Infected Passengers Research Articles

3D modelling and simulation of the dispersion of droplets and drops carrying the SARS-CoV-2 virus in a railway transport coach

Computational fluid dynamics (CFD) modelling and 3D simulations of the air flow and dispersion of droplets or drops in semi-confined ventilated spaces have found topical applications with the unfortunate development of the Covid-19 pandemic. As an illustration of this scenario, we have considered the specific situation of a railroad coach containing a seated passenger infected with the SARS-CoV-2 virus (and not wearing a face mask) who, by breathing and coughing, releases droplets and drops that contain the virus and that present aerodynamic diameters between 1 and 1000 µm. The air flow is generated by the ventilation in the rail coach. While essentially 3D, the flow is directed from the bottom to the top of the carriage and comprises large to small eddies visualised by means of streamlines. The space and time distribution of the droplets and drops is computed using both an Eulerian model and a Lagrangian model. The results of the two modelling approaches are fully consistent and clearly illustrate the different behaviours of the drops, which fall down close to the infected passenger, and the droplets, which are carried along with the air flow and invade a large portion of the rail coach. This outcome is physically sound and demonstrates the relevance of CFD for simulating the transport and dispersion of droplets and drops with any diameter in enclosed ventilated spaces. As coughing produces drops and breathing produces droplets, both modes of transmission of the SARS-CoV-2 virus in human secretions have been accounted for in our 3D numerical study. Beyond the specific, practical application of the rail coach, this study offers a much broader scope by demonstrating the feasibility and usefulness of 3D numerical simulations based on CFD. As a matter of fact, the same computational approach that has been implemented in our study can be applied to a huge variety of ventilated indoor environments such as restaurants, performance halls, classrooms and open-plan offices in order to evaluate if their occupation could be critical with respect to the transmission of the SARS-CoV-2 virus or to other airborne respiratory infectious agents, thereby enabling relevant recommendations to be made.

A knowledge graph-based method for epidemic contact tracing in public transportation

Contact tracing is an effective measure by which to prevent further infections in public transportation systems. Considering the large number of people infected during the COVID-19 pandemic, digital contact tracing is expected to be quicker and more effective than traditional manual contact tracing, which is slow and labor-intensive. In this study, we introduce a knowledge graph-based framework for fusing multi-source data from public transportation systems to construct contact networks, design algorithms to model epidemic spread, and verify the validity of an effective digital contact tracing method. In particular, we take advantage of the trip chaining model to integrate multi-source public transportation data to construct a knowledge graph. A contact network is then extracted from the constructed knowledge graph, and a breadth-first search algorithm is developed to efficiently trace infected passengers in the contact network. The proposed framework and algorithms are validated by a case study using smart card transaction data from transit systems in Xiamen, China. We show that the knowledge graph provides an efficient framework for contact tracing with the reconstructed contact network, and the average positive tracing rate is over 96%.

Effects of purifiers on the airborne transmission of droplets inside a bus.

During an airborne infectious disease outbreak, bus passengers can be easily infected by the dispersion of exhaled droplets from an infected passenger. Therefore, measures to control the transport of droplets are necessary, such as a mask or purifier. The current research examined aerosol transport in a bus with air-conditioning. To determine the dispersion path, deposition distribution, and droplet escape time, the computational fluid dynamics were used to predict the flow field and the dispersion of droplets considering the effects of droplet size, location of the infected person, and purifier type. In addition, based on the viability and the number of virus particles in a droplet, the total number of virus particles inhaled by passengers over a 4-h journey was obtained by the superposition method. The Wells–Riley equation was then used to assess the infection risk of the passengers in the bus cabin. The results showed that droplets with a size of 1–20 μm have essentially the same deposition characteristics, and the location of the infected passenger affects the distribution of droplets' transport and the effectiveness of a purifier in removing droplets. A purifier can effectively remove droplets from passengers' coughs and reduce the infection risk of passengers. The performance of the smaller purifiers is not as stable as that of the larger purifiers, and the performance is influenced by the airflow structure where the infected passenger is located.

