Coronavirus and Cities
There’s a meme going around the American discourse saying that the Covid-19 outbreak is proving that dense cities are bad. Most of this is bullshit from politicians, like Andrew Cuomo. But now there’s serious research on the subject, by a team at Marron led by the excellent Solly Angel. Solly’s paper looks at confirmed infection rates in American metropolitan areas as of late March and finds a significant correlation with density, but no significant correlation between deaths and density. In this post, I’m going to look at Germany. Here, big or dense cities are not disproportionately affected by the virus.
Why Germany?
Germany has pretty reliable data on infections because testing is fairly widespread, so far covering 1.6% of the population. Moreover, testing is this high throughout the country, whereas in the US, there are vast differences in testing as well as in other aspects of response by state, e.g. New York has tested 2% of state population, Louisiana 1.9%, Florida 0.8%, California and Texas 0.4%.
I also have granular data on infection rates in Germany, thanks to Zeit. The data I’m using is synchronic rather than diachronic, i.e. I’m looking at current infection rates rather than growth. Growth rates aren’t the same everywhere – in particular, they’re lower in North Rhine-Westphalia, which was the epicenter of the German outbreak weeks ago, than in southern Germany – but they’re low enough that I don’t think the situation will change in short order.
Size and density
Within Germany, there aren’t huge gradients in density between cities. More central neighborhoods have taller buildings than less central ones and higher ratios of building to courtyard, but there are no huge differences in residential built form the way there are between American cities.
For example, look at densities by neighborhood in Berlin, Hamburg, Munich, Frankfurt, Cologne, Stuttgart. There aren’t big differences in the pattern: the densest inner neighborhoods have about 15,000 people per square kilometer, and density falls to 3,000-5,000 in outer neighborhoods. Hamburg has a few areas with no residents, since they include the city’s immense port. Stuttgart’s densest districts are in the 5,000-6,000/km^2 range, but that’s because the districts are not very granular and the dense ring of inner-city neighborhoods just outside the commercial center is not congruent to district boundaries.
The upshot is that the big question about density and the risk of epidemics cannot be answered by comparing German cities to one another, but only to the surrounding rural areas. So the real question should be, are the major German cities more afflicted by the virus than the rest of the country?
Infection rates by city
As of the end of 2020-04-09, Zeit reports 118,215 confirmed coronavirus cases, which is 14.2 per 10,000 people. The six states of former East Germany, counting the entirety of Berlin and not just East Berlin, total only 12,873 cases, or 7.9 per 10,000. The Robert Koch Institute’s definitive numbers are slightly lower, but are also slightly outdated, as states sometimes take 1-2 days to report new cases. Going by Zeit data, we have the following infection rates by major city:
| City | Population | Cases | Cases/10,000 |
| Berlin | 3,644,826 | 4,357 | 12 |
| Hamburg | 1,841,179 | 3,518 | 19.1 |
| Munich | 1,471,508 | 4,123 | 28 |
| Hanover* | 1,157,624 | 1,389 | 12 |
| Cologne | 1,085,664 | 1,947 | 17.9 |
| Frankfurt | 753,056 | 730 | 9.7 |
| Stuttgart | 634,830 | 1,056 | 16.6 |
| Dusseldorf | 619,294 | 737 | 11.9 |
| Leipzig | 587,857 | 451 | 7.7 |
| Dortmund | 587,010 | 507 | 8.6 |
| Essen | 583,109 | 578 | 9.9 |
| Bremen | 569,352 | 425 | 7.5 |
| Dresden | 554,649 | 476 | 8.6 |
| Nuremberg | 518,365 | 733 | 14.1 |
| Duisburg | 498,590 | 525 | 10.5 |
*Zeit reports Hanover data for the entire region; the city itself only has 538,000 people
The sum total of the fifteen largest cities in Germany, with 15.1 million people, is 21,552 cases, which is 14.3 cases per 10,000 people. This is the same as in the rest of the country to within measurement error of total population, let alone to within measurement error of Covid-19 cases.
State patterns
Bavaria and Baden-Württemberg both have high confirmed case counts, averaging 23.6 and 21.7 per 10,000 people respectively. Munich’s rate is somewhat higher than the Bavarian average, but its suburbs are on a par with the city, as are some entirely rural areas all over the state. Oddly, the second and third largest cities in the state, Nuremberg and Augsburg, have lower rates – though both Fürth and the rural areas around Nuremberg and Fürth have very high rates as well.
