How should social mixing be measured: comparing web-based survey and sensor-based methods
Contact surveys and diaries have conventionally been used to measure contact networks in different settings for elucidating infectious disease transmission dynamics of respiratory infections. More recently, technological advances have permitted the use of wireless sensor devices, which can be worn b...
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description | Contact surveys and diaries have conventionally been used to measure contact networks in different settings for elucidating infectious disease transmission dynamics of respiratory infections. More recently, technological advances have permitted the use of wireless sensor devices, which can be worn by individuals interacting in a particular social context to record high resolution mixing patterns. To date, a direct comparison of these two different methods for collecting contact data has not been performed.
We studied the contact network at a United States high school in the spring of 2012. All school members (i.e., students, teachers, and other staff) were invited to wear wireless sensor devices for a single school day, and asked to remember and report the name and duration of all of their close proximity conversational contacts for that day in an online contact survey. We compared the two methods in terms of the resulting network densities, nodal degrees, and degree distributions. We also assessed the correspondence between the methods at the dyadic and individual levels.
We found limited congruence in recorded contact data between the online contact survey and wireless sensors. In particular, there was only negligible correlation between the two methods for nodal degree, and the degree distribution differed substantially between both methods. We found that survey underreporting was a significant source of the difference between the two methods, and that this difference could be improved by excluding individuals who reported only a few contact partners. Additionally, survey reporting was more accurate for contacts of longer duration, and very inaccurate for contacts of shorter duration. Finally, female participants tended to report more accurately than male participants.
Online contact surveys and wireless sensor devices collected incongruent network data from an identical setting. This finding suggests that these two methods cannot be used interchangeably for informing models of infectious disease dynamics. |
doi_str_mv | 10.1186/1471-2334-14-136 |
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We studied the contact network at a United States high school in the spring of 2012. All school members (i.e., students, teachers, and other staff) were invited to wear wireless sensor devices for a single school day, and asked to remember and report the name and duration of all of their close proximity conversational contacts for that day in an online contact survey. We compared the two methods in terms of the resulting network densities, nodal degrees, and degree distributions. We also assessed the correspondence between the methods at the dyadic and individual levels.
We found limited congruence in recorded contact data between the online contact survey and wireless sensors. In particular, there was only negligible correlation between the two methods for nodal degree, and the degree distribution differed substantially between both methods. We found that survey underreporting was a significant source of the difference between the two methods, and that this difference could be improved by excluding individuals who reported only a few contact partners. Additionally, survey reporting was more accurate for contacts of longer duration, and very inaccurate for contacts of shorter duration. Finally, female participants tended to report more accurately than male participants.
Online contact surveys and wireless sensor devices collected incongruent network data from an identical setting. This finding suggests that these two methods cannot be used interchangeably for informing models of infectious disease dynamics.</description><identifier>ISSN: 1471-2334</identifier><identifier>EISSN: 1471-2334</identifier><identifier>DOI: 10.1186/1471-2334-14-136</identifier><identifier>PMID: 24612900</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Communicable diseases ; Comparative analysis ; Contact Tracing - instrumentation ; Contact Tracing - methods ; Data Collection - instrumentation ; Data Collection - methods ; Development and progression ; Diaries ; Disease control ; Disease prevention ; Faculty ; Female ; Health aspects ; Humans ; Internet ; Male ; Measurement ; Medical Records ; Methods ; Models, Statistical ; Population ; Respiratory Tract Infections - transmission ; Schools ; Secondary schools ; Sensors ; Social Behavior ; Social Environment ; Social networks ; Students ; Studies ; Telemetry ; United States ; Wireless networks ; Wireless sensor networks ; Wireless Technology</subject><ispartof>BMC infectious diseases, 2014-03, Vol.14 (1), p.136-136, Article 136</ispartof><rights>COPYRIGHT 2014 BioMed Central Ltd.