Research of air-drop mixture particles movement in passenger aircraft cabin

The paper examined the mechanism of propagation and deposition of potentially pathogenic particles in the field of turbulent air flow of the heating and air conditioning system of the closed cabin of a passenger aircraft. In pandemic conditions, when the disease is transmitted from person to person through the air, knowledge and understanding of the patterns of movement of particles of the airborne droplet mixture in a small confined space with a high population density allows assessing the risks of infection and the amount of post-flight processing required, as well as the level of passenger control. Simulation model of air-drop mixture distribution in passenger aircraft cabin is proposed, which is built on the basis of three-dimensional finite-element model of flow motion in non-stationary setting. Two-factor dispersion analysis was carried out to determine the significance of the effect of flight time and cabin area on particle deposition intensity. A regression model of the propagation density of precipitated viral particles of the air drop mixture was constructed and investigated depending on the temperature, ventilation method, layout and number of infected passengers. Based on the results of the studies, temporal and volumetric characteristics of the distribution of particles of the air-drop mixture were obtained, directions and meanings of the mutual influence of the selected main factors of the model on the mechanism of distribution and deposition of potentially pathogenic particles were determined, recommendations were developed on the organization of the process of disinfection measures in the passenger aircraft cabin.

Aerosol tracer testing in Boeing 767 and 777 aircraft to simulate exposure potential of infectious aerosol such as SARS-CoV-2.

The COVID-19 pandemic has reintroduced questions regarding the potential risk of SARS-CoV-2 exposure amongst passengers on an aircraft. Quantifying risk with computational fluid dynamics models or contact tracing methods alone is challenging, as experimental results for inflight biological aerosols is lacking. Using fluorescent aerosol tracers and real time optical sensors, coupled with DNA-tagged tracers for aerosol deposition, we executed ground and inflight testing on Boeing 767 and 777 airframes. Analysis here represents tracer particles released from a simulated infected passenger, in multiple rows and seats, to determine the exposure risk via penetration into breathing zones in that row and numerous rows ahead and behind the index case. We present here conclusions from 118 releases of fluorescent tracer particles, with 40+ Instantaneous Biological Analyzer and Collector sensors placed in passenger breathing zones for real-time measurement of simulated virus particle penetration. Results from both airframes showed a minimum reduction of 99.54% of 1 μm aerosols from the index source to the breathing zone of a typical passenger seated directly next to the source. An average 99.97 to 99.98% reduction was measured for the breathing zones tested in the 767 and 777, respectively. Contamination of surfaces from aerosol sources was minimal, and DNA-tagged 3 μm tracer aerosol collection techniques agreed with fluorescent methodologies.

Algorithm for Preventing the Spread of COVID-19 in Airports and Air Routes by Applying Fuzzy Logic and a Markov Chain

Since the start of COVID-19 and its growth into an uncontrollable pandemic, the spread of diseases through airports has become a serious health problem around the world. This study presents an algorithm to determine the risk of spread in airports and air routes. Graphs are applied to model the air transport network and Dijkstra’s algorithm is used for generating routes. Fuzzy logic is applied to evaluate multiple demographics, health, and transport variables and identify the level of spread in each airport. The algorithm applies a Markov chain to determine the probability of the arrival of an infected passenger with the COVID-19 virus to an airport in any country in the world. The results show the optimal performance of the proposed algorithm. In addition, some data are presented that allow for the application of actions in health and mobility policies to prevent the spread of infectious diseases.

