Aerosol generating procedures (AGPs) and their mitigation in international guidelines: Fallow time

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Bottom line

The recommendations for  fallow time in dental practice following an AGP appears almost random in its application across half of international guidelines. Its basic idea appears to be centred on a single precautionary principle based on simulation studies that are only weakly supported by evidence. Policy makers will need to take a more balanced approach when assessing the benefits and harms fallow time creates.

Introduction

With the publication of, ‘Aerosol Generating Procedures and their Mitigation in International Dental Guidance Documents – A Rapid Review’ by the  COVID-19 Dental Services Evidence Review (CoDER) Working Group (Clarkson et al., 2020) it was interesting to note their finding regarding fallow time for non Covid-19 patients:

  • 48% of the guidelines recommend having a fallow period.
  • The amount of time recommended varied (2-180 mins) between guidelines and also within guidelines, depending on environmental mitigation.
  • None of the fallow period recommendations referenced any scientific evidence.

The fallow period is the ‘time necessary for clearance of infectious aerosols after a procedure before decontamination of the surgery can begin’ (FGDP, 2020), and this has caused considerable discussion/stress amongst the dentist returning to practice after lockdown in the UK (BAPD, 2020, Heffernan, 2020).

The fallow times following an AGP for both Covid-19 negative patients and Covid-19 positive patients are presented in Figure 1 and Table 2 using the data from the CoDER rapid review:

Figure 1. Stacked bar chart representing fallow times for both Covid negative and positive patients

Fallow times

Since the fallow times are not normally distributed the median value was utilised and the 95% confidence limit approximated according to Hill (Hill, 1987).

Table 1. Median fallow time

Aerosol generating procedure Median Fallow time (mins)
Non Covid-19 patient 15 (95% CI: 15 to 30)
Covid-19 positive patient 20 (95% CI: 10 to 60)

Much of the theory around the need for fallow time is based on the aerosol transmission of the Coronavirus SARS-CoV-2 and the need to allow the aerosol to settle or be physically removed from the room via ventilation or filtration. Initially the WHO supported the idea that spread was predominantly caused by large droplets and contact (WHO, 2020a) but under increased lobbying from the scientific community to include airborne transmission as a significant factor (Morawska and Milton, 2020) the WHO amended their position (WHO, 2020b) on the 9th July.

The evidence for airborne transmission of Coronavirus SARS-CoV-2 is uncertain and mostly based on mathematical modelling (Buonanno et al., 2020) but where there has been limited observational data Hota and co-workers concluded that the virus was not well transmitted by the airborne route compared to measles, SARS-1 or Tuberculosis  (Hota et al., 2020).

The reason there is no strong scientific evidence for fallow time and airborne transmission is possibly because it is based on two conceptual arguments:

The Precautionary Principle (PP)

The precautionary principle (PP) states that if an action or policy has a suspected risk of causing severe harm to the public domain (affecting general health or the environment globally), the action should not be taken in the absence of scientific near-certainty about its safety. Under these conditions, the burden of proof about absence of harm falls on those proposing an action, not those opposing it (Taleb et al., 2020). The confusion at the moment is that the PP has been reversed and the action is evidence-based ‘normal/enhanced PPE and cross infection policy’ rather than the imposition of untested application of ‘fallow time’ in general practice.

The Independent Action Hypothesis (IAH)

The IAH states that each virion has an equal, non-zero probability of causing a fatal infection especially where airborne spread via small droplets (5μm) is the proposed method of transmission (Stadnytskyi et al., 2020). The reality of the IAH is that evidence supporting this theory is oversimplified and indirect, based mainly on small sample studies of moth larvae, and tobacco mosaic virus (Zwart et al., 2009, Cornforth et al., 2015).

Discussion

The main problem for anyone challenging the PP and IAH is having to prove a ‘near certainty of safety’ when there are many confounding factors in play, and the application of a ‘non-zero’ probability of a single inhaled virus causing death results in an ill-defined probability of risk (Taleb et al., 2020). Unfortunately, once the PP was been invoked designing challenge studies to create the scientific proof that the action is safe can be unethical in humans or experimentally impossible due to the effect of low viral prevalence in the community on statistical power.

