How to visualize the spread of COVID-19 in Italy

Photo by James Yarema

Introduction

February 21st 2020. 16 Coronavirus cases were discovered in Lombardia, one of the crucial crossroads of Italy, a region where everyday thousands of people land and leave. The day after, the infected people were 60 and in the following days the first deaths were sadly signaled. In the same days, cases started appearing in Veneto too. On the 23rd, hoping to contain the spread of the disease, the government declared part of the province of Lodi and the town of Vo’ Euganeo (in Veneto) as zona rossa. Unfortunately, it was already too late: the virus had already started traveling all around Italy (…and the rest of the world). But how? Where? How fast? To answer these questions, it would be useful to visualize the evolution of the spread.

In the following, I will outline an intuitive way to describe and display how the virus’ situation evolved in Italy, by firstly illustrating the tools that I leveraged and then showing how to take advantage of them. In particular, in this article we will see:

1. What choropleth maps and GeoJSON are
2. Useful resources you can leverage to explore the case
3. How to generate a choropleth maps to visualize the virus spread

Choropleth Maps and GeoJSON

Choropleth Maps are maps composed of polygons, where the color of each polygon expresses a quantity. The polygons usually represent real geographic areas, hence real maps, and therefore these visualizations are extremely intuitive when you want to describe, for instance, the demographic distribution of a population.

To generate these maps, however, you need the structure of the polygons. This can be described by the use of GeoJSON, an open standard format designed for representing simple geographical features, along with their non-spatial attributes.

# Example of GeoJSON
{
  "type": "Feature",
  "geometry": {
    "type": "Point",
    "coordinates": [125.6, 10.1]
  },
  "properties": {
    "name": "Dinagat Islands"
  }
}