figure 13 shows that lower hospitalization is very strongly associated with lower mortality (p < 0.000000000001). Similarly, Figure 14 shows that improved recovery is very strongly associated with lower mortality (p < 0.000000000001). Considering the extremes, Singh et al. show an association between viral clearance and hospitalization or death, with p = 0.003 after excluding one large outlier from a mutagenic treatment, and based on 44 RCTs including 52,384 patients. Figure 15 shows that improved viral clearance is strongly associated with fewer serious outcomes. The association is very similar to Singh et al., with higher confidence due to the larger number of studies. As with Singh et al., the confidence increases when excluding the outlier treatment, from p = 0.00000011 to p = 0.0000000048.
Loading..
Figure 13. Lower hospitalization is associated with lower mortality, supporting pooled outcome analysis.
Loading..
Figure 14. Improved recovery is associated with lower mortality, supporting pooled outcome analysis.
Loading..
Figure 13. Improved viral clearance is associated with fewer serious outcomes, supporting pooled outcome analysis.
Currently, 53 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. 90% of these have been confirmed with one or more specific outcomes, with a mean delay of 4.8 months. When restricting to RCTs only, 55% of treatments showing statistically significant efficacy/harm with pooled effects have been confirmed with one or more specific outcomes, with a mean delay of 7.3 months. Figure 16 shows when treatments were found effective during the pandemic. Pooled outcomes often resulted in earlier detection of efficacy.
Loading..
Loading..
Figure 16. The time when studies showed that treatments were effective, defined as statistically significant improvement of ≥10% from ≥3 studies. Pooled results typically show efficacy earlier than specific outcome results. Results from all studies often shows efficacy much earlier than when restricting to RCTs. Results reflect conditions as used in trials to date, these depend on the population treated, treatment delay, and treatment regimen.
Pooled analysis could hide efficacy, for example a treatment that is beneficial for late stage patients but has no effect on viral clearance may show no efficacy if most studies only examine viral clearance. In practice, it is rare for a non-antiviral treatment to report viral clearance and to not report clinical outcomes; and in practice other sources of heterogeneity such as difference in treatment delay is more likely to hide efficacy.
Analysis validates the use of pooled effects and shows significantly faster detection of efficacy on average. However, as with all meta analyses, it is important to review the different studies included. We also present individual outcome analyses, which may be more informative for specific use cases.
Preclinical studies have also shown efficacy with chlorhexidine for influenza A virus32 and respiratory syncytial virus32.
Analysis of short-term changes in viral load using PCR may not detect effective treatments because PCR is unable to differentiate between intact infectious virus and non-infectious or destroyed virus particles. For example Tarragó‐Gil, Alemany perform RCTs with cetylpyridinium chloride (CPC) mouthwash that show no difference in PCR viral load, however there was significantly increased detection of SARS-CoV-2 nucleocapsid protein, indicating viral lysis. CPC inactivates SARS-CoV-2 by degrading its membrane, exposing the nucleocapsid of the virus. To better estimate changes in viral load and infectivity, methods like viral culture that can differentiate intact vs. degraded virus are preferred.
Studies to date use a variety of administration methods to the respiratory tract, including nasal and oral sprays, nasal irrigation, oral rinses, and inhalation. Table 4 shows the relative efficacy for nasal, oral, and combined administration. Combined administration shows the best results, and nasal administration is more effective than oral. Precise efficacy depends on the details of administration, e.g., mucoadhesion and sprayability for sprays.
Table 4. Respiratory tract administration efficacy. Relative efficacy of nasal, oral, and combined nasal/oral administration for treatments administered directly to the respiratory tract, based on studies for astodrimer sodium, chlorhexidine, cetylpyridinium chloride, chlorpheniramine, iota-carrageenan, hydrogen peroxide, nitric oxide, povidone-iodine, plasma-activated water, alkalinization, phthalocyanine, sodium bicarbonate, pHOXWELL, and sentinox. Results show random effects meta analysis for the most serious outcome reported for all prophylaxis and early treatment studies.
Nasal/oral administration to the respiratory tract ImprovementStudies
Oral spray/rinse38% [25‑49%]11
Nasal spray/rinse58% [49‑65%]20
Nasal & oral91% [74‑97%]7
Nasopharyngeal/oropharyngeal treatments may not be highly selective. In addition to inhibiting or disabling SARS-CoV-2, they may also be harmful to beneficial microbes, disrupting the natural microbiome in the oral cavity and nasal passages that have important protective and metabolic roles82. This may be especially important for prolonged use or overuse. Table 5 summarizes the potential for common nasopharyngeal/oropharyngeal treatments to affect the natural microbiome.
