Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis
Journal: 2020/June - The Lancet
Abstract:
Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 and is spread person-to-person through close contact. We aimed to investigate the effects of physical distance, face masks, and eye protection on virus transmission in health-care and non-health-care (eg, community) settings.
Methods: We did a systematic review and meta-analysis to investigate the optimum distance for avoiding person-to-person virus transmission and to assess the use of face masks and eye protection to prevent transmission of viruses. We obtained data for SARS-CoV-2 and the betacoronaviruses that cause severe acute respiratory syndrome, and Middle East respiratory syndrome from 21 standard WHO-specific and COVID-19-specific sources. We searched these data sources from database inception to May 3, 2020, with no restriction by language, for comparative studies and for contextual factors of acceptability, feasibility, resource use, and equity. We screened records, extracted data, and assessed risk of bias in duplicate. We did frequentist and Bayesian meta-analyses and random-effects meta-regressions. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. This study is registered with PROSPERO, CRD42020177047.
Findings: Our search identified 172 observational studies across 16 countries and six continents, with no randomised controlled trials and 44 relevant comparative studies in health-care and non-health-care settings (n=25 697 patients). Transmission of viruses was lower with physical distancing of 1 m or more, compared with a distance of less than 1 m (n=10 736, pooled adjusted odds ratio [aOR] 0·18, 95% CI 0·09 to 0·38; risk difference [RD] -10·2%, 95% CI -11·5 to -7·5; moderate certainty); protection was increased as distance was lengthened (change in relative risk [RR] 2·02 per m; pinteraction=0·041; moderate certainty). Face mask use could result in a large reduction in risk of infection (n=2647; aOR 0·15, 95% CI 0·07 to 0·34, RD -14·3%, -15·9 to -10·7; low certainty), with stronger associations with N95 or similar respirators compared with disposable surgical masks or similar (eg, reusable 12-16-layer cotton masks; pinteraction=0·090; posterior probability >95%, low certainty). Eye protection also was associated with less infection (n=3713; aOR 0·22, 95% CI 0·12 to 0·39, RD -10·6%, 95% CI -12·5 to -7·7; low certainty). Unadjusted studies and subgroup and sensitivity analyses showed similar findings.
Interpretation: The findings of this systematic review and meta-analysis support physical distancing of 1 m or more and provide quantitative estimates for models and contact tracing to inform policy. Optimum use of face masks, respirators, and eye protection in public and health-care settings should be informed by these findings and contextual factors. Robust randomised trials are needed to better inform the evidence for these interventions, but this systematic appraisal of currently best available evidence might inform interim guidance.
Funding: World Health Organization.
Relations:
Content
Citations
(408)
References
(74)
Diseases
(4)
Chemicals
(1)
Organisms
(3)
Similar articles
Articles by the same authors
Discussion board
Lancet 395(10242): 1973-1987

Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis

+38 authors

Supplementary Material

Supplementary appendix:

Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada
Department of Medicine, McMaster University, Hamilton, ON, Canada
The Research Institute of St Joe's Hamilton, Hamilton, ON, Canada
Department of Internal Medicine, American University of Beirut, Beirut, Lebanon
Clinical Research Institute, American University of Beirut, Beirut, Lebanon
Michael G DeGroote Cochrane Canada and GRADE Centres, Hamilton, ON, Canada
Holger J Schünemann: ac.retsamcm@henuhcs
Correspondence to: Prof Holger J Schünemann, Michael G DeGroote Cochrane Canada and McMaster GRADE Centres, McMaster University, Hamilton, ON L8N 3Z5, Canada ac.retsamcm@henuhcs
Study authors are listed in the appendix and at the end of the Article
Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 and is spread person-to-person through close contact. We aimed to investigate the effects of physical distance, face masks, and eye protection on virus transmission in health-care and non-health-care (eg, community) settings.

