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Introduction: During the SARS-CoV-2 pandemic, policymakers have to make far-reaching decisions that should be supported by scientific evidence. This presents a major challenge, given the limited availability of evidence, especially in the early phases of the pandemic. Decision-makers thus turned to scientific experts to help to convey and contextualize the evidence for public health policymaking. The way in which these experts were consulted varied widely. Some decision-makers called on expert committees in which they convened multiple experts from different disciplines. However, the composition and role of these committees have raised questions of transparency and representation. This study examines whether and how expert committees in Germany were convened at the federal and national level to advise governments and ministries during the SARS-CoV-2 pandemic. We investigated the disciplinary composition, gender representation and the transparency related to the convening of these bodies, work processes and the accessibility of results., Methods: We performed a multi-stage document analysis. Between May and July 2020, we submitted freedom-of-information requests to the governmental institutions at both a federal and a national level. In addition to analysing the responses to these requests, we conducted a thorough search and analysis of the i) pandemic preparedness plans, (ii) official press releases and (iii) minor interpellations ("Kleine Anfragen") at the federal and state level. We included documents on expert committees in the SARS-CoV-2 context for the period from January to the beginning of December 2020 and carried out a qualitative content analysis., Results: We identified a total of 21 expert committees that were established in ten federal states and four federal ministries. In eleven committees, the members were known by name, with women making up 26 % of the members. Biomedical disciplines such as virology, hygiene, medicine, and biology were the most commonly represented. Other disciplines including economics, law and sociology, and non-scientific experts were represented in seven federal states. The members of ten committees were not known by name. These committees covered different thematic areas (school and day-care, civil participation, medicine and care, economic topics), and their members were more commonly practitioners or came from affected populations., Discussion: The SARS-CoV-2 pandemic has led to an increased consultation of experts in public health policymaking. However, expert committees in Germany are not sufficiently representative and interdisciplinary to take different perspectives into account and ultimately advise politicians in complex pandemic situations. Furthermore, the work of these committees is not sufficiently transparent because access to information is limited., Conclusion: Due to this lack of transparency, it is unclear whether and how the expert committees exerted an influence on politics. Transparency of political decision-making processes and the consideration of pluralistic perspectives are considered essential for the legitimation and quality of political decisions in a pandemic and should therefore be strengthened in pandemic management in Germany., (Copyright © 2021. Published by Elsevier GmbH.)

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., (Copyright © 2021 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)

Background: In response to the spread of SARS-CoV-2 and the impact of COVID-19, national and subnational governments implemented a variety of measures in order to control the spread of the virus and the associated disease. While these measures were imposed with the intention of controlling the pandemic, they were also associated with severe psychosocial, societal, and economic implications on a societal level. One setting affected heavily by these measures is the school setting. By mid-April 2020, 192 countries had closed schools, affecting more than 90% of the world's student population. In consideration of the adverse consequences of school closures, many countries around the world reopened their schools in the months after the initial closures. To safely reopen schools and keep them open, governments implemented a broad range of measures. The evidence with regards to these measures, however, is heterogeneous, with a multitude of study designs, populations, settings, interventions and outcomes being assessed. To make sense of this heterogeneity, we conducted a rapid scoping review (8 October to 5 November 2020). This rapid scoping review is intended to serve as a precursor to a systematic review of effectiveness, which will inform guidelines issued by the World Health Organization (WHO). This review is reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist and was registered with the Open Science Framework., Objectives: To identify and comprehensively map the evidence assessing the impacts of measures implemented in the school setting to reopen schools, or keep schools open, or both, during the SARS-CoV-2/COVID-19 pandemic, with particular focus on the types of measures implemented in different school settings, the outcomes used to measure their impacts and the study types used to assess these., Search Methods: We searched the Cochrane COVID-19 Study Register, MEDLINE, Embase, the CDC COVID-19 Research Articles Downloadable Database for preprints, and the WHO COVID-19 Global literature on coronavirus disease on 8 October 2020., Selection Criteria: We included studies that assessed the impact of measures implemented in the school setting. Eligible populations were populations at risk of becoming infected with SARS-CoV-2, or developing COVID-19 disease, or both, and included people both directly and indirectly impacted by interventions, including students, teachers, other school staff, and contacts of these groups, as well as the broader community. We considered all types of empirical studies, which quantitatively assessed impact including epidemiological studies, modelling studies, mixed-methods studies, and diagnostic studies that assessed the impact of relevant interventions beyond diagnostic test accuracy. Broad outcome categories of interest included infectious disease transmission-related outcomes, other harmful or beneficial health-related outcomes, and societal, economic, and ecological implications., Data Collection and Analysis: We extracted data from included studies in a standardized manner, and mapped them to categories within our a priori logic model where possible. Where not possible, we inductively developed new categories. In line with standard expectations for scoping reviews, the review provides an overview of the existing evidence regardless of methodological quality or risk of bias, and was not designed to synthesize effectiveness data, assess risk of bias, or characterize strength of evidence (GRADE)., Main Results: We included 42 studies that assessed measures implemented in the school setting. The majority of studies used mathematical modelling designs (n = 31), while nine studies used observational designs, and two studies used experimental or quasi-experimental designs. Studies conducted in real-world contexts or using real data focused on the WHO European region (EUR; n = 20), the WHO region of the Americas (AMR; n = 13), the West Pacific region (WPR; n = 6), and the WHO Eastern Mediterranean Region (EMR; n = 1). One study conducted a global assessment and one did not report on data from, or that were applicable to, a specific country. Three broad intervention categories emerged from the included studies: organizational measures to reduce transmission of SARS-CoV-2 (n = 36), structural/environmental measures to reduce transmission of SARS-CoV-2 (n = 11), and surveillance and response measures to detect SARS-CoV-2 infections (n = 19). Most studies assessed SARS-CoV-2 transmission-related outcomes (n = 29), while others assessed healthcare utilization (n = 8), other health outcomes (n = 3), and societal, economic, and ecological outcomes (n = 5). Studies assessed both harmful and beneficial outcomes across all outcome categories., Authors' Conclusions: We identified a heterogeneous and complex evidence base of measures implemented in the school setting. This review is an important first step in understanding the available evidence and will inform the development of rapid reviews on this topic., (Copyright © 2020 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)

