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AGILE: GIScience Series Open-access proceedings of the Association of Geographic Information Laboratories in Europe
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Articles | Volume 2
AGILE GIScience Ser., 2, 44, 2021
AGILE GIScience Ser., 2, 44, 2021

  05 Jul 2021

05 Jul 2021

Promoting the adoption of agent-based modelling for synergistic interventions and decision-making during pandemic outbreaks

Phaedon Kyriakidis1,2, Dimitris Kavroudakis3, Philip Fayad1,2, Stylianos Hadjipetrou1,2, Georgios Leventis1,2, and Apostolos Papakonstantinou1 Phaedon Kyriakidis et al.
  • 1Department of Civil Engineering and Geomatics, Cyprus University of Technology, Limassol, Cyprus
  • 2Eratosthenes Centre of Excellence, Limassol, Cyprus
  • 3Department of Geography, University of the Aegean, Mytilene, Greece

Keywords: spatial simulation, lock-down, COVID-19

Abstract. Geography has long sought to explain spatial relationships between social and physical processes, including the spread of infectious diseases, within the context of modelling human-environment interactions. The spread of the recent COVID-19 pandemic, and its devastating effects on human activity and welfare, represent but examples of such complex human-environment interactions. In this paper, we discuss the value of agent-based models for simulating the spread of the COVID-19 virus to support decision-making with regards to non-pharmaceutical interventions, e.g., lock-down. We also develop a prototype agent-based model using a minimal set of rules regarding patterns of human mobility within a hypothetical town, and couple that with an epidemiological model of infectious disease spread. The coupled model is used to: (a) create synthetic trajectories corresponding to daily and weekly activities postulated between a set of predefined points of interest (e.g., home, work), and (b) simulate new infections at contact points and their subsequent effects on the spread of the disease. We finally use the model simulations as a means of evaluating decisions regarding the number and type of activities to be limited during a planned lockdown in a COVID-19 pandemic context.

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