Epidemics on Networks

2024/02/03 by Jan Kreischer, Kreischer, Jan, Adrian Iten +3 · 1 citation
Mathematics · #COVID-19 epidemiological studies #FOS: Computer and information sciences #FOS: Physical sciences #J.3 #K.4 #Networking and Internet Architecture (cs.NI) #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI)

paper · pdf · doi:10.48550/arxiv.2402.02234

openalex publication_date 2024/02/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Despite centuries of work on containment and mitigation strategies, infectious diseases are still a major problem facing humanity. This work is concerned with simulating heterogeneous contact structures and understanding how the structure of the underlying network affects the spread of the disease. For example, it has been empirically demonstrated and validated that scale free networks do not have an epidemic threshold. Understanding the relationship between network structure and disease dynamics can help to develop better mitigation strategies and more effective interventions.

Cited by

• Understanding How Network Geometry Influences Diffusion Processes in Complex Networks: A Focus on Cryptocurrency Blockchains and Critical Infrastructure Networks

Related

• Epidemic spread in networks: Existing methods and current challenges
• Epidemics and immunization in scale-free networks
• Analysis and Control of Epidemics: A survey of spreading processes on\n complex networks
• Large epidemic thresholds emerge in heterogeneous networks of heterogeneous nodes
• Networked Infectiousness: Cascades, Power Laws, and Kinetics