eprintid: 1426495
rev_number: 31
eprint_status: archive
userid: 608
dir: disk0/01/42/64/95
datestamp: 2014-04-08 18:52:27
lastmod: 2021-10-04 00:19:16
status_changed: 2014-04-08 18:52:27
type: article
metadata_visibility: show
item_issues_count: 0
creators_name: Potter, G
creators_name: Smieszek, T
creators_name: Sailer, K
title: Modeling workplace contact networks: the effects of organizational structure, architecture, and reporting errors on epidemic predictions
ispublished: pub
divisions: UCL
divisions: B04
divisions: C04
divisions: F36
keywords: contact network, space syntax, physical distance, epidemic model, social network, influenza
note: © Cambridge University Press 2015. This is an Open Access
article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
abstract: Face-to-face social contacts are potential transmission routes for acute respiratory infections, and understanding the contact network can improve our ability to predict, contain, and control epidemics. Although workplaces are important settings for infectious disease transmission, few studies have collected workplace contact data and estimated workplace contact networks. We use contact diaries, architectural distance measures, and institutional structures to estimate social contact networks within a Swiss research institute. Some contact reports were inconsistent, indicating reporting errors. We adjust for this via a latent variable model, jointly estimating the true (unobserved) network of contacts and duration-specific reporting probabilities. We find that contact probability decreases with distance, and research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0–5 minute) contacts. Adjusting for reporting error changed the estimate of the duration distribution, but did not change the estimates of covariate effects and had little effect on epidemic predictions. Our epidemic simulation study indicates that inclusion of network structure based on architectural and organizational structure data can improve the accuracy of epidemic forecasting models.
date: 2015-07-31
publisher: Cambridge Journals
official_url: http://dx.doi.org/10.1017/nws.2015.22
vfaculties: VBEF
oa_status: green
full_text_type: pub
primo: open
primo_central: open_green
article_type_text: Article
verified: verified_manual
elements_source: Manually entered
elements_id: 940414
doi: 10.1017/nws.2015.22
lyricists_name: Sailer, Kerstin
lyricists_id: KSAIL15
full_text_status: public
publication: Network Science
volume: 3
number: 3
place_of_pub: Cambridge
pagerange: 298-325
citation:        Potter, G;    Smieszek, T;    Sailer, K;      (2015)    Modeling workplace contact networks: the effects of organizational structure, architecture, and reporting errors on epidemic predictions.                   Network Science , 3  (3)   pp. 298-325.    10.1017/nws.2015.22 <https://doi.org/10.1017/nws.2015.22>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1426495/1/Modeling%20workplace%20contact%20networks%20The%20effects%20of%20organizational%20structure%2C%20architecture%2C%20and%20reporting%20errors%20on%20epidemic%20predictions.pdf
document_url: https://discovery.ucl.ac.uk/id/eprint/1426495/2/Potter%20supplementary%20material%201.pdf