Table 5. Potential effect of treatments on the nasophyrngeal/oropharyngeal microbiome.
TreatmentMicrobiome disruption potentialNotes
Iota-carrageenanLowPrimarily antiviral, however extended use may mildly affect the microbiome
Nitric OxideLow to moderateMore selective towards pathogens, however excessive concentrations or prolonged use may disrupt the balance of bacteria
AlkalinizationModerateIncreases pH, negatively impacting beneficial microbes that thrive in a slightly acidic environment
Cetylpyridinium ChlorideModerateQuaternary ammonium broad-spectrum antiseptic that can disrupt beneficial and harmful bacteria
PhthalocyanineModerate to highPhotodynamic compound with antimicrobial activity, likely to affect the microbiome
ChlorhexidineHighPotent antiseptic with broad activity, significantly disrupts the microbiome
Hydrogen PeroxideHighStrong oxidizer, harming both beneficial and harmful microbes
Povidone-IodineHighPotent broad-spectrum antiseptic harmful to beneficial microbes
Publishing is often biased towards positive results, however evidence suggests that there may be a negative bias for inexpensive treatments for COVID-19. Both negative and positive results are very important for COVID-19, media in many countries prioritizes negative results for inexpensive treatments (inverting the typical incentive for scientists that value media recognition), and there are many reports of difficulty publishing positive results83-86. For chlorhexidine, there is currently not enough data to evaluate publication bias with high confidence.
Pharmaceutical drug trials often have conflicts of interest whereby sponsors or trial staff have a financial interest in the outcome being positive. Chlorhexidine for COVID-19 lacks this because it is off-patent, has multiple manufacturers, and is very low cost. In contrast, most COVID-19 chlorhexidine trials have been run by physicians on the front lines with the primary goal 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, and ensuring accurate dosing), not all chlorhexidine trials represent the optimal conditions for efficacy.
Summary statistics from meta analysis necessarily lose information. As with all meta analyses, studies are heterogeneous, with differences in treatment delay, treatment regimen, patient demographics, variants, conflicts of interest, standard of care, and other factors. We provide analyses for specific outcomes and by treatment delay, and we aim to identify key characteristics in the forest plots and summaries. Results should be viewed in the context of study characteristics.
Some analyses classify treatment based on early or late administration, as done here, while others distinguish between mild, moderate, and severe cases. 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.
Details of treatment delay per patient is often not available. For example, a study may treat 90% of patients relatively early, but the events driving the outcome may come from 10% of patients treated very late. Our 5 day cutoff for early treatment may be too conservative, 5 days may be too late in many cases.
Comparison across treatments is confounded by differences in the studies performed, for example dose, variants, and conflicts of interest. Trials with conflicts of interest may use designs better suited to the preferred outcome.
In some cases, the most serious outcome has very few events, resulting in lower confidence results being used in pooled analysis, however the method is simpler and more transparent. This is less critical as the number of studies increases. Restriction to outcomes with sufficient power may be beneficial in pooled analysis and improve accuracy when there are few studies, however we maintain our pre-specified method to avoid any retrospective changes.
Studies show that combinations of treatments can be highly synergistic and may result in many times greater efficacy than individual treatments alone62-78. Therefore standard of care may be critical and benefits may diminish or disappear if standard of care does not include certain treatments.
This real-time analysis is constantly updated based on submissions. Accuracy benefits from widespread review and submission of updates and corrections from reviewers. Less popular treatments may receive fewer reviews.
No treatment or intervention is 100% available and effective for all current and future variants. Efficacy may vary significantly with different variants and within different populations. All treatments have potential side effects. Propensity to experience side effects may be predicted in advance by qualified physicians. We do not provide medical advice. Before taking any medication, consult a qualified physician who can compare all options, provide personalized advice, and provide details of risks and benefits based on individual medical history and situations.
2 of 5 studies combine treatments. The results of chlorhexidine alone may differ. 1 of 3 RCTs use combined treatment. Currently all studies are peer-reviewed.
Multiple reviews cover chlorhexidine for COVID-19, presenting additional background on mechanisms and related results, including87-89.
Additional preclinical or review papers suggesting potential benefits of chlorhexidine for COVID-19 include96-98. We have not reviewed these studies in detail.
SARS-CoV-2 infection and replication involves a complex interplay of 100+ host and viral proteins and other factors23-30, providing many therapeutic targets. Over 9,000 compounds have been predicted to reduce COVID-19 risk31, either by directly minimizing infection or replication, by supporting immune system function, or by minimizing secondary complications. Figure 17 shows an overview of the results for chlorhexidine in the context of multiple COVID-19 treatments, and Figure 18 shows a plot of efficacy vs. cost for COVID-19 treatments.
