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Covid19 infected cases in Germany / Saxony-Anhalt / Magdeburg: Graphs and personal shitposting.

magdeburg lichterfest
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  • Brainstormers: Anirban Saha, Indranil Maji, Chirag Mandal.
  • This post is going to be updated regularly, the text in it too might change.
  • This is in a blog post format, there might be citations missing or citations might be from non-scientific sources.
  • This is a really part-time thing I am doing on a Saturday morning. It neither aims nor is it capable of being a scientific work.
  • The graphics are updated regularly, the text is now.
  • This post is too exploratory in nature. Please do not expect conclusive statements from this blog post.
  • For now, if you would want to contribute, just drop me an email. My email address is mailme@anirbansaha.com
  • Last updated on 20.03.2020

Before the first case in Saxony-Anhalt was reported, there was an awareness about the novel Coronavirus in Germany. The first case of a covid19 patient in Germany was reported on February 15, 2020. Since then, as of today, there are over 22,300 cases of covid19 infections in Germany, causing over 80 deaths. Updated: 21.03.2020

The first case of the novel coronavirus (covid19) was recorded in Saxony Anhalt on March 10, 2020. Since then, the number of cases has increased to over 250. The local state government has taken preemptive policy measures like closing the university, the non-essential shops, etc. Updated: 21.03.2020

Update: 24.04.2020 The number of cases in Saxony-Anhalt stands at 1440 (23.04.2020). The state is preparing to get back to normalcy. Masks are mandatory for people who are going out. Shops smaller than 800 sq.mt to open by the next week. It’s a lovely spring and on ground, people are already out but maintaining social / physical distancing.

The objective of this blog post is to explore the spread of covid19 patients detected in Saxony-Anhalt, with reference to the rest of Germany. There would be a little emphasis on cases in Magdeburg.

Saxony-Anhalt might be a good case to explore because of the following reasons:

We have a set of basic assumptions as we attempt to explore this: 

Growth of Covid19 infected cases:

Graph 1
Graph 2
Graph 3
Information: The exponential model is trained with data until 20.03.2020.

When we observe Graph 1, we see there is a slight deflection from the exponential curve. However, it might be naive to assume that it is slowing down right now.

We see the growth of the number of covid19 infected patients in Germany (country) and Saxony-Anhalt (state) in Graph 1 and Graph 2. Let’s see how quickly the numbers grew.

Graph 4

Information: As I publish this post on 21.03.2020, the number of cases in Saxony Anhalt did not reach 300.

We observe that at first, the covid19 cases were growing faster in the rest of Germany as compared to its growth in Saxony-Anhalt. This slow down could be attributed to any one or more than one of the following hypothesizes:

Table 1

Quick Question: Is there a direct correlation between the spread of the covid19 affected cases and the population density of a state?

Intuitively the answer is yes! Because, the closer the people are together, the more are the chances of contamination. Population density is higher in cities and areas around the big cities. The data in Table 1 support the intuition. To gauge the spread, we are taking the number of cases per 1000 people living in that area.

The values towards the higher end are given some red shade. The values towards the lower end are given some share of blue to easily notice. Why Saxony, Bavaria is not following the trend is out of the scope of this discussion. Updated: 21.03.2020

Coming back, the amount of data observations for Graph 3 is just too few. Although it is expected to be exponential growth, we might want to predict it using a straight line. It does not make sense and it’s okay to be proven wrong later.

Graph 5

New Covid19 infected cases per day

Graph 6
Graph 7
Graph 8

The graphs are incomparable and that’s for later. For now, let’s explore something called the Growth Factor. The Growth Factor is representative of how soon we can expect a slowdown in the rise of the curve. At an inflection point, the growth rate is constant at 1.

Graph 9
Graph 10
Graph 11

This Growth Factor should be consistent at 1 for sometime before minimizing to 0 (a completely flattened curve). For Saxony-Anhalt, and the city of Magdeburg, we have too few data points. But this would be an interesting thing to notice in the future.

Predicting the next values!

One interesting aspect of the growth factor is this: the values follow a straight line before the curve finally flattens. I had previously observed this trend in the Saxony-Anhalt Data and made a prediction publicly here.

Update: 24.04.2020 Graph 12 removed. Graph 13 added.
Graph 13
Day 12 (Saxony-Anhalt), 21.03.2020: The number of covid19 infected patients reported in Saxony-Anhalt is 253. That fits the linear yellow line. Day 14, 22.03.2020: It has some growth upwards. It would be wise to keep this under observation for some time before forming an opinion about whether it is slowing down.

While it is too early to comment on too few data points, it would be interesting to see if the curve flattens for Saxony-Anhalt.

24.04.2020: While the graph for Germany is flattening, I am not sure if I would like to make a similar statement for the state of Saxony-Anhalt. The numbers are comparatively lower but we should be cautious as the normal life resumes. [To be continued.]

Data Sources:

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