Effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality: systematic review and meta-analysis
BMJ 2021; 375 doi: https://doi.org/10.1136/bmj-2021-068302 (Published 18 November 2021) Cite this as: BMJ 2021;375:e068302Linked Editorial
Public health measures for covid-19
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Dear Editor.
Talic and colleagues [1] find that “several personal protective and social measures, including handwashing, mask wearing, and physical distancing, are associated with reductions in the incidence of Covid-19”. While their introduction states that “Substantial benefits in reducing mortality were observed in countries with universal lockdowns in place, such as Australia, New Zealand, Singapore, and China” they maintain that “universal lockdowns are not sustainable.” They have been, however, demonstrably lifesaving when applied at the onset of the pandemic.
For example, the U.S. population has experienced >150-fold the number of Covid-19-related deaths than the official number in China, a country with a population >4 times that of the U.S. Furthermore, after an initial steep rise in reported Covid-19-related deaths in China, by late April 2020 deaths had largely plateaued, such that <1000 deaths in China have been recorded in the whole of 2021 according to the WHO tally [2]. Since the plateau commenced at a time when no more than one quarter of China's population could possibly have received a single dose of the locally available SARS-CoV-2 vaccine, powerful public health measures in China must have quelled Covid-19 infection, hospitalization and deaths.
Prominent among these public health measures was a very strict, early, universal population lock-down, suspension of public transport, border protection, and widespread use of a cell phone app. that notified individuals of their exposure status and instructed required responses. While the West may view some such measures as overbearing social control, they nevertheless represent public health initiatives that were overwhelmingly more successful than those adopted in most of other countries. China once topped the John Hopkins Resource Center's Covid-19 Dashboard but the U.S. has occupied that position throughout 2021 (followed currently by Germany #2, UK #3, Russia #4 and France #5), while China has dropped to position #123 [3]. Although prolonged periods of lockdown have had mental health implications, especially for children and adolescents [4], elder care has been disrupted and economic impact severe [1,5], implementation of a universal lockdown at the onset of a pandemic (combined with personal protection and social measures), as practiced in China [6] and New Zealand [7], is an invaluable component of the public health toolkit [8] for future use in global pandemics comparable to Covid-19.
References
01. Talic S, Shah S, Wild H, Gasevic D, Maharaj A, Ademi Z, et al. Effectiveness of public health measures in reducing the incidence of COVID-19, SARS-CoV-2 transmission, and COVID-19 mortality: systematic review and meta-analysis BMJ 2021; 375 :e068302 doi:10.1136/bmj-2021-068302.
02. World Health Organization. WHO Coronavirus (COVID-19) Dashboard for China. https://covid19.who.int/region/wpro/country/cn
03. John Hopkins Resource Center's Covid-19 Dashboard. https://coronavirus.jhu.edu/map.html
04. Singh S, Roy D, Sinha K, Parveen S, Sharma G, Joshi G. Impact of COVID-19 and lockdown on mental health of children and adolescents: A narrative review with recommendations. Psychiatry Res. 2020;293:113429. doi:10.1016/j.psychres.2020.113429
05. Cousins S. New Zealand eliminates COVID-19. Lancet. 2020;395(10235):1474. doi: 10.1016/S0140-6736(20)31097-7. PMID: 32386582; PMCID: PMC7252131.
06. Sayin Kasar K, Karaman E. Life in lockdown: Social isolation, loneliness and quality of life in the elderly during the COVID-19 pandemic: A scoping review. Geriatr Nurs. 2021;42:1222-1229. doi: 10.1016/j.gerinurse.2021.03.010.
07. Rozelle S, Rahimi H, Wang H, Dill E. Lockdowns are protecting China’s rural families from COVID-19, but the economic burden is heavy. In Covid-19 and Global Food Security. Washington DC: International Food Policy Research Institute, 2020;ch 11:52-55. doi.org/10.2499/p15738coll2.133762_11
08. Newman K. Tognotti E. Lessons from the history of quarantine, from plague to influenza A. Emerg Infect Dis. 2013;19:254-259. doi:10.3201/eid1902.120312
Competing interests: No competing interests
Dear Editor,
We congratulate Talic et al. for conducting a large review and meta-analysis on the very difficult topic of efficacy of public health measures against SARS-CoV-2 transmission. The area is challenged by marked heterogeneity in methodology, combinations of measures, the participants compliance etc. Our experience stems from the Danish face mask randomized trial of 6,000 participants, the DANMASK-19 trial. The present meta-analysis and the reached conclusions as well as some of the peer review comments raise some concerns.