Methods

We did a systematic review and meta-analysis to investigate the optimum distance for avoiding person-to-person virus transmission and to assess the use of face masks and eye protection to prevent transmission of viruses. We obtained data for SARS-CoV-2 and the betacoronaviruses that cause severe acute respiratory syndrome, and Middle East respiratory syndrome from 21 standard WHO-specific and COVID-19-specific sources. We searched these data sources from database inception to May 3, 2020, with no restriction by language, for comparative studies and for contextual factors of acceptability, feasibility, resource use, and equity. We screened records, extracted data, and assessed risk of bias in duplicate. We did frequentist and Bayesian meta-analyses and random-effects meta-regressions. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. This study is registered with PROSPERO, CRD42020177047.

Findings

Our search identified 172 observational studies across 16 countries and six continents, with no randomised controlled trials and 44 relevant comparative studies in health-care and non-health-care settings (n=25 697 patients). Transmission of viruses was lower with physical distancing of 1 m or more, compared with a distance of less than 1 m (n=10 736, pooled adjusted odds ratio [aOR] 0·18, 95% CI 0·09 to 0·38; risk difference [RD] −10·2%, 95% CI −11·5 to −7·5; moderate certainty); protection was increased as distance was lengthened (change in relative risk [RR] 2·02 per m; pinteraction=0·041; moderate certainty). Face mask use could result in a large reduction in risk of infection (n=2647; aOR 0·15, 95% CI 0·07 to 0·34, RD −14·3%, −15·9 to −10·7; low certainty), with stronger associations with N95 or similar respirators compared with disposable surgical masks or similar (eg, reusable 12–16-layer cotton masks; pinteraction=0·090; posterior probability >95%, low certainty). Eye protection also was associated with less infection (n=3713; aOR 0·22, 95% CI 0·12 to 0·39, RD −10·6%, 95% CI −12·5 to −7·7; low certainty). Unadjusted studies and subgroup and sensitivity analyses showed similar findings.

Interpretation

The findings of this systematic review and meta-analysis support physical distancing of 1 m or more and provide quantitative estimates for models and contact tracing to inform policy. Optimum use of face masks, respirators, and eye protection in public and health-care settings should be informed by these findings and contextual factors. Robust randomised trials are needed to better inform the evidence for these interventions, but this systematic appraisal of currently best available evidence might inform interim guidance.

Funding

World Health Organization.

Across studies, mean age was 30–60 years. SARS=severe acute respiratory syndrome. MERS=Middle East respiratory syndrome.

Table based on GRADE approach.26272829 Population comprised people possibly exposed to individuals infected with SARS-CoV-2, SARS-CoV, or MERS-CoV. Setting was any health-care or non-health-care setting. Outcomes were infection (laboratory-confirmed or probable) and contextual factors. Risk (95% CI) in intervention group is based on assumed risk in comparison group and relative effect (95% CI) of the intervention. All studies were non-randomised and evaluated using the Newcastle-Ottawa Scale; some studies had a higher risk of bias than did others but no important difference was noted in sensitivity analyses excluding studies at higher risk of bias; we did not further rate down for risk of bias. Although there was a high I2 value (which can be exaggerated in non-randomised studies)21 and no overlapping CIs, point estimates generally exceeded the thresholds for large effects and we did not rate down for inconsistency. We did not rate down for indirectness for the association between distance and infection because SARS-CoV-2, SARS-CoV, and MERS-CoV all belong to the same family and have each caused epidemics with sufficient similarity; there was also no convincing statistical evidence of effect-modification across viruses; some studies also used bundled interventions but the studies include only those that provide adjusted estimates. aOR=adjusted odds ratio. RR=relative risk. SARS-CoV-2=severe acute respiratory syndrome coronavirus 2. SARS-CoV=severe acute respiratory syndrome coronavirus. MERS-CoV=Middle East respiratory syndrome coronavirus.

