March 28, 2022
U.S. Department of Labor
Occupational Safety and Health Administration
200 Constitution Avenue, NW
Washington, D.C. 20210
Re: Docket No. OSHA-2020-0004
To Whom It May Concern:
On behalf of the American Association of Oral and Maxillofacial Surgeons (AAOMS), the professional
association that represents more than 9,000 oral and maxillofacial surgeons (OMSs) in the United States,
we are pleased to provide comment on the Occupational Safety and Health Administration’s Emergency
Temporary Standard in response to the March 23, 2022, Federal Register notice. We commend OSHA for
its efforts throughout the pandemic to ensure safe conditions for our nation’s workers and theparticular concern the agency has shown for our nation’s healthcare personnel.
OMSs are surgically and medically trained dental specialists who treat conditions, defects, injuries andesthetic aspects of the mouth, teeth, jaws, neck and face. After earning a dental degree from anaccredited four-year dental school, OMSs complete a minimum of four years of hospital-based oral andmaxillofacial surgery residency training, which includes rotations in such areas as general surgery,anesthesia and clinical research. As the surgical branch of dentistry, our members provided frontline
response to address the needs of emergent dental patients during the pandemic.
Throughout the pandemic, our goal has been to ensure that dental patients are treated outside of theemergency room so our nation’s hospitals are free to respond to pandemic patients. These dental
emergencies – which can be life threatening if left untreated – include treatment of facial trauma,dental pain, abscesses and other pathology, as well as dental treatment required prior to critical medical
procedures. To treat these conditions, OMSs must work in close proximity to patients and perform
aerosol-generating procedures.
Early in the pandemic, the uncertainty surrounding how SARS-CoV-2 spread forced most dental practices– including OMS offices – to temporarily close. As we all learned more about the virus, we were able toimplement protocols that would protect not only our patients but our healthcare staff. This allowed us
to transition from the use of respirators – such as N95 masks – when treating all patients, to strategic
use based on patient vaccination status, clinical pre-operative testing and community transmission
rates.

OSHA
March 28, 2022
Page 2
A recent study from the Ohio State University (Attachment 1) supported this recommendation,
concluding that “when infection control measures are used, such as preoperative mouth rinses andintraoral high-volume evacuation, dental treatment is not a factor in increasing the risk for transmissionof SARS-CoV-2 in asymptomatic patients and that standard infection control practices are sufficiently
capable of protecting personnel and patients from exposure to potential pathogens.” 1 Due to this andother similar studies that indicate dental aerosolizing procedures are not at risk, AAOMS believes thatrather than utilizing respirators, the use of fluid resistant masks or mask covers, eye protection and faceshields provides adequate protection for the treatment of asymptomatic patients in the dental and OMS
office. AAOMS urges OSHA to consider this study’s findings and our position when finalizing the
emergency temporary standard and transitioning it to a permanent regulation.
On behalf of AAOMS, thank you for your consideration. For questions or additional information, pleasecontact Sandy Guenther, manager of state government affairs and advocacy engagement at 800-8226637, ext. 4388 or sguenther@aaoms.org.
Sincerely,

J. David Johnson Jr., DDSAAOMS President

Meethil AP, Saraswat S, Chaudhary PP, Dabdoub SM, Kumar PS. Sources of SARS-CoV-2 and Other
Microorganisms in Dental Aerosols. Journal of Dental Research. 2021;100(8):817-823.
doi:10.1177/00220345211015948
1

1015948

research-article2021

JDRXXX10.1177/00220345211015948Journal of Dental ResearchSARS-CoV-2 and Other Microorganisms in Dental Aerosols

Research Reports: ClinicalSources of SARS-CoV-2 and Other
Microorganisms in Dental Aerosols

Journal of Dental Research
﻿1­–7© International & American Associations
for Dental Research 2021
Article reuse guidelines:
https://doi.org/10.1177/00220345211015948
sagepub.com/journals-permissions
DOI: 10.1177/00220345211015948
journals.sagepub.com/home/jdr

