Author: Patrick Bryant; Arne Elofsson
Title: Estimating the impact of mobility patterns on COVID-19 infection rates in 11 European countries Document date: 2020_4_17
ID: emejt26r_19
Snippet: The mobility data from Google is quite noisy, which makes it uncertain. We did not include the data for the mobility category "Parks" as this data displayed much noise and cyclic peaks, as would be expected with varying weather. Another source of uncertainty is the lack of access to the raw data, as these values have been extracted from pdfs provided by Google. Still, most countries display very similar changes in relative mobility patterns. The .....
Document: The mobility data from Google is quite noisy, which makes it uncertain. We did not include the data for the mobility category "Parks" as this data displayed much noise and cyclic peaks, as would be expected with varying weather. Another source of uncertainty is the lack of access to the raw data, as these values have been extracted from pdfs provided by Google. Still, most countries display very similar changes in relative mobility patterns. The narrow CI for mobility in the grocery and pharmacy sector further suggests the model's predictive power and yields support to the predictions made here.
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