Evidence of the effectiveness of travel-related measures during the early phase of the COVID- 19 pandemic: a rapid systematic review
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.169 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.022 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".