One solution may be to rapidly assess the retrospective infection rates associated with the provision of dental care in those countries with extended fallow times and compare then to countries of similar demographics that do not have fallow time (Table 1). Policy makers may need to revise their current interpretation of the precautionary principle and IAH  based on the fact that in a pandemic situation there may be multiple interacting factors that can cause significantly more second and third order harm to the public domain than the virus itself.

 

Table 2. Countries with/without(bold) fallow time. ND – no data

Country Non Covid-19 Covid-19   Country Non Covid-19 Covid-19
Ireland 0 60 Burkina Faso ND ND
Poland 0 0 Canada ND 180
Bolivia 2 2 Chile ND ND
Philippines 5 5 Columbia ND ND
Dominican Republic 10 10 Costa Rica ND ND
Ecuador 10 10 Croatia ND ND
Brazil 15 15 Denmark ND ND
France 15 15 Finland ND 30
Italy 15 ND Greece ND ND
Morocco 15 15 Guatemala ND ND
Romania 15 15 Honduras ND ND
Spain 15 ND India ND ND
Switzerland 15 30 Kenya ND ND
Tunisia 15 ND Kosovo ND ND
UAE 20 ND Malaysia ND ND
Germany 30 30 Mexico ND ND
Malta 30 ND Mozambique ND ND
Ukraine 30 ND Myanmar ND ND
Estonia 45 ND Netherlands ND ND
Singapore 45 ND New Zealand ND 20
Argentina 60 60 Norway ND ND
Bulgaria 60 60 Panama ND ND
Montenegro 60 60 Peru ND ND
UK 60 60 Portugal ND ND
UK – NI 60 60 Slovakia ND ND
UK – Wales 60 60 Slovenia ND 10
China 90 ND South Africa ND ND
Paraguay 180 180 UK – Scotland ND ND
Australia ND ND Uruguay ND ND
Austria ND ND USA ND ND
Belgium ND ND Zimbabwe ND ND

 

References

BAPD. 2020. BAPD urges government to reconsider PPE requirements for dentistry [Online]. Dentistry. [Accessed 30th July 2020 ].

BUONANNO, G., STABILE, L. & MORAWSKA, L. 2020. Estimation of airborne viral emission: Quanta emission rate of SARS-CoV-2 for infection risk assessment. Environ Int, 141, 105794.

CLARKSON J, RAMSAY C, RICHARDS D, ROBERTSON C, & ACEVES-MARTINS M; on behalf of the CoDER Working Group (2020). Aerosol Generating Procedures and their Mitigation in International Dental Guidance Documents – A Rapid Review.

CORNFORTH, D. M., MATTHEWS, A., BROWN, S. P. & RAYMOND, B. 2015. Bacterial Cooperation Causes Systematic Errors in Pathogen Risk Assessment due to the Failure of the Independent Action Hypothesis. PLoS Pathog, 11, e1004775.

FGDP. 2020. Implications of COVID-19 for the safe management of general dental practice A practical guide [Online]. [Accessed 30th July 2020 ].

HEFFERNAN, M. 2020. Is a one hour fallow period really necessary for dentistry in England? [Online]. Dentistry. [Accessed 30th July 2020 ].

HILL, I. 1987. 95% Confidence limits for the median. Journal of Statistical Computation and Simulation, 28, 80-81.

HOTA, B., STEIN, B., LIN, M., TOMICH, A., SEGRETI, J. & WEINSTEIN, R. A. 2020. Estimate of airborne transmission of SARS-CoV-2 using real time tracking of health care workers.

MORAWSKA, L. & MILTON, D. K. 2020. It is time to address airborne transmission of COVID-19. Clin Infect Dis, 6,ciaa939.

STADNYTSKYI, V., BAX, C. E., BAX, A. & ANFINRUD, P. 2020. The airborne lifetime of small speech droplets and their potential importance in SARS-CoV-2 transmission. Proc Natl Acad Sci U S A, 117, 11875-11877.

TALEB, N., READ, R. & DOUADY, R. 2020. The Precautionary Principle (with Application to the Genetic Modification of Organisms).

WHO 2020a. Modes of transmission of virus causing COVID-19: implications for IPC precaution recommendations: scientific brief, 27 March 2020. World Health Organization.

WHO 2020b. Transmission of SARS-CoV-2: implications for infection prevention precautions 9th July. World Health Organization.

ZWART, M. P., HEMERIK, L., CORY, J. S., DE VISSER, J. A., BIANCHI, F. J., VAN OERS, M. M., VLAK, J. M., HOEKSTRA, R. F. & VAN DER WERF, W. 2009. An experimental test of the independent action hypothesis in virus-insect pathosystems. Proc Biol Sci, 276, 2233-42.