The risk of SARS-CoV-2 outbreaks in low prevalence settings following the removal of travel restrictions

BackgroundCountries around the world have introduced travel restrictions to reduce SARS-CoV-2 transmission. As vaccines are gradually rolled out, attention has turned to when travel restrictions and other non-pharmaceutical interventions (NPIs) can be relaxed.MethodsUsing SARS-CoV-2 as a case study, we develop a mathematical branching process model to assess the risk that, following the removal of NPIs, cases arriving in low prevalence settings initiate a local outbreak. Our model accounts for changes in background population immunity due to vaccination. We consider two locations with low prevalence in which the vaccine rollout has progressed quickly – specifically, the Isle of Man (a British crown dependency in the Irish Sea) and the country of Israel.ResultsWe show that the outbreak risk is unlikely to be eliminated completely when travel restrictions and other NPIs are removed. This general result is the most important finding of this study, rather than exact quantitative outbreak risk estimates in different locations. It holds even once vaccine programmes are completed. Key factors underlying this result are the potential for transmission even following vaccination, incomplete vaccine uptake, and the recent emergence of SARS-CoV-2 variants with increased transmissibility.ConclusionsCombined, the factors described above suggest that, when travel restrictions are relaxed, it may still be necessary to implement surveillance of incoming passengers to identify infected individuals quickly. This measure, as well as tracing and testing (and/or isolating) contacts of detected infected passengers, remains useful to suppress potential outbreaks while global case numbers are high.

Computational study on the transmission of the SARS-CoV-2 virus through aerosol in an elevator cabin: Effect of the ventilation system.

Aerosol transmission is now well-established as a route in the spread of the SARS-CoV-2 virus. Factors influencing the transport of virus-laden particles in an elevator cabin are investigated computationally and include human respiratory events, locations of the infected person(s), and the ventilation system (ventilation mode, ventilation capacity, and vent schemes). “Breath,” “cough,” and “sneeze” are defined quantitatively by the fluid jet velocities and particle sizes. For natural ventilation, most particles exhaled by sneezing and coughing tend to deposit on surfaces quickly, but aerosol generated by breathing will remain suspended in the air longer. For forced ventilation, motions of particles under different ventilation capacities are compared. Larger particles otherwise deposited readily on solid surfaces may be slowed down by airflow. Air currents also accelerate the motions of smaller particles, facilitating the subsequent deposition of micrometer or sub-micrometer particles. Locations of the infected person(s) lead to different spreading scenarios due to the distinctive motions of the particles generated by the various respiratory events. Sneeze particles will likely contaminate the person in front of the infected passenger only. Cough particles will increase the risk of all the people around the injector. Breath particles tend to spread throughout the confined environment. An optimized vent scheme is introduced and can reduce particles suspended in the air by up to 80% as compared with commonly used schemes. The purification function of this vent model is robust to various positions of the infected passenger.

Transmission of SARS-CoV-2 associated with aircraft travel: a systematic review.

Rationale for the reviewAir travel may be associated with viruses spread via infected passengers and potentially through in-flight transmission. Given the novelty of the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, transmission associated with air travel is based on transmission dynamics of other respiratory viruses. Our objective was to provide a rapid summary and evaluation of relevant data on SARS-CoV-2 transmission aboard aircraft, report policy implications and to highlight research gaps requiring urgent attention.MethodsWe searched four electronic databases (1 February 2020–27 January 2021) and included studies on SARS-CoV-2 transmission aboard aircraft. We assessed study quality based on five criteria and reported important findings.Key findingsWe included 18 studies on in-flight SARS-CoV-2 transmission (130 unique flights) and 2 studies on wastewater from aircraft. The quality of evidence from most published studies was low. Two wastewater studies reported PCR-positive samples with high cycle threshold values (33–39). Index case definition was heterogeneous across studies. The proportion of contacts traced ranged from 0.68 to 100%. Authors traced 2800/19 729 passengers, 140/180 crew members and 8/8 medical staff. Altogether, 273 index cases were reported, with 64 secondary cases. Three studies, each investigating one flight, reported no secondary cases. Secondary attack rate among studies following up >80% of passengers and crew (including data on 10 flights) varied between 0 and 8.2%. The studies reported on the possibility of SARS-CoV-2 transmission from asymptomatic, pre-symptomatic and symptomatic individuals. Two studies performed viral cultures with 10 positive results. Genomic sequencing and phylogenetic analysis were performed in individuals from four flights.ConclusionCurrent evidence suggests SARS-CoV-2 can be transmitted during aircraft travel, but published data do not permit any conclusive assessment of likelihood and extent. The variation in design and methodology restricts the comparison of findings across studies. Standardized guidelines for conducting and reporting future studies of transmission on aircraft should be developed.

