The literature search identified 26 publications about COVID-19 testing at airports, including ten studies involving primary research of airport COVID-19 testing (details summarized in Table 2). The goals of the studies varied widely, and studies often had more than one primary goal; the five categories of goals are as follows: (A) determine a representative positivity rate of incoming travelers (6 studies); (B) detect positive cases (5 studies); (C) investigate an alternative test as a feasible option to the gold-standard test, i.e., rapid antigen test or salivary specimen (5 studies); (D) evaluate the effectiveness of a pre-travel program (2 studies); and (E) determine the most effective location for a screening center (1 study) [9••, 10••, 11••, 12,13,14,15,16,17,18]. Note that the study from Japan had two phases of its airport study where each phase is shown in its own columns.

Six of the ten studies provided an overall study participation rate. Of these, two had mandatory airport testing at either departure or arrival for all passengers; therefore, there was an implied 100% participation rate. Two studies had high participation rates of 72% and 89% with goals to reporting positivity rates, which were 0.7% and 1.2% respectively. Two studies had low participation rates, 27% and 40%, and both studies had primary goals of reporting the number of positive cases (248 and 88) and positivity rates (1.5% and 7.3%). Seven of the ten studies reported a positivity rate for their study population, in the order of Table 2: 0.7%, 1.5%, 0.1%, 7.3%, 1.2%, 1.6%, 0.7%, and 100.0%. One study reported only the number of positive cases (2 cases) but did not report the total number of study participants. One study did not report the number of positive cases but only the total number of study participants (1183); this study collected multiple specimens from participants and reported only the number of overall positive collected specimens rather than cases. One study did not report the number of positive cases nor the positivity rate.

Two of the studies involved testing at the departure airport, while eight studies involved testing at the arrival airport. Smaller studies tested an estimated range of 20–350 passengers, while larger studies tested an estimated range of 1000–70,000 passengers. The types of passengers varied among the studies: all passengers, only visitors, military personnel, passengers departing from high-risk areas, healthcare workers, or returning travelers who were symptomatic but stable. Half of the studies tested only asymptomatic passengers, while the other half tested either symptomatic or both (symptomatic and asymptomatic). The testing modalities included polymerase chain reaction (PCR), rapid antigen such as fluorescent immunoassay (FIA) or automated fluorescent immunoassay system (AFIAS), molecular testing, antibody testing, or loop-mediated isothermal amplification (LAMP). Seven of the studies used nasopharyngeal (NP) samples, while three studies included oral, nasal, oropharyngeal, and salivary specimens. All ten studies had testing on collection day 0; however, one difference for study 1 was that their collection occurred at the end of a visitor’s trip. Two studies added testing on successive days (days 1–7, or days 7 and 14). Six of the studies involved testing performed by study staff, while three studies involved self-testing. Three of the studies occurred in March–May 2020, four studies occurred in July–October 2020, and the three studies occurred in November 2020–May 2021. One airport study also included testing a ship port for border control. The countries involved in primary research of airport COVID-19 screening studies included the USA, Canada, Italy, Hong Kong, China, Malaysia, Italy, Japan, and South Korea.

One study had anonymous testing (with no enforced isolation), while five studies were not anonymous and carried consequence of isolation for positive results. Two studies included informing travelers about the airport testing ahead of time, while one study did not inform travelers ahead of time. The other seven studies did not report whether they informed travelers beforehand or not. Only three of the studies discuss selection bias or distortion, while the other seven did not address it. Seven studies recommended airport COVID-19 screening, while one study did not recommend it.

Tande et al. partnered with Delta Airlines and Mayo Clinic to run a pilot program for mandatory testing at the departure airport to evaluate the effectiveness of the pre-travel program (required testing 72 h before departure) [9••]. Of the 9853 passengers tested at the departure airport, five were positive, leading to a 0.04% positivity rate, which the authors pointed out was significantly lower than the average 1.1% community infection at that time. Positive cases were moved to designated hotels until the results of confirmatory tests became available. The authors concluded that the pre-travel testing program was effective. Since the pilot program resulted in such a low yield, they did not recommend mandatory airport testing (either at departure or arrival) in addition to the pre-travel testing. The authors discussed that one major limitation was that the prior knowledge of the additional mandatory airport testing (and consequence of isolation if tested positive) may have been a major deterrent to travelers. There may have been self-selection where travelers who perceived themselves as lower COVID-19 risks or have lower risk behaviors may have decided to still travel while others may have opted not to travel. Also, travelers may have behaved more cautiously since there would be airport testing. These may have led to a negative bias for the positivity rate.

Goel et al. conducted a Toronto Airport study with voluntary testing on arriving international passengers, who were solicited on the flight via announcement and by posted signs in the arrival areas [10••]. They reported that 248 of the 16,361 enrolled passengers tested positive, resulting in a positivity rate of 1.5% (CI 1.3–1.7%). Their best estimate of the participation rate approached 40%. The authors discuss probable self-selection bias that was both positive and negative, so the overall direction of bias is unclear. Passengers with higher risk behaviors may have avoided the voluntary testing. However, at the time, PCR testing was not widely available; many passengers may have tried to take advantage of the free testing. Selection bias likely affected the overall positivity rate, and given the low participation rate (40%), it is misleading to apply their positivity rate to all incoming travelers. Two-thirds of positive cases occurred on day 0 at the airport compared to days 7 and 14; therefore, the authors recommended airport screening on day 0 to detect the most positive cases at the border.

A pilot study partnered with the Hawaii Department of Health, Maui District, to evaluate the pre-travel program (required testing 72 h before departure) [11••]. Miller previously estimated a positivity rate of 0.65 cases per 1000 travelers arriving to Hawaii [19] and concluded that the pre-travel program was very effective at points of entry. Despite the large sample of nearly 22,000 post-arrival tests, concerns about bias arose regarding the low participation rate (< 10%) attributed to its online solicitation strategy and enforced isolation for positive results, as well as self-deselection biases and distortion [20•]. Based on a traveler survey, the Maui investigators determined that on-arrival testing faced barriers including the consequences of positive results (i.e., isolation for self and quarantine for co-travelers) and impact on travel plans. Thus, the Maui study enrolled visitors (with negative pre-travel COVID-19 tests) who stayed in Hawaii for ≤ 14 days, at the airport as they were leaving Maui, and positive results were only available to subjects (anonymous to health officials). The study had a high participation rate (72%) and among 281 passengers tested, there were two positive cases, leading to a positivity rate of up to 7 cases per 1000 travelers. One case from Wisconsin stayed in Maui for 1 day before testing while another from California had stayed in Maui for 7 days before testing. The latter case might have been infected in Maui; however, COVID-19 case rate had been 14-fold higher in California than Hawaii at the time, hence a higher likelihood of exposure in California. With the reduced selection bias, authors estimated that up to 20–30 infected travelers were arriving daily to Maui in November and December 2020, which surpassed the Maui District Health Office’s projected ability to accommodate 10 infected visitors daily. The investigators concluded that the pre-travel program was suboptimal and recommended airport testing to provide active surveillance of imported cases and new variants, and to continually monitor the effectiveness of pre-travel programs.