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

Abstract

Background: Routine 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.

Methods: In 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).

Findings: We 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 2520 days (1849-4158), a reduction of 70% (64-75) 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 3124 (2356-495), a reduction of 63% (58-66) 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.

Interpretation: Routine 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.

Funding: University of California, San Francisco.

Figure 1

Predicted number of cumulative SARS-CoV-2 infectious days over the travel period under different test-and-travel strategies Estimated number of cumulative infectious days without quarantine or isolation (y axis) over time for each test-and-travel strategy. The x axis shows the time over the simulation (in days) relative to the day of travel (vertical dashed line). Solid lines show the mean and shaded areas the 95% UI across 3000 simulations. UI=uncertainty interval.

Figure 2

Ratio of false positive to true positive test results for test-and-travel strategies under different baseline SARS-CoV-2 infection incidence settings Datapoints are mean and the vertical lines show 95% uncertainty intervals. The x axis shows SARS-CoV-2 infection incidence, including asymptomatic cases (daily cases per 100 000 people). The y axis shows the ratio of false positives to true positives, where higher numbers correspond to a higher number of false positives.

Figure 3

Change in population-level transmission of SARS-CoV-2 between origin and destination cities for airline travellers at various infection incidences by test-and-travel strategy For each strategy, we calculated the ratio of cumulative infectious days in an origin city relative to a destination city under different assumptions of SARS-CoV-2 infection incidence for both locations. The ratio is represented by the coloured boxes, where boxes in darker reds are high ratios (corresponding to higher importation risk) and yellow is lower ratios (corresponding to lower importation risk). The white boxes represent scenarios where the ratio is less than one, meaning travellers are moving from a low to high incidence city (corresponding to minimal relative importation risk). Test-and-travel strategies had the largest effect when they reduced the ratio of cumulative infectious days compared with base case (no testing), as shown by a shift from darker colour to lighter colour for a given incidence scenario.

Figure 4

Effect of pre-travel testing strategies on the absolute number of travellers with active SARS-CoV-2 infection Mean number of total actively infectious people on the day of travel in the cohort of 100 000 (y axis) under each pre-travel testing strategy. We varied the baseline SARS-CoV-2 infection incidence (x axis) from 5 to 500 daily infections per 100 000 people. The y axis represents the mean and 95% uncertainty interval across 3000 simulations.