Spread of virus laden aerosols inside a moving sports utility vehicle with open windows: A numerical study.

A three dimensional Computational Fluid Dynamics (CFD) model to study the dispersion of virus laden aerosols in a car moving with its windows open is reported. The aerosols are generated when a possibly infected passenger speaks. A sports utility vehicle having three rows of seats has been considered. As the vehicle moves forward, its interior will exchange air from the surroundings. The CFD model captures the flow patterns generated both outside and inside the vehicle. This internal aerodynamics will in turn dictate how aerosols will spread across the interior and whether or not they will be transported outside the vehicle. A Lagrangian approach is used to determine the transport of the aerosol particles and the effect of particle size on the simulation result has been studied. Four sets of scenarios of practical interest have been considered. The first set shows the effect of vehicle speed on aerosol transport, and the second set describes what happens when some of the windows are closed, while the third set describes how aerosol transport is affected by the location of the passenger speaking. The fourth set describes how a gush of cross wind affects aerosol transport. Simulation results reveal that when all windows are open, aerosols can go out of one window and then return back to the vehicle interior through another window. Results also reveal that when a passenger sitting in the second row speaks, the aerosols generated span across the entire volume of the car interior before going out through the open windows.

Passenger exposure to respiratory aerosols in a train cabin: Effects of window, injection source, output flow location.

Nowadays the use of public transportation (PT) has been identified as high risk as due to the transfer of particles carrying the coronavirus from an infected passenger to others. This study puts forward a new computational framework for predicting the spread of droplets produced while the infected passenger talking inside the cabin of a train during various scenarios, including the changes in the outflows' location and the infected passenger's position. CFD was used to conduct the study, using the Euler-Lagrange approach to capture the transmission of particles, and Reynolds-averaged Navier–Stokes equations (RANS) to compute the airflow field. The results revealed that opening the window reduces the duration of particles inside the domain. So that when the window is open, the particle's shelf time can decrease to 25 percent comparing with closed mode. It was found that the passenger sitting next to the infected passenger encountered the highest infection risk. The conclusions made in this work show that the most desirable situation is obtained when the infected passenger is sitting next to the exits, whether the window is closed or open. The results of this paper offer comprehensive insights into how to keep indoor environments safe against infection aerosols.

On the utility of a well-mixed model for predicting disease transmission on an urban bus.

The transport of virus-laden aerosols from a host to a susceptible person is governed by complex turbulent airflow and physics related to breathing, coughing and sneezing, mechanical and passive ventilation, thermal buoyancy effects, surface deposition, masks, and air filtration. In this paper, we study the infection risk via airborne transmission on an urban bus using unsteady Reynolds-averaged Navier–Stokes equations and a passive-scalar model of the virus-laden aerosol concentration. Results from these simulations are directly compared to the widely used well-mixed model and show significant differences in the concentration field and number of inhaled particles. Specifically, in the limit of low mechanical ventilation rates, the well-mixed model will overpredict the concentration far from the infected passenger and substantially underpredict the concentration near the infected passenger. The results reported herein also apply to other enclosed spaces.

Respiratory bioaerosol deposition from a cough and recovery of viable viruses on nearby seats in a cabin environment.

