Efficacy of FFP3 respirators for prevention of SARS-CoV-2 infection in healthcare workers

  1. Mark Ferris  Is a corresponding author
  2. Rebecca Ferris
  3. Chris Workman
  4. Eoin O'Connor
  5. David A Enoch
  6. Emma Goldesgeyme
  7. Natalie Quinnell
  8. Parth Patel
  9. Jo Wright
  10. Geraldine Martell
  11. Christine Moody
  12. Ashley Shaw
  13. Christopher JR Illingworth
  14. Nicholas J Matheson
  15. Michael P Weekes  Is a corresponding author
  1. Cambridge University Hospitals NHS Foundation Trust, United Kingdom
  2. University of Cambridge Occupational Health and Safety Service, United Kingdom
  3. School of Clinical Medicine, United Kingdom
  4. Clinical Microbiology & Public Health Laboratory, Public Health England, United Kingdom
  5. MRC Biostatistics Unit, United Kingdom
  6. Department of Applied Mathematics and Theoretical Physics, United Kingdom
  7. MRC-University of Glasgow Centre for Virus Research, United Kingdom
  8. Department of Medicine, University of Cambridge, United Kingdom
  9. Cambridge Institute of Therapeutic Immunology and Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, United Kingdom
  10. NHS Blood and Transplant, United Kingdom
  11. Cambridge Institute for Medical Research, United Kingdom
3 figures, 2 tables and 2 additional files

Figures

Figure 1 with 2 supplements
Comparison between total number of cases amongst healthcare workers (HCWs) and community incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Comparison between total number of cases amongst HCWs and community incidence of SARS-CoV-2. Community incidence is shown for the East of England, UK, derived from https://coronavirus.data.gov.uk/details/cases, with raw data shown in Figure 1—source data 1.

Figure 1—source data 1

Raw case numbers for the East of England region during the period of study.

https://cdn.elifesciences.org/articles/71131/elife-71131-fig1-data1-v2.xlsx
Figure 1—figure supplement 1
Proportion of cases ascertained by symptomatic testing and asymptomatic screening on green and red wards.
Figure 1—figure supplement 1—source data 1

Proportion of cases ascertained by symptomatic and asymptomatic screening on green and red wards.

https://cdn.elifesciences.org/articles/71131/elife-71131-fig1-figsupp1-data1-v2.xlsx
Figure 1—figure supplement 2
Relationship between number of healthcare worker (HCW) days per week worked on red wards and community incidence.
Figure 2 with 1 supplement
Weekly cases per healthcare worker (HCW) day amongst HCWs on red and green wards prior to and after the change in respiratory protective equipment (RPE).
Figure 2—figure supplement 1
Relationships between cases per ward day and community incidence.

Cases per ward day amongst healthcare workers (HCWs) on green wards (A) were strongly correlated with the number of community cases identified the previous week (p value <2.1 × 10–3, Pearson correlation test), suggesting that infection in the community explains cases amongst HCWs on these wards. Conversely, cases per ward day amongst HCWs on red wards (B) did not correlate with the community incidence (p value >0.62, Pearson correlation test). R2 values shown in the figures are coefficients of determination arising from linear regression calculations performed using the Mathematica software package (version 12.3.1.0).

Figure 3 with 2 supplements
Mathematical modelling of the risks of infection for healthcare workers (HCWs) on red and green wards.

(A, B) Comparison of modelled and actual cases. The model (black dashed line) aimed to reproduce the risks of infection amongst HCWs per ward day (A) on green wards (green solid line) and (B) on red wards (red solid line). (C) Risks inferred from the model. HCWs were vulnerable to coronavirus disease 2019 (COVID-19) infection from exposure to individuals in the community, with this risk increasing with community incidence (grey line). HCWs working on green wards faced a consistent, low risk of infection from direct, ward-based exposure (green line). HCWs working on red wards initially faced a much higher risk of infection from direct, ward-based exposure, falling to a value close to that on green wards upon the introduction of filtering face piece 3 (FFP3) respirators. In this figure, risks are expressed per ward day; a risk of 0.01 indicates that a particular source of risk would be expected to cause one HCW to develop an infection every 100 days that the ward was in operation. (D, E) Proportion of community-acquired cases. Proportion of infections on (D) green and (E) red wards inferred to have arisen via exposure to individuals in the community (green line, green wards; red line, red wards; confidence intervals shaded).

