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Comparative Study
. 2016 Apr 21;11(4):e0153690.
doi: 10.1371/journal.pone.0153690. eCollection 2016.

Estimates of Social Contact in a Middle School Based on Self-Report and Wireless Sensor Data

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Free PMC article
Comparative Study

Estimates of Social Contact in a Middle School Based on Self-Report and Wireless Sensor Data

Molly Leecaster et al. PLoS One. .
Free PMC article

Abstract

Estimates of contact among children, used for infectious disease transmission models and understanding social patterns, historically rely on self-report logs. Recently, wireless sensor technology has enabled objective measurement of proximal contact and comparison of data from the two methods. These are mostly small-scale studies, and knowledge gaps remain in understanding contact and mixing patterns and also in the advantages and disadvantages of data collection methods. We collected contact data from a middle school, with 7th and 8th grades, for one day using self-report contact logs and wireless sensors. The data were linked for students with unique initials, gender, and grade within the school. This paper presents the results of a comparison of two approaches to characterize school contact networks, wireless proximity sensors and self-report logs. Accounting for incomplete capture and lack of participation, we estimate that "sensor-detectable", proximal contacts longer than 20 seconds during lunch and class-time occurred at 2 fold higher frequency than "self-reportable" talk/touch contacts. Overall, 55% of estimated talk-touch contacts were also sensor-detectable whereas only 15% of estimated sensor-detectable contacts were also talk-touch. Contacts detected by sensors and also in self-report logs had longer mean duration than contacts detected only by sensors (6.3 vs 2.4 minutes). During both lunch and class-time, sensor-detectable contacts demonstrated substantially less gender and grade assortativity than talk-touch contacts. Hallway contacts, which were ascertainable only by proximity sensors, were characterized by extremely high degree and short duration. We conclude that the use of wireless sensors and self-report logs provide complementary insight on in-school mixing patterns and contact frequency.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1. WREN worn by student.
Fig 2. Framework and notation for enumeration of contact pairs.
Contact pairs are either proximal only, proximal talk/touch, or talk/touch only. The linkable data set is a subset of the captured contact pairs. We observe the quantity (XP + XPT)as the total WREN contacts and (XT + XPT) as the total Log contacts.
Fig 3. Frequency of contact pairs by contact duration (in minutes) on a log-log scale.
Fig 4. Normalized frequency of contact pairs by contact duration (in minutes) on a log-log scale for contacts captured by WREN only and contacts captured by both WREN and Log.
Fig 5. Contact matrices from observed WREN-recorded contacts (all durations and > 20 seconds) and Log-reported contacts using data from class period and lunch.
The total contacts recorded between two groups are divided by the number of participants in the column group (given in parentheses) to provide an average number of contacts. Numbers per cell are mean (top), median, and interquartile range (25th and 75th percentile).
Fig 6. Estimated average T, PT, and P (separated for ≤ and > 20 seconds) contacts per student during class periods and lunch.
Fig 7. Contact matrices of estimated average contacts per student.
Contacts matrices are presented for P (>20 seconds), PT, and T contacts per student during class-time and lunch and include 95% confidence intervals (below).

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