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.

Re-opening of dental services: A rapid review of international sources. Part II.

Separating the signal from the noise regarding masks.

Link to the Dental Elf

File:Face Masks used to prevent the spread of Coronavirus in ...

Bottom Line

As the number of clinical guidelines and standard operating procedures increases, we are seeing a reduction in consensus regarding a clear way forward in patient management. If we are going to take an evidence-based approach in a land devoid of direct evidence the policy makers are going to have to defer to the clinical expertise, and local knowledge of the profession in regards to the choice of PPE regarding Covid-19 negative patients requiring aerosol generating procedures.

Background

The recent ‘Cochrane Recommendations for the re-opening of dental services: a rapid review of international sources’ has been updated  on the 16th May to include a further 5 international guidelines. The document now reviews 17 guidance documents from 16 countries (France, Spain, Portugal, Austria, Switzerland, Belgium, Netherlands, Norway, Denmark, Malta, America CDC, America ADA, Canada, Australia, New Zealand, India). The common themes and the relevant recommendations were divided into 5 domains:

  1. Practice preparation and patient considerations.
  2. Personal protective equipment (PPE) for dental practice personnel.
  3. Management of the clinical room.
  4. Dental procedures.
  5. Post-operative cleaning/disinfection/waste management.

Methods

The data was extracted in a similar way to the previous review. The five domains have mostly remained the same with little change in domains 1, 3, 4, and 5. The exception being domain 2 (PPE for dental practice personnel). The domain almost doubled in size to 29 subgroups from the original 15, but at the same time there was a reduction in the consensus with the mean dropping from 58% to 30% (See Figure 1.).

Update_f1

As with the previous review I selected the subgroups that achieved to filter out the large number of subgroups with a low degree of consensus. In the original paper there were 10 subgroups that scored ≥ 50%, in the update this reduced to 7 which constitutes a 42% reduction in agreement considering the expansion of the domain. (See Figure 2).

Figure 2. Subgroups with greater than 50% consensus.

Update_f2

 

Looking at these subgroup headings there is a lot of duplication especially regarding the use of FFP2 and FFP3 masks and the infective status of the patient. To try and clarify this matter a subgroup analysis was undertaken (See Figure 3,).

Figure 3. Mask selection

update_f3

From this chart it was obvious that for Covid negative patients the consensus was for the use of surgical masks, and with Covid infective patients requiring an aerosol generating procedure (AGP) an FFP3 mask should be used. There was however a grey area around the use of a surgical mask combined with a face shield/visor, and an FFP2 mask for Covid negative patients requiring an AGP, the prevalence of asymptomatic patients being very low in the community (ONS, 2020). There was 41% (95% CI: 18% to 65%) agreement regarding the surgical masks, against 59% (95% CI: 35% to 82%) agreement for the use of an FFP2 mask, however as the sample size was small (n=17) the result was not statistically significant (p= 0.29).

Discussion

What can we conclude from the update? Due to the lack of hard evidence regarding the effectiveness of PPE in the real-world clinical environment the guidelines would appear to be based on opinion that ranges from the precautionary principle that all patients should be considered infective, to a more pragmatic approach based on the professions current cross infection strategies. In a perfect world we would like to see well  design randomised controlled studies to answer these questions, but this does not address the here-and-now of real-world dentistry. If we are going to follow the principles of evidence-based dentistry (Sackett et al., 1996) the clinicians are going have to make the decision of using surgical masks, or FFP2 masks  for AGPs based on individual clinical expertise, best available evidence, and their patients values and preferences rather than rigid guidelines that can’t adapt to local circumstances.

References

ONS. 2020. Coronavirus (COVID-19) Infection Survey pilot: England, 14 May 2020 [Online]. Available: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/coronaviruscovid19infectionsurveypilot/england14may2020 [Accessed].

SACKETT, D. L., ROSENBERG, W. M., GRAY, J. M., HAYNES, R. B. & RICHARDSON, W. S. 1996. Evidence based medicine: what it is and what it isn’t. British Medical Journal Publishing Group.

https://oralhealth.cochrane.org/news/recommendations-re-opening-dental-services-rapid-review-international-sources

Disclaimer:  The article has not been peer-reviewed; it should not replace individual clinical judgement, and the sources cited should be checked. The views expressed in this commentary represent the views of the author and not necessarily those of the host institution. The views are not a substitute for professional advice.