Respiratory bioaerosol deposition in public transport cabins is critical for risk analysis and control of contact transmission. In this work, we built a two‐row four‐seat setup and an air duct system to simulate a cabin environment. A thermal manikin on the rear left‐hand seat was taken as the infected passenger (IP) and “coughed” three times through a cough generator. The deposited viruses and droplets on nearby seats were measured by a cultivation method and microscope, respectively. The effects of seat backrest and overhead gasper jet were studied. Results showed that the number of deposited virus on the front seat was one order of magnitude higher than that on other seats which only contained droplets smaller than 10 µm in diameter. When the backrest was 15 cm higher than the cough, the deposited number of viruses was reduced to 5% of that with the backrest at the same height with the cough. The gasper jet above the IP with a velocity of 1.5 m/s can reduce the deposited viruses to 4% of that with gasper off. It indicates that both the gasper jet and backrest can work as mitigation measures to block the cough jet and protect the nearby passengers.

Probability and estimated risk of SARS-CoV-2 transmission in the air travel system

BackgroundAs an emerging virus, SARS-CoV-2 and the risk of transmission during air travel is of high interest. This paper is a retrospective estimate of the probability of an infectious passenger in the air travel system transmitting the SARS-CoV-2 virus to a fellow passenger. MethodsLiterature was reviewed from May–September 2020 to identify COVID-19 cases related to air travel. The studies were limited to publicly available literature for passengers; studies of flight crews were not reviewed. A novel quantitative approach was developed to estimate air travel transmission risk that considers secondary cases, the overall passenger population, and correction factors for asymptomatic transmission and underreporting. ResultsThere were at least 2866 index infectious passengers documented to have passed through the air travel system in a 1.4 billion passenger population. Using correction factors, the global risk of transmission during air travel is estimated at 1:1.7 million; acknowledging that assumptions exist around case detection rate and mass screenings. Uncertainty in the correction factors and a 95% credible interval indicate risk ranges from 1 case for every 712,000 travelers to 1 case for every 8 million travelers. ConclusionThe risk of COVID-19 transmission on an aircraft is low, even with infectious persons onboard.

Experimental evaluation of particle exposure at different seats in a single-aisle aircraft cabin

During the COVID-19 pandemic, exposure to particles exhaled by infected passengers in commercial aircraft cabins has been a great concern. Currently, aircraft cabins adopt mixing ventilation. However, complete mixing may not be achieved, and thus the particle concentration in the respiratory zone may vary from seat to seat in a cabin. To evaluate the particle exposure in a typical single-aisle aircraft cabin, this investigation constructed an aircraft cabin mockup for experimental tests. Particles were released from a single source or dual sources at different seats to represent particles exhaled by infected passengers. The particle concentrations in the respiratory zones at various seats were measured and compared. The particle exposure was evaluated in both a cross section and a longitudinal section. Leaving the middle seat vacant to reduce particle exposure was also addressed. In addition, the velocity fields and air temperatures were measured to provide a better understanding of particle transport. It was found that the particle exposure at the window seat is always the lowest, regardless of the particle release locations. If the passenger seated in the middle does not release particles, his/her presence enhances the particle dispersion and thereby reduces the particle exposure for adjacent passengers. In the cabin mockup, the released particles can be transported across at least four rows of seats in the longitudinal direction.

Hand hygiene and facemask use to prevent droplet-transmitted viral diseases during air travel: a systematic literature review

