Cover: COVID-19 Air Traffic Visualization

COVID-19 Air Traffic Visualization

Decisionmakers Should Base Travel Restrictions on Infection Rates Per Capita and Air Traffic Levels

Published Jun 5, 2020

by Russell Hanson, Christopher A. Mouton, Adam R. Grissom, John P. Godges

Key Finding

Travel advisories from the U.S. Department of State and warnings from the Centers for Disease Control and Prevention focus primarily on the risk of travel to particular countries. Additional metrics could measure the risk of travel from particular countries with both high infection rates and high numbers of air travelers to the United States. Future assessments focused on these alternative metrics would allow U.S. authorities to reduce passenger air travel, or at least increase the screening of air passengers, from the highest-risk countries.

In this report—one of several from a RAND Corporation team examining the role of commercial air travel in the coronavirus disease 2019 (COVID-19) pandemic—we use our COVID-19 Air Traffic Visualization (CAT-V) tool to quantify potential vectors of COVID-19 transmission to the United States resulting from commercial air travel. The tool combines COVID-19 case data from Johns Hopkins University with detailed air travel data from the International Air Transport Association.

We examined potential COVID-19 importation vectors into the United States, based on the infection rates in other countries and the numbers of incoming travelers originating from those countries. We found that countries with modest numbers of confirmed cases can still represent the greatest risks of virus exportation to the United States if those countries have relatively high active (i.e., currently infectious) case rates per capita and high levels of connectivity to the United States.

For instance, on February 2, 2020, the U.S. Department of State issued a travel advisory that designated China with the highest advisory level—Level 4: Do Not Travel. At that time, China had by far the most active COVID-19 cases in the world, with just fewer than 16,000 reported, while the United States had only 60 confirmed cases. China's figures represented only about one case per 90,000 residents. (Another report in this series shows that the true risk from China was likely much higher.) When factoring in China's officially reported infection rate, combined with the reduction of flights from China and other U.S. restrictions, the risk of COVID-19 transmission from China to the United States via air travel stood at less than one infected passenger per week.

On February 29, 2020, when the State Department designated South Korea with the second-highest advisory level—Level 3: Reconsider Travel—the country had just more than 3,100 cases (much fewer than the reported cases in China). Still, for South Korea, this caseload represented about one per 16,500 residents. When these data were coupled with the number of air passengers traveling from South Korea to the United States, which exceeded the number traveling from China (68 percent fewer passengers originated in China than in South Korea), the vector of risk from South Korea grew to about one infected passenger per day (see the map below). This risk was comparable to the risk that the United States faced from reported cases in China on February 2.

Air Travel Risks of COVID-19 Importation to the United States on February 29, 2020

A global heat map of inbound COVID-19 risk is overlaid with red lines showing air travel routes to the United States from countries throughout Europe and Southeast Asia. The line from South Korea is thickest, showing the highest risk to the U.S. of importing COVID-19.


In accordance with RAND's quality assurance standards, this analysis is based on the best available data. However, COVID-19 is an evolving threat, and even the best available data being used by government agencies and research institutes have very significant limitations. In the first report in this series, we outline several caveats about using country-level data, assuming equal passenger risk profiles, drawing on inaccurate country caseload reports, and being restricted by other data limitations.

In this report, it is important to reemphasize the data caveat about the variability of testing among and within countries. Our analysis highlights the elevated risk of infected passengers arriving from South Korea, and part of the reason we chose to examine risk from this country is that it had a relatively high rate of confirmed cases in late February. However, South Korea has been lauded for having some of the best COVID-19 testing in the world (according to a March 2020 Financial Times article, for example), so the country's ratio of confirmed to actual cases could be higher than that observed in other countries. As a result, South Korea could appear to be a relatively high risk for COVID-19 importation to the United States as a result of the robust testing done in South Korea compared with the testing done in other countries.


The COVID-19 Air Traffic Visualization tool combines confirmed COVID-19 case data from the Johns Hopkins University Center for Systems Science and Engineering's COVID-19 Dashboard with detailed air passenger data from the International Air Transport Association's Nationality Traffic Report program. Together, these data sets allow the researchers to visualize and analyze the estimated transmission of the novel coronavirus via air travel, outline the resulting implications, and offer suggestions for minimizing the most-dangerous potential vectors.

This research was sponsored by the Office of the Secretary of Defense and the U.S. Air Force and conducted jointly within the Acquisition and Technology Policy Center of the RAND National Security Research Division and the Strategy and Doctrine Program of RAND Project AIR FORCE.

This report is part of the RAND research report series. RAND reports present research findings and objective analysis that address the challenges facing the public and private sectors. All RAND reports undergo rigorous peer review to ensure high standards for research quality and objectivity.

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