TY - JOUR
T1 - Identifying mitigation strategies for COVID-19 superspreading on flights using models that account for passenger movement
AU - Namilae, Sirish
AU - Wu, Yuxuan
AU - Mubayi, Anuj
AU - Srinivasan, Ashok
AU - Scotch, Matthew
N1 - Funding Information:
This material is based upon work supported by the National Science Foundation under grant numbers 1931511 , 2027514 , 1931483 , and 2027518 . Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357 . This work also used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562 .
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/5/1
Y1 - 2022/5/1
N2 - Background: Despite 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. Methods: We 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. Results: Our 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. Conclusions: Our results suggest the need for more stringent guidelines to reduce aviation-related superspreading events of COVID-19.
AB - Background: Despite 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. Methods: We 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. Results: Our 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. Conclusions: Our results suggest the need for more stringent guidelines to reduce aviation-related superspreading events of COVID-19.
KW - Aircraft
KW - Infectious disease transmission
KW - Masks
KW - SARS-CoV-2
KW - Spatial interaction models
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U2 - 10.1016/j.tmaid.2022.102313
DO - 10.1016/j.tmaid.2022.102313
M3 - Article
C2 - 35306163
AN - SCOPUS:85126617194
SN - 1477-8939
VL - 47
JO - Travel Medicine and Infectious Disease
JF - Travel Medicine and Infectious Disease
M1 - 102313
ER -