First, the only RCT in the final version of the paper, the DANMASK-19 trial (published November 18, 2020) was surprisingly not included in the initially submitted version of the meta-analysis (submitted March 3, 2021) and a reviewer noticed: “(Page 49: “Third, no randomized trials have been published at the time when search was conducted to guide the nonpharmacological management of COVID-19.” This is confusing since authors cite a RCT from Denmark evaluating masks in the community setting on page 44 (ref) 139. Please clarify why this RCT wasn’t included in the systematic review? Cited in discussion, but not results.).” Not including the only RCT on the subject in your systematic review, but including it in your discussion seems counterintuitive to your “…main strength of this systematic review was the use of a comprehensive search strategy to identify and select studies for review and thereby minimise selection bias.” Considering that 10 authors of the meta-analysis screened the literature and missed the DANMASK-19 paper for the analysis - an all-time top 5 article according to Altmetric, we are concerned that applied study selection criteria for the meta-analysis may not have been adequate and other important papers may have been missed and skewed the conclusions.
Second, we are surprised that the authors classified equal risk of bias (moderate) for a classically designed and conducted RCT of >6,000 individuals and “natural experiments” (e.g. Krishnamachari et al, ref 43), which is inherently prone to bias due to introduction of masks simultaneously with many other measures. Under methods the authors state that the Rob 2 tool was used to assess risk of bias of RCT´s, however the RCT rating is detailed in “Supplementary file 2, Table 2. ROBINS-2 Risk of Bias Randomised Control Study”. On this basis it is unclear if the authors used the Rob 2 tool as stated in methods or ROBINS-2 as stated in supplementary materials (ROBINS an abbreviation for “Risk of Bias in Non-randomized Studies”). The categories for ROBINS-I scores are low, moderate, serious and critical, whereas the Rob 2 scores are low, some concern and high risk of bias. Thus, the rating of the RCT as “moderate”, does not disclose which tool was applied.
Furthermore, according to Figure 5 the authors weight both the “natural experiment” by Krishnamachari and the internet survey by Xu et al. higher than the RCT in the meta-analysis. The methods for including weighting natural experiments and RCT´s in one model is not clearly explained. In addition, the authors found an I2 value of 84% with regards to heterogeneity and Cochrane Handbook (1) states that an I2 value between 75%-100% has considerable heterogeneity. Thus, the heterogeneity of 84% challenges the interpretation of the meta-analysis.
Third, in the discussion the authors stated that “Additional empirical evidence from a recent randomised controlled trial (originally published as a preprint) indicates that mask wearing achieved a 9.3% reduction in seroprevalence of symptomatic SARS-CoV-2 infection (primary outcome) and an 11.9% reduction in the prevalence of covid-19-like symptoms.” This study was a large cluster-randomized trial from rural Bangladesh, however the randomization was not between mask wearing vs. control as referred to by Talic et al. The randomization was to a mask promotion strategy on village and household levels versus no mask promotion. Mask-wearing in this study “was assessed through direct observation in public locations including mosques, markets, the main entrance roads to villages, and tea stalls.” Talic et al. are of course not responsible by any means for the methodology of this study, however they are responsible for the presentation of the study in their discussion section. Perhaps more interesting to discuss the study “Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Personal Protective and Environmental Measures” (2) on influenza that “identified 10 RCTs that reported estimates of the effectiveness of face masks. In pooled analysis, they found no significant reduction in influenza transmission by use of face masks (RR 0.78, 95% CI 0.51–1.20)”.
Fourth, in the abstract the authors stated that the meta-analysis indicates that “…a reduction in incidence of covid-19 associated with handwashing (relative risk 0.47, 95% confidence interval 0.19 to 1.12, I2=12%), mask wearing (0.47, 0.29 to 0.75, I2=84%), and physical distancing (0.75, 0.59 to 0.95, I2=87%)”. Thus, according to the reported relative risks the effect of handwashing seems to be non-significant. Nonetheless, it was concluded in the abstract: “…that several personal protective and social measures, including handwashing, mask wearing, and physical distancing are associated with reductions in the incidence covid-19.”
