Cover: COVID-19 Air Traffic Visualization

COVID-19 Air Traffic Visualization

A New Tool Helps Analyze Commercial Air Travel Involving Infected Passengers

Published Jun 5, 2020

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

Cases of coronavirus disease 2019 (COVID-19), which was first reported in Wuhan, China, have been confirmed in all 50 U.S. states. In this report—the first of several from a RAND Corporation team examining the role of commercial air travel in the COVID-19 pandemic—we quantify potential vectors of virus transmission to the United States as a result of commercial air travel. Understanding the COVID-19 propagation patterns, regionally and globally, will help policymakers mitigate the resulting threats to public health.

The COVID-19 Air Traffic Visualization (CAT-V) tool combines case data from Johns Hopkins University with detailed air travel data from the International Air Transport Association. Together, these data sets make it possible to visualize how COVID-19 infections and commercial air travel have interacted to export infection risk across the world. Given air travel data and reported infection rates, our tool can also be used to estimate future patterns of COVID-19 transmission. As a result, policymakers, analysts, and others can estimate the impact of travel-related policy interventions, such as restricting air travel from various countries.

Using reported COVID-19 case data, we calculate case rates for every country. We combine the case rates with the numbers of air passengers originating from each country, along with the passenger destinations. These values combine to generate estimates over time of the numbers of infected passengers who travel from one place to another.

Specifically, we characterize the risk to country or region j, Rj, as

R sub j equals the sum over indices i and j, where i is not equal to j, of (A sub i over P sub i) times N sub ij

where Ai is the number of active (i.e., currently infected) cases in country or region i, while Pi is the population in country or region i. Nij is the number of passengers who travel from country or region i to country or region j.

Using our tool, we identified the eight countries with the highest risk of importing COVID-19 from China on January 24, 2020. Those countries, in descending order of risk, were Japan, Thailand, South Korea, the United States, Taiwan, Australia, Singapore, and Malaysia. This relative risk ranking is independent of the actual caseload in China, and, one week later, these same eight countries indeed had the most confirmed COVID-19 cases outside of China.

Built using the JavaScript React library, the CAT-V tool offers several metrics of interest. The first is the heat map feature, shown in the first figure below, which displays the relative risk of importing COVID-19 cases into different countries on January 29, 2020. The tool can generate additional heat maps showing total active cases, per-capita active cases, total confirmed cases (including previously infected individuals who have since either recovered or succumbed to the disease), and per-capita confirmed cases.

Relative Risks of COVID-19 Importation on January 29, 2020

Screenshot of the CAT-V tool showing inbound risk of COVID-19 on January 29, 2020, as a global heat map. The countries most at risk, portrayed by darker shades of red, correspond to the eight highest-risk countries described in the paragraphs preceding this figure.

The tool also allows the user to visualize the risk associated with individual air travel routes. The routes can be depicted as either importation risks or exportation risks. The figure below shows the routes of importation risk to the United States on January 29, 2020, with the thickest red line beginning in China and ending in the United States.

Air Travel Routes of COVID-19 Importation to the United States on January 29, 2020

A global heat map of inbound COVID-19 risk is overlaid with red lines showing air travel routes to the United States. Described by the paragraph preceding this figure.

As of the publication of this report, we continue to develop the CAT-V tool. The most important recent development is the ability to use real-time air travel data to drill down from the monthly data to daily data. Future tool developments will include the ability to examine province- or state-level data and the ability to visualize routes from and to specific airports.

We will continue to develop and use the CAT-V tool in new ways, and we will continue to release a stream of derivative findings on topics of interest to policymakers. The first set of findings released includes an estimate of the rate at which reported cases were being exported from China by the end of January 2020, an estimate of the rate at which cases were being underreported in China that same month, an estimate of the greatest source of importation risk to the United States in late February 2020, and the probable origin of cases in Gulf Cooperation Council countries.


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 significant limitations. Here, we outline several caveats regarding country-level data, passenger risk profiles, inaccurate country caseload reports, and other data limitations.

International air travelers from all parts of a country make up a relatively small subgroup of that country's population. This subgroup, including individuals who could be visitors to the country of origin, might be at greater or lesser risk of infection, relative to the national population as a whole, during any given stage of a pandemic outbreak.

Consistent with most academic research and public policy tools, our tool uses confirmed COVID-19 cases, as reported by individual countries. The true number of infected individuals in any given country is certainly higher than reported. Our tool does not correct for inaccurate or misleading case reporting.

Systemic differences between actual cases and reported cases could have material effects on our results. For example, a relatively high ratio of confirmed to actual cases in a country with strong testing protocols could falsely elevate the perceived risk of total infected passengers from that country.

To the extent possible, we framed the questions and conclusions of this analysis in a way that would reduce the sensitivity of our findings to these known differences.

Finally, the CAT-V tool simulates the movement of the coronavirus through air travel but does not assume or imply that the virus is transmitted on airplanes. The tool is about the movement of people from one country to another and the likelihood that those people are infected with the virus.

Future Work

As of May 2020, the most important caveat of the CAT-V tool is the use of country-level data and thus the assumption of equal passenger risk profiles. Future versions of the tool will incorporate province- and state-level data.

To exhibit one limitation of country-level data, we consider Hubei province, for example. Hubei initially had a much higher case rate than did other Chinese provinces. This limitation is particularly relevant if the travel patterns of air travelers from Hubei were different from the patterns of air travelers from China more broadly. Nonetheless, in our initial analysis, we assume that the frequency and pattern of international air travel from Hubei province were roughly similar to those from the rest of China.

As of the publication of this report, our tool does not account for the lag time associated with the infection. In reality, the number of active COVID-19 positive cases today could reflect the rate of infection up to two weeks ago. Such lag times could be incorporated into future uses of the tool.

This analysis and associated reports describing findings from using the CAT-V tool will be further updated and released as warranted. When feasible, we will adjust the assumptions and correct the conclusions in accordance with the caveats discussed here.

Audiences of Interest

This report and the CAT-V tool will be of interest to U.S. Department of Defense policymakers and planners at the strategic and operational levels. At the strategic level, projections of how COVID-19 is likely to propagate across the world can inform defense-related decisions on global deployment pathways and timing, force health protection measures, and emerging risks that competitors may exploit infection patterns for strategic advantage. At the operational level, the projections can inform

  1. theater assessments of where COVID-19 stress may increase the likelihood of political crises that threaten U.S. diplomatic and other facilities
  2. the viability of contingency operating locations required to respond to those crises
  3. the impacts of COVID‑19 restrictions on deployment timelines for crisis response forces.

These issues will be explored in future reports. The tool and associated reports will also be of interest to U.S. policymakers and planners in other fields, such as foreign policy, public health, transportation, and homeland security.


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.

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