This systematic review was commissioned and in part paid for by WHO. The authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy, or views of WHO. We thank Susan L Norris, April Baller, and Benedetta Allegranzi (WHO) for input in the protocol or the final article; Xuan Yu (Evidence Based Medicine Center of Lanzhou University, China), Eliza Poon, and Yuqing (Madison) Zhang for assistance with Chinese literature support; Neera Bhatnagar and Aida Farha (information specialists) for peer-reviewing the search strategy; Artur Nowak (Evidence Prime, Hamilton, ON, Canada) for help with searching and screening using artificial intelligence; and Christine Keng for additional support. DKC is a CAAIF-CSACI-AllerGen Emerging Clinician-Scientist Research Fellow, supported by the Canadian Allergy, Asthma and Immunology Foundation (CAAIF), the Canadian Society of Allergy and Clinical Immunology (CSACI), and AllerGen NCE (the Allergy, Genes and Environment Network).

Editorial note: the Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations.

Contributors

DKC, EAA, SD, KS, SY, and HJS designed the study. SY, SD, KS, and HJS coordinated the study. SY and LH designed and ran the literature search. All authors acquired data, screened records, extracted data, and assessed risk of bias. DKC did statistical analyses. DKC and HJS wrote the report. All authors provided critical conceptual input, analysed and interpreted data, and critically revised the report.

COVID-19 Systematic Urgent Review Group Effort (SURGE) study authors

Argentina—German Hospital of Buenos Aires (Ariel Izcovich); Canada—Cochrane Consumer Executive (Maureen Smith); McMaster University (Mark Loeb, Anisa Hajizadeh, Carlos A Cuello-Garcia, Gian Paolo Morgano, Leila Harrison, Tejan Baldeh, Karla Solo, Tamara Lotfi, Antonio Bognanni, Rosa Stalteri, Thomas Piggott, Yuan Zhang, Stephanie Duda, Derek K Chu, Holger J Schünemann); Southlake Regional Health Centre (Jeffrey Chan); University of British Columbia (David James Harris); Chile—Pontificia Universidad Católica de Chile (Ignacio Neumann); China—Beijing University of Chinese Medicine, Dongzhimen Hospital (Guang Chen); Guangzhou University of Chinese Medicine, The Fourth Clinical Medical College (Chen Chen); China Academy of Chinese Medical Sciences (Hong Zhao); Germany—Finn Schünemann; Italy—Azienda USL–IRCCS di Reggio Emilia (Paolo Giorgi Rossi); Universita Vita-Salute San Raffaele, Milan, Italy (Giovanna Elsa Ute Muti Schünemann); Lebanon—American University of Beirut (Layal Hneiny, Amena El-Harakeh, Fatimah Chamseddine, Joanne Khabsa, Nesrine Rizk, Rayane El-Khoury, Zahra Saad, Sally Yaacoub, Elie A Akl); Rafik Hariri University Hospital (Pierre AbiHanna); Poland—Evidence Prime, Krakow (Anna Bak, Ewa Borowiack); UK—The London School of Hygiene & Tropical Medicine (Marge Reinap); University of Hull (Assem Khamis).

Declaration of interests

ML is an investigator of an ongoing clinical trial on medical masks versus N95 respirators for COVID-19 (NCT04296643). All other authors declare no competing interests.

Contributor Information

COVID-19 Systematic Urgent Review Group Effort (SURGE) study authors:

Click here to view.(980K, pdf)