A.P. Meethil1, S. Saraswat1, P.P. Chaudhary2, S.M. Dabdoub1 ,and P.S. Kumar1,3

Abstract
On March 16, 2020, 198,000 dentists in the United States closed their doors to patients, fueled by concerns that aerosols generated
during dental procedures are potential vehicles for transmission of respiratory pathogens through saliva. Our knowledge of theseaerosol constituents is sparse and gleaned from case reports and poorly controlled studies. Therefore, we tracked the origins of
microbiota in aerosols generated during ultrasonic scaling, implant osteotomy, and restorative procedures by combining reverse
transcriptase quantitative polymerase chain reaction (to identify and quantify SARS-CoV-2) and 16S sequencing (to characterize theentire microbiome) with fine-scale enumeration and source tracking. Linear discriminant analysis of Bray-Curtis dissimilarity distances
revealed significant class separation between the salivary microbiome and aerosol microbiota deposited on the operator, patient,assistant, or the environment (P < 0.01, analysis of similarities). We also discovered that 78% of the microbiota in condensate could betraced to the dental irrigant, while saliva contributed to a median of 0% of aerosol microbiota. We also identified low copy numbersof SARS-CoV-2 virus in the saliva of several asymptomatic patients but none in aerosols generated from these patients. Together, thebacterial and viral data encourage us to conclude that when infection control measures are used, such as preoperative mouth rinses andintraoral high-volume evacuation, dental treatment is not a factor in increasing the risk for transmission of SARS-CoV-2 in asymptomaticpatients and that standard infection control practices are sufficiently capable of protecting personnel and patients from exposure topotential pathogens. This information is of immediate urgency, not only for safe resumption of dental treatment during the ongoing
COVID-19 pandemic, but also to inform evidence-based selection of personal protection equipment and infection control practices at
a time when resources are stretched and personal protection equipment needs to be prioritized.
Keywords: ultrasonics, dental implants, irrigant, saliva, microbiota, DNA sequence analysis

Introduction
On March 11, 2020, the World Health Organization declared
coronavirus disease 2019 (COVID-19) a pandemic. On March
16, the American Dental Association responded with a recommendation that dental offices refrain from providing nonemergency services, resulting in 198,000 dentists closing theirdoors to patients in the United States alone. Nine months later,
restrictions on the use of key instruments and procedures arestill in place, fueling concern in providers and patients alike(Zhao et al. 2020). This is despite the fact that 3.5 billion
individuals experience caries, periodontitis, or oral cancer(Kassebaum et al. 2014)—diseases that not only impede essential functions, such as speech and mastication (National
Institute of Dental and Craniofacial Research 2014), but canalso influence the course and outcomes of diabetes, atherosclerosis, and rheumatoid arthritis (D’Aiuto et al. 2005; de Pablo
et al. 2009; Tonetti et al. 2013). Indeed, emerging evidence
suggests that untreated periodontitis might increase the risk fordeveloping severe forms of COVID-19 (Gupta and Sahni
2020; Pitones-Rubio et al. 2020).
Regulators and health authorities based this guidancelargely on literature that aerosols generated during medical
procedures, such as intubation/extubation, bronchoscopy, ventilation, and airway suctioning, can transmit infections (Davies

et al. 2009; Judson and Munster 2019; Centers for Disease
Control and Prevention 2020). Although microorganisms havebeen identified in dental aerosols (Grenier 1995; Harrel et al.
1998), our recent review found no information regarding their
origins (Kumar and Subramanian 2020). Therefore, there is anurgent need to inform infection control science by definitively
identifying the source of bacteria and viruses in aerosolgenerating dental procedures (AGDPs).
We combined a rigorous clinical study with microbiomics
and robust ecologic statistics to test the hypothesis thatmicroorganisms from AGDPs are of nonsalivary origin. This

1

Division of Periodontology, College of Dentistry, The Ohio State
University, Columbus, OH, USA
2
Laboratory of Clinical Immunology and Microbiology, National Instituteof Allergy and Infectious Diseases, National Institutes of Health,Rockville, MD, USA
3James Cancer Center, The Ohio State University, Columbus, OH, USA
A supplemental appendix to this article is available online.
Corresponding Author:
P.S. Kumar, Division of Periodontology, College of Dentistry, The Ohio
State University, 4111 Postle Hall, 305, W 12th Avenue, Columbus, OH
43210, USA.
Email: kumar.83@osu.edu

2Journal of Dental Research 00(0)enabled us to fill a critical gap in our knowledge and provide
urgently needed information for appropriately apportioning
our already stretched resources and guiding best practices for
infection control during the COVID-19 pandemic and beyond.

shields of the operator and assistant, the patient’s chest, and anarea 6 ft distant from the site of operation (“environment”).

