Methods Inf Med 2020; 59(06): 179-182
DOI: 10.1055/s-0041-1726276
Short Paper

The Relationship between Mobility and COVID-19 in Germany: Modeling Case Occurrence using Apple's Mobility Trends Data

Mark David Walker
1  Department of the Natural and Built Environment, Sheffield Hallam University, Sheffield, United Kingdom
Mihály Sulyok
2  Department of Pathology, Institute of Pathology and Neuropathology, Eberhard Karls University, Tübingen, Germany
3  Institute of Tropical Medicine, Eberhard Karls University, Tübingen, Germany
› Author Affiliations


Background Restrictions on social interaction and movement were implemented by the German government in March 2020 to reduce the transmission of coronavirus disease 2019 (COVID-19). Apple's “Mobility Trends” (AMT) data details levels of community mobility; it is a novel resource of potential use to epidemiologists.

Objective The aim of the study is to use AMT data to examine the relationship between mobility and COVID-19 case occurrence for Germany. Is a change in mobility apparent following COVID-19 and the implementation of social restrictions? Is there a relationship between mobility and COVID-19 occurrence in Germany?

Methods AMT data illustrates mobility levels throughout the epidemic, allowing the relationship between mobility and disease to be examined. Generalized additive models (GAMs) were established for Germany, with mobility categories, and date, as explanatory variables, and case numbers as response.

Results Clear reductions in mobility occurred following the implementation of movement restrictions. There was a negative correlation between mobility and confirmed case numbers. GAM using all three categories of mobility data accounted for case occurrence as well and was favorable (AIC or Akaike Information Criterion: 2504) to models using categories separately (AIC with “driving,” 2511. “transit,” 2513. “walking,” 2508).

Conclusion These results suggest an association between mobility and case occurrence. Further examination of the relationship between movement restrictions and COVID-19 transmission may be pertinent. The study shows how new sources of online data can be used to investigate problems in epidemiology.

Supplementary Material

Publication History

Received: 28 September 2020

Accepted: 22 January 2021

Publication Date:
26 March 2021 (online)

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