References

  • 1. Worldometer COVID-19 coronavirus pandemic2020.
  • 2. Guo ZD, Wang ZY, Zhang SFAerosol and surface distribution of severe acute respiratory syndrome coronavirus 2 in hospital wards, Wuhan, China, 2020. Emerg Infect Dis. 2020 doi: 10.3201/eid2607.200885. published online April 10. ] [[Google Scholar]
  • 3. Chia PY, Coleman KK, Tan YKDetection of air and surface contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in hospital rooms of infected patients. medRxiv. 2020 doi: 10.1101/2020.03.29.20046557. published online April 9. (preprint). [[PubMed][Google Scholar]
  • 4. Santarpia JL, Rivera DN, Herrera VTransmission potential of SARS-CoV-2 in viral shedding observed at the University of Nebraska Medical Center. medRxiv. 2020 doi: 10.1101/2020.03.23.20039446. published online March 26. (preprint). [[PubMed][Google Scholar]
  • 5. Cheng V, Wong S-C, Chen JEscalating infection control response to the rapidly evolving epidemiology of the coronavirus disease 2019 (COVID-19) due to SARS-CoV-2 in Hong Kong. Infect Control Hosp Epidemiol. 2020;41:493–498.[Google Scholar]
  • 6. Wong SCY, Kwong RT-S, Wu TCRisk of nosocomial transmission of coronavirus disease 2019: an experience in a general ward setting in Hong Kong. J Hosp Infect. 2020;105:119–127.[Google Scholar]
  • 7. Faridi S, Niazi S, Sadeghi KA field indoor air measurement of SARS-CoV-2 in the patient rooms of the largest hospital in Iran. Sci Total Environ. 2020;725[Google Scholar]
  • 8. Ong SWX, Tan YK, Chia PYAir, surface environmental, and personal protective equipment contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from a symptomatic patient. JAMA. 2020;323:1610–1612.[Google Scholar]
  • 9. Qualls N, Levitt A, Kanade NCommunity mitigation guidelines to prevent pandemic influenza: United States, 2017. MMWR Recomm Rep. 2017;66:1–34.[Google Scholar]
  • 10. Feng S, Shen C, Xia N, Song W, Fan M, Cowling BJRational use of face masks in the COVID-19 pandemic. Lancet Respir Med. 2020;8:434–436.[Google Scholar]
  • 11. MacIntyre R, Chughtai A, Tham CD, Seale HCOVID-19: should cloth masks be used by healthcare workers as a last resort? April 9, 2020.
  • 12. Loeb M, Dafoe N, Mahony JSurgical mask vs N95 respirator for preventing influenza among health care workers: a randomized trial. JAMA. 2009;302:1865–1871.[PubMed][Google Scholar]
  • 13. Bartoszko JJ, Farooqi MAM, Alhazzani W, Loeb MMedical masks vs N95 respirators for preventing COVID-19 in healthcare workers: a systematic review and meta-analysis of randomized trials. Influenza Other Respir Viruses. 2020 doi: 10.1111/irv.12745. published online April 4. ] [[Google Scholar]
  • 14. Schünemann HJ, Moja L. Reviews: rapid! Rapid! Rapid! . . . and systematic. Syst Rev. 2015;4:4.
  • 15. Cochrane Training Cochrane handbook for systematic reviews of interventions, version 62019. [PubMed]
  • 16. Guyatt GH, Oxman AD, Vist GEGRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336:924–926.[Google Scholar]
  • 17. Moher D, Liberati A, Tetzlaff J, Altman DGPreferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol. 2009;62:1006–1012.[PubMed][Google Scholar]
  • 18. Stroup DF, Berlin JA, Morton SCMeta-analysis of observational studies in epidemiology: a proposal for reporting. JAMA. 2000;283:2008–2012.[PubMed][Google Scholar]
  • 19. Jefferson T, Del Mar CB, Dooley LPhysical interventions to interrupt or reduce the spread of respiratory viruses. Cochrane Database Syst Rev. 2011;7[Google Scholar]