BackgroundTransmission of viral diseases (e.g., influenza A H1N1) via respiratory droplets takes place mainly in confined spaces, including in aircraft during commercial air travel. The adoption of hygiene measures may help to prevent disease spread aboard aircraft. This review summarizes the evidence on hand hygiene and the use of facemasks as viral disease prevention measures in aircraft.MethodsA literature search was performed in the PubMed, Scopus, and Web of Science databases up to 10 June 2020, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria. A population, intervention, comparison, outcomes, and study design (PICOS) approach was used to define the review question.ResultsWe included four studies published between 2007 and 2020, all targeting influenza virus disease, in the qualitative synthesis. Three studies used mathematical models to simulate single- or multiple-direction flights, and two of them showed that facemask (e.g., N95 respirator) use considerably reduced infection probability. In the third study, hand cleaning by 20 to 60% of people at any time in all airports (including on aircraft) reduced the measure of airports’ power to spread the disease across the globe by ~ 24 to 69%. The fourth study was a case-control study designed to trace an influenza outbreak in two flights during the 2009 influenza A H1N1 pandemic. The study showed that none (0%) of nine infected passengers compared to 15 (47%) of 32 healthy control passengers in the aircraft cabin during one of these flights wore a facemask (odds ratio, 0.0; 95% confidence interval, 0.0–0.7). In contrast, both case and control passengers appeared to be equally compliant in self-assessed hand hygiene.ConclusionsFacemask use combined with hand hygiene may minimize the chance of droplet-transmitted virus spread by air travelers. Thus, it is necessary that hygiene measures become an integral part of standard procedures in commercial air travel.

Lack of cross-transmission of SARS-CoV-2 between passenger's cabins on the Diamond Princess cruise ship

An outbreak of COVID-19 occurred on the Diamond Princess cruise ship in January and February 2020 in Japan. We analysed information on the cases of infection to infer whether airborne transmission of SARS-CoV-2, the causative agent of COVID-19, had occurred between cabins. We infer from our analysis that most infections in passengers started on 28 January and were completed by 6 February, except in those who shared a cabin with another infected passenger. The distribution of the infected cabins was random, and no spatial cluster of the infected can be identified. We infer that the ship's central air-conditioning system for passenger's cabins did not play a role in SARS-CoV-2 transmission, i.e. airborne transmission did not occur between cabins during the outbreak, suggesting that the sufficient ventilation was provided. We also infer that the ship's cabin drainage system did not play a role. Most transmission appears to have occurred in the public areas of the cruise ship, likely due to crowding and insufficient ventilation in some of these areas.

Routine asymptomatic testing strategies for airline travel during the COVID-19 pandemic: a simulation study

BackgroundRoutine viral testing strategies for SARS-CoV-2 infection might facilitate safe airline travel during the COVID-19 pandemic and mitigate global spread of the virus. However, the effectiveness of these test-and-travel strategies to reduce passenger risk of SARS-CoV-2 infection and population-level transmission remains unknown.MethodsIn this simulation study, we developed a microsimulation of SARS-CoV-2 transmission in a cohort of 100 000 US domestic airline travellers using publicly available data on COVID-19 clinical cases and published natural history parameters to assign individuals one of five health states of susceptible to infection, latent period, early infection, late infection, or recovered. We estimated a per-day risk of infection with SARS-CoV-2 corresponding to a daily incidence of 150 infections per 100 000 people. We assessed five testing strategies: (1) anterior nasal PCR test within 3 days of departure, (2) PCR within 3 days of departure and 5 days after arrival, (3) rapid antigen test on the day of travel (assuming 90% of the sensitivity of PCR during active infection), (4) rapid antigen test on the day of travel and PCR test 5 days after arrival, and (5) PCR test 5 days after arrival. Strategies 2 and 4 included a 5-day quarantine after arrival. The travel period was defined as 3 days before travel to 2 weeks after travel. Under each scenario, individuals who tested positive before travel were not permitted to travel. The primary study outcome was cumulative number of infectious days in the cohort over the travel period without isolation or quarantine (population-level transmission risk), and the key secondary outcome was the number of infectious people detected on the day of travel (passenger risk of infection).FindingsWe estimated that in a cohort of 100 000 airline travellers, in a scenario with no testing or screening, there would be 8357 (95% uncertainty interval 6144–12831) infectious days with 649 (505–950) actively infectious passengers on the day of travel. The pre-travel PCR test reduced the number of infectious days from 8357 to 5401 (3917–8677), a reduction of 36% (29–41) compared with the base case, and identified 569 (88% [76–92]) of 649 actively infectious travellers on the day of flight; the addition of post-travel quarantine and PCR reduced the number of infectious days to 1474 (1087–2342), a reduction of 82% (80–84) compared with the base case. The rapid antigen test on the day of travel reduced the number of infectious days to 5674 (4126–9081), a reduction of 32% (26–38) compared with the base case, and identified 560 (86% [83–89]) actively infectious travellers; the addition of post-travel quarantine and PCR reduced the number of infectious days to 2518 (1935–3821), a reduction of 70% (67–72) compared with the base case. The post-travel PCR alone reduced the number of infectious days to 4851 (3714–7679), a reduction of 42% (35–49) compared with the base case.InterpretationRoutine asymptomatic testing for SARS-CoV-2 before travel can be an effective strategy to reduce passenger risk of infection during travel, although abbreviated quarantine with post-travel testing is probably needed to reduce population-level transmission due to importation of infection when travelling from a high to low incidence setting.FundingUniversity of California, San Francisco.