It is also striking – and not commented on by the authors - that the meta-analysis reported a relative risk of SARS-CoV-2 transmission in wearers of masks of 0.47 (95% CI 0.29-0.75). The DANMASK-19 RCT was powered to detect a 50% reduction, which was found by the current study, but the RCT only found an OR of 0.82 (95% CI 0.54-1.23).
This study has attracted significant attention; however, decision makers, public media and lay persons may only read the conclusion and may not take the potentially considerable methodological flaws into account. The strong focus on observational studies with marked risk of bias, the unclear assessments of bias as well as of weighting and the high level of heterogeneity combined with the concluded much higher effect of mask protection as compared to findings in RCTs is worrisome.
Means to reduce the risk of SARS-CoV-2 transmission are of crucial importance globally, and proper studies reaching robust results and careful interpretations to the public are keys to improve compliance and general trust in health care recommendations.
Thanks,
Dr. Johan, Professor Kasper and Professor Henning
Copenhagen, Denmark
References
1. Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.2 (updated February 2021). Cochrane, 2021.
2. Xiao J, Shiu E, Gao H, Wong JY, Fong MW, Ryu S, et al. Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Personal Protective and Environmental Measures. Emerg Infect Dis. 2020;26(5):967-975. https://doi.org/10.3201/eid2605.190994
Competing interests: No competing interests
Dear Editor,
We have some concerns regarding the methodology of the review (BMJ 2021;375:e068302) and included meta-analysis that we would like to address in the following.
The included studies all comprise patients that are not vaccinated and therefore this meta-analysis does not represent the current population in many countries. The interventions are highly heterogeneous and therefore a pooling of all these studies should be done with great caution or maybe not at all. The comparison groups in the included studies might also have large heterogeneity and a spill over effect in the studies where the two groups are compared simultaneously in time, should be considered. The bias assessment that the authors have done with the ROBINS-I tool, shows that there is high risk of bias in many of the included studies, especially regarding risk of confounding. The results of the bias assessment should therefore make readers wary of the conclusions drawn from this review.
When looking at a meta-analysis, it is important to pay close attention to heterogeneity. The statistical heterogeneity is measured by the I2 value. For two of the meta-analyses in the paper, the I2 value is 84% (mask wearing) and 87% (physical distancing). According to the Cochrane Handbook (1) an I2 value above 75% represents considerable heterogeneity.
However, the authors have not stated any pre-planned methods of how to address heterogeneity.
According to the Cochrane Handbook, there are several strategies for addressing heterogeneity:
1. Check again that the data are correct. We assume that the authors have done so, and that incorrect data do not explain the heterogeneity.
2. Do not do a meta-analysis. A systematic review need not contain any meta-analyses. If there is considerable variation in results, and particularly if there is inconsistency in the direction of effect, it may be misleading to quote an average value for the intervention effect.
Several other options are listed in the Cochrane Handbook including sensitivity analyses to look for reasons for heterogeneity. We believe that the most methodologically correct thing to do in this case would be to not perform the meta-analysis, if heterogeneity is considerable meaning I2 is above 75% or if study design is very different between studies (2). For mask wearing there was only one randomized controlled trial (that did not show an effect of wearing a mask in a non-vaccinated population) and the other study designs included in the meta-analysis was case-control, natural experiment, cross sectional comparative, and a retrospective cohort study. Nevertheless, these five studies with very different study designs were included in the meta-analysis, and with an I2 value of 84%.
In conclusion, we believe that two meta-analyses (mask wearing and physical distancing) with large statistical heterogeneity should not have been part of the review, as they are potentially misleading. Therefore, the statement that the authors make: “This systematic review identified a statistically significant reduction in the incidence of covid-19 through the implementation of mask wearing and physical distancing” is not correct, as the meta-analyses should not have been done since the authors could neither explore nor explain the heterogenity. Many readers, including public media, lay persons, as well as decision makers, will simply look at the diamond at the bottom of the forrest plot and take it as the truth. Thus, because of these serious methodological flaws and because we have no data on these public health measures in a vaccinated population, this meta-analysis cannot be used to argue for mask wearing or physical distancing in countries with very high vaccination rates.
Kristoffer Andresen, MD, PhD, managing editor
Jacob Rosenberg, MD, DSc, professor, coordinating editor
Cochrane Colorectal
email: cochranecolorectal@gmail.com
1. Cochrane Handbook for Systematic Reviews of Interventions. https://training.cochrane.org/handbook (December 2, 2021).
2. Burcharth J, Pommergaard H-C, Rosenberg J. Performing and evaluating meta-analyses. Surgery 2015; 157: 189-93.
Competing interests: No competing interests
Dear Editor
We read with interest the systematic review and meta-analysis conducted by Talic and colleagues on the effectiveness of mask-wearing, handwashing, and physical distancing on the incidence of SARS-CoV-2 infection.[1] We question the validity of the pooled estimates because of the low quality of the studies included.