  • 20. Offeddu V, Yung CF, Low MSF, Tam CCEffectiveness of masks and respirators against respiratory infections in healthcare workers: a systematic review and meta-analysis. Clin Infect Dis. 2017;65:1934–1942.[Google Scholar]
  • 21. Guyatt GH, Oxman AD, Kunz RGRADE guidelines, 7: rating the quality of evidence—inconsistency. J Clin Epidemiol. 2011;64:1294–1302.[PubMed][Google Scholar]
  • 22. Iorio A, Spencer FA, Falavigna MUse of GRADE for assessment of evidence about prognosis: rating confidence in estimates of event rates in broad categories of patients. BMJ. 2015;350:h870.[PubMed][Google Scholar]
  • 23. Moskalewicz A, Oremus MNo clear choice between Newcastle-Ottawa Scale and Appraisal Tool for Cross-Sectional Studies to assess methodological quality in cross-sectional studies of health-related quality of life and breast cancer. J Clin Epidemiol. 2020;120:94–103.[PubMed][Google Scholar]
  • 24. Wells GA, Shea B, O'Connell D. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. 2019. [PubMed]
  • 25. Sterne JAC, Savović J, Page MJRoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366[PubMed][Google Scholar]
  • 26. Guyatt G, Oxman AD, Akl EAGRADE guidelines, 1: introduction—GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011;64:383–394.[PubMed][Google Scholar]
  • 27. Guyatt GH, Thorlund K, Oxman ADGRADE guidelines, 13: preparing summary of findings tables and evidence profiles—continuous outcomes. J Clin Epidemiol. 2013;66:173–183.[PubMed][Google Scholar]
  • 28. Santesso N, Carrasco-Labra A, Langendam MImproving GRADE evidence tables part 3: detailed guidance for explanatory footnotes supports creating and understanding GRADE certainty in the evidence judgments. J Clin Epidemiol. 2016;74:28–39.[PubMed][Google Scholar]
  • 29. Santesso N, Glenton C, Dahm PGRADE guidelines, 26: informative statements to communicate the findings of systematic reviews of interventions. J Clin Epidemiol. 2020;119:126–135.[PubMed][Google Scholar]
  • 30. Higgins JP, Thompson SGControlling the risk of spurious findings from meta-regression. Stat Med. 2004;23:1663–1682.[PubMed][Google Scholar]
  • 31. Jefferson T, Jones M, Al Ansari LAPhysical interventions to interrupt or reduce the spread of respiratory viruses, part 1: face masks, eye protection and person distancing—systematic review and meta-analysis. medRxiv. 2020 doi: 10.1101/2020.03.30.20047217. published online April 7. (preprint). [[PubMed][Google Scholar]
  • 32. Sutton AJ, Abrams KRBayesian methods in meta-analysis and evidence synthesis. Stat Methods Med Res. 2001;10:277–303.[PubMed][Google Scholar]
  • 33. Goligher EC, Tomlinson G, Hajage DExtracorporeal membrane oxygenation for severe acute respiratory distress syndrome and posterior probability of mortality benefit in a post hoc Bayesian analysis of a randomized clinical trial. JAMA. 2018;320:2251–2259.[PubMed][Google Scholar]
  • 34. Alraddadi BM, Al-Salmi HS, Jacobs-Slifka KRisk factors for Middle East respiratory syndrome coronavirus infection among healthcare personnel. Emerg Infect Dis. 2016;22:1915–1920.[Google Scholar]
  • 35. Arwady MA, Alraddadi B, Basler CMiddle East respiratory syndrome coronavirus transmission in extended family, Saudi Arabia, 2014. Emerg Infect Dis. 2016;22:1395–1402.[Google Scholar]
  • 36. Bai Y, Wang X, Huang QSARS-CoV-2 infection in health care workers: a retrospective analysis and a model study. medRxiv. 2020 doi: 10.1101/2020.03.29.20047159. published online April 1. (preprint). [[PubMed][Google Scholar]
