Literature DB >> 33504823

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

Kyra H Grantz1,2,3, Derek A T Cummings1,2,3, Shanta Zimmer4,5, Charles Vukotich4, David Galloway6, Mary Lou Schweizer4, Hasan Guclu6,7, Jennifer Cousins6,8, Carrie Lingle6,9, Gabby M H Yearwood10, Kan Li6,11, Patti Calderone4, Eva Noble3, Hongjiang Gao12, Jeanette Rainey12,13, Amra Uzicanin12, Jonathan M Read14,15.   

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.

Entities:  

Year:  2021        PMID: 33504823      PMCID: PMC7840989          DOI: 10.1038/s41598-021-81673-y

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  60 in total

1.  Dynamic social networks and the implications for the spread of infectious disease.

Authors:  Jonathan M Read; Ken T D Eames; W John Edmunds
Journal:  J R Soc Interface       Date:  2008-09-06       Impact factor: 4.118

2.  Collecting close-contact social mixing data with contact diaries: reporting errors and biases.

Authors:  T Smieszek; E U Burri; R Scherzinger; R W Scholz
Journal:  Epidemiol Infect       Date:  2011-06-21       Impact factor: 2.451

Review 3.  Emerging infections: pandemic influenza.

Authors:  W P Glezen
Journal:  Epidemiol Rev       Date:  1996       Impact factor: 6.222

4.  Inference of seasonal and pandemic influenza transmission dynamics.

Authors:  Wan Yang; Marc Lipsitch; Jeffrey Shaman
Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-17       Impact factor: 11.205

5.  The relative importance of frequency of contacts and duration of exposure for the spread of directly transmitted infections.

Authors:  Elisabetta De Cao; Emilio Zagheni; Piero Manfredi; Alessia Melegaro
Journal:  Biostatistics       Date:  2014-04-04       Impact factor: 5.899

6.  Transmissibility of swine flu at Fort Dix, 1976.

Authors:  Justin Lessler; Derek A T Cummings; Steven Fishman; Amit Vora; Donald S Burke
Journal:  J R Soc Interface       Date:  2007-08-22       Impact factor: 4.118

7.  Social mixing patterns in rural and urban areas of southern China.

Authors:  Jonathan M Read; Justin Lessler; Steven Riley; Shuying Wang; Li Jiu Tan; Kin On Kwok; Yi Guan; Chao Qiang Jiang; Derek A T Cummings
Journal:  Proc Biol Sci       Date:  2014-04-30       Impact factor: 5.349

8.  Social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong.

Authors:  Kathy Leung; Mark Jit; Eric H Y Lau; Joseph T Wu
Journal:  Sci Rep       Date:  2017-08-11       Impact factor: 4.379

9.  Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors, Contact Diaries and Friendship Surveys.

Authors:  Rossana Mastrandrea; Julie Fournet; Alain Barrat
Journal:  PLoS One       Date:  2015-09-01       Impact factor: 3.240

10.  Measuring large-scale social networks with high resolution.

Authors:  Arkadiusz Stopczynski; Vedran Sekara; Piotr Sapiezynski; Andrea Cuttone; Mette My Madsen; Jakob Eg Larsen; Sune Lehmann
Journal:  PLoS One       Date:  2014-04-25       Impact factor: 3.240

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