Estimating the impact of control measures to prevent outbreaks of COVID-19 associated with air travel into a COVID-19-free country
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Abstract
We aimed to estimate the risk of COVID-19 outbreaks associated with air travel to a COVID-19-free country [New Zealand (NZ)]. A stochastic version of the SEIR model CovidSIM v1.1, designed specifically for COVID-19 was utilised. We first considered historical data for Australia before it eliminated COVID-19 (equivalent to an outbreak generating 74 new cases/day) and one flight per day to NZ with no interventions in place. This gave a median time to an outbreak of 0.2 years (95% range of simulation results: 3 days to 1.1 years) or a mean of 110 flights per outbreak. However, the combined use of a pre-flight PCR test of saliva, three subsequent PCR tests (on days 1, 3 and 12 in NZ), and various other interventions (mask use and contact tracing) reduced this risk to one outbreak after a median of 1.5 years (20 days to 8.1 years). A pre-flight test plus 14 days quarantine was an even more effective strategy (4.9 years; 2,594 flights). For a much lower prevalence (representing only two new community cases per week in the whole of Australia), the annual risk of an outbreak with no interventions was 1.2% and had a median time to an outbreak of 56 years. In contrast the risks associated with travellers from Japan and the United States was very much higher and would need quarantine or other restrictions. Collectively, these results suggest that multi-layered interventions can markedly reduce the risk of importing the pandemic virus via air travel into a COVID-19-free nation. For some low-risk source countries, there is the potential to replace 14-day quarantine with alternative interventions. However, all approaches require public and policy deliberation about acceptable risks, and continuous careful management and evaluation.
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SciScore for 10.1101/2020.06.10.20127977: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:With such information policy-makers could then decide: Study strengths and limitations: This is the first such modeling study (that we know of), to consider interventions to control SARS-CoV-2 spread by air travel between two countries. We were also able to consider a wide range of control interventions and to package these in multiple …
SciScore for 10.1101/2020.06.10.20127977: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:With such information policy-makers could then decide: Study strengths and limitations: This is the first such modeling study (that we know of), to consider interventions to control SARS-CoV-2 spread by air travel between two countries. We were also able to consider a wide range of control interventions and to package these in multiple layers of defense and estimate uncertainty intervals. Nevertheless, there is quite high uncertainty around some of the parameters we used. For example, the prevalence of infection in Australia is highly variable by States/Territories, and this is also likely to vary over time. Real-world effectiveness of masks on aircraft is still uncertain, along with how well SARS-CoV-2 can spread on aircraft. For example, there is some evidence that this pandemic virus is particularly involved in super-spreading events with one estimate being that 80% of secondary transmissions may have been caused by a small fraction (e.g., ∼10%) of infectious individuals (39). Given all such issues and ongoing improvements in knowledge of the transmission dynamics of SARS-CoV-2, this type of modeling work should be regularly revised and be performed using different types of models.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a protocol registration statement.
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