Last update: 21st May, 2020. Due to changes in the way data for Spain is provided by the source this page is not updated anymore.

See similar analysis for countries using global data

**What this page is not.**

Since the lockdown started in Spain I’ve been reading articles and looking at a lot of data and graphs posted online about the 2020 coronavirus pandemic. Now I’ve decided to share my take on the analysis of the available data. This page is not a way of predicting what’s going to happen with the pandemic. I’m not that smart nor pretend to be. For that we have professional people in charge around the world working right now (and even before this all blew up). I hope only to translate the data to make it easily understandable and show what’s really happening through graphs.

**The data**

The page shows the data from Spain and its *Comunidades Autónomas* (from now on CCAA), plus Ceuta and Melilla.

The number of cases, this is, how many people have tested positive for coronavirus, is a piece of data that needs to be handled cautiously. Not all the CCAA, and for that reason not every country, has the same resources so they are not doing the same number of tests proportionally to their population. Even if they were, the fact that people can be asymptomatic despite having the coronavirus means, and everyone in the world knows this right now, that the number of infected people is greater than is being recorded. So, registered cases are just that, and they don’t imply anything else other than knowing how many people have been tested. This is the reason why cases should be ignored when the progress of the pandemic is to be analysed.

There is also something extremely important that for some reason is been overlooked, which is the number of deaths (and why not? Also cases.) proportional to the population of each CCAA (or country). As an example, just the municipalities of Móstoles, Alcobendas and Getafe in Madrid have the same population together of Cantabria. So 500 deaths are not the same level of pandemic in Madrid and Cantabria.

#### Timeline heatmap of daily cases by CCAA.

#### Timeline heatmap of daily deaths by CCAA.

**Ok, so is this a fair comparison then?**

No. There are so many factors that should be included and it’s almost impossible to measure them, that there is no way to compare CCAA. A virus outbreak is worse where the density of population is bigger. Madrid has a bigger density of population than Cantabria for example. And these numbers are just averages, so you should also check how many cities every CCAA has with a bigger density of population than a particular threshold. And now, what threshold should you determine? And we are talking about factors that somehow you can measure, what about lifestyle, movement of people, tourism, and how tourists move around the CCAA, do they visit just the city of Madrid or move around several cities in the region?, geography isolation of a CCAA (Canary Islands and Balearic Islands are more isolated, but also receive lots of tourists), time to see it coming, percentage of old population (and how much they move and their health conditions)… So, no.

**The graphs**

*All graphs are interactive: double click on a CCAA on the legend and only that trace is shown, then click on others to add them to the graph. Double click on a white area of the legend to bring back the original graph. All the graphs have time as the x-axis, unless something else is specified.*

Legends are all organised in descending order (higher on the legend is worse) and the names correspond from top to bottom to the traces of the graph.

**The most important graph of all **(if you are going to see just one graph, this is the one)

It would be an error to compare how ‘well’ every CCAA is doing against the rest by just looking at today’s number of deaths, because some CCAA are in a more advanced state of the pandemic than others. In order to make a fair comparison, graphs should be shifted according to the starting point when every CCAA had a certain number of deaths per population. Like in a cycling race against the clock, you would measure every cyclist at determined checkpoints of the track because not all of them start at the same time. This is what the next graph shows: traces from all the CCAA have been shifted so the starting point (t=0) is the first day when the deaths per 100K people were greater than 1; and also, it measures the deaths per 100K people on the vertical axis.

Summing up, this graph is the fairest visual when comparing the pandemic state in every CCAA, as it measures the pandemic proportionally to their population both on time and amount of deaths:

*Double click on a name on the legend to show only that CCAA. Then, add more clicking on their name.*

In the following slider you can see a total of 20 graphs that show for each condition: cases, deaths, hospitalised, intensive care and recovered, their cumulative/cumulative per 10K people/daily/daily per 100K people. *Click on the arrows to move between graphs.*

Records of the several conditions start on different dates:

**Cases**: February 27th 2020 **Deaths**: March 3rd 2020 **Hospitalised**: March 21st 2020

**Intensive Care**: March 4th 2020 **Released from hospital**: March 16th 2020

(Note that the CCAA of Madrid, C. la Mancha, C, y León and C. Valenciana have descending cumulative hospitalised data for some dates which is obviously not possible. Apparently daily and not cumulative data was communicated in this cases for these CCAA).

The next graph shows the cumulative cases, deaths, hospitalised, intensive care and discharged from hospital for the overall of Spain: (Since 27/04/2020 data for hospitalised and IC of Madrid are cumulative, this is the reason why the curves for the next two graphs skyrocket on that day).

And now the daily new cases, deaths, hospitalised, intensive care and discharged from hospital for the overall of Spain:

Data of the pandemic from Datadista. Population for each CCAA (2018) from the Instituto Nacional de Estadística.

** Thanks to Guillermo Mercapide for his help gathering data and ideas for this page.