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The role of heterogeneity in contact timing and duration in network models of influenza spread in schools

tetano

Editor, Senior Moderator
J R Soc Interface. 2015 Jul 6;12(108). pii: 20150279. doi: 10.1098/rsif.2015.0279.
[h=1]The role of heterogeneity in contact timing and duration in network models of influenza spread in schools.[/h] Toth DJ[SUP]1[/SUP], Leecaster M[SUP]2[/SUP], Pettey WB[SUP]2[/SUP], Gundlapalli AV[SUP]3[/SUP], Gao H[SUP]4[/SUP], Rainey JJ[SUP]4[/SUP], Uzicanin A[SUP]4[/SUP], Samore MH[SUP]5[/SUP].
[h=3]Author information[/h]

[h=3]Abstract[/h] Influenza poses a significant health threat to children, and schools may play a critical role in community outbreaks. Mathematical outbreak models require assumptions about contact rates and patterns among students, but the level of temporal granularity required to produce reliable results is unclear. We collected objective contact data from students aged 5-14 at an elementary school and middle school in the state of Utah, USA, and paired those data with a novel, data-based model of influenza transmission in schools. Our simulations produced within-school transmission averages consistent with published estimates. We compared simulated outbreaks over the full resolution dynamic network with simulations on networks with averaged representations of contact timing and duration. For both schools, averaging the timing of contacts over one or two school days caused average outbreak sizes to increase by 1-8%. Averaging both contact timing and pairwise contact durations caused average outbreak sizes to increase by 10% at the middle school and 72% at the elementary school. Averaging contact durations separately across within-class and between-class contacts reduced the increase for the elementary school to 5%. Thus, the effect of ignoring details about contact timing and duration in school contact networks on outbreak size modelling can vary across different schools.
? 2015 The Author(s) Published by the Royal Society. All rights reserved.


[h=4]KEYWORDS:[/h] contact network; epidemiology; influenza; mathematical model; schools

PMID: 26063821 [PubMed - in process]
 
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