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BACKGROUND: Conflicts of interest (COIs) of contributors to a guideline project and the funding of that project can influence the development of the guideline. Comprehensive reporting of information on COIs and funding is essential for the transparency and credibility of guidelines. OBJECTIVE: To develop an extension of the Reporting Items for practice Guidelines in HealThcare (RIGHT) statement for the reporting of COIs and funding in policy documents of guideline organizations and in guidelines: the RIGHT-COI&F checklist. DESIGN: The recommendations of the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) network were followed. The process consisted of registration of the project and setting up working groups, generation of the initial list of items, achieving consensus on the items, and formulating and testing the final checklist. SETTING: International collaboration. PARTICIPANTS: 44 experts. MEASUREMENTS: Consensus on checklist items. RESULTS: The checklist contains 27 items: 18 about the COIs of contributors and 9 about the funding of the guideline project. Of the 27 items, 16 are labeled as policy related because they address the reporting of COI and funding policies that apply across an organization's guideline projects. These items should be described ideally in the organization's policy documents, otherwise in the specific guideline. The remaining 11 items are labeled as implementation related and they address the reporting of COIs and funding of the specific guideline. LIMITATION: The RIGHT-COI&F checklist requires testing in real-life use. CONCLUSION: The RIGHT-COI&F checklist can be used to guide the reporting of COIs and funding in guideline development and to assess the completeness of reporting in published guidelines and policy documents. PRIMARY FUNDING SOURCE: The Fundamental Research Funds for the Central Universities of China.
Subject(s)
Checklist , Conflict of Interest , Practice Guidelines as Topic , Humans , Research Support as Topic/ethics , DisclosureABSTRACT
BACKGROUND: Clinical and public health guidelines include a variety of types of normative statements concerning interventions. "Recommendations" are usually the central focus, and are based on one or more systematic reviews of research evidence. Guidelines may include other types of normative statements, however, including Grading of Recommendations, Assessment, Develoment, and Evaluation (GRADE) good (or best) practice statements (GPS), which represent recommendations that guideline panels feel are important but are not appropriate for formal ratings of quality of evidence because it is sufficiently obvious that desirable effects outweigh undesirable effects. These normative statements are typically supported by a great deal of high-certainty, indirect evidence, which the authors feel would be a waste of time to examine. There are a number of conceptual and methodological issues with GRADE GPS, however, and these are manifested in guidelines, including both inappropriate overuse and underuse, and unclear interpretation and impact among end-users. This situation has arisen in part from lack of clarity in, and misunderstandings of, GRADE guidance, the lumping of many different types of normative statements under one label ("GPS"), from limitations in GRADE's approach to linked bodies of evidence, and because the appropriate basis for many normative statements about interventions is not reviews of research evidence. A new typology is needed for normative statements on interventions and policies that are not optimally based on reviews of research evidence. PROPOSED TYPOLOGY: This proposed typology differentiates normative statements about interventions by the type or nature of the most appropriate basis for the statement. The typology encompasses the range of statements encompassed by GPS, but provides a more nuanced categorization designed to assist both guideline developers and end-users. This typology encompasses two main types of normative statements about interventions (including policies): (1) statements that indicate when to use (or not) an intervention, which intervention to use, and if, when and how to use it and (2) the principles, practices, or norms that inform or underpin such interventions. These correspond to normative statements based on empirical evidence, and those based on human rights, ethics, or norms, respectively. Normative statements based on empirical evidence include: (1) recommendations based on systematic reviews of human or animal evidence on effectiveness and harms, including linked bodies of evidence; (2) normative statements based on scientific fundamentals (eg, physical/biological/chemical properties, theories, laws, or principles); and (3) implementation guidance based most commonly on experiential evidence such as case studies. Normative statements based on human rights, ethics, or norms include: (1) guiding principles, based on human rights standards and conventions and/or ethics principles; and (2) practice norms and standards, based on clinical and public health norms and/or professional standards. CONCLUSION: There are conceptual and methodological problems with GRADE GPS, leading to their misapplication, with overuse and underuse. This paper presents a proposal for a new typology for normative statements on interventions, according to the basis for the statement. This typology encompasses and replaces GPS, providing a more nuanced set of statements. Testing of this proposed approach is needed among both guideline developers and end-users.
