Transmission of SARS-CoV-2 on aircraft: A scoping review

Transmission of SARS-CoV-2 on aircraft: A scoping review | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Transmission of SARS-CoV-2 on aircraft: A scoping review Constantine I. Vardavas , Katerina Nikitara , Katerina Aslanoglou , Apostolos Kamekis , Nithya Ramesh , Emmanouil Symvoulakis , Revati Phalkey , Jo Leonardi-Bee , Varvara Mouchtouri , Christos Hadjichristodoulou , Agoritsa Baka , Favelle Lamb , Jonathan E. Suk , Emmanuel Robesyn doi: https://doi.org/10.1101/2024.10.22.24315911 Constantine I. Vardavas 1 School of Medicine, University of Crete , Heraklion, Crete, Greece 2 Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Harvard University , Boston, MA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: vardavasc{at}uoc.gr Katerina Nikitara 1 School of Medicine, University of Crete , Heraklion, Crete, Greece Find this author on Google Scholar Find this author on PubMed Search for this author on this site Katerina Aslanoglou 1 School of Medicine, University of Crete , Heraklion, Crete, Greece Find this author on Google Scholar Find this author on PubMed Search for this author on this site Apostolos Kamekis 1 School of Medicine, University of Crete , Heraklion, Crete, Greece Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nithya Ramesh 2 Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Harvard University , Boston, MA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Emmanouil Symvoulakis 1 School of Medicine, University of Crete , Heraklion, Crete, Greece Find this author on Google Scholar Find this author on PubMed Search for this author on this site Revati Phalkey 3 Centre for Evidence Based Healthcare, Division of Epidemiology and Public Health, School of Medicine, University of Nottingham , UK 4 Heidelberg Institute of Global Health, University of Heidelberg , Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jo Leonardi-Bee 3 Centre for Evidence Based Healthcare, Division of Epidemiology and Public Health, School of Medicine, University of Nottingham , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Varvara Mouchtouri 5 Laboratory of Hygiene and Epidemiology, Medical Faculty, University of Thessaly Find this author on Google Scholar Find this author on PubMed Search for this author on this site Christos Hadjichristodoulou 5 Laboratory of Hygiene and Epidemiology, Medical Faculty, University of Thessaly Find this author on Google Scholar Find this author on PubMed Search for this author on this site Agoritsa Baka 6 Emergency Preparedness and Response Support, European Centre for Disease Prevention and Control , Stockholm, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site Favelle Lamb 6 Emergency Preparedness and Response Support, European Centre for Disease Prevention and Control , Stockholm, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jonathan E. Suk 6 Emergency Preparedness and Response Support, European Centre for Disease Prevention and Control , Stockholm, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site Emmanuel Robesyn 6 Emergency Preparedness and Response Support, European Centre for Disease Prevention and Control , Stockholm, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF ABSTRACT Introduction The assessment of empirical epidemiological data is needed to assess the transmissibility of SARS-CoV-2 in aircraft settings. This review summarises reported contact- tracing data and evaluates the secondary attack rates (SAR) and factors associated with SARS- CoV-2 transmission in aircraft, to provide insight for future decision making in the context of future respiratory pandemics. Methods This scoping literature review assessed studies published between December 2020 to November 2023 in Ovid Medline, Embase and Cochrane Library databases. The inclusion criteria were based on the PCC framework (P-Population, C-Concept, C-Context). The study population was restricted to passengers and crew (population) to assess transmission (concept) in an aircraft setting (context). Results Thirty-one studies which assess SARS-CoV-2 transmission in 521 domestic and international flights were included in this systematic review. The SAR reported in the studies with an identified index case ranged from 0% to 16%. Significant variation in the reporting across studies was noted. Overall, the studies reported that using face masks or respirators by passengers and crew members during flight seemed to be a possible strategy for mitigating SARS-CoV-2 transmission while sitting within close proximity to index cases (≤2 seats in every direction) was associated with a higher SAR. Conclusions Our results are consistent with sporadic clusters happening onboard aircraft. Close proximity to COVID-19 cases within the aircraft was associated with a higher SAR. Our findings further underscore the need for a systematic approach to examining and reporting