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Modeling workplace contact networks: The effects of organizational structure, architecture, and reporting errors on epidemic predictions.

Potter GE, Smieszek T, Sailer K - Netw Sci (Camb Univ Press) (2015)

Bottom Line: We find that contact probability decreases with distance, and that research group membership, role, and shared projects are strongly predictive of contact patterns.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.

View Article: PubMed Central - PubMed

Affiliation: California Polytechnic State University, San Luis Obispo, CA, USA; Center for Statistics and Quantitative Infectious Disease, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

ABSTRACT

Face-to-face social contacts are potentially important 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 with 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 that research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0-5 min 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.

No MeSH data available.


Related in: MedlinePlus

An example office layout with axial topology and four architectural distance measures computed from A to B.
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Figure 1: An example office layout with axial topology and four architectural distance measures computed from A to B.

Mentions: This paper uses different ways of measuring the architectural distance between desks of co-workers, as initially introduced by Sailer & McCulloh (2012). In order to represent distances, a map of lines following possible routes through the office building is drawn using Space Syntax methodologies (Hillier & Hanson, 1984; Hillier, 1996). This line map consists of all longest straight lines covering all relevant parts of the office, reaching all individual workstations and minimizing the number of lines and elements needed to go from one space to another (see Figure 1). The different floors of the office are linked through the staircases, again with lines representing the potential movement flow of people up and down the flights of the stair.


Modeling workplace contact networks: The effects of organizational structure, architecture, and reporting errors on epidemic predictions.

Potter GE, Smieszek T, Sailer K - Netw Sci (Camb Univ Press) (2015)

An example office layout with axial topology and four architectural distance measures computed from A to B.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4663701&req=5

Figure 1: An example office layout with axial topology and four architectural distance measures computed from A to B.
Mentions: This paper uses different ways of measuring the architectural distance between desks of co-workers, as initially introduced by Sailer & McCulloh (2012). In order to represent distances, a map of lines following possible routes through the office building is drawn using Space Syntax methodologies (Hillier & Hanson, 1984; Hillier, 1996). This line map consists of all longest straight lines covering all relevant parts of the office, reaching all individual workstations and minimizing the number of lines and elements needed to go from one space to another (see Figure 1). The different floors of the office are linked through the staircases, again with lines representing the potential movement flow of people up and down the flights of the stair.

Bottom Line: We find that contact probability decreases with distance, and that research group membership, role, and shared projects are strongly predictive of contact patterns.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.

View Article: PubMed Central - PubMed

Affiliation: California Polytechnic State University, San Luis Obispo, CA, USA; Center for Statistics and Quantitative Infectious Disease, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

ABSTRACT

Face-to-face social contacts are potentially important 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 with 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 that research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0-5 min 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.

No MeSH data available.


Related in: MedlinePlus