Modelling the potential impact of mask use in schools and society on COVID-19 control in the UK

Panovska‐Griffiths, Jasmina; Kerr, Cliff C.; Waites, William; Stuart, Robyn M.; Mistry, Dina; Foster, Derek; Klein, D. J.; Viner, Russell; Bonell, Chris

doi:10.1038/s41598-021-88075-0

Cited by 39 publications

(30 citation statements)

References 36 publications

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“…The applicability of surgical masks for preventing the transmission of the human coronavirus and the influenza virus from symptomatic individuals has been confirmed. 7 , 17 , 18 …”

Section: Discussionmentioning

confidence: 99%

Adverse Reactions to Facemasks in Health-Care Workers: A Cross-Sectional Survey

Liu¹,

Ye²,

Zhu³

et al. 2022

CCID

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Background Coronavirus disease 2019 (COVID-19) has developed into a worldwide pandemic, which presents several challenges for frontline health-care workers (HCWs). HCWs are highly prone to various skin diseases due to prolonged use of personal protective equipment (PPE). The most frequently used type of PPE is facemasks. To effectively control adverse skin reactions, there is an urgent need for a range of preventive practices. Methods This cross-sectional study was conducted at 12 hospitals in Zhejiang province, China. HCWs were invited to participate in the web survey. Data were extracted by two independent reviewers using a predesigned data collection form and analyzed with SPSS 20.0. Results A total of 1147 questionnaires were collected, and of these, 1090 (95.03%) were valid and returned. The incidence of chest tightness and shortness of breath and face eczema was significantly higher in HCWs wearing N95 facemasks (41.91%; 31.62%) than in the HCWs wearing medical facemasks (38.05%, P = 0.010; 21.91%, P = 0.012). The incidence of ear pain and indentation was significantly higher in HCWs wearing hang-facemasks (83.81%) than in HCWs wearing strains-facemasks (61.19%, P < 0.001). The incidence of ear pain and indentation was significantly higher in HCWs wearing undiscriminating size code facemasks (79.88%) than in the HCWs wearing discriminating size code facemasks (67.86%, P = 0.031). There was a significant reduction ( P < 0.001) in the incidence of HCWs without adverse reactions (ADRs) with increasing time wearing facemasks. Conclusion Incidence of ADRs does not significantly increase with the durations of mask wear where wearing mask time exceeded 4 hours per day. The medical staff generally wore masks for more than 4 hours per day; therefore, we recommend taking 15 min of rest after 2 hours of mask-wearing. Results in this study support the conclusion that the type of strain-facemasks and discriminating size code facemasks has a lower incidence of ADRs than other type of medical facemasks.

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“…The applicability of surgical masks for preventing the transmission of the human coronavirus and the influenza virus from symptomatic individuals has been confirmed. 7 , 17 , 18 …”

Section: Discussionmentioning

confidence: 99%

Adverse Reactions to Facemasks in Health-Care Workers: A Cross-Sectional Survey

Liu¹,

Ye²,

Zhu³

et al. 2022

CCID

View full text Add to dashboard Cite

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“…To alleviate some of these drawbacks, other classes of models have been advanced for estimating the probability of COVID-19 transmission and identifying compliance with social distancing measures. These include various hybrid models integrating neural networks and SEIR modeling 33 , 34 , simulation systems (e.g., agent-based models) 35 – 37 and video processing for object detection (e.g., You Only Look Once (YOLO)) 38 , 39 . Some other studies have used econometric models (e.g., linear regression, structural equation model) to identify the factors that influence the diffusion of COVID-19 and associated mitigation measures 16 , 40 .…”

Section: Literature Reviewmentioning

confidence: 99%

Spatio-temporal prediction of the COVID-19 pandemic in US counties: modeling with a deep LSTM neural network

Nikparvar

Rahman

Hatami

et al. 2021

Sci Rep

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Prediction of complex epidemiological systems such as COVID-19 is challenging on many grounds. Commonly used compartmental models struggle to handle an epidemiological process that evolves rapidly and is spatially heterogeneous. On the other hand, machine learning methods are limited at the beginning of the pandemics due to small data size for training. We propose a deep learning approach to predict future COVID-19 infection cases and deaths 1 to 4 weeks ahead at the fine granularity of US counties. The multi-variate Long Short-term Memory (LSTM) recurrent neural network is trained on multiple time series samples at the same time, including a mobility series. Results show that adding mobility as a variable and using multiple samples to train the network improve predictive performance both in terms of bias and of variance of the forecasts. We also show that the predicted results have similar accuracy and spatial patterns with a standard ensemble model used as benchmark. The model is attractive in many respects, including the fine geographic granularity of predictions and great predictive performance several weeks ahead. Furthermore, data requirement and computational intensity are reduced by substituting a single model to multiple models folded in an ensemble model.

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“…A parallel study by Kunzmann et al considered the impact of such measures in primary schools, reaching a similar conclusion that serial contact testing alone would be insufficient to contain outbreaks, recommending a combination of mass testing and isolation of close contacts 27 . Other studies have explored the impact of alternative within-school control measures, such as PCR-based testing strategies 28 , dividing classes into discrete cohorts 29 , 30 , and mask-wearing 31 . Owing to the paucity of information surrounding SARS-CoV-2 transmission rates between children within schools, such studies typically consider a range of pupil-to-pupil transmission rates.…”

Section: Introductionmentioning

confidence: 99%

Quantifying pupil-to-pupil SARS-CoV-2 transmission and the impact of lateral flow testing in English secondary schools

et al. 2022

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A range of measures have been implemented to control within-school SARS-CoV-2 transmission in England, including the self-isolation of close contacts and twice weekly mass testing of secondary school pupils using lateral flow device tests (LFTs). Despite reducing transmission, isolating close contacts can lead to high levels of absences, negatively impacting pupils. To quantify pupil-to-pupil SARS-CoV-2 transmission and the impact of implemented control measures, we fit a stochastic individual-based model of secondary school infection to both swab testing data and secondary school absences data from England, and then simulate outbreaks from 31st August 2020 until 23rd May 2021. We find that the pupil-to-pupil reproduction number, Rschool, has remained below 1 on average across the study period, and that twice weekly mass testing using LFTs has helped to control pupil-to-pupil transmission. We also explore the potential benefits of alternative containment strategies, finding that a strategy of repeat testing of close contacts rather than isolation, alongside mass testing, substantially reduces absences with only a marginal increase in pupil-to-pupil transmission.

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Modelling the potential impact of mask use in schools and society on COVID-19 control in the UK

Cited by 39 publications

References 36 publications

Adverse Reactions to Facemasks in Health-Care Workers: A Cross-Sectional Survey

Adverse Reactions to Facemasks in Health-Care Workers: A Cross-Sectional Survey

Spatio-temporal prediction of the COVID-19 pandemic in US counties: modeling with a deep LSTM neural network

Quantifying pupil-to-pupil SARS-CoV-2 transmission and the impact of lateral flow testing in English secondary schools

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