Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 and is spread personto-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. MethodsWe did a systematic review and meta-analysis to investigate the optimum distance for avoiding person-toperson 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 metaregressions. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. This study is registered with PROSPERO, CRD42020177047. FindingsOur 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; p interaction =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; p interaction =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.

Background Measures of socioeconomic disadvantage may enable improved targeting of programs to prevent rehospitalizations, but obtaining such information directly from patients can be difficult. Measures of US neighborhood socioeconomic disadvantage are more readily available, although rarely employed clinically. Objective To evaluate the association between neighborhood socioeconomic disadvantage at the census block-group level, as measured by Singh’s validated Area Deprivation Index (ADI), and 30-day rehospitalization. Design Retrospective cohort study Setting United States Patients Random 5% national sample of fee-for-service Medicare patients discharged with congestive heart failure, pneumonia or myocardial infarction, 2004–2009 (N = 255,744) Measurements 30-day rehospitalizations. Medicare data were linked to 2000 Census data to construct an ADI for each patient’s census block-group, which were then sorted into percentiles by increasing ADI. Relationships between neighborhood ADI grouping and rehospitalization were evaluated using multivariate logistic regression models, controlling for patient sociodemographics, comorbidities/severity, and index hospital characteristics. Results The 30-day rehospitalization rate did not vary significantly across the least disadvantaged 85% of neighborhoods, which had an average rehospitalization rate=21%. However, within the most disadvantaged 15% of neighborhoods, rehospitalization rates rose from 22% to 27% with worsening ADI. This relationship persisted after full adjustment, with the most disadvantaged neighborhoods having a rehospitalization risk (adjusted risk ratio = 1.09, confidence interval 1.05–1.12) similar to that of chronic pulmonary disease (1.06, 1.04–1.08) and greater than that of diabetes (0.95, 0.94–0.97). Limitations No direct markers of care quality, access Conclusions Residence within a disadvantaged US neighborhood is a rehospitalization predictor of magnitude similar to chronic pulmonary disease. Measures of neighborhood disadvantage, like the ADI, could potentially be used to inform policy and post-hospital care. Primary Funding Source National Institute on Aging

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Background: Stakeholder engagement has become widely accepted as a necessary component of guideline development and implementation. While frameworks for developing guidelines express the need for those potentially affected by guideline recommendations to be involved in their development, there is a lack of consensus on how this should be done in practice. Further, there is a lack of guidance on how to equitably and meaningfully engage multiple stakeholders. We aim to develop guidance for the meaningful and equitable engagement of multiple stakeholders in guideline development and implementation. Methods: This will be a multi-stage project. The first stage is to conduct a series of four systematic reviews. These will (1) describe existing guidance and methods for stakeholder engagement in guideline development and implementation, (2) characterize barriers and facilitators to stakeholder engagement in guideline development and implementation, (3) explore the impact of stakeholder engagement on guideline development and implementation, and (4) identify issues related to conflicts of interest when engaging multiple stakeholders in guideline development and implementation.Discussion: We will collaborate with our multiple and diverse stakeholders to develop guidance for multi-stakeholder engagement in guideline development and implementation. We will use the results of the systematic reviews to develop a candidate list of draft guidance recommendations and will seek broad feedback on the draft guidance via an online survey of guideline developers and external stakeholders. An invited group of representatives from all stakeholder groups will discuss the results of the survey at a consensus meeting which will inform the development of the final guidance papers. Our overall goal is to improve the development of guidelines through meaningful and equitable multi-stakeholder engagement, and subsequently to improve health outcomes and reduce inequities in health.

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