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Practice Guidelines as Topic , Humans , Practice Guidelines as Topic/standards , Evidence-Based Medicine/standardsABSTRACT
Despite the increasing number of radiological case reports, the majority lack a standardised methodology of writing and reporting. We therefore develop a reporting guideline for radiological case reports based on the CAse REport (CARE) statement. We established a multidisciplinary group of experts, comprising 40 radiologists, methodologists, journal editors and researchers, to develop a reporting guideline for radiological case reports according to the methodology recommended by the Enhancing the QUAlity and Transparency Of health Research network. The Delphi panel was requested to evaluate the significance of a list of elements for potential inclusion in a guideline for reporting mediation analyses. By reviewing the reporting guidelines and through discussion, we initially drafted 46 potential items. Following a Delphi survey and discussion, the final CARE-radiology checklist is comprised of 38 items in 16 domains. CARE-radiology is a comprehensive reporting guideline for radiological case reports developed using a rigorous methodology. We hope that compliance with CARE-radiology will help in the future to improve the completeness and quality of case reports in radiology.
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OBJECTIVES: To systematically collect and analyse diverse definitions of 'evidence' in both health and social sciences, and help users to correctly use the term 'evidence' and rethink what is the definition of 'evidence' in scientific research. DESIGN: Scoping review. METHODS: Definitions of evidence in the health sciences and social sciences were included. We have excluded the definition of evidence applied in the legal field, abstracts without full text, documents not published in either Chinese or English and so on. We established a multidisciplinary working group and systematically searched five electronic databases including Medline, Web of Science, EBSCO, the Chinese Social Sciences Citation Index and the Chinese Science Citation Database from their inception to 26 February 2022. We also searched websites and reviewed the reference lists of the identified studies. Six reviewers working in pairs, independently, selected studies according to the inclusion and exclusion criteria, and extracted information. Any differences were discussed in pairs, and if there was disagreement, it was resolved via discussion or with the help of a third reviewer. Reviewers extracted document characteristics, the original content for the definitions of 'evidence', assessed definitions as either intensional or extensional, and any citations for the given definition. RESULTS: Forty-nine documents were finally included after screening, and 68 definitions were obtained. After excluding duplicates, a total of 54 different definitions of 'evidence' were identified. There were 42 intensional definitions and 12 extensional definitions. The top three definiens were 'information', 'fact' and 'research/study'. The definition of 'evidence' differed between health and social sciences. The term 'research' appeared most frequently in the definitions. CONCLUSIONS: The definition of 'evidence' has gradually attracted the attention of many scholars and decision-makers in health and social sciences. Nevertheless, there is no widely recognised and accepted definition in scientific research. Given the wide use of the term, we need to think about whether, or under what circumstances, a standardised, clear, meaningful and widely applicable definition of 'evidence' might be helpful.
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BACKGROUND: This study aimed to develop a comprehensive instrument for evaluating and ranking clinical practice guidelines, named Scientific, Transparent and Applicable Rankings tool (STAR), and test its reliability, validity, and usability. METHODS: This study set up a multidisciplinary working group including guideline methodologists, statisticians, journal editors, clinicians, and other experts. Scoping review, Delphi methods, and hierarchical analysis were used to develop the STAR tool. We evaluated the instrument's intrinsic and interrater reliability, content and criterion validity, and usability. RESULTS: STAR contained 39 items grouped into 11 domains. The mean intrinsic reliability of the domains, indicated by Cronbach's α coefficient, was 0.588 (95% confidence interval [CI]: 0.414, 0.762). Interrater reliability as assessed with Cohen's kappa coefficient was 0.774 (95% CI: 0.740, 0.807) for methodological evaluators and 0.618 (95% CI: 0.587, 0.648) for clinical evaluators. The overall content validity index was 0.905. Pearson's r correlation for criterion validity was 0.885 (95% CI: 0.804, 0.932). The mean usability score of the items was 4.6 and the median time spent to evaluate each guideline was 20 min. CONCLUSION: The instrument performed well in terms of reliability, validity, and efficiency, and can be used for comprehensively evaluating and ranking guidelines.
