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Characterizing the Initial Phase of Epidemic Growth on some Empirical NetworksPrimeFaces.cw("AccordionPanel","widget_formSmash_some",{id:"formSmash:some",widgetVar:"widget_formSmash_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_all",{id:"formSmash:all",widgetVar:"widget_formSmash_all",multiple:true});
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2018 (English)In: Stochastic Processes and Applications / [ed] Sergei Silvestrov, Anatoliy Malyarenko, Milica Rančić, Springer, 2018, p. 315-334Conference paper, Published paper (Refereed)
##### Abstract [en]

##### Place, publisher, year, edition, pages

Springer, 2018. p. 315-334
##### Series

Springer Proceedings in Mathematics & Statistics, ISSN 2194-1009, E-ISSN 2194-1017 ; 271
##### Keywords [en]

Epidemics, Exponential growth, Generalized growth model, Reproduction number, Stochastic processes
##### National Category

Mathematics
##### Research subject

Mathematical Statistics
##### Identifiers

URN: urn:nbn:se:su:diva-154927DOI: 10.1007/978-3-030-02825-1_13ISBN: 978-3-030-02824-4 (print)ISBN: 978-3-030-02825-1 (electronic)OAI: oai:DiVA.org:su-154927DiVA, id: diva2:1195903
##### Conference

SPAS2017, International Conference on Stochastic Processes and Algebraic Structures – From Theory Towards Applications, Västerås and Stockholm, Sweden, October 4-6, 2017
#####

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PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt553",{id:"formSmash:j_idt553",widgetVar:"widget_formSmash_j_idt553",multiple:true});
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PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt559",{id:"formSmash:j_idt559",widgetVar:"widget_formSmash_j_idt559",multiple:true});
##### Funder

Swedish Research Council, 2016-04566Available from: 2018-04-06 Created: 2018-04-06 Last updated: 2018-12-13Bibliographically approved
##### In thesis

A key parameter in models for the spread of infectious diseases is the basic reproduction number R0">R 0 R0 , which is the expected number of secondary cases a typical infected primary case infects during its infectious period in a large mostly susceptible population. In order for this quantity to be meaningful, the initial expected growth of the number of infectious individuals in the large-population limit should be exponential. We investigate to what extent this assumption is valid by simulating epidemics on empirical networks and by fitting the initial phase of each epidemic to a generalised growth model, allowing for estimating the shape of the growth. For reference, this is repeated on some elementary graphs, for which the early epidemic behaviour is known. We find that for the empirical networks tested in this paper, exponential growth characterizes the early stages of the epidemic, except when the network is restricted by a strong low-dimensional spacial constraint.

1. Random networks with weights and directions, and epidemics thereon$(function(){PrimeFaces.cw("OverlayPanel","overlay1197294",{id:"formSmash:j_idt851:0:j_idt858",widgetVar:"overlay1197294",target:"formSmash:j_idt851:0:parentLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

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