• Skip navigation
  • Skip to navigation
  • Skip to the bottom
Simulate organization breadcrumb open Simulate organization breadcrumb close
ZISC
  • FAUTo the central FAU website
Suche öffnen
  • Campo
  • StudOn
  • FAUdir
  • Jobs
  • Map
  • Help

ZISC

Navigation Navigation close
  • The ZISC
    • About the ZISC
    • Organigram
    • List of ZISC Members
    • Staff
    Portal The ZISC
  • Research
    • Member Profiles
    • Projects
      • Current Projects
      • Completed Projects
    • Publications
    • The P&G SimCenter
    • Software
    • Student Theses/Assistant Jobs
    Portal Research
  • COVID-19
  • Activities
    • Collaboration Possibilities for Industrial Partners
    • Education
    • Meeting Organization
    • Software Acquisition
    Portal Activities
  • Contact and Downloads
  1. Home
  2. COVID-19
  3. Research
  4. Different travel scenarios

Different travel scenarios

In page navigation: COVID-19
  • People
  • Education
  • Research
    • Airborne pathogens
    • Analytical Mechanics
    • Simulation models for COVID-19
    • Ambulance Logistics
    • Different travel scenarios
    • Modelling with spatial resolution
    • Integro-differential equation
    • Data-driven modeling
    • Assessment of effective mitigation and prediction of the spread of SARS-CoV-2 (Seminar Talk)
    • MD Simulations of SARS-CoV-2 Spike
  • Papers and Preprints

Different travel scenarios

Simulations of the spread of Covid-19 for different travel scenarios

By using spatially-resolved SEIR-simulations we study the spread of Covid-19 in Germany for different travel scenarios. The fast initial spread of Covid-19 only can be explained by frequent long-distance travelling that is modeled in our simulations with an underlying scale-free travel network. In contrast, if travelling is restricted to local travel, the spread can be confined in a certain region. Even if typical commuting is allowed it takes a long time for the spread to affect Germany as a whole. However, our simulations also show that during the initial growth the total number of infected persons cannot be changed by travel restrictions if other restrictions are absent.

In future, we want to characterize typical patterns of the spread of Covid-19 in order to understand how these patterns are related to the travel behavior. Furthermore, we want to employ artificial intelligence to analyze these patterns.

Michael Schmiedeberg

Friedrich-Alexander-Universität Erlangen-Nürnberg
Zentralinstitut für Scientific Computing

Martensstrasse 5a
91058 Erlangen
  • Impressum
  • Datenschutz
  • Facebook
  • RSS Feed
  • Twitter
  • Xing
Up