Risk of symptomatic COVID-19 due to aircraft transmission: a retrospective cohort study of contact-traced flights during England's containment phase.

BackgroundKnowledge gaps remain regarding SARS‐CoV‐2 transmission on flights. We conducted a retrospective cohort study to estimate risk of acquiring symptomatic SARS‐CoV‐2 on aircraft, to inform contact tracing and infection control efforts.MethodsWe identified co‐passengers of infectious passengers on 18 England‐bound flights from European cities up to 12/03/2020, using manifests received for contact tracing. Infectious passengers were laboratory‐confirmed cases with symptom onset from 7 days before to 2 days after the flight. Possible aircraft‐acquired cases were laboratory‐confirmed with onset 3‐14 days post‐flight with no known non‐flight exposure. Manifests was merged with the national case management dataset (identifying cases, onset dates, contact tracing status) and the national COVID‐19 linelist. Contact tracing notes were reviewed to identify non‐flight exposures. We calculated attack rates (ARs) among all co‐passengers and within subgroups, including by distance from infectious cases and number of infectious cases on‐board.ResultsThere were 55 infectious passengers and 2313 co‐passengers, including 2221 flight‐only contacts. Five possible aircraft‐acquired cases were identified; ARs of 0.2% (95%CI 0.1‐0.5) among all flight‐only contacts and 3.8% (95%CI 1.3‐10.6) among contact‐traced flight‐only contacts sat within a two‐seat radius. The AR among 92 co‐travellers with known non‐flight exposure to infectious cases was 13.0% (95%CI 7.6%‐21.4%). There were insufficient numbers to assess differences between subgroups.ConclusionWe conclude that risk of symptomatic COVID‐19 due to transmission on short to medium‐haul flights is low, and recommend prioritising contact‐tracing of close contacts and co‐travellers where resources are limited. Further research on risk on aircraft is encouraged.

Airplane Seating Assignment Problem

SARS-CoV-2, the virus that causes COVID-19, began infecting humans in late 2019 and has since spread to over 57 million people and caused over 1.75 million deaths, as of December 27, 2020. In response to reduced demand and travel restrictions as a result of COVID-19, airlines experienced a 94% reduction in passenger capacity worldwide in April and an estimated 60% reduction in passengers transported for all of 2020. SARS-CoV-2 has been shown to spread on airplanes by infected passengers, so minimizing the risk of secondary infections aboard aircraft may save lives. We present the airplane seating assignment problem (ASAP) to minimize transmission risks on airplanes, and we provide two models to solve ASAP. We show that both models can be effectively solved using a standard commercial solver and that seating assignments provided by these models have lower aggregate risk than the strategy of blocking the middle seats, given the same number of passengers. The available risk models for aircraft are based on influenza data, and hence risk models based on SARS-CoV-2 should be developed to maximize the benefits of our research.