Figure 3—source data 1

Mathematical modelling of the risks of infection for healthcare workers (HCWs) on red and green wards.

https://cdn.elifesciences.org/articles/71131/elife-71131-fig3-data1-v2.xlsx
Figure 3—figure supplement 1
Effect of changing the attribution of positive cases to wards in which a contemporaneous designation change occurred (e.g. from green to red).

Cases were by default attributed to the type of ward on which each positive-testing healthcare worker (HCW) worked 5 days prior to reporting symptoms (if symptomatic) or testing positive (if asymptomatic). This analysis examines how maximum likelihood inferences (dots) and confidence intervals (lines) change upon varying the 5 day cutoff to between 3 and 7 days. A ratio of 0.4 corresponds to a 60 % reduction in HCW risk upon the introduction of filtering face piece 3 (FFP3) respirators.

Figure 3—figure supplement 1—source data 1

Effect of changing the attribution of positive cases to wards in which a contemporaneous designation change occurred.

https://cdn.elifesciences.org/articles/71131/elife-71131-fig3-figsupp1-data1-v2.xlsx
Figure 3—figure supplement 2
Comparison of modelled and actual cases when critical care wards were included in the dataset.

The model (black dashed line) aimed to reproduce the risks of infection amongst healthcare workers (HCWs) per ward day on green wards (green line), red wards (red solid line), and on critical care wards (blue line). Red dots show the maximum likelihood ratio between ward-specific risks to HCWs on red wards before and after the introduction of filtering face piece 3 (FFP3) respirators, with vertical lines indicating 95 % confidence intervals for this statistic. Our model fitted a rate of community-based infection, plus ward-type-specific rates of infection for red, green, and critical care wards.

Figure 3—figure supplement 2—source data 1

Comparison of modelled and actual cases when critical care wards were included in the dataset.

https://cdn.elifesciences.org/articles/71131/elife-71131-fig3-figsupp2-data1-v2.xlsx

Tables

Table 1
Weekly numbers of cases amongst HCWs on red and green wards, and cases per HCW day weeks following the change in RPE are highlighted in grey.

Community incidence (total cases per week) is shown for the East of England, UK, with raw data shown in Figure 1—source data 1.

WeekWeek startRed casesRed HCW daysRed cases per 103 HCW daysGreen casesGreen HCW daysGreen cases per 103 HCW daysExcluded casesTotalCommunity
102/11/20200980532551.5416217876
209/11/202029820.41732412.1633429499
316/11/202011985.05331410.9626307998
423/11/202012384.20531011.6124317203
530/11/2020323812.61631011.9320299441
607/12/2020523821.011031013.22334816,535
714/12/202012384.20731012.26414931,219
821/12/2020323812.611031013.22566937,259
928/12/202023575.602029826.71588050,110
1004/01/202145057.9234283412.007010841,663
1111/01/202158485.9033249113.256310231,341
  1. HCW, healthcare worker; RPE, respiratory protective equipment.

Table 2
Statistics and parameter ratios inferred from the model.
StatisticModel parameterMaximum likelihood estimateConfidence interval
Force of community-based infection per community casek1.95 × 10−7[1.49 × 10−7, 2.39 × 10−7]
Force of direct infection per HCW day (green ward)g2.53 × 10−4[0, 1.10 × 10−3]
Force of direct infection per HCW day (red ward, pre-FFP3)r17.97 × 10−3[3.65 × 10−3, 1.40 × 10−2]
Force of direct infection per ward day (red ward, post-FFP3)r26.84 × 10−10[0, 3.38 × 10−3]
Relative direct risk on red wards post- versus pre-FFP3r2/r10.00[0, 0.478]
Relative direct risk on red ward versus green ward pre-FFP3r1/g31.47[5.92, ∞)
Relative direct risk on red ward versus green ward post-FFP3r2/g0.00[0, ∞)
  1. FFP3, filtering face piece 3; HCW, healthcare worker.

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  1. Mark Ferris
  2. Rebecca Ferris
  3. Chris Workman
  4. Eoin O'Connor
  5. David A Enoch
  6. Emma Goldesgeyme
  7. Natalie Quinnell
  8. Parth Patel
  9. Jo Wright
  10. Geraldine Martell
  11. Christine Moody
  12. Ashley Shaw
  13. Christopher JR Illingworth
  14. Nicholas J Matheson
  15. Michael P Weekes
(2021)
Efficacy of FFP3 respirators for prevention of SARS-CoV-2 infection in healthcare workers
eLife 10:e71131.
https://doi.org/10.7554/eLife.71131