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_18
Snippet: Since R 0 is assumed to be highly dependent on the mobility data, rapid changes in mobility result in rapid changes in epidemic development. This assumption of the model should be sound since intermixing of individuals increases the number of contacts and thus spread, while the opposite reduces it. The model shows that the grocery and pharmacy sector has the biggest impact on changes in R o , the underlying reason for this is not clear, but we ca.....
Document: Since R 0 is assumed to be highly dependent on the mobility data, rapid changes in mobility result in rapid changes in epidemic development. This assumption of the model should be sound since intermixing of individuals increases the number of contacts and thus spread, while the opposite reduces it. The model shows that the grocery and pharmacy sector has the biggest impact on changes in R o , the underlying reason for this is not clear, but we can speculate. It is possible that this sector enables contacts between different communities, while people in the same communities likely go to the same restaurants and interact in similar sectors. Alternatively, it is also possible that more infected people visited the grocery and pharmacy sector before the lockdowns.
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