SARS-CoV-2 transmission onboard aircraft. This evidence may assist policymakers and transportation authorities in the development of emergency preparedness measures and travel guidance during the post-pandemic COVID-19 era. INTRODUCTION Aerosol and droplet transmission and contact with infected surfaces may all contribute to the onboard transmission of SARS-CoV-2, as in other closed environments [ 1 ]. Additionally, congregation during flights as well as during boarding and disembarking may also affect the likelihood of infection transmission within aircraft settings [ 2 ]. Measures such as mask use, screening, restriction of in-flight services, physical distancing measures, along with the use of high ventilation rates and high-efficiency particulate air (HEPA) filtration in the aircraft have been actions implemented by the aviation industry aiming to mitigate transmission within aircraft settings [ 3 ]. To better understand aircraft transmission, studies have been developed based on the dynamics of other respiratory infectious diseases such as influenza, and SARS-CoV-1, or have used experimental aerosol dispersion or modelling data to estimate the possibility and likelihood of in- flight transmission [ 4 , 5 ]. While previous systematic reviews using studies published up to 2022 indicated that SARS-CoV-2 could be transmitted during aircraft travel [ 6 , 7 ], we sought further epidemiological data for assessing the transmissibility of SARS-CoV-2 in aircraft, taking the entire duration of the COVID-19 pandemic and the most recent evidence into account. This review summarises reported contact-tracing information and provides and overview of reported secondary attack rates (SAR) and factors associated with in-flight SARS-CoV-2 transmission, that could be used to support both study design and public health decision-making within the context of future respiratory pandemics. METHODS The scoping review was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) [ 8 ] and MOOSE (Meta-analyses Of Observational Studies in Epidemiology) guidelines [ 9 ]. The protocol was not pre-registered in a database for systematic reviews. Outcomes and inclusion/exclusion criteria Peer-reviewed studies published between December 1, 2020 and November 3, 2023 were identified through systematic electronic searches using OVID Medline, EMBASE, and the Cochrane Library. While a repository of reviews and not original studies, the Cochrane Library was searched so as to assess the reference lists of potential relevant reviews systematic and non- systematic literature reviews. The detailed search strategies are presented in Supplementary - Appendix 1 . Predefined inclusion and exclusion criteria were used to determine the eligibility of the studies based on the PCC framework (P-Population, C-Concept, C-Context). The study population was restricted to passengers and crew members of the aircraft (population) to assess transmission (concept) in an aircraft setting (context). The exposure period was defined to include, apart from the flight duration, also pre-boarding and post-boarding time at the airport and time in transit (jointly hereon referred to as ‘flight-associated’). The primary outcome of our review was the existence of transmission of SARS-CoV-2, estimated through the Secondary Attack Rate (SAR) or other indexes of secondary transmission. An event of flight-associated transmission was defined as SARS-CoV-2 infection with no other reported source of infection. The classifications of index cases, secondary cases and the methods for case definition and diagnosis were extracted from the original studies. Modelling studies, experimental lab studies and opinion pieces were excluded from the review. Study selection Studies identified from the searches were uploaded into a bibliographic database and duplicates were removed. Initially, a pilot training title/abstract screening process was used, where a random sample of 100 titles was independently screened for eligibility by two reviewers to enable consistency in screening and identify areas for amendments in the inclusion criteria. A high measure of inter-rater agreement was achieved (percentage agreement >90%), and hence the remaining titles were distributed between the two reviewers. For the full-text screening, a similar process was followed. Ten randomly selected studies were independently screened for eligibility by two reviewers, showing high agreement, after which the remaining of the full texts were subsequently distributed between the two reviewers for separate screening. Any disagreements were independently assessed by a third reviewer. Data extraction, synthesis, and presentation Data extracted were related to the study design, study setting flight characteristics (domestic, international), sample characteristics (crew, passengers), number of cases/contacts traced/tested, definition of index cases and contacts, the