For the mask-wearing analyses, one randomised controlled trial (RCT)[2] and five observational[3-7] studies were included, but all have potentially serious or critical flaws that limit the interpretation of the estimates they contribute to the meta-analysis. The limitations of the DANMASK-19 RCT[2] have been discussed elsewhere[8-10] with one of the most concerning being the use of serologic outcomes during a 1-month follow-up period, when this is not much longer than the time taken for antibodies to develop after an infection, meaning there would be considerable dilution of any effect of the mask intervention.[9] The other 5 studies included cohort,[6] case-control,[3 4] and cross-sectional[5] studies with potential for substantial reporting biases, and an ecologic study examining the effect of mask mandates (on top of existing mask use in the community) on SARS-CoV-2 incidence.[7] Ecologic data on mask effectiveness is of limited value and remain difficult to interpret given the multiple interventions simultaneously deployed, behavioural changes, and heterogenous reporting. Mask mandates are different from the intervention of mask distribution and instruction in the RCT[2] or the exposures of mask compliance in the other 4 observational studies.[3-6] Furthermore, even among the observational non-ecologic studies, the measurements of the mask compliance are different. Wang et al. assessed mask wearing at home (both index cases and contacts),[6] whereas Lio et al. and Xu et al. assessed mask wearing outside the household,[4 5] and Doung-Ngern et al. assessed mask wearing (contacts only) when in contact with the index cases regardless of setting.[3] One unfortunate observation is that the two most problematic of these observational studies (the ecologic study and the cross-sectional online survey) carried the most weight (50.2%) in the mask meta-analysis.[5 7]
While Talic et al. published a pooled mask effectiveness estimate of 53% reduction, we believe it is not a valid estimate of real-world effectiveness of masks and agree with the linked editorial by Glasziou et al.[11] that such high estimates encompass several overlapping protective behaviours and interventions. If one is to believe the 53% estimate, it would mean DANMASK-19 was not underpowered as is already widely acknowledged. Had DANMASK-192 (18% reduction in infection risk due to surgical masks) and the Bangladesh preprint mask cluster RCT[12] (9% reduction in symptomatic infection) been combined in a systematic review and meta-analysis, analyses would have resulted in an estimate of approximately 10%. Although Talic et al. mentioned the preprint RCT, they did not include it in their analyses. Evidence points toward an effect size of masks that is likely between higher estimates seen in observational studies and lower ones reported in RCTs—perhaps in the range 10%–20%.[8 9 13 14] This small-to-moderate effect of masks, particularly in households or settings with sustained stronger viral exposures, substantiates the need for a combination of non-pharmaceutical interventions (NPIs) to achieve greater prevention of SARS-CoV-2 transmission.[8 15] To complicate matters further, a single estimate of mask effectiveness is unrealistic given the heterogeneity due to setting, wearer’s adherence, type of mask, etc.[8]
The three studies on hand hygiene[3-5] were a subset of the same studies included in the mask analysis and have similar risks of reporting biases and variations in the measurement of exposures. There are 5 studies included in physical distancing analysis[3 5 6 16 17] and three of them overlap with the studies in the mask analysis.[3 5 6] The other two studies are an ecologic study[17] and a retrospective cohort study.[16] Vokó et al. examined the effects of stay-at-home orders on SARS-CoV-2 incidence and have similar problems as the ecologic study by Krishnamachari et al. The measurements of the compliance to physical distancing are different, where van den Berg et al. and Xu et al. only measured distance and Doung-Ngern et al. and Wang et al. measured both distance and contact frequency or duration.