Methods

Investigators conducting the analyses were blinded to thesource of samples. An RNA extraction–free dual-plexed
reverse transcriptase quantitative polymerase chain reaction
method for SARS-CoV-2 detection (SalivaDirect version 5)
was used according to the developers’ instructions (Vogels
et al. 2020). Briefly, 50 µL of homogenized saliva was mixed
with 2 µL of 50-mg/mL proteinase K, and 5 µL was used in a
20-µL reaction containing FAM-labeled primers and probes
targeting SARS-CoV-2 N1 and N2 and amplified for 44 cycles
in triplicate reactions. RNA from TRIzol-inactivated virus(obtained from Dr. Wang of The Ohio State University) wasused as positive control and to generate standard curves.

Ethics Statement
This study was approved by the institutional review board of
The Ohio State University (protocol 2020H0155) and carriedout according to the approved guidelines and in accordancewith the STROBE guidelines (Strengthening the Reporting ofObservational Studies in Epidemiology) for human observational investigations.

Participant Selection and Recruitment
Informed consent was obtained from 28 individuals seeking
dental treatment in the College of Dentistry of The Ohio State
University between May 4 and July 10, 2020. Exclusion criteria were age <18 y, current pregnancy, requirement for antibiotics prior to dental therapy, self-reported HIV or COVID-19
history, COVID-19–like symptoms since January 2020, andantibiotic therapy within 3 mo of sample collection. The sample size was based on previous evidence from in vitro andclinical studies on aerosol spread (King et al. 1997; Muzzin
et al. 1999; Nulty et al. 2020; Allison et al. 2021) during scaling and restorative procedures.

Operating Conditions
The AGDPs were dental implants, restorative procedures withhigh-speed handpieces, and ultrasonic scaling and were delivered by 5 operators and assistants in 2 enclosed operatories
measuring 10.5 × 10 × 12 ft, with 6-exchange/min ventilation.
Since aerosols are generated during normal physiologic activity, the operator, assistant, and sample collector wore N95
masks during the entire period to reduce microorganisms fromextraneous sources. High-volume intraoral evacuators (meansuction capacity, 7.1 L/min; range, 6.6 to 7.4 L/min) were usedthroughout the AGDPs. Magnetostrictive ultrasonic scalers
were used at a water flow of 19.3 mL/min. Implant osteotomies
were performed at a flow rate of 30 mL/min. A high-speed
handpiece with a single coolant port and flow rate of 23 mL/
min was used for restorative procedures. Twenty-three individuals used a preprocedural rinse of 1% hydrogen peroxide(30 mL for 1 min), and 5 who underwent scaling did not use therinse.

Sample Collection
Prior to the procedure, 1 mL of unstimulated saliva and irrigant
from the dental (or implant) unit was collected in tubes containing RNA stabilizer (RNALater; Oragene). At 30 min following the procedure, condensate was collected from the face

Virus Identification

Sequencing and Analysis Pipeline
DNA was isolated from 100 µL of the sample with a Qiagen
MiniAmp Kit, after a 90-min incubation with lysozyme (2 mg/
mL; Thermo Fisher Scientific). V1 to V3 and V4 to V5 (Kumar
et al. 2011) regions of the 16S rDNA were sequenced on the
Miseq system (2 × 250 bp). Negative and positive controls(defined culture mixture) were used in all runs. Ampliconsequence variants (ASVs) were inferred with the DADA2 version 1.16 pipeline (Callahan et al. 2016). Sequences were truncated on the basis of quality plots and filtered, dereplicated,and denoised with standard parameters, following which chimeras were identified and removed. Paired ends of denoised
sequences were then merged. To be retained in the data set, thesequence had to be detected at least once in at least 5% of thesamples. ASVs were assigned taxonomic identity with naive
Bayes classifiers (QIIME2 q2-feature-classifier; Caporaso
et al. 2010) trained for each primer pair by extracting the corresponding hypervariable region from the SILVA database (asof November 12, 2020; Quast et al. 2013).

