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Population density: not a primary factor in Covid-19

Hervé Le Bras
Hervé Le Bras
Research director in demographics at EHESS and Emeritus research director at Ined

From a demo­graph­ic stand­point, what can we say about the Covid-19 crisis?

In my book Serons-nous sub­mergés ?, which was pub­lished in Octo­ber 2020, I stud­ied the way the first wave of the pan­dem­ic unfold­ed, day after day, in four coun­tries – France, Switzer­land, Italy and Spain. I stud­ied them at the lev­el of regions, coun­ties and provinces. The results showed that geo­graph­ic – rather than social – fac­tors were key for dynam­ics of the epi­dem­ic. Cer­tain­ly, as many stud­ies have shown, immi­grants and low-income peo­ple have a high­er risk of dying from Covid-19 than the rest of the pop­u­la­tion. Not because of where they’re from or how much they earn, how­ev­er. Rather, it is because of their prox­im­i­ty to the virus. These pop­u­la­tions work in hos­pi­tals, at super­mar­ket check­outs, as deliv­ery per­sons or taxi dri­vers. That is why they are more impact­ed. The virus can­not dis­tin­guish between an immi­grant and a non-immi­grant, nor can it tell how much mon­ey you make. Rather, it goes straight to the near­est per­son, and we can learn a lot more about who the near­est per­son will be through geography.

We often think of Covid-19 as an “urban virus”. How­ev­er, your study found that pop­u­la­tion den­si­ty was not one of the key fac­tors in its spread. Why is that?

When you com­pare Coro­n­avirus deaths between 1st March and 15th May 2020 with the den­si­ty of French départe­ments, there are huge dif­fer­ences. Over that peri­od, the mor­tal­i­ty rate in Ter­ri­toire de Belfort (1.18 per 1000 res­i­dents) was 170 times high­er than that of Ariège (.007 per 1,000). The con­trast between a map of mor­tal­i­ty rate and a map of pop­u­la­tion den­si­ty shows no cor­re­la­tion (see below)

Left: Covid-19 deaths per 1,000 inhab­i­tants on 15th May 2020. Right: Den­si­ty of French regions in 2019 in population/km2. (Source: Serons-nous sub­mergés ? L’aube)

Den­si­ty is not a fac­tor in the large-scale spread of the virus. What mat­ters is the loca­tion of clus­ters, which are ini­tial­ly linked to just one per­son. The more peo­ple are con­t­a­m­i­nat­ed before the infect­ed per­son realis­es, the hard­er it is to con­tain the epi­dem­ic. This is what hap­pened with the sec­ond wave, but the dif­fer­ences in mor­tal­i­ty remain con­sid­er­ably dif­fer­ent – some­times as much as ten­fold high­er. And we see that “patient zeros” appear in both the coun­try­side and the city includ­ing large towns such as Mul­house and Ajac­cio, but also small­er ones like Auray, Creil or even a vil­lage in Savoie, Les Contamines-Montjoie. 

Hence, while den­si­ty mat­ters as the epi­dem­ic spreads, the ini­tial impact is min­i­mal. The only thing that we can say is that patient zero is a trav­eller. So, they often appear near big inter­na­tion­al hubs (Gene­va, Milan, Rois­sy Air­port near Paris, New York, etc.). But they also trav­el out of the city, which is where the clus­ter devel­ops, i.e. Crépy-en-Val­ois, La Bastide-Mon­tjoie, Bergame. This is actu­al­ly what hap­pened at the start of the AIDS epidemic. 

So to con­trol the spread one must first con­trol people’s move­ments – hence the lock­down. After expo­nen­tial growth of cas­es in the first clus­ters (Mul­house, Auray, Milan, etc.), the epi­dem­ic in the first wave was con­tained. For exam­ple, it prac­ti­cal­ly didn’t get into the Loire at all, nor into Andalu­sia or South­ern Italy. It also explains why deaths were thir­ty times high­er in Milan than in Naples. It’s a reminder of how, dur­ing the last out­break of the bubon­ic plague in France (Mar­seille, 1721), lines of sol­diers were deployed to pre­vent the epi­dem­ic from spread­ing beyond the Provence region.

Let’s go back to social cri­te­ria. Which did you select for your study?

In each of the coun­tries includ­ed in our study, fig­ures for Covid-19 deaths were com­pared with four indi­ca­tors: den­si­ty, pover­ty, the pro­por­tion of immi­grants in the pop­u­la­tion, and the pro­por­tion of peo­ple over 70 years old. The geo­graph­ic dis­tri­b­u­tion of these four fac­tors gave us no indi­ca­tion of which seg­ment of the pop­u­la­tion would be impact­ed. The maps speak vol­umes. This is due to the fact that the first wave was con­tained in the four coun­tries studied.

What about the sec­ond wave?

Para­dox­i­cal­ly, the sec­ond wave orig­i­nat­ed at the end of the first lock­down. The num­ber of dai­ly cas­es was very low at the end of June. But peo­ple in the 15–49 age brack­et account­ed for two thirds of new cas­es. Many of them passed by unde­tect­ed, as they were asymp­to­matic. With peo­ple trav­el­ling for the sum­mer hol­i­days, the virus spread all over France. Old­er peo­ple, par­tic­u­lar­ly grand­par­ents, were also infected.

As such, in Octo­ber France found itself with a large num­ber of clus­ters. With the excep­tion of Mayenne, these could not be con­tained as seen in Ajac­cio, Auray and Les Con­t­a­mines-Mon­tjoie. As a result, the epi­dem­ic spread pret­ty much every­where, as it had done in the two big clus­ters in the first wave in Creil and Mulhouse.

Because of more wide­spread safe­ty mea­sures and improved health­care, the virus did not spread very quick­ly. The spread of Covid-19 across almost the entire coun­try has pro­duced new social dif­fer­ences con­nect­ed to what hap­pened dur­ing the first wave – cer­tain groups are more care­ful than oth­ers, as shown by debates about mask-wear­ing. Nev­er­the­less, region­al dif­fer­ences are not insignif­i­cant – between coastal Brit­tany and the Lyon region, the rate of cas­es and the mor­tal­i­ty rate varies by a fac­tor of ten.

Just as we saw in the first wave, the sec­ond lock­down (pre­vent­ing peo­ple from trav­el­ling) will prob­a­bly main­tain these dif­fer­ences, once the wave has been stopped. Like oth­er con­tact epi­demics through­out his­to­ry, con­trol­ling people’s mobil­i­ty remains an essen­tial fac­tor for con­trol­ling the epi­dem­ic. We had bet­ter remem­ber that if we want to pre­vent a third wave.

Interview by Clément Boulle

Contributors

Hervé Le Bras

Hervé Le Bras

Research director in demographics at EHESS and Emeritus research director at Ined

Historian and demographer, Hervé Le Bras holds the "territories and topulations" chair at the FMSH's College of World Studies, Fellow of Churchill College (Cambridge). He has directed the Laboratoire de démographie historique (CNRS) and chaired the scientific council of the DATAR. He is the author of some sixty books, including Naissance de la mortalité (Gallimard) and The Nature of Demography (Princeton U. P.). He is also a graduate of the Ecole polytechnique (X63).