=> numbers last updated: Sun, 29 Mar 2020 12:07:52 CEST <=

Event Horizon - COVID-19

As of , total cases of COVID-19 have been confirmed worldwide.

Background

The current outbreak of the COVID-19 virus started in Wuhan City, Hubei Province, China. While the first cases were reported as early as December 8, 2019, the outbreak gained global attention on December 31, 2019, when the World Health Organization (WHO) was alerted to “several cases of pneumonia” by an unknown virus.

The new virus was soon identified as a novel coronavirus and named COVID-19. It belongs to the family of viruses that include the common cold and viruses such as SARS and MERS. On January 20, 2020, it was confirmed that the coronavirus can be transmitted between humans, greatly increasing the risk of global spread.

Current situation

The spread of the virus on an international scale is dominated by air travel. Wuhan, the seventh largest city in China with 11 million residents, was a major domestic air transportation hub with many connecting international flights before the city was effectively quarantined and the Wuhan airport closed on January 23, 2020. By then, the virus had already spread to other Chinese provinces as well as other countries.

All case data on this site is provided by Johns Hopkins University's Center for Systems Science and Engineering (CSSE) via their online GIS dashboard.

Modeling the spread of COVID-19

The import risk model estimates the

  1. Relative import risk
  2. Most probable spreading routes
  3. Relative arrival time

for airports, countries, and continental regions worldwide.

Relative import risk

By looking at air travel passenger numbers, we can estimate how likely it is that the virus spreads to other areas. The busier a flight route, the more probable it is that an infected passenger travels this route. Using these probabilistic concepts, we calculate the relative import risk to other airports. When calculating the import risk, we also take into account connecting flights and travel routes that involve multiple destintions.

The import risk model describes the situation during the early phase of the pandemic, before massive circulation of SARS-CoV-2 in countries outside of Mainland China started. Now that the COVID-19 epidemic has reached pandemic level with circulation in more than 100 countries is happending, this model is no longer applicable.

If you are uncertain what relative import risk means or how to interpret it, it is recommended that you first have a look at the Relative Import Risk Explained section.

Current import risk estimates for the top 50 countries (excluding Mainland China) at highest risk of importation. Hover over a country to display in the inset the relative import risk of the top airports in the selected country. The national import risk is the cumulative import risk of all airports in that country. Countries with confirmed cases of COVID-19 are depicted in red; the current number of cases per country are listed on the right-hand side. More extensive analyses are provided in the Import Risk Analysis section.

Most probable spreading routes

Given an outbreak location and an origin airport close to it, the model identifies the most probable spreading routes to all other airports in the worldwide air transportation network. Even though passengers can take different routes to a final destination, global spreading patterns are dominated by the most probable paths. When viewed from the origin airport (the root node), these paths make up a shortest path tree that shows how the spreading process can reach all other airports in the network. These trees are important for identifying what airports play a pivotal role in distributing the spreading process thoughout the network.

An interactive visualization of the most probable routes and effective distances is offered in the Route Analysis & Effective Distance section.

The most probable spreading routes from the Beijing International Airport (PEK) to all other airports in the network.

The most probable spreading routes from the Beijing International Airport (PEK) to all other airports in the network.

Effective distance and expected arrival time

In the figure above, the vertical distance to the root node represents the effective distance to the outbreak location. The notion of effective distance was derived from traffic flux statistics and introduced in the paper The Hidden Geometry of Complex, Network-Driven Contagion Phenomena, D. Brockmann & D. Helbing, Science: 342, 1337-1342 (2013). In short, two airports are effectively close to one another if there is substantial air travel between them.

Effective distance has been shown to be a much better predictor of expected arrival time of an epidemic than traditional geodesic distances.

References & resources