MFA by country

• Author: Sermi, F.; Iacus, S.; Vespe, M.; Santamaria, C.; Spyratos, S.; Tarchi, D.
• Pages: 11-40

5 MFA by country

We now review, without commenting it, the additional 14 countries with a special split in

case of Norway where data from two different MNOs are available. Odd peaks and anomalies

are due to different kinds of error in the original data; since these outliers are not considered

in the definition of the persistent MFA, they do not affect the analysis, but only the graphical

patterns (see, e.g., Figure 21). Although the gra phics are self-explanatory, we can suggest

the reader to focus on some common and diverging evidence in what follows. Common,

and vastly expected, evidence can be summarised as follows:

— intra-weekly patterns, i.e., workdays are different from weekends days and holidays;

— persistence of the MFAs across countries is clear;

— pre- and post- lockdown MFAs are different, meaning that mobility has been effectively

reduced when lockdown measures have been implemented;

— administrative areas are, on average, much different from MFAs

— persistent MFAs spreads across more than one administrative though not covering an

entire administrative area;

— lockdown MFAs are smaller that persistent MFA, usually confined with an administrative

area and their number is larger than the persistent MFAs.

On the contrary, it is worth noticing that in some countries the dissimilarity matrixes

are darker than for other countries, meaning that the mobility have been more affected by

lockdown measures than other countries (see also Figure 36). The shading of the intensity

is also a sign of the speed of reversion of the human mobility to pre-crisis level. This is also

expected, as there are different types and intensities of lockdown measures.

Further, for those countries in which nation-wide measures have not been enforced but

only self-restrictions to mobility, the shapes of the pre- and post-lockdown MFAs are only

slightly different.

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5.1 Austria

0.2

0.3

0.4

0.5

0.6

0.7

2020−01−30

2020−02−06

2020−02−13

2020−02−20

2020−02−27

2020−03−05

2020−03−12

2020−03−19

2020−03−26

2020−04−02

2020−04−09

2020−04−16

2020−04−23

2020−04−30

2020−05−07

2020−05−14

2020−05−21

2020−05−28

2020−06−04

2020−06−11

2020−06−18

2020−06−25

2020−07−02

Similarity

Target

Districts

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

0.2

0.4

0.6

2020−01−30

2020−02−06

2020−02−13

2020−02−20

2020−02−27

2020−03−05

2020−03−12

2020−03−19

2020−03−26

2020−04−02

2020−04−09

2020−04−16

2020−04−23

2020−04−30

2020−05−07

2020−05−14

2020−05−21

2020−05−28

2020−06−04

2020−06−11

2020−06−18

2020−06−25

2020−07−02

Similarity

Target

daily MFA

Post−MFA

Districts

Similarity with persistent MFA

2020−02−01

2020−02−08

2020−02−15

2020−02−22

2020−02−29

2020−03−07

2020−03−14

2020−03−21

2020−03−28

2020−04−04

2020−04−11

2020−04−18

2020−04−25

2020−05−02

2020−05−09

2020−05−16

2020−05−23

2020−05−30

2020−06−07

2020−06−14

2020−06−21

2020−06−28

2020−02−01

2020−02−08

2020−02−15

2020−02−22

2020−02−29

2020−03−07

2020−03−14

2020−03−21

2020−03−28

2020−04−04

2020−04−11

2020−04−18

2020−04−25

2020−05−02

2020−05−09

2020−05−16

2020−05−23

2020−05−30

2020−06−07

2020−06−14

2020−06−21

2020−06−28

0.00

0.25

0.50

0.75

1.00

Similarity

Weekday

holiday

working

Similarity among all days

Figure 7: AUSTRIA: Intra-weekly similarity of MFAs (top) and daily similarity of the MFAs with respect

to persistent and post lockdown MFAs and Austrian districts (middle). Full similarity matrix among

daily MFAs (bottom).

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