There are several minor errors in the report which are concerning. For example, most of the “Relative risk” estimates in the facemask meta-analysis figure seem to be odds ratios based on the results in the original articles.[2-4 6] The confidence intervals in the meta-analysis Figure 5 are inconsistent with those presented in Doung-Ngern et al., Lio et al., and Wang et al.[3 4 6] We were unable to determine how relative risks (or odds ratios) of 0.77 (95% CI 0.71–0.84) for Krishnamachari et al. and 0.34 (95% CI 0.24–0.48) for Xu et al. were derived from the adjusted rate ratios and unadjusted risk ratio or adjusted odds ratio in the original articles, respectively.[5 7]
Additionally, Talic et al. assessed the risk of bias for each included study, but did not rate the quality of evidence. According to the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) framework, assessing risk of bias is a component in quality assessment for evidence.[18] Under the GRADE framework, the quality of evidence for RCTs starts at high-quality and observational studies at low-quality evidence and then the ratings could go up or down based on several factors, including risk of bias.[18] As there are potentially substantial biases in the seven observational studies in the meta-analysis, these studies are likely to be low- or very low-quality of evidence. It may therefore not be justified to include any of them in a meta-analysis.
Systematic reviews and meta-analyses on the effectiveness of various NPIs are valuable to provide real-world data evidence. However, the validity of such analyses depends on the quality of the underlying data. The most important contribution of Talic et al. was to identify the serious deficiencies in available data, sadly, more than 18 months into the pandemic. Further high-quality original studies and careful reviews that provide reliable estimates and acknowledge study limitations in the context of appropriate data interpretation are needed to avoid unrealistic expectations or overselling of the effectiveness of some NPIs.[14]
Jingyi Xiao [1], Kevin Escandón [2], Benjamin J. Cowling [1,3]
1. WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
2. Division of Infectious Diseases and International Medicine, University of Minnesota, Minneapolis, MN, USA
3. Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China
References
1. Talic S, Shah S, Wild H, et al. Effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality: systematic review and meta-analysis. BMJ 2021;375:e068302. doi: 10.1136/bmj-2021-068302 [published Online First: 2021/11/19]
2. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of Adding a Mask Recommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers : A Randomized Controlled Trial. Ann Intern Med 2021;174(3):335-43. doi: 10.7326/m20-6817 [published Online First: 2020/11/19]
3. Doung-Ngern P, Suphanchaimat R, Panjangampatthana A, et al. Case-Control Study of Use of Personal Protective Measures and Risk for SARS-CoV 2 Infection, Thailand. Emerg Infect Dis 2020;26(11):2607-16. doi: 10.3201/eid2611.203003 [published Online First: 2020/09/16]
4. Lio CF, Cheong HH, Lei CI, et al. Effectiveness of personal protective health behaviour against COVID-19. BMC Public Health 2021;21(1):827. doi: 10.1186/s12889-021-10680-5 [published Online First: 2021/05/01]
5. Xu H, Gan Y, Zheng D, et al. Relationship Between COVID-19 Infection and Risk Perception, Knowledge, Attitude, and Four Nonpharmaceutical Interventions During the Late Period of the COVID-19 Epidemic in China: Online Cross-Sectional Survey of 8158 Adults. J Med Internet Res 2020;22(11):e21372. doi: 10.2196/21372 [published Online First: 2020/10/28]
6. Wang Y, Tian H, Zhang L, et al. Reduction of secondary transmission of SARS-CoV-2 in households by face mask use, disinfection and social distancing: a cohort study in Beijing, China. BMJ Glob Health 2020;5(5) doi: 10.1136/bmjgh-2020-002794 [published Online First: 2020/05/30]
7. Krishnamachari B, Morris A, Zastrow D, et al. The role of mask mandates, stay at home orders and school closure in curbing the COVID-19 pandemic prior to vaccination. Am J Infect Control 2021;49(8):1036-42. doi: 10.1016/j.ajic.2021.02.002 [published Online First: 2021/02/13]
8. Escandón K, Rasmussen AL, Bogoch II, et al. COVID-19 false dichotomies and a comprehensive review of the evidence regarding public health, COVID-19 symptomatology, SARS-CoV-2 transmission, mask wearing, and reinfection. BMC Infectious Diseases 2021;21(1):1-47.
9. Cowling BJ, Leung GM. Face masks and COVID-19: don’t let perfect be the enemy of good. Eurosurveillance 2020;25(49):2001998.
10. Frieden TR, Cash-Goldwasser S. Of Masks and Methods. Ann Intern Med 2021;174(3):421-22. doi: 10.7326/m20-7499 [published Online First: 2020/11/19]
11. Glasziou PP, Michie S, Fretheim A. Public health measures for covid-19. BMJ 2021;375:n2729. doi: 10.1136/bmj.n2729 [published Online First: 2021/11/19]
12. Abaluck J, Kwong LH, Styczynski A, et al. The Impact of Community Masking on COVID-19: A Cluster Randomized Trial in Bangladesh 2021. Available from: https://www.poverty-action.org/publication/impact-community-masking-covi....