</rights><rights>2014 Smieszek et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.</rights><rights>Copyright © 2014 Smieszek et al.; licensee BioMed Central Ltd. 2014 Smieszek et al.; licensee BioMed Central Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c559t-79a3a916fb58c67a04258f5799b1483e2eb62de48bb0bbef2d74c2ba80c7c7a3</citedby><cites>FETCH-LOGICAL-c559t-79a3a916fb58c67a04258f5799b1483e2eb62de48bb0bbef2d74c2ba80c7c7a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3984737/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3984737/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24612900$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Smieszek, Timo</creatorcontrib><creatorcontrib>Barclay, Victoria C</creatorcontrib><creatorcontrib>Seeni, Indulaxmi</creatorcontrib><creatorcontrib>Rainey, Jeanette J</creatorcontrib><creatorcontrib>Gao, Hongjiang</creatorcontrib><creatorcontrib>Uzicanin, Amra</creatorcontrib><creatorcontrib>Salathé, Marcel</creatorcontrib><title>How should social mixing be measured: comparing web-based survey and sensor-based methods</title><title>BMC infectious diseases</title><addtitle>BMC Infect Dis</addtitle><description>Contact surveys and diaries have conventionally been used to measure contact networks in different settings for elucidating infectious disease transmission dynamics of respiratory infections. More recently, technological advances have permitted the use of wireless sensor devices, which can be worn by individuals interacting in a particular social context to record high resolution mixing patterns. To date, a direct comparison of these two different methods for collecting contact data has not been performed.
We studied the contact network at a United States high school in the spring of 2012. All school members (i.e., students, teachers, and other staff) were invited to wear wireless sensor devices for a single school day, and asked to remember and report the name and duration of all of their close proximity conversational contacts for that day in an online contact survey. We compared the two methods in terms of the resulting network densities, nodal degrees, and degree distributions. We also assessed the correspondence between the methods at the dyadic and individual levels.
We found limited congruence in recorded contact data between the online contact survey and wireless sensors. In particular, there was only negligible correlation between the two methods for nodal degree, and the degree distribution differed substantially between both methods. We found that survey underreporting was a significant source of the difference between the two methods, and that this difference could be improved by excluding individuals who reported only a few contact partners. Additionally, survey reporting was more accurate for contacts of longer duration, and very inaccurate for contacts of shorter duration. Finally, female participants tended to report more accurately than male participants.
Online contact surveys and wireless sensor devices collected incongruent network data from an identical setting. This finding suggests that these two methods cannot be used interchangeably for informing models of infectious disease dynamics.</description><subject>Communicable diseases</subject><subject>Comparative analysis</subject><subject>Contact Tracing - instrumentation</subject><subject>Contact Tracing - methods</subject><subject>Data Collection - instrumentation</subject><subject>Data Collection - methods</subject><subject>Development and progression</subject><subject>Diaries</subject><subject>Disease control</subject><subject>Disease prevention</subject><subject>Faculty</subject><subject>Female</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Internet</subject><subject>Male</subject><subject>Measurement</subject><subject>Medical Records</subject><subject>Methods</subject><subject>Models, Statistical</subject><subject>Population</subject><subject>Respiratory Tract Infections - transmission</subject><subject>Schools</subject><subject>Secondary schools</subject><subject>Sensors</subject><subject>Social Behavior</subject><subject>Social Environment</subject><subject>Social networks</subject><subject>Students</subject><subject>Studies</subject><subject>Telemetry</subject><subject>United