ArticleTravel medicine and infectious disease
Identifying mitigation strategies for COVID-19 superspreading on flights using models that account for passenger movement.
Article in Travel medicine and infectious disease. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 32 citations in OpenAlex.
- Acute respiratory infection (COVID-19) risk prediction in travelers: A random forest model.Infectious Disease Modelling · 2026Article
- Contraction of Respiratory Viral Infection During air Travel: An Under-Recognized Health Risk for Athletes.Sports medicine - open · 2024Article
- Article
- Stability of SARS-CoV-2 on Commercial Aircraft Interior Surfaces with Implications for Effective Control Measures.International journal of environmental research and public health · 2023Article
- COVID-19 pandemic and air transportation: Summary of Recent Research, Policy Consideration and Future Research Directions.Transportation research interdisciplinary perspectives · 2022Article
- Travel in the Time of COVID: A Review of International Travel Health in a Global Pandemic.Current infectious disease reports · 2022Review
- Comments on "Identifying mitigation strategies for COVID-19 superspreading on flights using models that account for passenger movement".Travel medicine and infectious diseaseArticle
- Reply to comments on "Identifying mitigation strategies for COVID-19 superspreading on flights using models that account for passenger movement".Travel medicine and infectious diseaseArticle
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite commercial airlines mandating masks, there have been multiple documented events of COVID-19 superspreading on flights. Conventional models do not adequately explain superspreading patterns on flights, with infection spread wider than expected from proximity based on passenger seating. An important reason for this is that models typically do not consider the movement of passengers during the flight, boarding, or deplaning. Understanding the risks for each of these aspects could provide insight into effective mitigation measures.
methodsWe modeled infection risk from seating and fine-grained movement patterns - boarding, deplaning, and inflight movement. We estimated infection model parameters from a prior superspreading event. We validated the model and the impact of interventions using available data from three flights, including cabin layout and seat locations of infected and uninfected passengers, to suggest interventions to mitigate COVID-19 superspreading events during air travel. Specifically, we studied: 1) London to Hanoi with 201 passengers, including 13 secondary infections among passengers; 2) Singapore to Hangzhou with 321 passengers, including 12 to 14 secondary infections; 3) a non-superspreading event on a private jet in Japan with 9 passengers and no secondary infections.
resultsOur results show that the inclusion of passenger movement better explains the infection spread patterns than conventional models do. We also found that FFP2/N95 mask usage would have reduced infection by 95-100%, while cloth masks would have reduced it by only 40-80%. Results indicate that leaving the middle seat vacant is effective in reducing infection, and the effectiveness increases when combined with good quality masks. However, with a good mask, the risk is quite low even without the middle seats being empty.
conclusionsOur results suggest the need for more stringent guidelines to reduce aviation-related superspreading events of COVID-19.
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