  • 37. Burke RM, Balter S, Barnes EEnhanced contact investigations for nine early travel-related cases of SARS-CoV-2 in the United States. medRxiv. 2020 doi: 10.1101/2020.04.27.20081901. published online May 3. (preprint). [[PubMed][Google Scholar]
  • 38. Caputo KM, Byrick R, Chapman MG, Orser BJ, Orser BAIntubation of SARS patients: infection and perspectives of healthcare workers. Can J Anaesth. 2006;53:122–129.[PubMed][Google Scholar]
  • 39. Chen WQ, Ling WH, Lu CYWhich preventive measures might protect health care workers from SARS? BMC Public Health. 2009;9:81.[Google Scholar]
  • 40. Cheng H-Y, Jian S-W, Liu D-P, Ng T-C, Huang W-T, Lin H-HHigh transmissibility of COVID-19 near symptom onset. medRxiv. 2020 doi: 10.1101/2020.03.18.20034561. published online March 19. (preprint). [[PubMed][Google Scholar]
  • 41. Wang X, Pan Z, Cheng ZAssociation between 2019-nCoV transmission and N95 respirator use. J Hosp Infect. 2020;105:104–105.[Google Scholar]
  • 42. Ha LD, Bloom SA, Hien NQLack of SARS transmission among public hospital workers, Vietnam. Emerg Infect Dis. 2004;10:265–268.[Google Scholar]
  • 43. Hall AJ, Tokars JI, Badreddine SAHealth care worker contact with MERS patient, Saudi Arabia. Emerg Infect Dis. 2014;20:2148–2151.[Google Scholar]
  • 44. Heinzerling A, Stuckey MJ, Scheuer TTransmission of COVID-19 to health care personnel during exposures to a hospitalized patient: Solano County, California, February 2020. MMWR Morb Mortal Wkly Rep. 2020;69:472–476.[PubMed][Google Scholar]
  • 45. Ho KY, Singh KS, Habib AGMild illness associated with severe acute respiratory syndrome coronavirus infection: lessons from a prospective seroepidemiologic study of health-care workers in a teaching hospital in Singapore. J Infect Dis. 2004;189:642–647.[Google Scholar]
  • 46. Van Kerkhove MD, Alaswad S, Assiri ATransmissibility of MERS-CoV infection in closed setting, Riyadh, Saudi Arabia, 2015. Emerg Infect Dis J. 2019;25:1802–1809.[Google Scholar]
  • 47. Ki HK, Han SK, Son JS, Park SORisk of transmission via medical employees and importance of routine infection-prevention policy in a nosocomial outbreak of Middle East respiratory syndrome (MERS): a descriptive analysis from a tertiary care hospital in South Korea. BMC Pulm Med. 2019;19:190.[Google Scholar]
  • 48. Kim T, Jung J, Kim SMTransmission among healthcare worker contacts with a Middle East respiratory syndrome patient in a single Korean centre. Clin Microbiol Infect. 2016;22:e11–e13.[Google Scholar]
  • 49. Kim CJ, Choi WS, Jung YSurveillance of the Middle East respiratory syndrome (MERS) coronavirus (CoV) infection in healthcare workers after contact with confirmed MERS patients: incidence and risk factors of MERS-CoV seropositivity. Clin Microbiol Infect. 2016;22:880–886.[Google Scholar]
  • 50. Lau JTF, Lau M, Kim JH, Tsui HY, Tsang T, Wong TWProbable secondary infections in households of SARS patients in Hong Kong. Emerg Infect Dis. 2004;10:235–243.[Google Scholar]
  • 51. Liu W, Tang F, Fang LQRisk factors for SARS infection among hospital healthcare workers in Beijing: a case control study. Trop Med Int Health. 2009;14(suppl 1):52–59.[PubMed][Google Scholar]
  • 52. Liu ZQ, Ye Y, Zhang H, Guohong X, Yang J, Wang JLAnalysis of the spatio-temporal characteristics and transmission path of COVID-19 cluster cases in Zhuhai. Trop Geogr. 2020 doi: 10.13284/j.cnki.rddl.003228. published online March 12. [[PubMed][Google Scholar]