Controls
We used multiple internal controls in experimental design aswell as analysis to validate these results. As a first level of control, we chose the same irrigant (dental unit water line) thatpassed through 2 different devices operating on 2 different
principles (high-speed handpiece and ultrasonic scaler). We
then selected a second therapeutic option, where a different
irrigant source (saline) flows through a similar type of device(implant handpiece). By doing so, we controlled for the type ofdevice as well as the type of coolant. In an effort to separate
environmental bacteria found normally in water and aerosols
from reagent contaminants, we subtracted the sequences foundin our negative controls from samples. The negative controls
were sterile Petri dishes opened by the sample collector in theclinic environment before the patient, operator, or assistantentered it and subjected to DNA isolation and polymerase

SARS-CoV-2 and Other Microorganisms in Dental Aerosols

A

3

B

C
Assistant
Environment
Operator
Patient
SalivaAssistant
Environment
Operator
Patient
Salivap = 0.007

D

Assistant
Environment
Operator
Patient
Salivap = 0.001

E

F
Assistant
Environment
Operator
Patient
SalivaAssistant
Environment
Operator
Patient
Salivap = 0.001

Assistant
Environment
Operator
Patient
Salivap = 0.02

Figure 1. Differences in beta diversity between saliva and aerosol deposited on the operator, assistant, patient and the clinic environment. Linear
discriminant analysis of Bray-Curtis dissimilarity distances are shown. Two hypervariable regions of the 16S rRNA gene (V1 to V3 and V4 to V5) weresequenced and analyzed separately. Amplicon sequence variants (ASVs) generated from V1-V3 (A–C), and V4-V5 regions (D–F) are shown. Samples
were acquired during (A, D) implant surgery, (B, E) ultrasonic scaling, and (C, F) restorative procedures. Saliva demonstrated significant clustering fromall aerosol samples irrespective of procedure (P < 0.05, Dunn test for joint ranking).

chain reaction amplification in the same manner as the samples. It is well established that the hypervariable region that issequenced can be a source of bias in determining the composition of the microbiome (Kumar et al. 2011). To overcome this,we used 2 primer pairs targeting 2 hypervariable regions andinducted them into separate sequence analysis pipelines.

Statistical Analysis
ASVs were used to compute alpha diversity (within group) andbeta diversity (between group). As an initial step, the negative
controls were used to rarefy each data set. However, thesequencing depth still varied among the samples by a magnitude of 100 in some cases, especially between saliva and environmental condensate. Since current evidence does not support
rarefying the microbiome to compensate for sequencing effort(McMurdie and Holmes 2014), we used cumulative sum scaling normalization from the Bioconductor package metagenomeSeq. Linear discriminant analysis (LDA) was performed
with the MASS package for R. The input for LDA was a matrixof variance-stabilized (arc-sin square root transformed) relative abundances of ASVs (Shchipkova et al. 2010). MASS:lda
provided singular value decomposition values, which wereused to calculate the percentage variance explained in eachdimension. The Dunn test with joint ranking was used to test
significance of LDA clustering. SourceTracker version 0.9.5(Knights et al. 2011) was applied to identify the source of
microorganisms. Saliva and irrigant were designated as possible sources, and the operator, assistant, patient, and ambientenvironment were set as targets. Data sets were filtered toremove ASVs that were not present in at least 1% of samples.
The following default parameters were used for analysis: rarefaction depth, 1,000; burn-in, 100; restart, 10; and alpha(0.001) and beta (0.01) Dirichlet hyperparameters.