States</subject><subject>Wireless networks</subject><subject>Wireless sensor networks</subject><subject>Wireless Technology</subject><issn>1471-2334</issn><issn>1471-2334</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqNkktr3DAUhU1paB7tvqti6KZZONXDsqQuCiGkTSAQaEOhKyHJ1zMKtjSV7Dz-fWQyGWZKF0UCXY6-e4QupyjeY3SCsWg-45rjilBaVzhv2rwqDjbS6616vzhM6RYhzAWRb4p9UjeYSIQOit8X4b5MyzD1bZmCdbovB_fg_KI0UA6g0xSh_VLaMKx0nOV7MJXRCTI-xTt4LLXPJfgU4lofYFyGNr0t9jrdJ3i3Po-Km2_nN2cX1dX198uz06vKMibHiktNtcRNZ5iwDdeoJkx0jEtpcC0oEDANaaEWxiBjoCMtry0xWiDLLdf0qPj6bLuazACtBT9G3atVdIOOjypop3ZvvFuqRbhTVIqaU54NPq0NYvgzQRrV4JKFvtcewpQU5ozWnAjSZPTjX-htmKLPv1OYYYY4omiLWugelPNdyO_a2VSdMioZz6DI1Mk_qLxaGJwNHjqX9Z2G452GzIzwMC70lJK6_Pnj_9nrX7ssemZtDClF6Dazw0jNKVNzjNQco1ypnLLc8mF75puGl1jRJx57ypU</recordid><startdate>20140310</startdate><enddate>20140310</enddate><creator>Smieszek, Timo</creator><creator>Barclay, Victoria C</creator><creator>Seeni, Indulaxmi</creator><creator>Rainey, Jeanette J</creator><creator>Gao, Hongjiang</creator><creator>Uzicanin, Amra</creator><creator>Salathé, Marcel</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QL</scope><scope>7T2</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PIMPY</scope><scope>PJZUB</scope><scope>PKEHL</scope><scope>PPXIY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>5PM</scope></search><sort><creationdate>20140310</creationdate><title>How should social mixing be measured: comparing web-based survey and sensor-based methods</title><author>Smieszek, Timo ; Barclay, Victoria C ; Seeni, Indulaxmi ; Rainey, Jeanette J ; Gao, Hongjiang ; Uzicanin, Amra ; Salathé, Marcel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c559t-79a3a916fb58c67a04258f5799b1483e2eb62de48bb0bbef2d74c2ba80c7c7a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Communicable diseases</topic><topic>Comparative analysis</topic><topic>Contact Tracing - 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More recently, technological advances have permitted the use of wireless sensor devices, which can be worn by individuals interacting in a particular social context to record high resolution mixing patterns. To date, a direct comparison of these two different methods for collecting contact data has not been performed.
We studied the contact network at a United States high school in the spring of 2012. All school members (i.e., students, teachers, and other staff) were invited to wear wireless sensor devices for a single school day, and asked to remember and report the name and duration of all of their close proximity conversational contacts for that day in an online contact survey. We compared the two methods in terms of the resulting network densities, nodal degrees, and degree distributions. We also assessed the correspondence between the methods at the dyadic and individual levels.
We found limited congruence in recorded contact data between the online contact survey and wireless sensors. In particular, there was only negligible correlation between the two methods for nodal degree, and the degree distribution differed substantially between both methods. We found that survey underreporting was a significant source of the difference between the two methods, and that this difference could be improved by excluding individuals who reported only a few contact partners. Additionally, survey reporting was more accurate for contacts of longer duration, and very inaccurate for contacts of shorter duration. Finally, female participants tended to report more accurately than male participants.
Online contact surveys and wireless sensor devices collected incongruent network data from an identical setting. This finding suggests that these two methods cannot be used interchangeably for informing models of infectious disease dynamics.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>24612900</pmid><doi>10.1186/1471-2334-14-136</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Communicable diseases Comparative analysis Contact Tracing - instrumentation Contact Tracing - methods Data Collection - instrumentation Data Collection - methods Development and progression Diaries Disease control Disease prevention Faculty Female Health aspects Humans Internet Male Measurement Medical Records Methods Models, Statistical Population Respiratory Tract Infections - transmission Schools Secondary schools Sensors Social Behavior Social Environment Social networks Students Studies Telemetry United States Wireless networks Wireless sensor networks Wireless Technology |
title | How should social mixing be measured: comparing web-based survey and sensor-based methods |
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