Coronavirus SARS-CoV-2 screening: Could it accidentally cause local lockdowns?

lockdown

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As a dentist I have a particular interest in how we can protect both our patients and staff during the Covid-19 pandemic and as a consequence have been closely following the development if the NHS test and trace protocols.

One of the major concerns at present is the asymptomatic carriers of the virus and the risk they pose to public health as potential super spreaders (Dental Elf – 2nd Jun. 2020). The proportion of asymptomatic test positive patients in the ONS data from July 2020 was 67% (ONS, 2020a). There are similarly high number of asymptomatics if we look at the results from Iceland at 43% (Oran and Topol, 2020).

Could this figure be correct or is it due to the high number of false positives created by a low level of infection in the community coupled with increased testing/screening (Watson et al., 2020)?  There has been a push for increased screening to help unlock the community or identify hotspots, but could this screening create false hotspots because of the false-positive rate?

Method

Using the following assumptions: –  

  • The prevalence in England as of July was 0.05% (ONS, 2020b)
  • Our testing is near perfect: sensitivity 99%, specificity 99% (Dental Elf – 12th May 2020)
  • Following a local outbreak in a factory we randomly screen 5000 individuals from a large town (Population 100,000)

Figure 1. Frequency tree for Covid-19 screening

SARS-CoV@ screening fig1.We get 2 positives and 50 false positives, so the test results is 2/52 or 3.8% accurate but the town becomes locked down causing considerable second and third order harm to the population in the form of reduced access to the hospital/GP/dental practice, and local business failures. Secondly it feeds the impression of high numbers of asymptomatic carriers since the 50 false positives will not have symptoms. I could not find any evidence that individuals having a positive swab were immediately tested again, if they were the diagnosis would be 67% accurate as shown in the following figure

Figure 2. Frequency tree for repeat Covid-19 screening of positive tests

SARS-CoV@ screening fig2

*NB. Figure of 53 is obtained because of rounding outcome data from figure 1.

Summary

  • Low prevalence of Covid-19 can be problematic if governments do not understand how diagnostic tests work.
  • Screening sounds like a good idea if it is backed up by an immediate second or third retest for an initial positive swab, thus allowing the false positive patients to come out of an unnecessary quarantine.
  • Testing, Track and trace, self-isolating and local lock downs could be severely compromised by the false positive rates even with good testing.

 References

ONS. 2020a. Coronavirus (COVID-19) Infection Survey pilot England, 24 July 2020.  [Accessed 26th July].

ONS 2020b. Coronavirus (COVID-19) infections in the community in England July 2020. [Accessed 26th July].

Oran DP, Topol EJ. Prevalence of Asymptomatic SARS-CoV-2 Infection: A Narrative Review [published online ahead of print, 2020 Jun 3]. Ann Intern Med. 2020;M20-3012. doi:10.7326/M20-3012

Watson J, Whiting PF, Brush JE. Interpreting a covid-19 test result. BMJ. 2020;369:m1808. Published 2020 May 12. doi:10.1136/bmj.m1808

Influence of blinding on treatment effect size estimate in randomized controlled trials of oral health interventions

Scales,justice,blind,fold,fairness - free image from needpix.com

Introduction

The coronavirus pandemic has highlighted many of the strengths and weaknesses in trying to develop evidence-based healthcare strategies from the huge amount of data created in the past 8 months. The most obvious strength is the rapid sharing of research papers via the preprint servers; the limitations are a lack of high-quality peer review, or research methodology in the rush to publish. In a recent article Aronson and co-workers looked at the large number of Covid-19 drug trials and the lack of  suitable blinding/masking which is essential in reducing the effects of bias within a trial. The authors found that out of 142 trails only 36% were masked (Aronson et al., 2020) raising important ethical issues about bias and unreliable reporting of study results.

The importance of blinding/masking has been highlighted in an oral health review by Saltaji and co-workers (Saltaji et al., 2018) that showed studies that did not mask both participants and investigators gave treatment effect size estimates that were, on average higher than masked studies. This review is described below. Their research questions were:

  • Do oral health randomised controlled trials (RCTs) with adequate blinding of participants, outcome assessors, and health care providers yield different treatment effect sizes (ESs) than trials with lack or unclear blinding?
  • Do specific non-methodological meta-analysis characteristics (e.g., dental specialty, type of treatment, type of outcome [objective vs. subjective], magnitude of the treatment ES estimate, heterogeneity of meta-analysis) modify the association between blinding and treatment ES estimates?

