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Comment by Grue3 | Hacker News Reader

The number of cases per people statistic is silly. It might make sense when the virus is common around the world, but when it's just spreading the number of cases itself is more important. For example if you detected 100 people infected with a virus in some region, does it matter if it has 200 million people (Uttar Pradesh) or 10 million (Lombardy)? These political divisions are arbitrary anyway.

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I initially thought the same thing, but revised my thinking after I kept reading. I made a comment here [0], but the author is correct that in this case (as in almost every conceivable visualization case), mapping the cases-per-person value is necessary. The mapping of absolute counts almost completely hides the severity of the impact in Hubei province, and how the severity in other provinces has a direct relationship to their geographic distance from Hubei.

> These political divisions are arbitrary anyway.

Not sure how interstate activity and travel is regulated/limited in China (in normal times), but in the U.S., state borders are not just some imaginary political construct. Laws and services – and therefore, impact to respective populations – can drastically differ by state lines, and ignoring that is a huge mistake.

[0] https://news.ycombinator.com/item?id=22436842

I think what they mean by the political divisions being arbitrary is that you could use a different division system, for example city boundaries instead of province, and have something completely different, with even more contrast in densities.

I concur. If you are concerned about catching it during your travels, people who don't have it are just as irrelevant as the number of automobiles who don't have it; thus, cases per people is just as irrelevant as cases per (people + automobiles).

You should be concerned about the fraction of land area on which you are at high risk. If 100 people have it, and each person creates a high risk across A area (and the areas don't overlap), that is 100*A / country-area. Which is proportional to cases/area (presuming A is constant) the first statistic he used.

EDIT: if you know you are going to interact with N people, the cases per population figure is relevant again.

> presuming A is constant

It's that the case anywhere? Even city centre / suburbs will have different values, much less a whole province where A may contain an empty field or a group of residential buildings with 50 floors and shared lifts.

I could see how it would be useful for a map of a city, or maybe even at a scale of some regions... but not for comparing totals between regions.

Of course you are always going to interact with N people. Your family consists of n₀ people, there are n₁ people in your office, there are n₂ people around you on the train, etc. Area calculations would matter if each infected person somehow densely contaminated an entire circle of a large diameter.

Interesting point. How would you plot the likelihood of infection?

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