Loading..
Figure 17. Scatter plot showing results within the context of multiple COVID-19 treatments. Diamonds shows the results of random effects meta-analysis. 0.6% of 9,000+ proposed treatments show efficacy99.
Loading..
Loading..
Figure 18. Efficacy vs. cost for COVID-19 treatments.
SARS-CoV-2 infection typically starts in the upper respiratory tract. Progression may lead to cytokine storm, pneumonia, ARDS, neurological issues, organ failure, and death. Stopping replication in the upper respiratory tract, via early or prophylactic nasopharyngeal/oropharyngeal treatment, can avoid the consequences of progression to other tissues, and avoid the requirement for systemic treatments with greater potential for side effects.
Studies to date show that chlorhexidine is an effective treatment for COVID-19. Significantly lower risk is seen for progression, cases, and viral clearance. 5 studies from 5 independent teams in 5 countries show significant benefit. Meta analysis using the most serious outcome reported shows 71% [57‑80%] lower risk. Results are similar for Randomized Controlled Trials.
Currently there is limited data, with only 722 patients in trials to date.
Chlorhexidine may be detrimental to the natural microbiome, raising concern for side effects, especially with prolonged or excessive use.
Viral load, culture 96% Improvement Relative Risk Viral load, PCR 69% Chlorhexidine  Bonn et al.  EARLY TREATMENT Does chlorhexidine + CPC reduce short-term viral load for COVID-19? Prospective study of 62 patients in Germany (Jan - Feb 2022) Improved viral clearance with chlorhexidine + CPC (p=0.031) c19early.org Bonn et al., J. Dental Research, March 2023 Favorschlorhexidine Favorscontrol 0 0.5 1 1.5 2+
Prospective study of 61 COVID+ patients showing a significant reduction in viral load and infectivity with a mouthwash containing 0.05% cetylpyridinium chloride (CPC) and 0.05% chlorhexidine digluconate (CHX). Mouthwash containing 0.9% NaCl showed a trend towards lower infectivity. The study only analyzes short-term changes in viral load 30 minutes after treatment. Submit Corrections or Updates.
Viral clearance, all patients 75% Improvement Relative Risk Viral clearance, spray and.. 85% Viral clearance, rinse only 60% Chlorhexidine  Huang et al.  LATE TREATMENT  RCT Is late treatment with chlorhexidine beneficial for COVID-19? RCT 294 patients in the USA (May - December 2020) Improved viral clearance with chlorhexidine (p<0.000001) c19early.org Huang et al., J. Medical Virology, Apr 2021 Favorschlorhexidine Favorscontrol 0 0.5 1 1.5 2+
RCT 294 hospitalized patients in the USA, showing faster oropharyngeal viral clearance with chlorhexidine. Results were better with a combination of oropharyngeal rinse and posterior oropharyngeal spray compared with the rinse alone. Submit Corrections or Updates.
129 patient chlorhexidine early treatment RCT with results not reported over 3 years after completion. Submit Corrections or Updates.
Olfactory or gustatory dy.. 79% OGD Improvement Relative Risk VAS olfactory severe 97% VAS gustatory severe 95% TSS severe 83% Chlorhexidine  Jing et al.  EARLY TREATMENT  DB RCT Is early treatment with chlorhexidine + budesonide and saline beneficial for COVID-19? Double-blind RCT 260 patients in China (May - June 2022) Lower progression (p<0.0001) and severe cases (p<0.0001) c19early.org Jing et al., QJM: An Int. J. Medicine, Nov 2023 Favorschlorhexidine Favorscontrol 0 0.5 1 1.5 2+
RCT 379 mild COVID-19 cases showing significantly lower prevalence and severity of olfactory and gustatory dysfunction with budesonide nasal spray, chlorhexidine mouthwash, and saline nasal irrigation. The control group received no intervention, the saline group received saline nasal irrigation plus saline nasal spray and mouthwash, and the drug group received saline nasal irrigation plus budesonide nasal spray and chlorhexidine mouthwash. Saline nasal irrigation plus nasal spray and mouthwash were administered once and four times daily, respectively. Both treatment groups had significantly lower prevalence and severity olfactory and gustatory dysfunction. Prevalence was lower for the drug vs. saline group, without statistical significance. Submit Corrections or Updates.