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Reproducibility of Results , Surveys and Questionnaires , Practice Guidelines as Topic , HumansABSTRACT
BACKGROUND: In February 2021, over one hundred scientists and policy experts participated in a web-based Workshop to discuss the ways that divergent evaluations of evidence and scientific uncertainties are used to delay timely protection of human health and the environment from exposures to hazardous agents. The Workshop arose from a previous workshop organized by the European Environment Agency (EEA) in 2008 and which also drew on case studies from the EEA reports on 'Late Lessons from Early Warnings' (2001, 2013). These reports documented dozens of hazardous agents including many chemicals, for which risk reduction measures were delayed for decades after scientists and others had issued early and later warnings about the harm likely to be caused by those agents. RESULTS: Workshop participants used recent case studies including Perfluorooctanoic acid (PFOA), Extremely Low Frequency - Electrical Magnetic Fields (ELF-EMF fields), glyphosate, and Bisphenol A (BPA) to explore myriad reasons for divergent outcomes of evaluations, which has led to delayed and inadequate protection of the public's health. Strategies to overcome these barriers must, therefore, at a minimum include approaches that 1) Make better use of existing data and information, 2) Ensure timeliness, 3) Increase transparency, consistency and minimize bias in evidence evaluations, and 4) Minimize the influence of financial conflicts of interest. CONCLUSION: The recommendations should enhance the production of "actionable evidence," that is, reliable evaluations of the scientific evidence to support timely actions to protect health and environments from exposures to hazardous agents. The recommendations are applicable to policy and regulatory settings at the local, state, federal and international levels.
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Medical Informatics , Humans , Uncertainty , Education , InternetABSTRACT
OBJECTIVES: We developed guidance to inform decisions regarding the inclusion of nonrandomized studies of interventions (NRSIs) in systematic reviews (SRs) of the effects of interventions. STUDY DESIGN AND SETTING: The guidance workgroup comprised SR experts and used an informal consensus generation method. RESULTS: Instead of recommending NRSI inclusion only if randomized controlled trials (RCTs) are insufficient to address the SR key question, different topics may require different decisions regarding NRSI inclusion. We identified important considerations to inform such decisions from topic refinement through protocol development. During topic scoping and refinement, considerations were related to the clinical decisional dilemma, adequacy of RCTs to address the key questions, risk of bias in NRSIs, and the extent to which NRSIs are likely to complement RCTs. When NRSIs are included, during SR team formation, familiarity with topic-specific data sources and advanced analytic methods for NRSIs should be considered. During protocol development, the decision regarding NRSI inclusion or exclusion should be justified, and potential implications explained. When NRSIs are included, the protocol should describe the processes for synthesizing evidence from RCTs and NRSIs and determining the overall strength of evidence. CONCLUSION: We identified specific considerations for decisions regarding NRSI inclusion in SRs and highlight the importance of flexibility and transparency.