The pattern around Stuttgart is perhaps similar to that around Nuremberg. The city’s infection rate is not much higher than the national average, but the infection rates in counties and cities around it are: Esslingen (24.8/10,000), Reutlingen (29.3), Tübingen (47.9), Böblingen (28.4), Ludwigsburg (22.9).
NRW’s rate is 13.9/10,000, i.e. essentially the same as the national average. The worst is in areas right on the Belgian border, like Heinsberg. Cologne has a noticeably higher rate, but Dusseldorf has a lower rate, and the cities of the Ruhr area a yet lower one. Don’t let the fact that these cities only have around 600,000 people each fool you – they’re major city centers, with the density and transportation network to boot. Dortmund alone has three independent subway-surface trunks, meeting in a Soviet triangle; total public transportation ridership in Dortmund across all modes is 130 million per year. Essen has two subway-surface trunks, one technically light rail and one technically a streetcar tunnel; total ridership there and in Mülheim, population 170,000, is 140 million per year.
What’s going on in Frankfurt?
There is some correlation between wealth and a high infection rate, since Bavaria and Baden-Württemberg have high rates of confirmed cases and the East German states have low ones. However, Frankfurt’s rate is fairly low as well, as are the rates of surrounding suburbs like Offenbach and Darmstadt. Frankfurt is not as rich as Munich, but like Hamburg and Stuttgart, it is fairly close, all three metro regions surpassing Ile-de-France and roughly matching London per Eurostat’s per capita market income net of rent and interest table.
In particular, it is unlikely that the greater international connections of rich cities like Munich explain why they have higher rates. Frankfurt Airport is the primary international hub in Germany, with many passengers standing in line at the terminal and coughing on other people. It would have been the easiest for imported infections to arise there rather than in the Rhineland, and yet it doesn’t have a major cluster.
Frankfurt also has extensive O&D business travel; Wikipedia puts it third after Berlin and Munich, but Frankfurt’s visitors are most likely disproportionately business travelers rather than tourists. This is important, since February and March are low season for tourism, whereas business travelers are if anything more likely to be going to Frankfurt during low season because during the summer high season they go on vacation in more interesting places.
So, is urban density more vulnerable to infectious diseases?
Probably not. Rural Germany has some areas with Korean levels of confirmed cases per capita, and some where 1% of the population and counting has tested positive. Overall, there isn’t much of an urban-rural difference – the 15 largest cities in Germany collectively have the same rate as the rest of the country, and moreover, where there are notable state-level patterns, they also hold for the states’ big cities. If Munich’s high infection rate is caused by its high rate of U- and S-Bahn usage, then the suburbs should have lower infection rates (they’re more auto-oriented) and the rest of Bavaria should be much lower; in reality, nearly the entirety of Bavaria has high rates.
The highest density in the developed world does not exist in Germany. German neighborhoods top at 15,000/km^2, with individual sections scratching 20,000; Paris tops at 40,000 in the 11th Arrondissement, New York scratches 50,000 on the Upper East Side, and Hong Kong has entire districts in the 50s. So the “density doesn’t matter” null hypothesis, while amply supported on German data, requires some extrapolation for the handful of world cities with the highest density.
Nonetheless, these are not huge caveats. German data is pretty reliable in the density range for which it exists; if cities today had the infection rates they did before modern plumbing, when a noticeable fraction of a city’s population might die in a single epidemic, it would be noticeable today. But there is no mass death, nor are urban hospitals here collapsing under the strain. On both the level of a basic sanity check and that of looking at the data, cities do not appear to be vulnerable to disease.
What does this mean?
There is no need to redesign the world to be less urban or dense in the wake of the coronavirus. Nor is there any need to let go of collective public transportation. The Rhine-Ruhr and Frankfurt are not Tokyo or Hong Kong in their public transportation usage, or even Paris or Berlin, but they have extensive urban and regional connections by train. And yet, the Heinsberg disaster zone and the high infection rate of Cologne have not been exported to the Ruhr, nor is southern Hesse particularly affected by German standards.
The virus has exposed serious issues with cleanliness. But even given Germany’s current levels of urban cleanliness, those issues are not enough to turn Berlin, Frankfurt, Hanover, or the Ruhr cities into hotspots. There is no danger to public health coming from urbanization, density, development, or public transportation. Cities should keep investing in all four in order to reduce the costs of transportation and environmental damage, even if the occasional failed politician blames the virus on density to deflect attention from his own incompetence.
