
Ask HN: Why so many contagious in my small town? - creolabs
Hi, I am Marco and I live in a small town in Italy called Viadana (in Lombardy to be more precise). The exact location is: https:&#x2F;&#x2F;goo.gl&#x2F;maps&#x2F;UsUKshzvHGwVZ4nL6<p>In Lombardy, we are all following the same strict rules and we are forced to spend most of our time inside our house.<p>What I am unable to understand is why my small town has so many contagious, much more than a bigger city like Mantova.<p>The following is a table with all the nearby towns, with number of citizens and official contagious count:<p>Name         # Population   # Contagious
=======      ============   ============
Mantova      49400          32
Castiglione  23700          29
Suzzara      21300          4
Viadana*     20150          64
Porto M.     16000          9
Curtatone    14900          11<p>Further details about surface and density can be found here:
https:&#x2F;&#x2F;www.tuttitalia.it&#x2F;lombardia&#x2F;provincia-di-mantova&#x2F;50-comuni&#x2F;popolazione&#x2F;<p>Up-to-date contagious count:
http:&#x2F;&#x2F;www.altramantova.it&#x2F;it&#x2F;cronacaam&#x2F;mantova-am&#x2F;24775-emergenza-coronavirus-aggiornamento-i-contagi-salgono-a-456-in-provincia-di-mantova-impennata-di-casi-a-viadana-ora-sono-64-cresce-anche-mantova-che-arriva-a-32.html<p>Is there any explanation?
If not, which kind of data I should collect in order to be able to find out an answer?
======
ColinWright
I haven't looked in detail, so I can't give you a definite answer, but I offer
you this maxim:

Random processes clump.

When you have things happening at random you'll find that there are clumps
here and there with gaps scattered. If you look at something and find that
it's well spread and reasonably even, then it's not random.

There will always be some places that have more than average, more than
"expected", and there will be places that seem magically to escape.

So maybe there's no reason other than it's simply where you are, and it's
mostly random. Maybe there is a reason, but really, there might not be.

Edit:

The comment[0] by gus_massa[1] is completely plausible.

[0]
[https://news.ycombinator.com/item?id=22609125](https://news.ycombinator.com/item?id=22609125)

[1]
[https://news.ycombinator.com/user?id=gus_massa](https://news.ycombinator.com/user?id=gus_massa)

~~~
gus_massa
It's a good explanation for a lot of cases and patterns, and it must be the
first explanation to try. For example for cancer, that apear with a random
distribution, there are spatial and temporal clusters. People usually try to
find an explanation for them, but most the patterns are just noise. Even
uniform random produce more clustering than what people expect.

But in this case I disagree. When there is an initial part of an epidemic with
an exponential growing, the time of arrival of the first infected person is
very important. It is growing like x2 each week, so an alternative explanation
is that the first case arrived to the city one or two weeks earlier.

It can be a mix of the two cases. The x2 grow per week is only an average.

@OP: Sometimes is good to run a few simulations to see how this work. Start
1000 or 1000000 towns with 1 infected "person" and each day the total number
of infected persons is multiplied by a random number between 0.9 and 1.3.
After two months, look the distribution of the outcomes of the simulated
towns. Most will be near the mode, but there will be some lucky and some
unlucky outliers. Note that this is a very bad epidemiology model, and the
numbers are totally made up, but is simple and enough to see the clustering.

(I made and Exel with 1000 "towns", and I got most of the towns with 10-11-12
ill people. But I got two towns with only 2 ill people and a vey unlucky town
with 81 ill people. YMMV)

If the initial patient reach the town a different day, you will see that the
towns that started the infection earlier usually have more ill people, but
some lucky or unlucky towns are in the wrong order when you sort them by the
number of patients.

Formatted table

    
    
      Name         # Population  # Contagious
      ===========  ============  ============
      Mantova             49400            32
      Castiglione         23700            29
      Suzzara             21300             4
      Viadana*            20150            64
      Porto M.            16000             9
      Curtatone           14900            11

------
Arnt
You may have read about the 31st patient in South Korea? He didn't have any
symptoms himself and infected thousands of people, so they got a giant clump
around him.

You may have one or a few people like that.

[https://www.repubblica.it/salute/medicina-e-
ricerca/2020/03/...](https://www.repubblica.it/salute/medicina-e-
ricerca/2020/03/16/news/coronavirus_studio_il_50-75_dei_casi_a_vo_sono_asintomatici_e_molto_contagiosi-251474302/)
BTW.

------
pmontra
In short: only bad luck. gus_massa gives a thoughtful explanation in another
answer.

Cheers from Milano.