Mean total symptoms 61% Improvement Relative Risk Mean week 1 symptoms 82% Mean week 2 symptoms 56% Mean week 3 symptoms 11% Mean week 4 symptoms 95% Case 57% Chlorhexidine  Karami et al.  Prophylaxis  DB RCT Is prophylaxis with chlorhexidine beneficial for COVID-19? Double-blind RCT 76 patients in Iran (July - October 2022) Lower progression (p=0.041) and fewer cases (p=0.027) c19early.org Karami et al., Iranian J. Nursing and .., Jan 2024 Favorschlorhexidine Favorscontrol 0 0.5 1 1.5 2+
RCT 116 healthcare workers comparing 0.2% chlorhexidine mouthwash (n=36), 7.5% sodium bicarbonate mouthwash (n=40), and placebo (n=40) twice daily for 2 weeks, with symptoms followed for 4 weeks. There were lower symtoms and cases in both treatment groups, with statistical significance for chlorhexidine only. The treatments were stopped after two weeks, results may be better with continued use, more frequent use, and with the addition of nasal use. Submit Corrections or Updates.
245 participant chlorhexidine + PVP-I prophylaxis RCT with results not reported over 2 years after completion. Submit Corrections or Updates.
48 patient chlorhexidine early treatment RCT with results not reported over 3 years after completion. Submit Corrections or Updates.
Viral load 54% Improvement Relative Risk Chlorhexidine  Sulistyani et al.  EARLY TREATMENT Is early treatment with chlorhexidine beneficial for COVID-19? Prospective study of 30 patients in Indonesia Improved viral clearance with chlorhexidine (p=0.001) c19early.org Sulistyani et al., Dental and Medical .., Apr 2025 Favorschlorhexidine Favorscontrol 0 0.5 1 1.5 2+
Prospective study of 45 COVID-19 patients showing improved viral clearance with chlorhexidine gluconate and povidone-iodine mouthwash use. Submit Corrections or Updates.
Estimated 90 patient chlorhexidine early treatment RCT with results not reported over 3 years after estimated completion. Submit Corrections or Updates.
We perform ongoing searches of PubMed, medRxiv, Europe PMC, ClinicalTrials.gov, The Cochrane Library, Google Scholar, Research Square, ScienceDirect, Oxford University Press, the reference lists of other studies and meta-analyses, and submissions to the site c19early.org. Search terms are chlorhexidine and COVID-19 or SARS-CoV-2. Automated searches are performed twice daily, with all matches reviewed for inclusion. All studies regarding the use of chlorhexidine for COVID-19 that report a comparison with a control group are included in the main analysis. 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 have preference. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms are not used, the next most serious outcome with one or more events is used. 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 outcomes are considered more important than viral test 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 little or no room for an effective treatment to do better, however faster recovery is valuable. 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 compute the relative risk when possible, or convert to a relative risk according to100. Reported confidence intervals and p-values were used when available, using adjusted values when provided. If multiple types of adjustments are reported propensity score matching and multivariable regression has preference over propensity score matching or weighting, which has preference over multivariable regression. Adjusted 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 1103. 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 (3.13.3) with scipy (1.15.3), pythonmeta (1.26), numpy (2.2.6), statsmodels (0.14.4), and plotly (6.0.1).
Forest plots are computed using PythonMeta104 with the DerSimonian and Laird random effects model (the fixed effect assumption is not plausible in this case) and inverse variance weighting. Results are presented with 95% confidence intervals. Heterogeneity among studies was assessed using the I2 statistic. Mixed-effects meta-regression results are computed with R (4.4.0) using the metafor (4.6-0) and rms (6.8-0) packages, and using the most serious sufficiently powered outcome. For all statistical tests, a p-value less than 0.05 was considered statistically significant. Grobid 0.8.2 is used to parse PDF documents.
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 effective47,48.
We received no funding, this research is done in our spare time. We have no affiliations with any pharmaceutical companies or political parties.
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://c19early.org/chxmeta.html.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
Bonn, 3/21/2023, prospective, Germany, peer-reviewed, 14 authors, study period 4 January, 2022 - 22 February, 2022, this trial uses multiple treatments in the treatment arm (combined with CPC) - results of individual treatments may vary, trial DRKS00027812. viral load, 95.8% lower, relative load 0.04, p = 0.03, treatment median 1.0 IQR 0.5 n=31, control median 24.0 IQR 153.3 n=31, inverted to make RR<1 favor treatment, relative infectious viral load, 30 min vs. baseline, CPC+CHX.
viral load, 69.2% lower, relative load 0.31, p = 0.04, treatment 31, control 31, relative PCR viral load, 30 min vs. baseline, CPC+CHX.