Results
A total of 4,500,063 classifiable sequences representing 22,013
ASVs were used for microbial analysis. We began by characterizing the microbiota in saliva and the aerosol deposited on
the operator, assistant, patient, and environment with anincreasingly granular top-down approach. We found significant group separation between the salivary and aerosol microbiomes irrespective of the type of aerosol-generating procedure(P < 0.001, Dunn method for joint ranking of Bray-Curtis dissimilarity distances; Fig. 1, Appendix Table 1). By contrast, nosuch clustering was demonstrable among the aerosol depositedon the operator, assistant, patient, and environment. We thenexplored the abundances of individual taxa in the condensate
generated from each procedure. Irrespective of the procedureor the area of deposition, 70% of the microbial abundance wasattributable to 2 ASVs that mapped to uncultured
Vulcaniibacteria. These ASVs were also the predominant taxa
in the irrigants. Salivary bacteria, when present, accounted for
0.1% to 1.2% of the microbial abundance of aerosol.
Source-tracking analysis revealed that, irrespective of theAGDP, microbiota from irrigants contributed to a median 78%
of the microbiota in condensate (range, 2.5% to 100%; Fig. 2),

4

Journal of Dental Research 00(0)Figure 2. Source of microorganisms in aerosols generated during dental procedures. The relative contributions of saliva, irrigant fluid and unknown
sources to the microbial composition of the condensate deposited on the assistant (A), environment (B), operator (C), and patient (D) are shown.
The proportions were estimated using SourceTracker. For each subject, irrigant and saliva were designated as potential sources, and the operator,
assistant, patient and the ambient environment were set as targets. Datasets were filtered to remove taxa that were not present in at least 1% ofsamples. Default parameters (rarefaction depth 1000, burn-in 100, restart 10, alpha [0.001] and beta [0.01] dirichlet hyperparameter) were used foranalysis.

while saliva contributed to a median 0% (range, 0% to 82%).
On average, 20% of the microbiota could not be attributed toeither source (range, 0% to 90%). Salivary bacteria weredetectable in the condensate in only 8 participants out of the
28. Of these, 5 had not used a preprocedural rinse. In these 8
cases, the patient’s chest was the most frequent site of deposition (P < 0.05, chi-square test). LDA and SourceTracker
revealed similar trends for ASVs generated from V1 to V3 andV4 to V5, indicating that our findings were robust againstsequencing targets (Fig. 1).
We then investigated if aerosol dispersion of SARS-CoV-2
virus followed the same pattern, and it was identified in thesaliva of 19 participants, with a viral load between 27 and912 copies/mL. The virus was undetectable in the condensate
on the operator, assistant, patient, or environment in any ofthese cases (Table).

Discussion
The impetus for this study came from our recent review of theliterature on aerosols generated during dental procedures(Kumar and Subramanian 2020). We found that while several
investigations measured the radius of contamination following
AGDPs and demonstrated the presence of microbiota in thesecontaminated areas (Grenier 1995; Harrel et al. 1998; RiveraHidalgo et al. 1999; Petti and Vitali 2017; Kobza et al. 2018;
Jain et al. 2020), few characterized the types of microorganisms, and none identified their source. Understanding thesources of microbial bioload in aerosols is of immediateurgency, not only for infection control in dental operatories
during the COVID-19 pandemic, but also to inform best practices in aerosol reduction, mitigation, and abatement in thelong term. To the best of our knowledge, this study sets thestage for future work on risk of disease transmission among
dental health care workers and patients.

We deliberately elected to employ a passive air-sampling
methodology over other aerosol-harvesting methods (Grecoand Lai 2008; Verreault et al. 2008; O’Neil et al. 2017), sincedental procedures generate a variety of airborne particles,
ranging from spatter and particulate matter to aerosolized
microorganisms, any of which could pose a health hazard topatient and personnel. Our method allowed us to collect everything that was generated during the AGDP as well as everything that settled on the surfaces during the following 30 min.
This method has been widely used in similar studies, since it isreflective of events that occur in a treatment session (Bentley
et al. 1994; Bennett et al. 2000; Hallier et al. 2010).
This study was conducted at the height of the COVID-19
pandemic, and patients were inducted into the study based onpresentation for treatment to the dental clinics. We did not do a
COVID-19 test before starting the study because the primers
and probes had not been optimized when we began our recruitment. An extensive review of the literature revealed wide heterogeneity in sample size, with a minimum of 3 (Bentley et al.
1994) and a maximum of 20 (Serban et al. 2013; Singh et al.
2016). As a result, we included 15 participants for the ultrasonic group. During the same time frame, 10 patients who presented for implant therapy consented to participate. Thus, we
did an interim analysis to see if we could detect differencesamong the aerosols deposited on the various surfaces with 10
participants, and since there were significant differences, weused this as our endpoint. Three studies used 3 subjects/replicates per group for restorative procedures and to estimate
SARS-CoV-2 spread (van Doremalen et al. 2020; Allison et al.
2021) and therefore we included the restorative data from 3
subjects for completeness.
With all the procedural controls described in the methods,
we used an emergent bioinformatics approach to characterize
microbial assemblages: ASVs. Bioinformatics has traditionallysought to reduce large 16S sequence data sets into manageable