Are we sleepwalking into PPE paralysis?

“When the facts change, I change my mind. What do you do, Sir?” – John Maynard Keynes

sleepwalkers-figure-roof-sky-royalty-free-thumbnail

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Bottom line answer

As we approach a return to clinical practice policy makers need to be mindful that the dental profession is already highly proficient in cross infection control, and the benefits of new elaborate PPE protocols regarding aerosol generating procedures may be marginal in the light of low disease prevalence. If we need 300,000 participants in a  study it may be impossible to practically demonstrate  significant benefits to patient safety from the perfect PPE model compared to the harms created by expense and access.

 

Background

The most important element of Keynes’s famous quote relating to the current coronavirus pandemic is the word ‘fact’. Facts at this moment in time are constantly changing as this disease spreads, and what was true two weeks ago is now a distant memory. One major problem we face as far as healthcare policy is concerned is a lack of accurate base-rate data on the prevalence of the disease in the population, this was initially addresses by Professor Ioannidis (Ioannidis, 2020). His article in STAT caused quite a lot of online controversy (Bastian, 2020, Taleb, 2020) but what it did is highlight the difficulties of being objective and human. At this moment in time it is extremely difficult not to be influenced by the problems of base-rate neglect, loss aversion, and availability bias via the media as we count the daily international infection/death figures (Gaurav, 2020). In this post I want to concentrate on how important it is to understand the significance of accurate base-rate (prevalence) reporting  so we can allocate the correct amount of training and resources to the dental profession based of the potential aerosol risk in virus transmission. In a paper by Chambers on base-rates in dental decision-making there is a quote (Chambers, 1999):

‘Base your decisions on either the baseline alone or the evidence alone, depending on which one contains the most information.’

What we are seeing now is a rapid accumulation of both base-line data and evidence,  but policy decisions about the future are being based on data and precautionary principles that were only valid at the start of this pandemic. To highlight this, I would like to explore how we are going to test the real-world effectiveness of the personal protective equipment (PPE) and cross infection protocols that are flooding the profession now.

Methods

I am going to look at three areas here, base-rates (prevalence), numbers of asymptomatic individuals, and power calculations regarding PPE use. For clarity I will use natural frequencies wherever possible.

Firstly, on the 14th May the Office of National Statistics (ONS) in the UK published the results of its coronavirus (Covid-19) infection survey (ONS, 2020). This data was based on 10,705 participants’ swab tests taken over a two-week period from 27th April to 10th May, the sample was drawn from households in which someone has already participated in an ONS survey to ensure the sample was representative of the wider population. From this sample 33 individuals in 30 households tested positive for COVID-19. This equates according to the ONS to 0.27% (95% confidence interval: 0.17% to 0.41%) of the population of England.

Secondly, one of the key problems with Covid-19 is asymptomatic spread (Bai et al., 2020) but there is no reliable data so any calculations here need to be looked on as a Fermi (back of an envelope) problem. To get a best estimate on the proportion of asymptomatic patients I conducted a meta-analysis of the data presented on the Oxford Covid-19 Evidence Service (Heneghan et al., 2020). The meta-analysis was carries out in R using a random effects model (See Figure 1.)

Figure 1. Forest plot of asymptomatic individuals

Asympto

There are two points of note from this forest plot, the summary estimate for asymptomatic individuals is 27% (95% CI: 12 to 45%) and the heterogeneity between studies (variability) is extremely high.

The next stage is to put the base-rate and number of asymptomatics together in the form of a frequency tree. For ease of calculation I have rounded the figures so a base-rate of 0.27% becomes 1 in 400,  and the number of asymptomatics becomes 30% (See Figure 2.).

Figure 2. Frequency tree of asymptomatic vs symptomatic

Asympto_1

The frequency tree illustrates that in this population 1 out of every 1333 people could be an asymptomatic carrier of Covid-19.