13. Brainard J, Jones NR, Lake IR, et al. Community use of face masks and similar barriers to prevent respiratory illness such as COVID-19: a rapid scoping review. Eurosurveillance 2020;25(49):2000725.
14. Brosseau LM, Ulrich A, Escandón K, et al. COMMENTARY: What can masks do? Part 2: What makes for a good mask study — and why most fail 2021. Available from: https://www.cidrap.umn.edu/news-perspective/2021/10/commentary-what-can-....
15. Cheng Y, Ma N, Witt C, et al. Face masks effectively limit the probability of SARS-CoV-2 transmission. Science 2021 doi: 10.1126/science.abg6296 [published Online First: 2021/05/22]
16. van den Berg P, Schechter-Perkins EM, Jack RS, et al. Effectiveness of 3 versus 6 ft of physical distancing for controlling spread of coronavirus disease 2019 among primary and secondary students and staff: A retrospective, statewide cohort study. Clin Infect Dis 2021
17. Vokó Z, Pitter JG. The effect of social distance measures on COVID-19 epidemics in Europe: an interrupted time series analysis. GeroScience 2020;42(4):1075-82.
18. Guyatt G, Oxman AD, Akl EA, et al. GRADE guidelines: introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol 2011;64(4):383-94.
Competing interests: No competing interests
Dear Editor,
I was somewhat confused by the summary of results in Table 5 citing reference-68 for Xu et al, as that paper does not contain the results stated. From correspondence with the author, I gather this is mislabelled and should cite reference 60. If you could correct this error, or otherwise indicate it, that might save others the same confusion.
I do have some queries about 2 of the studies used as input into the meta-analysis.
Xu et al, reference 60, doi:10.2196/21372, is an analysis of self-reported results via online Internet survey - conducted via WeChat. Participants recruited by seeding the survey to students and staff at a medical college, and a CDC - along with whomever the study team could recruit. The authors are explicit this was not a random sample.
Can I ask what the reasoning was for assigning an equal risk of bias to this as to the Bundgaard, et al - a well-designed, decently powered, RCT? Further, can I ask why the Internet-survey results of Xu et al have been given /more/ weight than the RCT of Bundgaard?
Krishnamachari et al, doi:10.1016/j.ajic.2021.02.002, ref 43, an observational study rated at "serious
or critical" risk of bias. Yet this was also weighted more in the meta-analysis than the one RCT of Bundgaard, et al.
Krishnamachari is - as with all observational studies at that scale, over such a wide geographic range (inc. large disparities in climate and factors affecting seasonal forcing) - surely is at serious risk of many confounding factors, hence that bias rating. Xu et al, as as a completely non-systematically sampled Internet questionnaire surely is at even greater risk of bias.
So this weighting of these studies at or above that of the RCT is curious. Could the authors give a reasoning to justify this?
I note that the result of the meta-analysis, of 0.47 RR, is substantially greater than the Bundgaard RCT result. Yet the Bundgaard RCT was designed to be able to clearly detect a 50% effect, at the designed for prevalence - which prevailed over the study period. And it did not find any strong effect.
For this meta-analysis to find a >50% effect, at odds with the RCT evidence that should clearly have detected such a large effect but did not, suggests a problem. Particularly when the 53% effect in this meta-analysis relies so heavily on observational, non-randomised. A plausible explanation is that those observational studies are heavily confounded and unreliable - and have been over-weighted.
Can the authors explain this discrepancy, and explain why the observational evidence (inc. the Internet questionnaire results) should be weighted so heavily, thus leading to this discrepency?
Additionally, the results in the Xu et al, and Krishnamachari, et al, studies were not in the form required for the meta-analysis. I gather from correspondence with the author a process of recasting that data into the form needed for this meta-analys. It would be good to describe that process in at least some detail in this paper, or as an update annex.
Thanks,
Paul
Competing interests: No competing interests
Dear Editor
All this talk of mandating the wearing of masks to prevent further waves of COVID-19 reminds me of the story of King Canute sitting on his throne on the beach, trying to stop the tide coming in. You can require people to wear masks and impose restrictions until the cows come home, but the SARS-CoV-2 virus will always be with us. Does this mean we will have to wear masks forever?