variant of SARS-CoV-2, NPIs implemented before, during or following air travel, and numerical outcome measures including SAR also other statistical indexes of secondary transmission noted in the original manuscripts such as risk ratios (RR) and odds ratios (OR). Assessment of Risk of Bias The nine point risk of bias tool developed by Leitmeyer & Adlhoch [ 10 ] was used to evaluate the risk of bias of the included studies, with the quality was categorised as low, medium or high based on the individual score of each study (0–3 low, 4–6 medium, 7–9 high). Low quality studies were not removed from the assessment, but subsequently flagged as LQ for reader’s information. It is important to note that this tool was developed for the assessment of single flight studies and hence may not be directly applicable to those studies which report multiple flights. The appraisal was performed independently by two reviewers, and disagreements were assessed and resolved by a third reviewer. RESULTS A total number of 3,169 studies were identified according to the specified selection criteria from Medline, Embase and the Cohrane Library for systematic reviews. After the removal of duplicates, 2,543 were screened against their title and abstract, and 125 studies were assessed for full-text eligibility. Through the assessment of complete texts, 31 studies were included in the final study list, 26 identified through systematic electronic searches using OVID Medline, EMBASE, and the Cochrane Library and 5 identified through the reference lists of the included articles [ 11 – 41 ]. The flowchart of the study selection is presented in Figure 1 . Real-time polymerase chain reaction (RT-PCR) to identify COVID-19 cases and contacts was conducted in all studies. Flight duration, origin and destination, index cases, contacts traced, data for secondary cases and SAR were available for most studies and are summarised in Tables 1 , 2 & 3 . The risk of bias assessment of the included studies are presented in detail in Supplementary – Appendix 2 . All studies were of moderate or high quality, with the exception of one single flight study [ 29 ] and three multiple flight studies [ 17 , 33 , 41 ]. View this table: View inline View popup Table 1. Methodological and epidemiological investigation characteristics of included studies (n=31) assessing flight-associated transmission of SARS-CoV-2 published up to November 2023. View this table: View inline View popup Table 2. Single flight details and Secondary Attack Rates (SARs) of flight-associated SARS-CoV-2 transmission, grouped by risk of Bias assessment, published up to November 2023. Secondary Attack Rate (SAR) of SARS-CoV-2 in aircraft Among the 31 studies included in this systematic review, 521 domestic and international flights were examined for SARS-CoV-2 transmission ( Table 2 & 3), with the results grouped based on study quality; with ten studies reporting on multiple flights ( Table 3 ) . The search results included flight-associated outbreaks occurring from 24 January 2020 to the 26 th June 2021. View this table: View inline View popup Table 3. Multiple flight details and Secondary Attack Rates (SARs) of flight-associated SARS-CoV-2 transmission, grouped by risk of bias assessment, published up to November 2023. The extensive heterogeneity in definitions precluded the ability to perform pooled analyses and hence the results on SAR are presented below narratively. Within the current review, in four studies, the highest number of index cases were identified in studies looking at single flights rather than those providing evidence from multiple flights. These studies included two domestic flights reviewed by Speake et al. [MQ] [ 37 ] and Chen et al. [HQ] [ 27 ] and two international flights by Dhanasekaran et al. [ 11 ] and Hoehl et al. [ 29 ]. Regarding the domestic flights, Speake et al., conducted a cohort study on a five-hour domestic flight from Sydney to Perth, Australia, with a total of 241 passengers and 18 index cases, of which 11 had been infectious during the flight [ 37 ]. Chen et al. also conducted a cohort study on a flight from Singapore to Hangzhou, China, with 335 passengers and 11 crew members and reported 15 index cases, nine of which were symptomatic [ 27 ]. Regarding the studies looking at international flights, Dhanasekaran et al. [ 11 ] identified seven index cases in a large cluster of 59 cases that were linked to a single flight from New Delhi, India to Hong Kong, China, with 146 passengers. Finally, a case series conducted for a 4-hour flight from Tel Aviv, Israel to Frankfurt, Germany by Hoehl et al. (LQ) identified seven index cases (four symptomatic, two pre-symptomatic and one asymptomatic) [ 29 ]. All other studies referring to single flights reported a range of 1-3 index cases [ 17 , 20 , 22 , 24 , 26 – 28 , 31 , 33 – 35 , 37 , 39 , 42 , 43 ]. Of 31 studies included in the analysis, the