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Health Services Research , Research Design , Humans , Systematic Reviews as Topic , Bias , Delivery of Health CareABSTRACT
Importance: Developing core outcome sets is essential to ensure that results of clinical trials are comparable and useful. A number of core outcome sets in pediatrics have been published, but a comprehensive in-depth understanding of core outcome sets in this field is lacking. Objective: To systematically identify core outcome sets in child health, collate the diseases to which core outcome sets have been applied, describe the methods used for development and stakeholder participation, and evaluate the methodological quality of existing core outcome sets. Evidence Review: MEDLINE, SCOPUS, Cochrane Library, and CINAHL were searched using relevant search terms, such as clinical trials, core outcome, and children, along with relevant websites, such as Core Outcome Measures in Effectiveness Trials (COMET). Four researchers worked in teams of 2, performed literature screening and data extraction, and evaluated the methodological quality of core outcome sets using the Core Outcome Set-Standards for Development (COS-STAD). Findings: A total of 77 pediatric core outcome sets were identified, mainly developed by organizations or researchers in Europe, North America, and Australia and mostly from the UK (22 [29%]) and the US (22 [29%]). A total of 77 conditions were addressed; the most frequent International Classification of Diseases, 11th Revision category was diseases of the digestive system (14 [18%]). Most of the outcomes in pediatric core outcome sets were unordered (34 [44%]) or presented in custom classifications (29 [38%]). Core outcome sets used 1 or more of 8 development methods; the most frequent combination of methods was systematic review/literature review/scoping review, together with the Delphi approach and consensus for decision-making (10 [14%]). Among the 6 main types of stakeholders, clinical experts were the most frequently involved (74 [100%]), while industry representatives were rarely involved (4 [5%]). Only 6 core outcome sets (8%) met the 12 criteria of COS-STAD. Conclusions and Relevance: Future quality of pediatric core outcome sets should be improved based on the standards proposed by the COMET initiative, while core outcome sets methodology and reporting standards should be extended to pediatric populations to help improve the quality of core outcome sets in child health. In addition, the COMET outcome taxonomy should also add items applicable to children.
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Child Health , Research Design , Child , Humans , Endpoint Determination/methods , Delphi Technique , Treatment Outcome , Outcome Assessment, Health CareABSTRACT
Mathematical modeling studies are frequently conducted to guide policy in global health. However, the contribution of mathematical modeling studies to World Health Organization (WHO) guideline recommendations, and the quality of evidence contributed by these studies remains unknown. We conducted a systematic review of the WHO Guidelines Review Committee database to identify guideline recommendations that included evidence from mathematical modeling studies since inception of the Guidelines Review Committee on 1 December, 2007. We included WHO guideline recommendations citing a mathematical modeling study in the primary evidence base. We defined a mathematical model as a framework that predicted epidemiologic, health or economic impact of an intervention or decision in the clinical or public health context. The primary outcome was inclusion of evidence from mathematical modeling studies in a guideline recommendation. We evaluated each unique modeling study across multiple domains of quality. Between 1 December 2007 and 1 April 2019, the WHO Guidelines Review Committee approved 154 guidelines providing 1619 guideline recommendations. Mathematical modeling studies informed 46 WHO guidelines (29.9%) and 101 unique guideline recommendations (6.2%). Modeling evidence addressed topics related to infectious diseases in 38 guidelines (82.6%) and 81 recommendations (80.2%), most commonly for HIV and tuberculosis. Evidence from modeling studies was assessed in the GRADE evidence profile for 12 recommendations (12.9%) and GRADE evidence-to-decision framework for 45 recommendations (44.6%). Modeling-informed recommendations were more likely than other recommendations within the same guidelines to be issued with a "conditional" rather than "strong" strength of recommendation (53.5% versus 37.8%), and the evidence underlying modeling-informed recommendations was more likely to be assessed as very low quality (41.6% versus 24.1%). Upon review of individual modeling studies, we estimated that 33.8% of models performed a calibration, 29.4% of models performed a validation of results, and 20.6% of models reported a change in the study conclusion in the sensitivity analysis. While policy recommendations in WHO guidelines are informed by evidence from modeling studies, the validity of modeling studies included in guidelines development is heterogeneous. Quality assessment is needed to support the evaluation and incorporation of evidence from mathematical modeling studies in guidelines development.