When thinking about social separation, I think it helps to have a visual aid. Observe how when someone lights a cigarette you can smell the smoke from considerably further than 2 metres away and if they are smoking in a poorly ventilated room, how the cloud of smoke can linger for a prolonged period of time. It’s not difficult for me to imagine that an aerosol of coronavirus could behave in a very similar way. A person infected with SARS-CoV-2 walks out of a room. The cloud of virus they leave behind is still in the air when another person later walks into the room. The two people were separated in both space in time and yet the second person can still become infected.
From my perspective as a lay person, I observe how different levels of restrictions imposed by different countries don’t seem to make much difference to the final outcome. The SARS-CoV-2 virus appears to work its way through populations regardless of what measures you impose to prevent it. It is interesting to note in terms of deaths from COVID-19 per 100,000 population, the UK has one of the highest mortality rates in the world (John Hopkins University 2021). In spite of all the restrictions and periods of lockdown we have had to endure, we are near the top of the table. In light of this, I would advocate concentrating resources on vaccinating the population.
At the time of the pandemic of 1918-1919 we did not have the benefit of electron microscopes, we could not easily identify, study, or classify viruses, we had no understanding of the structure and function of DNA/RNA and we did not know how to make an effective vaccine. We had very limited resources to fight the H1N1 virus, and yet in time the pandemic abated and life returned to normal. I am optimistic that the same will happen this time round.
John Hopkins University (2021) [Online]. Available from https://coronavirus.jhu.edu/data/mortality [Accessed 23rd November 2021]
Competing interests: No competing interests
Dear Editor
Thank you for compiling the evidence and reinforcing public health officials' message throughout the pandemic. I hope readers keep their discussion focused on what is on hand and read the full-text as it might answer some of their questions.
Competing interests: No competing interests
Dear Editor,
Masks are proven effective. Great, but not enough!
One is inclined to imagine an even better effect with masks worn in a manner that takes the predominant aerosol transmission into account (1)
Unfortunately, looking around indoors and watching the media one sees countless utterly ineffective masks:
- masks under the nose (aerosols are emitted and inhaled simply by breathing),
- masks with aerosol nozzles on the sides, especially because of the crossed elastic attaches,
- masks not fitted around the nose.
- people alone in their unventilated office or shop innocently drop the mask, hence the accumulation of their respiratory aerosols where a potential victim will inevitably enter sooner or later, whose poorly worn or leaking masks or uncovered nose won't protect.
- masks aren't mandatory nor deemed essential in building's shared areas, particularly lifts, which are poorly ventilated and may be cramped. Aerosols linger there.
Unfortunately, in France and perhaps elsewhere, no effort is made to inform the public about these details that harbour the devil. And those in power are also often setting a bad example.
The media have not been helpful in taking over from the failing authorities. They instead validate the wrong uses by continuously displaying misused masks images without due comment.
How can we not imagine that a wealth of lives and suffering could be avoided by education on mundane but critical details?
I have written a short illustrated plea in this spirit that I've been sending to my national authorities since July 2020.
1- Wang CC, Prather KA Sznitman J, et al. Airborne transmission of respiratory viruses Science Aug 2021
https://doi.org/10.1126/science.abd9149
Axel Ellrodt Twitter : @EllrodtAxel
Competing interests: No competing interests
Dear Editor,
Good review and commentary.
Suggests that masks and hand hygiene are effective and social distance isn't.
Argues against shutdown (social distance), but in favour of social separation (i.e no hugging/handshakes etc).
Explains why plane travel is safe. (People behave with discipline)
I dont really care about theory,... but seems possible that this this virus gets everywhere, and that includes faecal-oral, and oral-hands-surface-hands-oral transmission.
Facemasks should not work for aerosols which ought to go straight through them? ....but may well work by interrupting surface contact-hands-oral transmission, by stopping face touching in risk areas in public (after years of nail biting, I now have perfect cuticles!)
If aerosols were important, social distance should be effective ,... and it isn't.
SO
For wards, FP3 masks should be mandated. (Cambridge data)
For. elsewhere (and especially in crowded places with likely contacts), surgical masks and hand hygiene TOGETHER seem critical in preventing waves?