Background: In late 2019, first cases of coronavirus disease 2019, or COVID-19, caused by the novel coronavirus SARS-CoV-2, were reported in Wuhan, China. Subsequently COVID-19 spread rapidly around the world. To contain the ensuing pandemic, numerous countries have implemented control measures related to international travel, including border closures, partial travel restrictions, entry or exit screening, and quarantine of travellers., Objectives: To assess the effectiveness of travel-related control measures during the COVID-19 pandemic on infectious disease and screening-related outcomes., Search Methods: We searched MEDLINE, Embase and COVID-19-specific databases, including the WHO Global Database on COVID-19 Research, the Cochrane COVID-19 Study Register, and the CDC COVID-19 Research Database on 26 June 2020. We also conducted backward-citation searches with existing reviews., Selection Criteria: We considered experimental, quasi-experimental, observational and modelling studies assessing the effects of travel-related control measures affecting human travel across national borders during the COVID-19 pandemic. We also included studies concerned with severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) as indirect evidence. Primary outcomes were cases avoided, cases detected and a shift in epidemic development due to the measures. 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: One review author screened titles and abstracts; all excluded abstracts were screened in duplicate. Two review authors independently screened full texts. One review author extracted data, assessed risk of bias and appraised study quality. At least one additional review author checked for correctness of all data reported in the 'Risk of bias' assessment, quality appraisal and data synthesis. For assessing 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, ROBINS-I for observational ecological studies and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed certainty of evidence with GRADE, and the review author team discussed ratings., Main Results: We included 40 records reporting on 36 unique studies. We found 17 modelling studies, 7 observational screening studies and one observational ecological study on COVID-19, four modelling and six observational studies on SARS, and one modelling study on SARS and MERS, covering a variety of settings and epidemic stages. Most studies compared travel-related control measures against a counterfactual scenario in which the intervention measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of travel restrictions, or a combination of measures. There were concerns with the quality of many modelling studies and the risk of bias of observational studies. Many modelling studies used potentially inappropriate assumptions about the structure and input parameters of models, and failed to adequately assess uncertainty. Concerns with observational screening studies commonly related to the reference test and the flow of the screening process. Studies on COVID-19 Travel restrictions reducing cross-border travel Eleven studies employed models to simulate a reduction in travel volume; one observational ecological study assessed travel restrictions in response to the COVID-19 pandemic. Very low-certainty evidence from modelling studies suggests that when implemented at the beginning of the outbreak, cross-border travel restrictions may lead to a reduction in the number of new cases of between 26% to 90% (4 studies), the number of deaths (1 study), the time to outbreak of between 2 and 26 days (2 studies), the risk of outbreak of between 1% to 37% (2 studies), and the effective reproduction number (1 modelling and 1 observational ecological study). Low-certainty evidence from modelling studies suggests a reduction in the number of imported or exported cases of between 70% to 81% (5 studies), and in the growth acceleration of epidemic progression (1 study). Screening at borders with or without quarantine Evidence from three modelling studies of entry and exit symptom screening without quarantine suggests delays in the time to outbreak of between 1 to 183 days (very low-certainty evidence) and a detection rate of infected travellers of between 10% to 53% (low-certainty evidence). Six observational studies of entry and exit screening were conducted in specific settings such as evacuation flights and cruise ship outbreaks. Screening approaches varied but followed a similar structure, involving symptom screening of all individuals at departure or upon arrival, followed by quarantine, and different procedures for observation and PCR testing over a period of at least 14 days. The proportion of cases detected ranged from 0% to 91% (depending on the screening approach), and the positive predictive value ranged from 0% to 100% (very low-certainty evidence). The outcomes, however, should be interpreted in relation to both the screening approach used and the prevalence of infection among the travellers screened; for example, symptom-based screening alone generally performed worse than a combination of symptom-based and PCR screening with subsequent observation during quarantine. Quarantine of travellers Evidence from one modelling study simulating a 14-day quarantine suggests a reduction in the number of cases seeded by imported cases; larger reductions were seen with increasing levels of quarantine compliance ranging from 277 to 19 cases with rates of compliance modelled between 70% to 100% (very low-certainty evidence)., Authors' Conclusions: With much of the evidence deriving from modelling studies, notably for travel restrictions reducing cross-border travel and quarantine of travellers, there is a lack of 'real-life' evidence for many of these measures. The certainty of the evidence for most travel-related control measures is very low and the true effects may be substantially different from those reported here. Nevertheless, some travel-related control measures during the COVID-19 pandemic may have a positive impact on infectious disease outcomes. Broadly, travel restrictions may limit the spread of disease across national borders. Entry and exit symptom screening measures on their own are not likely to be effective in detecting a meaningful proportion of cases to prevent seeding new cases within the protected region; combined with subsequent quarantine, observation and PCR testing, the effectiveness is likely to improve. There was insufficient evidence to draw firm conclusions about the effectiveness of travel-related quarantine on its own. Some of the included studies suggest that effects are likely to depend on factors such as the stage of the epidemic, the interconnectedness of countries, local measures undertaken to contain community transmission, and the extent of implementation and adherence., (Copyright © 2020 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)