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Understanding components of mobility during the COVID-19 pandemic
Peter Edsberg Møllgaard1, Sune Lehmann1,2, Laura Alessandretti1,3
1Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark.
Summary
Analyzing COVID-19 spread, this study reveals how different travel patterns, like commuting and holidays, impact disease transmission. Mobility data decomposition shows workday travel declines during restrictions, while weekend travel increases, affecting epidemic spread.
Area of Science:
- Epidemiology
- Network Science
- Data Science
Background:
- Travel restrictions are key in controlling COVID-19 spread by delaying propagation.
- Understanding how diverse travel behaviors (commuting, holidays) influence infectious disease spread is crucial.
Purpose of the Study:
- To decompose mobility flow networks into interpretable components.
- To analyze the impact of different travel types on epidemic spreading during 2020.
Main Methods:
- Utilized factorization techniques to analyze temporal mobility networks.
- Employed datasets from Danish mobile network operators and Facebook Data-For-Good.
- Measured effective distance to quantify disease travel speed between municipalities.
Main Results:
- Mobility patterns were decomposed into workday, weekend, and holiday components.
- Workday travel significantly decreased during strict travel restrictions, while weekend travel increased.
- Different mobility components showed varying contributions to epidemic spread dynamics.
Conclusions:
- Mobility patterns are aggregations of distinct travel behaviors (workday, weekend, holiday).
- Shifts in travel behavior during restrictions (less work, more weekend travel) alter epidemic propagation.
- Understanding these components is vital for effective infectious disease surveillance and control strategies.
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