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Record W3109382244 · doi:10.1101/2020.11.23.20236703

Evidence of the effectiveness of travel-related measures during the early phase of the COVID- 19 pandemic: a rapid systematic review

2020· preprint· en· W3109382244 on OpenAlexaff
Karen A. Grépin, Tsi Lok Ho, Zhihan Liu, Summer Marion, Julianne Piper, Catherine Z Worsnop, Kelley Lee

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsObservational studyPandemicCoronavirus disease 2019 (COVID-19)Systematic reviewProtocol (science)Quality (philosophy)Meta-analysisMedicineBusinessPsychologyEnvironmental healthMEDLINEActuarial sciencePublic economicsPolitical scienceEconomicsAlternative medicine

Abstract

fetched live from OpenAlex

Abstract Objective To review evidence of the effectiveness of travel measures implemented during the early stages of the COVID-19 pandemic in order to recommend change on how evidence is incorporated in the International Health Regulations (2005) (IHR). Design We used an abbreviated preferred reporting items for systematic reviews and meta-analysis protocol (PRISMA-P) and a search strategy aimed to identify studies that investigated the effectiveness of travel-related measures (advice, entry and exit screening, medical examination or vaccination requirements, isolation or quarantine, the refusal of entry, and entry restrictions), pre-printed or published by June 1, 2020. Results We identified 29 studies, of which 26 were modelled (vs. observational). Thirteen studies investigated international measures while 17 investigated domestic measures (one investigated both), including suspended transportation (24 studies), border restrictions (21), and screening (5). There was a high level of agreement that the adoption of travel measures led to important changes in the dynamics of the early phases of the COVID-19 pandemic. However, most of the identified studies investigated the initial export of cases out of Wuhan, which was found to be highly effective, but few studies investigated the effectiveness of measures implemented in other contexts. Early implementation was identified as a determinant of effectiveness. Most studies of international travel measures failed to account for domestic travel measures, and thus likely led to biased estimates. Poor data and other factors contributed to the low quality of the studies identified. Conclusion Travel measures, especially those implemented in Wuhan, played a key role in shaping the early transmission dynamics of the COVID-19 pandemic, however, the effectiveness of these measures was short-lived. There is an urgent need to address important evidence gaps, but also a need to review the way in which evidence is incorporated in the IHR in the early phases of a novel infectious disease outbreak. What is already known on this subject? Previous reviews of the evidence from outbreaks of influenza and other infectious disease have generally found that there is limited evidence that travel-measures are effective at containing outbreaks. However, it is unclear if the lessons from other infectious disease outbreaks would be relevant in the context of COVID-19. Based on evidence at the time, WHO did not recommend any travel restrictions when it declared COVID-19 a Public Health Emergency of International Concern. What does this study add? This study rapidly reviews the evidence on the effectiveness of travel measures implemented in the early phase of the pandemic on epidemiological countries. The study investigated both international and domestic travel measures and a wide range of travel measures. The study finds that the domestic travel measures implemented in Wuhan were effective at reducing the importation of cases internationally and within China. The study also finds that travel measures are more effective when implemented earlier in the outbreak. The findings generate recommendations on how to incorporate evidence into the International Health Regulations and highlights important research gaps that remain. How might this affect future outbreaks? The findings of this study suggest the need to decouple recommendations of travel measures from the declaration of a public health emergency of international concern. Highlights the need to evaluate the potential effectiveness of travel measures for each outbreak, and not just assume effectiveness based on past outbreak scnearios.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.193
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.193
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.391
GPT teacher head0.440
Teacher spread0.049 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2020
Admission routes1
Has abstractyes

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