Methods

This paper was part of a larger oral health study regarding the methodology used in randomised control trials. Their protocol was registered on PROSPERO (CRD42014014070).

The authors searched six electronic databases (PubMed, MEDLINE, EMBASE, ISI Web of Science, Evidence-Based Medicine Reviews–Cochrane Database of Systematic Reviews, and Health

STAR) from database inception to May 2014. The search was not limited to the English language.

Two independent assessors extracted the relevant data. Study quality was assessed on the different levels of study blinding and whether they were present/absent or unclear. Meta-analysis was undertaken using the raw data extracted from the individual studies with the summary estimate being the difference in ESs plus 95% confidence intervals. Subgroup analysis was undertaken in a similar fashion.

Results

  • 64 systematic reviews (32 Cochrane and 32 non-Cochrane reviews) satisfied the eligibility criteria for the present report. A total of 540 trials analysing 137,957 patients were considered for this study:
    • Periodontics (36 reviews; 271 trials)
    • Dental public health and paediatric dentistry (10 reviews; 145 trials)
    • Oral medicine and pathology (11 reviews; 80 trials)
    • Oral and maxillofacial surgery (4 reviews; 26 trials)
    • Orthodontics and dentofacial orthopaedics (2 reviews; 12 trials)
    • Restorative dentistry (1 review; 6 trials).
  • Risk of Bias – Blinding of patients was judged as adequate (low risk of bias) in 71.5% (n = 386) of the trials, and blinding of the outcome assessment was judged as adequate (low risk of bias) in 59.4% of the trials.
  • Quality assessment – Only 33.5% (n=181) of studies were described as double blind.
  • Trials with inadequate patient blinding had significantly larger treatment ES estimates (difference = 0.12, 95% confidence interval 0.00 to 0.23, p = 0.046).
  • Trials with a lack of blinding of both patients and assessors (difference = 0.19; 95% CI: 0.06 to 0.32)
  • Trials with a lack of blinding of patients, assessors, and care-providers concurrently (difference = 14; 95% CI: 0.03 to 0.25).
  • Subgroup analysis stratified by other characteristics of meta-analyses (heterogeneity of meta-analysis, type of outcome, and dental speciality) was not statistically significant for any of the characteristics.

Conclusion (the author concluded)

We found significant differences in treatment ESs between oral health RCTs based on lack of patient and assessor blinding. RCTs that lacked patient and assessor blinding had significantly larger treatment ES estimates. Treatment ES estimates were 0.19 and 0.14 larger in trials with lack of blinding of both patients and assessors and blinding of patients, assessors, and care-providers concurrently. No significant differences were identified in other blinding criteria. Future meta-epidemiological assembling of a greater number of meta-analyses and trials that takes other biases and different degrees of blinding into account is needed.

 Comments

This was a well-constructed methodological meta-analysis demonstrating the importance of including blinding wherever it is possible within a study design to reduce the effects of bias. Poorly designed trials can overestimate benefits and therefore obscure harms to patients. Good methodology must not be sacrificed on the alter of producing results with amplified effect sizes in an attempt to get published as this not only represent bad science it is also unethical (WHO, 2014).

 References

ARONSON, J., DEVITO, N. & FERNER, R. 2020. The ethics of COVID-19 treatment studies: too many are open, too few are double-masked [Online]. Oxford COVID-19 Evidence Service. Available: https://www.cebm.net/covid-19/the-ethics-of-covid-19-treatment-studies-too-many-are-open-too-few-are-double-masked/ [Accessed].

SALTAJI, H., ARMIJO-OLIVO, S., CUMMINGS, G. G., AMIN, M., DA COSTA, B. R. & FLORES-MIR, C. 2018. Influence of blinding on treatment effect size estimate in randomized controlled trials of oral health interventions. BMC Med Res Methodol, 18, 42.

WHO. 2014. Ethical considerations for use of unregistered interventions for Ebola virus disease: Report of an advisory panel to WHO [Online]. Available: https://www.who.int/csr/resources/publications/ebola/ethical-considerations/en/ [Accessed].