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Evidence-Based Medicine , Models, Theoretical , Calibration , Evidence-Based Medicine/methods , Public Health , World Health OrganizationABSTRACT
BACKGROUND: The World Health Organization (WHO) and the International Labour Organization (ILO) have produced the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury (WHO/ILO Joint Estimates). For these, systematic reviews of studies estimating the prevalence of exposure to selected occupational risk factors have been conducted to provide input data for estimations of the number of exposed workers. A critical part of systematic review methodology is to assess the quality of evidence across studies. In this article, we present the approach applied in these WHO/ILO systematic reviews for performing such assessments on studies of prevalence of exposure. It is called the Quality of Evidence in Studies estimating Prevalence of Exposure to Occupational risk factors (QoE-SPEO) approach. We describe QoE-SPEO's development to date, demonstrate its feasibility reporting results from pilot testing and case studies, note its strengths and limitations, and suggest how QoE-SPEO should be tested and developed further. METHODS: Following a comprehensive literature review, and using expert opinion, selected existing quality of evidence assessment approaches used in environmental and occupational health were reviewed and analysed for their relevance to prevalence studies. Relevant steps and components from the existing approaches were adopted or adapted for QoE-SPEO. New steps and components were developed. We elicited feedback from other systematic review methodologists and exposure scientists and reached consensus on the QoE-SPEO approach. Ten individual experts pilot-tested QoE-SPEO. To assess inter-rater agreement, we counted ratings of expected (actual and non-spurious) heterogeneity and quality of evidence and calculated a raw measure of agreement (Pi) between individual raters and rater teams for the downgrade domains. Pi ranged between 0.00 (no two pilot testers selected the same rating) and 1.00 (all pilot testers selected the same rating). Case studies were conducted of experiences of QoE-SPEO's use in two WHO/ILO systematic reviews. RESULTS: We found no existing quality of evidence assessment approach for occupational exposure prevalence studies. We identified three relevant, existing approaches for environmental and occupational health studies of the effect of exposures. Assessments using QoE-SPEO comprise three steps: (1) judge the level of expected heterogeneity (defined as non-spurious variability that can be expected in exposure prevalence, within or between individual persons, because exposure may change over space and/or time), (2) assess downgrade domains, and (3) reach a final rating on the quality of evidence. Assessments are conducted using the same five downgrade domains as the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach: (a) risk of bias, (b) indirectness, (c) inconsistency, (d) imprecision, and (e) publication bias. For downgrade domains (c) and (d), the assessment varies depending on the level of expected heterogeneity. There are no upgrade domains. The QoE-SPEO's ratings are "very low", "low", "moderate", and "high". To arrive at a final decision on the overall quality of evidence, the assessor starts at "high" quality of evidence and for each domain downgrades by one or two levels for serious concerns or very serious concerns, respectively. In pilot tests, there was reasonable agreement in ratings for expected heterogeneity; 70% of raters selected the same rating. Inter-rater agreement ranged considerably between downgrade domains, both for individual rater pairs (range Pi: 0.36-1.00) and rater teams (0.20-1.00). Sparse data prevented rigorous assessment of inter-rater agreement in quality of evidence ratings. CONCLUSIONS: We present QoE-SPEO as an approach for assessing quality of evidence in prevalence studies of exposure to occupational risk factors. It has been developed to its current version (as presented here), has undergone pilot testing, and was applied in the systematic reviews for the WHO/ILO Joint Estimates. While the approach requires further testing and development, it makes steps towards filling an identified gap, and progress made so far can be used to inform future work in this area.
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Occupational Diseases , Occupational Exposure , Cost of Illness , Humans , Occupational Diseases/epidemiology , Occupational Diseases/etiology , Prevalence , Review Literature as Topic , World Health OrganizationABSTRACT
BACKGROUND: Evidence-to-decision (EtD) frameworks provide a structured and transparent approach for groups of experts to use when formulating recommendations or making decisions. While extensively used for clinical and public health recommendations, EtD frameworks are not in widespread use in environmental health. This review sought to identify, compare and contrast key EtD frameworks for decisions on interventions used in clinical medicine, public health or environmental health. This information can be used to develop an EtD framework suitable for formulating recommendations for interventions in environmental health. METHODS: We identified a convenience sample of EtD frameworks used by a range of organizations. We searched Medline for systematic reviews of frameworks. We summarized the decision criteria in the selected frameworks and reviews in a qualitative manner. FINDINGS: Fourteen organizations provided 18 EtD frameworks; most frameworks focused on clinical medicine or public health interventions; four focused on environmental health and three on economic considerations. Harms of interventions were examined in all frameworks and benefits in all but one. Other criteria included certainty of the body of evidence (15 frameworks), resource considerations (15), feasibility (13), equity (12), values (11), acceptability (11), and human rights (2). There was variation in how specific criteria were defined. The five identified systematic reviews reported a similar spectrum of EtD criteria. INTERPRETATION: The EtD frameworks examined encompassed similar criteria, with tailoring to specific audience needs. Existing frameworks are a useful starting point for development of one tailored to decision-making in environmental health. FUNDER: JPB Foundation.
