title: Epidemic progression on networks based on disease generation time.
abstract: We investigate the time evolution of disease spread on a network and present an analytical framework using the concept of disease generation time. Assuming a susceptible-infected-recovered epidemic process, this network-based framework enables us to calculate in detail the number of links (edges) within the network that are capable of producing new infectious nodes (individuals), the number of links that are not transmitting the infection further (non-transmitting links), as well as the number of contacts that individuals have with their neighbours (also known as degree distribution) within each epidemiological class, for each generation period. Using several examples, we demonstrate very good agreement between our analytical calculations and the results of computer simulations.
authors.affiliation: Division of Mathematical Modeling, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada.
authors.forename: Bahman
authors.initials: B
authors.lastname: Davoudi
authors.forename: Flavia
authors.initials: F
authors.lastname: Moser
authors.forename: Fred
authors.initials: F
authors.lastname: Brauer
authors.forename: Babak
authors.initials: B
authors.lastname: Pourbohloul
mesh_terms: D016000:Cluster Analysis; D003141:Communicable Diseases / Q000453:epidemiology* / Q000635:transmission*; D003198:Computer Simulation; D058872:Epidemics / Q000706:statistics & numerical data; D015981:Epidemiologic Factors; D006801:Humans; D055641:Mathematical Concepts; D008954:Models, Biological; D011157:Population Dynamics; D013997:Time Factors
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