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Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys

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Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys. / Grantz, K.H.; Cummings, D.A.T.; Zimmer, S. et al.
In: Scientific Reports, Vol. 11, No. 1, 2319, 27.01.2021.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Grantz, KH, Cummings, DAT, Zimmer, S, Vukotich Jr, C, Galloway, D, Schweizer, ML, Guclu, H, Cousins, J, Lingle, C, Yearwood, GMH, Li, K, Calderone, P, Noble, E, Gao, H, Rainey, J, Uzicanin, A & Read, JM 2021, 'Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys', Scientific Reports, vol. 11, no. 1, 2319. https://doi.org/10.1038/s41598-021-81673-y

APA

Grantz, K. H., Cummings, D. A. T., Zimmer, S., Vukotich Jr, C., Galloway, D., Schweizer, M. L., Guclu, H., Cousins, J., Lingle, C., Yearwood, G. M. H., Li, K., Calderone, P., Noble, E., Gao, H., Rainey, J., Uzicanin, A., & Read, J. M. (2021). Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys. Scientific Reports, 11(1), Article 2319. https://doi.org/10.1038/s41598-021-81673-y

Vancouver

Grantz KH, Cummings DAT, Zimmer S, Vukotich Jr C, Galloway D, Schweizer ML et al. Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys. Scientific Reports. 2021 Jan 27;11(1):2319. doi: 10.1038/s41598-021-81673-y

Author

Grantz, K.H. ; Cummings, D.A.T. ; Zimmer, S. et al. / Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys. In: Scientific Reports. 2021 ; Vol. 11, No. 1.

Bibtex

@article{29568d5731c7470d93b9d093d3aeec06,
title = "Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys",
abstract = "Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission. {\textcopyright} 2021, The Author(s).",
author = "K.H. Grantz and D.A.T. Cummings and S. Zimmer and {Vukotich Jr}, C. and D. Galloway and M.L. Schweizer and H. Guclu and J. Cousins and C. Lingle and G.M.H. Yearwood and K. Li and P. Calderone and E. Noble and H. Gao and J. Rainey and A. Uzicanin and J.M. Read",
year = "2021",
month = jan,
day = "27",
doi = "10.1038/s41598-021-81673-y",
language = "English",
volume = "11",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",

}

RIS

TY - JOUR

T1 - Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys

AU - Grantz, K.H.

AU - Cummings, D.A.T.

AU - Zimmer, S.

AU - Vukotich Jr, C.

AU - Galloway, D.

AU - Schweizer, M.L.

AU - Guclu, H.

AU - Cousins, J.

AU - Lingle, C.

AU - Yearwood, G.M.H.

AU - Li, K.

AU - Calderone, P.

AU - Noble, E.

AU - Gao, H.

AU - Rainey, J.

AU - Uzicanin, A.

AU - Read, J.M.

PY - 2021/1/27

Y1 - 2021/1/27

N2 - Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission. © 2021, The Author(s).

AB - Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission. © 2021, The Author(s).

U2 - 10.1038/s41598-021-81673-y

DO - 10.1038/s41598-021-81673-y

M3 - Journal article

VL - 11

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 2319

ER -