Institute for Health Research, Faculty of Health and Social Sciences, University of Bedfordshire, Luton, UK
Department of Rheumatology, University of Medicine Mandalay, Mandalay, Myanmar.
BMJ Open. 2020 Oct 22;10(10):e041383. doi: 10.1136/bmjopen-2020-041383.
Implementing non-pharmaceutical interventions (NPIs) protect the public from COVID-19. However, the impact of NPIs has been inconsistent and remains unclear. This study, therefore, aims to measure the impact of major NPIs (social distancing, social isolation and quarantine) on reducing COVID-19 transmission.
We will conduct a systematic review and meta-analysis research of both randomised and non-randomised controlled trials. We will undertake a systematic search of: MEDLINE, Embase, Allied & Complementary Medicine, COVID-19 Research, WHO database on COVID-19, ClinicalTrails.Gov for clinical trials on COVID-19, Cochrane Resources on Coronavirus (COVID-19), Oxford COVID-19 Evidence Service and Google Scholar for published and unpublished literatures on COVID-19 including preprint engines such as medRxiv, bioRxiv, Litcovid and SSRN for unpublished studies on COVID-19 and will be reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Outcomes of interest for impact analysis will include the reduction of COVID-19 transmission, avoiding crowds and restricting movement, isolating ill and psychological impacts. The Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols checklist has been used for this protocol. For quality of included studies, we will use the Cochrane Collaboration's tool for assessing risk of bias for randomised controlled trials and the Newcastle-Ottawa Scale for observational studies. The Grading of Recommendations Assessment, Development and Evaluation approach will grade the certainty of the evidence for all outcome measures across studies. Random-effects model for meta-analysis will measure the effect size of NPIs or the strengths of relationships. For quantitative data, risk ratio or OR, absolute risk difference (for dichotomous outcome data), or mean difference or standardised mean difference (for continuous data) and their 95% CIs will be calculated. Where statistical pooling is not possible, a narrative synthesis will be conducted for the included studies. To assess the heterogeneity of effects, I together with the observed effects will be evaluated to provide the true effects in the analysis.
Formal ethical approval from an institutional review board or research ethics committee is not required as primary data will not be collected. The final results of this study will be published in an open-access peer-reviewed journal, and abstract will be presented at suitable national/international conferences or workshops. We will also share important information with public health authorities as well as with the WHO. In addition, we may post the submitted manuscript under review to medRxiv, or other relevant preprint servers.
CRD42020207338.
实施非药物干预（NPIs）可保护公众免受 COVID-19 的侵害。然而，NPIs 的影响一直不一致，目前尚不清楚。因此，本研究旨在衡量主要 NPIs（社交距离、社交隔离和检疫）对减少 COVID-19 传播的影响。
我们将对随机和非随机对照试验进行系统评价和荟萃分析研究。我们将系统地搜索：MEDLINE、Embase、辅助与补充医学、COVID-19 研究、世卫组织 COVID-19 数据库、临床试验.gov 上的 COVID-19 临床试验、考科蓝冠状病毒资源（COVID-19）、牛津 COVID-19 证据服务以及 Google 学术，以查找 COVID-19 的已发表和未发表文献，包括 medRxiv、bioRxiv、Litcovid 和 SSRN 等预印本引擎上的 COVID-19 未发表研究，并将根据系统评价和荟萃分析的首选报告项目进行报告。影响分析的感兴趣结果包括减少 COVID-19 传播、避免人群和限制流动、隔离患者和心理影响。本方案使用了系统评价和荟萃分析首选报告项目清单。对于纳入研究的质量，我们将使用 Cochrane 协作对随机对照试验进行评估偏倚的工具和纽卡斯尔-渥太华量表对观察性研究进行评估。推荐评估、制定和评估方法将对所有研究的所有结果指标的证据确定性进行分级。荟萃分析将使用随机效应模型来衡量 NPIs 的效果大小或关系强度。对于定量数据，将计算风险比或 OR、绝对风险差异（二分类结局数据）、或均数差异或标准化均数差异（连续数据）及其 95%CI。如果无法进行统计学合并，将对纳入的研究进行叙述性综合。为了评估效应的异质性，将对我观察到的效应进行评估，以在分析中提供真实效应。
由于不会收集原始数据，因此不需要来自机构审查委员会或研究伦理委员会的正式伦理批准。本研究的最终结果将发表在开放获取的同行评议期刊上，并将在合适的国家/国际会议或研讨会上进行摘要报告。我们还将与公共卫生当局以及世界卫生组织分享重要信息。此外，我们可能会将提交的审稿中的论文发布到 medRxiv 或其他相关预印本服务器上。
CRD42020207338。