SARS-CoV-2 and Other Microorganisms in Dental Aerosols

5

Table. Levels of SARS-CoV-2 Virus in 28 Asymptomatic Patients with Noncontributory COVID-19 History and in Aerosols Generated during Dental
Procedures on Them.
SalivaID

Procedure

S1

Ultrasonic Generalized
moderate
periodontitis
Ultrasonic Periodontal health
Ultrasonic Periodontal health
Drilling Periodontal health
Ultrasonic Periodontal health
Ultrasonic Generalized
moderate
periodontitis
Implant Periodontal healthImplant Periodontal health
Ultrasonic Periodontal health
Ultrasonic Generalized
moderate
periodontitis
Implant Periodontal health
Ultrasonic Generalized
moderate
periodontitis
Ultrasonic Generalized
moderate
periodontitis
Ultrasonic Generalized
moderate
periodontitis
Implant Periodontal health
Ultrasonic Periodontal health
Ultrasonic Generalized
moderate
periodontitis
Ultrasonic Periodontal health
Drilling Periodontal healthImplant Periodontal healthImplant Periodontal healthImplant Periodontal healthImplant Periodontal healthImplant Periodontal healthImplant Periodontal health
Ultrasonic Periodontal healthImplant Periodontal health
Drilling Periodontal health