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Decision Making , Evidence-Based Medicine , Environmental Health , Humans , Public Health , Systematic Reviews as TopicABSTRACT
BACKGROUND/OBJECTIVE: International travel measures to contain the coronavirus disease of 2019 (COVID-19) pandemic represent a relatively intrusive form of non-pharmaceutical intervention. To inform decision-making on the (re)implementation, adaptation, relaxation or suspension of such measures, it is essential to not only assess their effectiveness but also their unintended effects. METHODS: This scoping review maps existing empirical studies on the unintended consequences, both predicted and unforeseen, and beneficial or harmful, of international travel measures. We searched multiple health, non-health and COVID-19-specific databases. The evidence was charted in a map in relation to the study design, intervention and outcome categories identified and discussed narratively. RESULTS: Twenty-three studies met our inclusion criteria-nine quasi-experimental, two observational, two mathematical modelling, six qualitative and four mixed-methods studies. Studies addressed different population groups across various countries worldwide. Seven studies provided information on unintended consequences of the closure of national borders, six looked at international travel restrictions and three investigated mandatory quarantine of international travellers. No studies looked at entry and/or exit screening at national borders exclusively, however six studies considered this intervention in combination with other international travel measures. In total, 11 studies assessed various combinations of the aforementioned interventions. The outcomes were mostly referred to by the authors as harmful. Fifteen studies identified a variety of economic consequences, six reported on aspects related to quality of life, well-being, and mental health and five on social consequences. One study each provided information on equity, equality, and the fair distribution of benefits and burdens, environmental consequences and health system consequences. CONCLUSION: This scoping review represents the first step towards a systematic assessment of the unintended benefits and harms of international travel measures during COVID-19. The key research gaps identified might be filled with targeted primary research, as well as the additional consideration of gray literature and non-empirical studies.
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COVID-19 , Pandemics , Humans , Pandemics/prevention & control , Quality of Life , Quarantine , SARS-CoV-2ABSTRACT
BACKGROUND: In late 2019, the first cases of coronavirus disease 2019 (COVID-19) were reported in Wuhan, China, followed by a worldwide spread. Numerous countries have implemented control measures related to international travel, including border closures, travel restrictions, screening at borders, and quarantine of travellers. OBJECTIVES: To assess the effectiveness of international travel-related control measures during the COVID-19 pandemic on infectious disease transmission and screening-related outcomes. SEARCH METHODS: We searched MEDLINE, Embase and COVID-19-specific databases, including the Cochrane COVID-19 Study Register and the WHO Global Database on COVID-19 Research to 13 November 2020. SELECTION CRITERIA: We considered experimental, quasi-experimental, observational and modelling studies assessing the effects of travel-related control measures affecting human travel across international borders during the COVID-19 pandemic. In the original review, we also considered evidence on severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). In this version we decided to focus on COVID-19 evidence only. Primary outcome categories were (i) cases avoided, (ii) cases detected, and (iii) a shift in epidemic development. Secondary outcomes were other infectious disease transmission outcomes, healthcare utilisation, resource requirements and adverse effects if identified in studies assessing at least one primary outcome. DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles and abstracts and subsequently full texts. For studies included in the analysis, one review author extracted data and appraised the study. At least one additional review author checked for correctness of data. To assess the risk of bias and quality of included studies, we used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for observational studies concerned with screening, and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed the certainty of evidence with GRADE, and several review authors discussed these GRADE judgements. MAIN RESULTS: Overall, we included 62 unique studies in the analysis; 49 were modelling studies and 13 were observational studies. Studies covered a variety of settings and levels of community transmission. Most studies compared travel-related control measures against a counterfactual scenario in which the measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of stringency of the measures (including relaxation of restrictions), or a combination of measures. Concerns with the quality of modelling studies related to potentially inappropriate assumptions about the