reported SAR varied from 0% to 16%, three studies lacked the information needed to estimate flight-associated SAR [ 28 , 34 , 40 ], while one reported ranges of SAR estimates based on scenarios [ 18 ] and one based on travel class within the airplane [ 14 ]. Among the studies where SAR could be calculated, no secondary flight-associated transmission was reported in six studies [ 11 , 16 , 21 , 25 , 31 , 33 ]. Eight flights noted SARs between 5-16.2%, all on single flights [ 35 , 39 ] [ 14 , 19 , 32 , 38 , 41 ]. Finally, seven studies presented a SAR between 1-5% [ 17 , 22 , 24 , 26 , 29 , 30 , 36 , 37 ] and six studies reported a SAR below 1% [ 13 , 15 , 21 , 23 , 27 , 36 ]. Only four studies in our review provided explicit data considering the transmission of specific SARS-CoV-2 variants [ 11 , 20 , 35 , 39 ], while studies performed early into the COVID-19 pandemic self-classified the strain as the initial wild-type SARS-CoV-2 variant [ 14 , 17 ]. Flight-related mitigation measures Regarding NPIs implemented during the flights, mask use was stated to be mandatory in nine studies [ 11 , 15 , 20 , 24 , 25 , 31 , 34 , 35 , 39 ], while the use of masks was not obliged in 12 investigations [ 18 , 21 – 24 , 29 , 31 , 32 , 36 , 37 , 39 , 42 ], while one study performed a pre-post facemask regulation comparison of SAR [ 17 ]. Most of the included flights occurred in early 2020, therefore, this may in part explain this heterogeneity in the application of mask use. Of the studies reporting on the effectiveness of mitigation measures, Williamson et al., within the context of one flight reported that removal of mask during flight (P=0.03), including eating (RR5.3) and drinking (RR10.6) were associated with an increased risk of passengers becoming a case [ 20 ], while Ngeh et al., noted that passengers that did not wear a mask at all the time during the flight had a RR of 2.79, (95%C.I: 1.09-7.17) to be secondary case [ 39 ]. Among the first eight studies with the highest SARs [ 14 , 18 – 20 , 32 , 35 , 38 , 39 , 41 ], mask use was not mandatory in five of them [ 14 , 18 , 19 , 32 , 38 ], while the study by Moek et al., (LQ) noted that among fights after mandatory masking, the SAR among close contacts was 3.6% (95% CI 0.6%–13.4%) while 5.1% (95% CI 0.9%–18.6%) before masking [ 17 ]. Aircraft occupancy was described in seven studies [ 11 , 14 , 18 , 20 , 27 , 34 , 38 ], with four [ 10 , 19 , 20 , 21 ] indicating more than 80% occupancy (range 17-89%). All passengers were tested upon arrival in three studies [ 11 , 24 , 25 , 39 ], and screening for body temperature and respiratory symptoms was recorded in another four investigations [ 14 , 19 , 21 , 26 ]. Passengers were quarantined for 14 to 21 days in 13 studies [ 13 , 17 – 19 , 24 – 26 , 31 – 34 , 41 – 43 ], while in one study [ 23 ] only travelers from high-incidence areas and their reachable contacts were isolated and quarantined and in six studies only close contacts or suspected cases were quarantined [ 30 , 31 , 33 , 37 , 38 , 40 ]. Distance from the index case Ten studies reported data regarding the distance of secondary cases from the index cases in the aircraft [ 12 , 14 , 17 , 19 , 23 , 29 , 30 , 32 , 34 , 36 , 38 , 39 ]. In general, sitting within two rows of the index case was used as a measure of proximity. Khahn et al noted that seating at a distance <2 seats away from the index case was associated with an RR of 7.3, 95%C.I: 1.2-46.2)[ 14 ], while Ngeh noted an RR of 2.7 for the same distance, which increased to 6.2 (95%C.I:1.74-22.24), among those that did not wear a mask at all times [ 39 ]. In the study of Blomquist et al. [ 23 ], from the five secondary cases, four were sitting within two rows of an index case and one five rows away. Similarly, Swadi et al. [ 32 ] reported four passengers as secondary cases, all seated within two rows of index cases. Also, in the study by Kong et al. [ 30 ], all nine confirmed and suspected secondary cases were seated within two rows from the index case. Among the 15 probable secondary cases described in the study of Quach et al. [ 19 ], 12 were in the travelling class as the index case, while 11 were sitting at a distance of ≤2 seats from the index case. Likewise, all secondary cases were sitting within two rows from the index case in the study of Hoehl et al. [ 29 ], Eichler et al. [ 34 ], and Pavli et al. [ 36 ]. Toyokawa et al. [ 38 ] stated that the passengers seated within two rows from the index patient was 4.8 (95% CI: 1.46–15.8) times more likely to get infected with SARS-CoV-2. Finally, in the study by Williamson et al., where the index case was a crew member, sitting where the index case predominately worked was associated with an increased risk of transmission [ 20 ]. In summary, for almost all studies presenting distance from the index cases, secondary cases were more likely to be within close proximity to the index case. DISCUSSION During 