Identifying Mitigation Strategies for COVID-19 Superspreading on Flights using Models that Account for Passenger Movement

TL;DR

This study models COVID-19 superspreading on flights, showing passenger movement is crucial for understanding spread and highlighting the effectiveness of high-filtration masks like FFP2/N95 in reducing infections.

Contribution

It introduces models that incorporate passenger movement to better explain infection spread and evaluates mitigation strategies, including mask efficacy, during air travel.

Findings

Passenger movement improves infection spread modeling.

FFP2/N95 masks could reduce infections by up to 100%.

Cloth masks reduce infections by 40-80%.

Abstract

Despite commercial airlines mandating masks, there have been multiple documented events of COVID-19 superspreading on flights. We used 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. We show that 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%. This suggests the need for more stringent guidelines to reduce aviation-related superspreading events of COVID-19.