  • 53. Loeb M, McGeer A, Henry BSARS among critical care nurses, Toronto. Emerg Infect Dis. 2004;10:251–255.[Google Scholar]
  • 54. Ma HJ, Wang HW, Fang LQA case-control study on the risk factors of severe acute respiratory syndromes among health care workers. Zhonghua Liu Xing Bing Xue Za Zhi. 2004;25:741–744. (in Chinese). [[PubMed][Google Scholar]
  • 55. Nishiura H, Kuratsuji T, Quy TRapid awareness and transmission of severe acute respiratory syndrome in Hanoi French Hospital, Vietnam. Am J Trop Med Hyg. 2005;73:17–25.[PubMed][Google Scholar]
  • 56. Nishiyama A, Wakasugi N, Kirikae TRisk factors for SARS infection within hospitals in Hanoi, Vietnam. Jpn J Infect Dis. 2008;61:388–390.[PubMed][Google Scholar]
  • 57. Olsen SJ, Chang HL, Cheung TYTransmission of the severe acute respiratory syndrome on aircraft. N Engl J Med. 2003;349:2416–2422.[PubMed][Google Scholar]
  • 58. Park BJ, Peck AJ, Kuehnert MJLack of SARS transmission among healthcare workers, United States. Emerg Infect Dis. 2004;10:244–248.[PubMed][Google Scholar]
  • 59. Park JY, Kim BJ, Chung KH, Hwang YIFactors associated with transmission of Middle East respiratory syndrome among Korean healthcare workers: infection control via extended healthcare contact management in a secondary outbreak hospital. Respirology. 2016;21(suppl 3):89. (abstr APSR6-0642). [PubMed][Google Scholar]
  • 60. Peck AJ, Newbern EC, Feikin DR. Lack of SARS transmission and U.S. SARS case-patient. Emerg Infect Dis. 2004;10:217–224.
  • 61. Pei LY, Gao ZC, Yang ZInvestigation of the influencing factors on severe acute respiratory syndrome among health care workers. Beijing Da Xue Xue Bao Yi Xue Ban. 2006;38:271–275.[PubMed][Google Scholar]
  • 62. Rea E, Laflèche J, Stalker SDuration and distance of exposure are important predictors of transmission among community contacts of Ontario SARS cases. Epidemiol Infect. 2007;135:914–921.[Google Scholar]
  • 63. Reuss A, Litterst A, Drosten CContact investigation for imported case of Middle East respiratory syndrome, Germany. Emerg Infect Dis. 2014;20:620–625.[Google Scholar]
  • 64. Reynolds MG, Anh BH, Thu VHFactors associated with nosocomial SARS-CoV transmission among healthcare workers in Hanoi, Vietnam, 2003. BMC Public Health. 2006;6:207.[Google Scholar]
  • 65. Ryu B, Cho SI, Oh MDSeroprevalence of Middle East respiratory syndrome coronavirus (MERS-CoV) in public health workers responding to a MERS outbreak in Seoul, Republic of Korea, in 2015. Western Pac Surveill Response J. 2019;10:46–48.[Google Scholar]
  • 66. Scales DC, Green K, Chan AKIllness in intensive care staff after brief exposure to severe acute respiratory syndrome. Emerg Infect Dis. 2003;9:1205–1210.[Google Scholar]
  • 67. Seto WH, Tsang D, Yung RWHEffectiveness of precautions against droplets and contact in prevention of nosocomial transmission of severe acute respiratory syndrome (SARS) Lancet. 2003;361:1519–1520.[Google Scholar]
  • 68. Teleman MD, Boudville IC, Heng BH, Zhu D, Leo YSFactors associated with transmission of severe acute respiratory syndrome among health-care workers in Singapore. Epidemiol Infect. 2004;132:797–803.[Google Scholar]
  • 69. Tuan PA, Horby P, Dinh PNSARS transmission in Vietnam outside of the health-care setting. Epidemiol Infect. 2007;135:392–401.[Google Scholar]