S10a
S11
S12
S13
S14
S16
S17
S18
S19
S2
S20
S21a
S22a
S23
S24
S26a
S27a
S28
S29
S3
S30
S4
S5
S6
S7
S8
S9

Operator

Assistant

Viral
Load

Average Ct

Viral
Load

Average Ct

40.00

ND

NA

NA

36.61
37.41
38.45
37.01
35.01

109.4
62.2
29.9
82.2
338.2

40
40
40
40
40

40.00
40.00
37.12
37.14

ND
ND
76.3
75.4

40.00
35.81

Environment

Patient

Viral
Load Average Ct

Viral
Load

NA

NA

NA

NA

NA

NA

ND
ND
ND
ND
ND

40
40
40
40
40

ND
ND
ND
ND
ND

40
40
40
40
40

ND
ND
ND
ND
ND

40
40
40
40
40

ND
ND
ND
ND
ND

NA
NA
40
40

NA
NA
ND
ND

NA
NA
40
40

NA
NA
ND
ND

NA
NA
40
40

NA
NA
ND
ND

NA
NA
40
40

NA
NA
ND
ND

ND
192.6

NA
40

NA
ND

NA
40

NA
ND

NA
40

NA
ND

NA
40

NA
ND

36.30

136.1

40

ND

40

ND

40

ND

40

ND

33.60

912.5

40

ND

40

ND

40

ND

40

ND

36.07
37.27
35.09

160.4
68.7
318.6

40
40
40

ND
ND
ND

40
40
40

ND
ND
ND

40
40
40

ND
ND
ND

40
40
40

ND
ND
ND

36.92
37.83
40.00
37.02
38.56
40.00
40.00
40.00
40.00
36.57
37.53

88.0
46.2
ND
81.9
27.7
ND
ND
ND
ND
112.3
57.2

40
40
NA
40
40
NA
NA
NA
NA
40
40

ND
ND
NA
ND
ND
NA
NA
NA
NA
ND
ND

40
40
NA
40
40
NA
NA
NA
NA
40
40

ND
ND
NA
ND
ND
NA
NA
NA
NA
ND
ND

40
40
NA
40
40
NA
NA
NA
NA
40
40

ND
ND
NA
ND
ND
NA
NA
NA
NA
ND
ND

40
40
NA
40
40
NA
NA
NA
NA
40
40

ND
ND
NA
ND
ND
NA
NA
NA
NA
ND
ND

Periodontal Status Average Ct

Viral
Average Ct LoadNA, aerosol sample not analyzed since the virus was not identified in the saliva samples; ND, not detected by reverse transcriptase quantitative
polymerase chain reaction at a detection threshold of 40 reaction cycles.
aPatient did not use a mouth rinse.

operational units, either by assigning them a taxonomic identity by comparison with a database or by identifying taxonindependent operational taxonomic units with a sequencesimilarity threshold (Huse et al. 2010). Both these approaches
fail to capture the immense diversity of environmental bacteria, many of which have not been assigned definitive taxonomic identities or entered into curated databases (Callahan
et al. 2017). The decision to use ASVs over operational taxonomic units was driven by the need for a finer scale resolutionof bacterial identities than could be provided by traditional
methods. This allowed us to exploit the immense sensitivity

built into the 16S rRNA gene and overcome the limitations
imposed by incomplete reference databases to better discriminate ecologic patterns (Prodan et al. 2020).
Our key discovery was that the irrigant fluid contributes tothe majority of the bioload in dental aerosols. Although this is
the first time that it is being reported, this is not entirely surprising, since we estimated that the irrigant flow dilutes thesaliva by 20- to 200-fold (assuming a salivary flow rate of 0.1
to 1.0 mL/min; Iorgulescu 2009). This discovery lends credence to previous studies on the transmission of legionellosis,
a waterborne infection, and pneumonia, from dental unit water

6
lines (Ricci et al. 2012; Petti and Vitali 2017). It also validates
recent reports of extremely low COVID-19 transmission
among dental personnel (Estrich et al. 2020).
One surprising finding was the discovery of microorganisms in the implant irrigant, which was sterile saline. To confirm that this was not an artifact, we sequenced the saline
before and after it passed through the implant handpiece anddiscovered a diverse microbiome in reusable handpieces.
However, since these handpieces were sterilized by autoclaving, we anticipate that these organisms are not viable.
The salivary SARS-CoV-2 load in our study is consistent
with previous reports of 102 to 106 copies/mL (Chau et al.
2020); however, none was detected in any aerosol. Interestingly,
participant 22 demonstrated the highest salivary viral load, andwhile bacteria of salivary origin could be identified on theoperator and environment, the virus was not detectable in thesame samples. This was true of those individuals with periodontitis and those who were periodontally healthy. The 20- to
200-fold dilution factor and our discovery that the irrigant, notthe saliva, is the primary and predominant source of airborne
microbiota might explain the absence of SARS-CoV-2 in aerosol. Preprocedural mouth rinsing serves to further reduce
potential salivary contaminants in aerosol.
In summary, we find sufficient evidence to reject our null
hypothesis that saliva is a potential source of disease transmission during AGDPs. Instead, we identify, for the first time, thatthe irrigant used in dental equipment is the primary and major
source of microorganisms during AGDPs. We also demonstrate that high-volume intraoral evacuators are highly effective in reducing salivary contamination of the surrounding
environment and that preprocedural mouth rinses consistently
reduce salivary microbial bioloads. Within the limitations of asmall sample size, we conclude that the risk for transmission of
SARS-CoV-2 and other respiratory pathogens from aerosolized saliva in dental operatories is moderately low and that current infection control practices are adequately robust to protect
personnel and patients alike.

Author Contributions
A.P. Meethil, S. Saraswat, P.P. Chaudhary, S.M. Dabdoub, P.S.
Kumar, contributed to conception, design, and data acquisition,
drafted and critically revised manuscript. All authors gave final
approval and agree to be accountable for all aspects of the work.

Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.

Funding
The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs
S.M. Dabdoub
https://orcid.org/0000-0002-1374-8347
P.S. Kumar
https://orcid.org/0000-0001-5844-1341

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