2022, there was a significant rise in international tourism compared with the previous two years, with nearly 900 million international trips recorded worldwide, albeit still substantially lower than pre-pandemic levels [ 42 , 43 ]. This review aimed to assess in-flight transmission of SARS-CoV-2, and indicated the existence of sporadic clusters of transmission, within which the measured SAR rate was found to range from 0% to 10.2%. Similar to our results from 521 reported flights, the findings of an earlier systematic review of Rosca et al., indicate that the SAR reported in published research (following up >80% of passengers and crew for 130 flights) varied between 0 and 8.2% [ 6 ], while a recent review by Lu et al., noted a SAR of 7.6%, ranging between 2.6% to 16.1%. Previous research has suggested that mask-wearing may mitigate transmission [ 44 , 45 ]. Within the context of our review and across the limited data that were available, when studies reported that most passengers and crew members used face masks during the flight, this strategy was deemed to be potentially effective in limiting the spread of SARS-CoV-2 [ 15 , 21 , 25 , 31 ]. In contrast, within the studies when masks use was not implemented during the flight, the reported SAR was higher [ 19 , 23 , 37 ]. These results are further corroborated by recent modelling studies which indicate that FFP2/N95 mask use may decrease infection by 95-100%, while distancing measures – such as leaving the middle seat empty - may further reduce transmission [ 46 ]. Furthermore, although only one study in our review noted that facemasks were removed during food service [ 25 ], previous experimental work has indicated that the removal of masks, even for short periods on a long haul flight, such as for a 1-hour meal service, increases the average probability of infection by as much as 59%, compared to the situation where the mask is worn continuously [ 5 ]. Distance, based on studies of tracer gas/particle dispersion, is also considered a significant determinant of contaminant exposure on airplanes [ 47 ]. For example, results during the assessment of SARS-CoV-1 transmission in 2003 suggested that passengers within two rows of cases had a higher likelihood of infection compared to those seated further away [ 48 ]. According to our review, proximity to index cases was another significant parameter as passengers who were seated within two rows from the index cases were more likely to get infected. Our results also concur with the findings of Rosca et al., who noted that distance between the passengers and the index case on board could have impacted the spread of COVID-19 [ 6 ] and with the review of Lu et al., [ 7 ] that noted that the risk ratios of infection for passengers seated within and outside the two rows of the index cases were 5.64 (95% CI:1.94–16.40). While the role of HEPA filtration was not assessed within the context of this review as it is implemented by default in the aviation industry, it is possible that these filters may reduce generalized airborne transmission and hence limit direct transmission to close contacts [ 49 ]. With regards to flight duration, it is not clear from our review if it can affect the COVID-19 spread, as there were both long flights with secondary cases [ 31 ] and short flights (<5 h) with indications of transmission [ 38 ]. According to the systematic review of Rosca et al., who categorised flight duration as short, medium, or long, with a low or high proportion of secondary cases, transmission did not necessarily increase with flight duration [ 6 ]. More studies reported secondary cases of Kappa variant than of Alpha or Delta variants, although this is expected to depend mostly on the circulating variant at the time of the cluster. The infections were found despite RT-PCR tests being performed within 72 hours pre- departure, and personal protective measures were implemented during the flight [ 11 ]. In the study of Lv et al., the flight-associated transmission was from an index case who was infected by the Delta variant, which is known to have higher transmissibility compared to previous strains, with also in this study passengers required to have a 48-hour negative PCR test before departure, and mandatory mask use on board [ 35 ]. No conclusions can be drawn regarding transmissibility between variants based on the small number of reported observations of flight-associated transmission. Strengths and limitations The systematic approach that was applied during study identification, data extraction, and risk of bias assessment are strengths of our study – including the recent November 2023 cut-off, which should allow for the identification of evidence collected for the duration of the COVID-19 pandemic. Despite these strengths, limitations of this review should be acknowledged. Firstly, there was no homogenous or systematic approach to the reporting of