Competing interests: No competing interests
Misrepresenting data of peer reviewed published scientific papers by mainstream media: a potential threat for public trust in healthcare
Dear Editor,
The article by Talic et al was noticed by the main stream media (26). The article was represented with the headline “Mask wearing cuts Covid incidence by 53 % says global study” in many mainstream media all over the world (11-14), and was presented in The Guardian by the text:
“Results from more than 30 studies from around the world were analyzed in detail, showing a statistically significant 53 % reduction in the incidence of Covid with mask wearing and 25 % reduction with physical distancing. Handwashing also indicated a substantial 53% reduction in Covid incidence although this was not statistically significant after adjusting for the small number of handwashing studies.”
Moreover, the health editor Andrew Gregory writes in the same article:
"Public health on non pharmaceutical interventions are known to be beneficial in fighting respiratory tract infections like flu, and countries around the world have tried using them curb the spread of Covid."
Unfortunately both the CDC and WHO presented in their official guidelines until may-june 2020 that mask wearing by the general public to prevent viral infections like flu do not have any benefits, it could even increase infections (1,3,7,15).
Unfortunately the data of this study do not support these claims made by the journalists. The text and data of the study is different:
“Overall pooled analysis of six studies on mask wearing showed a 53 % reduction in Covid19 incidence although heterogeneity between studies was substantial. The analysis on the effects of handwashing was estimated 53% non statistically significant reduction in Covid19 incidence. Pooled data analysis of five studies indicated 25 % reduction in incidence of Covid19 by physical distancing. Heterogeneity among studies was substantial and risk of bias ranged from moderate to serious or critical for the presented analysis with a special serious-high risk on confounding (Figure 2).
"It was not possible to evaluate the impact of type of face mask (eg surgical, fabric, N95 respirators) and compliance and frequency of wearing masks owing to a lack of data. Similarly it was not feasible to assess the differences in effect that different recommendations for physical distances have as preventive strategies."
In the limitations and methodology paragraph the authors highlighted: "High quality evidence on SARS-CoV-2 and the effectiveness of public health measures is still limited with most studies having different underlying target variables. In addition the meta analytical portion of this study was limited by significant heterogeneity observed across studies, which could neither be explored nor explained by subgroup analysis or meta regression. Several studies failed to define and assess for potential confounders which made it difficult for our review to draw a one directional or causal conclusion”.
Up to now there have been no studies that allow the conclusion that wearing masks beyond any doubt can protect against infection or transmission of the virus (2,5,15,16,18,19). A report of the ECDC concluded there is no real evidence in favor of facemasks (9).
However, a number of studies suggest that masks may be harmful to human health and climate. Toxic compounds such as graphene oxide have been found in masks. In several countries (Belgium, Germany, Canada, The Netherlands) masks delivered by governments have been retracted from the market (20,21,29).
The safety of masks used by the general public cannot be guaranteed (6). A recent review concluded there is a risk of MIES (Mask Induced Exhaustion Syndrome) by longterm wearing of masks (17). Worldwide disposable masks or face shields are discarded at a rate of 3,4 billion and 1,8 billion per day respectively. People and planet health are at increasing risk, while there is no risk-benefit analysis for mask mandates available (4,8,10,22-25,27,28).
The broader remit of the BMJ is to create a healthier world. Without an ethical compass and honest information to the public, trust in doctors, scientists and public health is at risk. Talic et al. advised in their article that when implementing public health measures it is important to consider specific health and sociocultural needs of the communities and to weigh the potential negative effects of the public health measures against the positive effects for general populations. Important values for better health outcomes are social justice and equity. Ethical principles require that benefits and possible harms should be equally and truthfully presented to the public. Journalists could play an important and supportive role for an urgent transformation to a healthier world in delivering honest science based information to the public based on critical analysis.
References
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17. Kiesilinski K, Giboni P, Prescher A, Klosterhaffen D, Graessel D et al. Is a mask that covers mout hand nose free from undesirable side effects in everyday use and free of potential hazards. Int. J. Environ. Res. Public Health 2021, 18, 4344. https://doi.org/10.3390/ijerph18084344. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8072811/pdf/ijerph-18-04344...
18. Liu IT, Prasad V, Darrow JJ. Evidence for Community Cloth Face Masking to Limit the Spread of SARS-C0V-2: A crical review” Running paper of the CATO Institute published online November 8 2021. https://www.cato.org/working-paper/evidence-community-cloth-face-masking...
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20. Ministerie keurt nog eens 308 miljoen mondmaskers, brillen en schorten af. Nu.nl 9 november 2021. https://www.nu.nl/coronavirus/6166754/ministerie-keurt-nog-eens-308-milj...
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Competing interests: No competing interests