Jacox, 10/20/2021, Double Blind Randomized Controlled Trial, USA, trial NCT04584684 (history) (MOR). 129 patient RCT with results unknown and over 3 years late.
Jing, 11/21/2023, Double Blind Randomized Controlled Trial, China, peer-reviewed, 7 authors, study period 5 May, 2022 - 16 June, 2022, this trial uses multiple treatments in the treatment arm (combined with budesonide and saline) - results of individual treatments may vary, trial ChiCTR2200059651. olfactory or gustatory dysfunction, 79.2% lower, RR 0.21, p < 0.001, treatment 10 of 120 (8.3%), control 56 of 140 (40.0%), NNT 3.2, OGD.
VAS olfactory severe, 96.5% lower, RR 0.03, p < 0.001, treatment 0 of 120 (0.0%), control 15 of 140 (10.7%), NNT 9.3, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
VAS gustatory severe, 95.3% lower, RR 0.05, p = 0.001, treatment 0 of 120 (0.0%), control 11 of 140 (7.9%), NNT 13, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
TSS severe, 83.3% lower, RR 0.17, p = 0.07, treatment 1 of 120 (0.8%), control 7 of 140 (5.0%), NNT 24.
Mira, 1/8/2022, Double Blind Randomized Controlled Trial, placebo-controlled, trial NCT05543603 (history). 48 patient RCT with results unknown and over 3 years late.
Sulistyani, 4/30/2025, prospective, Indonesia, peer-reviewed, 8 authors. viral load, 54.2% lower, relative load 0.46, p = 0.001, treatment 15, control 15, relative increase in Ct value, day 5.
Xie, 2/28/2022, Double Blind Randomized Controlled Trial, placebo-controlled, trial NCT04931004 (history). Estimated 90 patient RCT with results unknown and over 3 years late.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
Huang, 4/30/2021, Randomized Controlled Trial, USA, peer-reviewed, median age 62.0, 2 authors, study period 20 May, 2020 - 15 December, 2020. risk of no viral clearance, 74.6% lower, RR 0.25, p < 0.001, treatment 38 of 159 (23.9%), control 127 of 135 (94.1%), NNT 1.4, all patients, day 4.
risk of no viral clearance, 85.1% lower, RR 0.15, p < 0.001, treatment 13 of 93 (14.0%), control 75 of 80 (93.8%), NNT 1.3, oropharyngeal rinse and spray, day 4.
risk of no viral clearance, 59.9% lower, RR 0.40, p < 0.001, treatment 25 of 66 (37.9%), control 52 of 55 (94.5%), NNT 1.8, oropharyngeal rinse only, day 4.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
Karami, 1/9/2024, Double Blind Randomized Controlled Trial, Iran, peer-reviewed, 4 authors, study period July 2022 - October 2022, trial IRCT20220328054364N1. relative mean total symptoms, 61.0% better, RR 0.39, p = 0.04, treatment mean 1.8 (±3.67) n=36, control mean 4.62 (±7.37) n=40.
relative mean week 1 symptoms, 82.0% better, RR 0.18, p = 0.08, treatment mean 0.22 (±1.17) n=36, control mean 1.22 (±3.14) n=40.
relative mean week 2 symptoms, 56.0% better, RR 0.44, p = 0.13, treatment mean 0.66 (±2.05) n=36, control mean 1.5 (±2.63) n=40.
relative mean week 3 symptoms, 11.3% better, RR 0.89, p = 0.84, treatment mean 0.86 (±2.66) n=36, control mean 0.97 (±2.16) n=40.
relative mean week 4 symptoms, 94.6% better, RR 0.05, p = 0.048, treatment mean 0.05 (±0.23) n=36, control mean 0.92 (±2.58) n=40.
risk of case, 56.8% lower, RR 0.43, p = 0.03, treatment 7 of 36 (19.4%), control 18 of 40 (45.0%), NNT 3.9.
Keating, 6/30/2022, Randomized Controlled Trial, USA, this trial uses multiple treatments in the treatment arm (combined with PVP-I) - results of individual treatments may vary, trial NCT04478019 (history) (SHIELD). 245 patient RCT with results unknown and over 2 years late.
Viral infection and replication involves attachment, entry, uncoating and release, genome replication and transcription, translation and protein processing, assembly and budding, and release. Each step can be disrupted by therapeutics.
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Treatments and other interventions are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment or intervention is 100% available and effective for all current and future variants. 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. IMA and WCH provide treatment protocols.
  or use drag and drop   
Submit