  • 70. Wang Q, Huang X, Bai YEpidemiological characteristics of COVID-19 in medical staff members of neurosurgery departments in Hubei province: a multicentre descriptive study. medRxiv. 2020 doi: 10.1101/2020.04.20.20064899. published online April 24. (preprint). [[PubMed][Google Scholar]
  • 71. Wiboonchutikul S, Manosuthi W, Likanonsakul SLack of transmission among healthcare workers in contact with a case of Middle East respiratory syndrome coronavirus infection in Thailand. Antimicrob Resist Infect Control. 2016;5:21.[Google Scholar]
  • 72. Wilder-Smith A, Teleman MD, Heng BH, Earnest A, Ling AE, Leo YSAsymptomatic SARS coronavirus infection among healthcare workers, Singapore. Emerg Infect Dis. 2005;11:1142–1145.[Google Scholar]
  • 73. Wong TW, Lee CK, Tam WCluster of SARS among medical students exposed to single patient, Hong Kong. Emerg Infect Dis. 2004;10:269–276.[Google Scholar]
  • 74. Wu J, Xu F, Zhou WRisk factors for SARS among persons without known contact with SARS patients, Beijing, China. Emerg Infect Dis. 2004;10:210–216.[Google Scholar]
  • 75. Yin WW, Gao LD, Lin WSEffectiveness of personal protective measures in prevention of nosocomial transmission of severe acute respiratory syndrome. Zhonghua Liu Xing Bing Xue Za Zhi. 2004;25:18–22.[PubMed][Google Scholar]
  • 76. Yu ITS, Wong TW, Chiu YL, Lee N, Li YTemporal-spatial analysis of severe acute respiratory syndrome among hospital inpatients. Clin Infect Dis. 2005;40:1237–1243.[Google Scholar]
  • 77. Yu IT, Xie ZH, Tsoi KKWhy did outbreaks of severe acute respiratory syndrome occur in some hospital wards but not in others? Clin Infect Dis. 2007;44:1017–1025.[Google Scholar]
  • 78. Verbeek JH, Rajamaki B, Ijaz SPersonal protective equipment for preventing highly infectious diseases due to exposure to contaminated body fluids in healthcare staff. Cochrane Database Syst Rev. 2019;7[Google Scholar]
  • 79. MacIntyre CR, Wang Q, Seale HA randomized clinical trial of three options for N95 respirators and medical masks in health workers. Am J Respir Crit Care Med. 2013;187:960–966.[PubMed][Google Scholar]
  • 80. Campbell A. Chapter eight: it's not about the mask: SARS Commission final report, volume 3. December, 2006. [PubMed]
  • 81. Webster POntario issues final SARS Commission report. Lancet. 2007;369:264.[Google Scholar]
  • 82. Rimmer ACOVID-19: experts question guidance to reuse PPE. BMJ. 2020;369[PubMed][Google Scholar]
  • 83. Mackenzie DReuse of N95 masks. Engineering. 2020 doi: 10.1016/j.eng.2020.04.003. published online April 13. ] [[Google Scholar]
  • 84. Greenhalgh T, Schmid MB, Czypionka T, Bassler D, Gruer LFace masks for the public during the covid-19 crisis. BMJ. 2020;369[PubMed][Google Scholar]
  • 85. Bahl P, Doolan C, de Silva C, Chughtai AA, Bourouiba L, MacIntyre CRAirborne or droplet precautions for health workers treating coronavirus disease 2019? J Infect Dis. 2020 doi: 10.1093/infdis/jiaa189. published online April 16. ] [[Google Scholar]
  • 86. Schünemann HJ, Khabsa J, Solo KVentilation techniques and risk for transmission of coronavirus disease, including COVID-19: a living systematic review of multiple streams of evidence. Ann Intern Med. 2020 doi: 10.7326/M20-2306. published online May 22. ] [[Google Scholar]
  • 87. Leung NHL, Chu DKW, Shiu EYCRespiratory virus shedding in exhaled breath and efficacy of face masks. Nat Med. 2020;26:676–680.[PubMed][Google Scholar]
Collaboration tool especially designed for Life Science professionals.Drag-and-drop any entity to your messages.