parameters that may be linked with flight-associated transmission. Secondly, we can not rule out publication bias as the reporting of larger clusters is to be expected, which if calculated, would decrease SARs. Thirdly, there was a broad handling of cases across studies where some of the studies did not screen asymptomatic index and secondary cases, while in others studies passengers were never traced successfully; therefore, the actual number of secondary cases remains unknown. Fourthly, there was significant heterogeneity in the in-parallel implemented NPIs across studies. Finally, as SARS-CoV-2 transmission was multifactorial, and potentially impacted by multiple factors such as passenger and crew individual behaviour and mobility, adherence to facemask use, vaccination status of participants, the transmissibility of the variants at the time of each study, and the proximity and duration of interactions between passengers, comparisons between studies cannot be directly made and the results should be interpreted with caution. Future studies should aim for a complete screening and evaluation of all passengers and crew members during follow- up, documenting aspects such as the genomics of the variants detected, distance from index cases, implemented pre and post-boarding procedures, and in-flight NPIs that are applied. The further standardisation of definitions and diagnostic procedures (including of index, primary, secondary, and close contact cases), across studies is further warranted. Despite the above limitations, this review provides a novel overview of the factors that may have impacted flight- associated transmission within the context of the COVID-19 pandemic, information which can be used in future emergency preparedness planning. CONCLUSIONS Our results are consistent with sporadic clusters happening onboard aircraft. At the same time, close proximity to COVID-19 cases within the aircraft was associated with a higher SAR. Further research is still needed to better assess the impact of implementing NPIs during flight, boarding and disembarking on the transmission of SARS-CoV-2, including the type of masks used and ventilation. Our findings underscore the need for a systematic approach to examining and reporting SARS-CoV-2 transmission onboard aircrafts, which is required to decrease the variation in parameters reported between studies. This evidence may assist policymakers and transportation authorities in the development of emergency preparedness measures and travel guidance during the post-pandemic COVID-19 era. Data Availability Data sharing is not applicable to this article as no new data were created or analysed in this study. Funding This report was produced under a service contract 17-ECD.12552, within Framework contract ECDC/2019/001 Lot 1B, with the European Centre for Disease Prevention and Control (ECDC), acting under the mandate from the European Commission. The information and views set out in this piece of work are those of the authors and do not necessarily reflect the official opinion of the Commission/Agency. The Commission/Agency do not guarantee the accuracy of the data included in this analysis. Neither the Commission/Agency nor any person acting on the Commission’s/Agency’s behalf may be held responsible for the use which may be made of the information contained therein. Conflicts of interest/Competing interests None to report. Supporting information S1 File. Search strategy for the assessment of flight-associated transmission of SARS-CoV-2. (DOC) S2 File. Results of the Risk of Bias assessment of included studies related to flight associated transmission of SARS-CoV-2 as per the quality appraisal tool by Leitmeyer & Adlhoch. (DOC) S3 File. PRISMA ScR Checklist (DOC) Acknowledgments We would like to thank Katerina Papathanasaki, Stella Vogiatzidaki and Anastasia Manta for their assistance in data archiving. REFERENCES 1. ↵ ECDC . Risk Assessment Guidelines for Infectious Diseases Transmitted on Aircraft (RAGIDA) - Influenza . : European Centre for Disease Prevention and Control ; 2014 [cited 2021 23 March 2021]. Available from: https://www.ecdc.europa.eu/en/publications-data/risk-assessment-guidelines-infectious-diseases-transmitted-aircraft-ragida#no-link . 2. ↵ ECDC. European Centre for Disease Prevention and Control. 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OpenUrl 48. ↵ Hertzberg VS , Weiss H . On the 2-Row Rule for Infectious Disease Transmission on Aircraft . Ann Glob Health . 2016 ; 82 ( 5 ): 819 – 23 . OpenUrl PubMed 49. ↵ Ueki H , Ujie M , Komori Y , Kato T , Imai M , Kawaoka Y . Effectiveness of HEPA Filters at Removing Infectious SARS-CoV-2 from the Air . mSphere . 2022 ; 7 ( 4 ): e0008622 . OpenUrl PubMed View the discussion thread. Back to top Previous Next Posted October 22, 2024. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. 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