How does this relate to dentistry? On the precautionary principle we are operating under at the moment the presumption is that all (100%) the patients are asymptomatic carriers rather than the true figure of 0.075% ( I have assumed symptomatic patients will not be attending a dental surgery or will be triaged out prior to entering the clinical environment). This becomes important when we want to test if our PPE and protocols are effectively protecting both the patients and the staff.  We now need to set up a study comparing PPE that is adequately powered to eliminate the effects of random chance around such a small prevalence statistic (Button et al., 2013). I have created three examples of PPE for aerosol generating procedures:

  • Perfect PPE model (fluid resistant disposable gowns, FFP3 masks, visors, ventilation, long fallow periods etc) with a 99%  chance of reducing viral contamination
  • Realistic expectations of enhanced PPE practice (FFP2, reusable surgical gown, rubber dam etc) at 93%.
  • Standard practice (surgical masks etc) at 80%.

I placed the data into an apriori sample size calculator (G*Power 3.19.2) with a error probability is 0.05 and power (1-b error probability) of 0.8 (See Table 1).

Table 1. Sample sizes for a well powered study into PPE effectiveness

asympto_tableAs we can see even in a simulation study, we are going to have to at least place over a hundred individuals in each arm of the study. To see if the benefit translates into the real-world, we need to go up two orders of magnitude to see if there is a significant difference between perfect and good PPE  based on accurate population base-rate figures.

Discussion

The purpose of this opinion paper was to highlight the potential problems that a precautionary principle can create in healthcare when we work on the assumption that 100% of the patients attending a dental surgery are infectious. Guidelines and protocols need to take into consideration the absolute risk within the population based on data that is accurate and up to date. Simulation studies, and pilot studies rarely carry their full reported success into the real world (Kistin and Silverstein, 2015). Without taking a deep breath and objectively assessing the changing data regarding Covid-19, policy makers, academics, and clinicians can unconsciously fall fowl of the base-rate fallacy and availability biases created by the modern media. High quality PPE and staff training is a vital component of keeping everyone safe from this virus but we must be mindful of the other effects that perfect practice can have on the health economics and affordability of health care to those most vulnerable.

Disclaimer:  The article has not been peer-reviewed; it should not replace individual clinical judgement, and the sources cited should be checked. The views expressed in this commentary represent the views of the author and not necessarily those of the host institution. The views are not a substitute for professional advice.

References

BAI, Y., YAO, L., WEI, T., TIAN, F., JIN, D. Y., CHEN, L. & WANG, M. 2020. Presumed Asymptomatic Carrier Transmission of COVID-19. JAMA.

BASTIAN, H. 2020. A rebuttal to “A fiasco in the making?” [Online]. Available: http://hildabastian.net/index.php/8-secondary/87-a-rebuttal-to-a-fiasco-in-the-making [Accessed].

BUTTON, K. S., IOANNIDIS, J. P., MOKRYSZ, C., NOSEK, B. A., FLINT, J., ROBINSON, E. S. & MUNAFÒ, M. R. 2013. Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14, 365-376.

CHAMBERS, D. W. 1999. The roles of evidence and the baseline in dental decision making. J Am Coll Dent, 66, 60-7.

GAURAV, S. 2020. Behavioural Economics in the Fight Against COVID-19: BOMA Framework.

HENEGHAN, C., BRASSEY, C. & JEFFERSON, T. 2020. COVID-19: What proportion are asymptomatic? [Online]. Available: https://www.cebm.net/covid-19/covid-19-what-proportion-are-asymptomatic/ [Accessed].

IOANNIDIS, J. P. 2020. A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data [Online]. STAT. Available: https://www.statnews.com/2020/03/17/a-fiasco-in-the-making-as-the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-data/ [Accessed].

KISTIN, C. & SILVERSTEIN, M. 2015. Pilot studies: a critical but potentially misused component of interventional research. Jama, 314, 1561-1562.

ONS. 2020. Coronavirus (COVID-19) Infection Survey pilot: England, 14 May 2020 [Online]. Available: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/coronaviruscovid19infectionsurveypilot/england14may2020 [Accessed].

TALEB, N. 2020. EVIDENCE BASED is often BS [Online]. Available: https://twitter.com/nntaleb/status/1240641133820207104 [Accessed].