Epidemic spreading via
Polish railway network
Natalia Kruszewska1
, Andrzej Grabowski2
, Piotr Jezierski1
1
Institute of M...
Main objective
To study dynamic phenomena such as
epidemic spreading in polish cities (chosen
from the ones which are conn...
Structure of the network
Data source: Map of trains' routes in Poland (from PKP website)
Nodes:
cities - stations
Links:
r...
Structure of the network
Degree distribution P(k).
k (nearest neighbors) is a number of stations
which are right connected...
Simulation results
Number of infected
people grows very fast –
super-diffusive process.
Number of infected
people grows ve...
Simulation results
Number of infected
people grows very fast –
super-diffusive process.
Number of infected
people grows ve...
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Epidemic spreading via Polish railway network

We study a dynamic phenomena such as epidemic spreading in polish cities chosen from the ones which are connected to each other by railway network.
Published on: Mar 4, 2016
Published in: Science      
Source: www.slideshare.net


Transcripts - Epidemic spreading via Polish railway network

  • 1. Epidemic spreading via Polish railway network Natalia Kruszewska1 , Andrzej Grabowski2 , Piotr Jezierski1 1 Institute of Mathematics and Physics, UTP University of Science and Technology, Bydgoszcz 2 Central Institute for Labour Protection, National Research Institute, Warsaw FNP project SKILLS 2015
  • 2. Main objective To study dynamic phenomena such as epidemic spreading in polish cities (chosen from the ones which are connected to each other by railway network) by • examining structure of the network, • performing computer simulation of diffusion of a virus with assumption that infection spreads by – trains, – connections of people in the cities.
  • 3. Structure of the network Data source: Map of trains' routes in Poland (from PKP website) Nodes: cities - stations Links: rails Red circles: numbers of infected people Blue circles: trains Trains schedule (start-stations and end-stations) has been picked at random from all bigger cities. Trains schedule (start-stations and end-stations) has been picked at random from all bigger cities.
  • 4. Structure of the network Degree distribution P(k). k (nearest neighbors) is a number of stations which are right connected to chosen station via rails. Distribution is characteristic for scale-free networks.
  • 5. Simulation results Number of infected people grows very fast – super-diffusive process. Number of infected people grows very fast – super-diffusive process. Open question: is railway network structure significant for epidemic spreading? Rotavirus-type disease
  • 6. Simulation results Number of infected people grows very fast – super-diffusive process. Number of infected people grows very fast – super-diffusive process. Open question: is railway network structure significant for epidemic spreading? Rotavirus-type disease

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