2015/01/20 by Lorenzo Pellis, Simon E. F. Spencer, Pellis, Lorenzo +3
Mathematics · Medicine · Physics and Astronomy · #05C82 #60K20 #92D30 #COVID-19 epidemiological studies #Complex Network Analysis Techniques #FOS: Biological sciences #FOS: Mathematics #Mathematical and Theoretical Epidemiology and Ecology Models #Populations and Evolution (q-bio.PE) #Probability (math.PR)
paper · pdf · doi:10.48550/arxiv.1501.04824
openalex publication_date 2015/01/20 · openalex created_date 2022/10/05 · openalex updated_date 2026/07/28
Networks have become an important tool for infectious disease epidemiology.\nMost previous theoretical studies of transmission network models have either\nconsidered simple Markovian dynamics at the individual level, or have focused\non the invasion threshold and final outcome of the epidemic. Here, we provide a\ngeneral theory for early real-time behaviour of epidemics on large\nconfiguration model networks (i.e. static and locally unclustered), in\nparticular focusing on the computation of the Malthusian parameter that\ndescribes the early exponential epidemic growth. Analytical, numerical and\nMonte-Carlo methods under a wide variety of Markovian and non-Markovian\nassumptions about the infectivity profile are presented. Numerous examples\nprovide explicit quantification of the impact of the network structure on the\ntemporal dynamics of the spread of infection and provide a benchmark for\nvalidating results of large scale simulations.\n