structure and input parameters, and an inadequate assessment of model uncertainty. Concerns with risk of bias in observational studies related to the selection of travellers and the reference test, and unclear reporting of certain methodological aspects. Below we outline the results for each intervention category by illustrating the findings from selected outcomes. Travel restrictions reducing or stopping cross-border travel (31 modelling studies) The studies assessed cases avoided and shift in epidemic development. We found very low-certainty evidence for a reduction in COVID-19 cases in the community (13 studies) and cases exported or imported (9 studies). Most studies reported positive effects, with effect sizes varying widely; only a few studies showed no effect. There was very low-certainty evidence that cross-border travel controls can slow the spread of COVID-19. Most studies predicted positive effects, however, results from individual studies varied from a delay of less than one day to a delay of 85 days; very few studies predicted no effect of the measure. Screening at borders (13 modelling studies; 13 observational studies) Screening measures covered symptom/exposure-based screening or test-based screening (commonly specifying polymerase chain reaction (PCR) testing), or both, before departure or upon or within a few days of arrival. Studies assessed cases avoided, shift in epidemic development and cases detected. Studies generally predicted or observed some benefit from screening at borders, however these varied widely. For symptom/exposure-based screening, one modelling study reported that global implementation of screening measures would reduce the number of cases exported per day from another country by 82% (95% confidence interval (CI) 72% to 95%) (moderate-certainty evidence). Four modelling studies predicted delays in epidemic development, although there was wide variation in the results between the studies (very low-certainty evidence). Four modelling studies predicted that the proportion of cases detected would range from 1% to 53% (very low-certainty evidence). Nine observational studies observed the detected proportion to range from 0% to 100% (very low-certainty evidence), although all but one study observed this proportion to be less than 54%. For test-based screening, one modelling study provided very low-certainty evidence for the number of cases avoided. It reported that testing travellers reduced imported or exported cases as well as secondary cases. Five observational studies observed that the proportion of cases detected varied from 58% to 90% (very low-certainty evidence). Quarantine (12 modelling studies) The studies assessed cases avoided, shift in epidemic development and cases detected. All studies suggested some benefit of quarantine, however the magnitude of the effect ranged from small to large across the different outcomes (very low- to low-certainty evidence). Three modelling studies predicted that the reduction in the number of cases in the community ranged from 450 to over 64,000 fewer cases (very low-certainty evidence). The variation in effect was possibly related to the duration of quarantine and compliance. Quarantine and screening at borders (7 modelling studies; 4 observational studies) The studies assessed shift in epidemic development and cases detected. Most studies predicted positive effects for the combined measures with varying magnitudes (very low- to low-certainty evidence). Four observational studies observed that the proportion of cases detected for quarantine and screening at borders ranged from 68% to 92% (low-certainty evidence). The variation may depend on how the measures were combined, including the length of the quarantine period and days when the test was conducted in quarantine. AUTHORS' CONCLUSIONS: With much of the evidence derived from modelling studies, notably for travel restrictions reducing or stopping cross-border travel and quarantine of travellers, there is a lack of 'real-world' evidence. The certainty of the evidence for most travel-related control measures and outcomes is very low and the true effects are likely to be substantially different from those reported here. Broadly, travel restrictions may limit the spread of disease across national borders. Symptom/exposure-based screening measures at borders on their own are likely not effective; PCR testing at borders as a screening measure likely detects more cases than symptom/exposure-based screening at borders, although if performed only upon arrival this will likely also miss a meaningful proportion of cases. Quarantine, based on a sufficiently long quarantine period and high compliance is likely to largely avoid further transmission from travellers. Combining quarantine with PCR testing at borders will likely improve effectiveness. Many studies suggest that effects depend on factors, such as levels of community transmission, travel volumes and duration, other public health measures in place, and the exact specification and timing of the measure. Future research should be better reported, employ a range of designs beyond modelling and assess potential benefits and harms of the travel-related control measures from a societal perspective.