Literature DB >> 24100954

The impact of illness on social networks: implications for transmission and control of influenza.

Kim Van Kerckhove, Niel Hens, W John Edmunds, Ken T D Eames.   

Abstract

We expect social networks to change as a result of illness, but social contact data are generally collected from healthy persons. Here we quantified the impact of influenza-like illness on social mixing patterns. We analyzed the contact patterns of persons from England measured when they were symptomatic with influenza-like illness during the 2009 A/H1N1pdm influenza epidemic (2009-2010) and again 2 weeks later when they had recovered. Illness was associated with a reduction in the number of social contacts, particularly in settings outside the home, reducing the reproduction number to about one-quarter of the value it would otherwise have taken. We also observed a change in the age distribution of contacts. By comparing the expected age distribution of cases resulting from transmission by (a)symptomatic persons with incidence data, we estimated the contribution of both groups to transmission. Using this, we calculated the fraction of transmission resulting from (a)symptomatic persons, assuming equal duration of infectiousness. We estimated that 66% of transmission was attributable to persons with symptomatic disease (95% confidence interval: 0.23, 1.00). This has important implications for control: Treating symptomatic persons with antiviral agents or encouraging home isolation would be expected to have a major impact on transmission, particularly since the reproduction number for this strain was low.

Entities:  

Keywords:  R0 ratio; behavioral change; contact networks; disease transmission; influenza; social interaction

Mesh:

Year:  2013        PMID: 24100954      PMCID: PMC3842903          DOI: 10.1093/aje/kwt196

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  21 in total

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3.  The impact of school holidays on the social mixing patterns of school children.

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4.  Comparison of three methods for ascertainment of contact information relevant to respiratory pathogen transmission in encounter networks.

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Journal:  BMC Infect Dis       Date:  2010-06-10       Impact factor: 3.090

5.  Dynamics of person-to-person interactions from distributed RFID sensor networks.

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6.  Age-specific incidence of A/H1N1 2009 influenza infection in England from sequential antibody prevalence data using likelihood-based estimation.

Authors:  Marc Baguelin; Katja Hoschler; Elaine Stanford; Pauline Waight; Pia Hardelid; Nick Andrews; Elizabeth Miller
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Authors:  Elizabeth Miller; Katja Hoschler; Pia Hardelid; Elaine Stanford; Nick Andrews; Maria Zambon
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8.  Social contacts of school children and the transmission of respiratory-spread pathogens.

Authors:  R T Mikolajczyk; M K Akmatov; S Rastin; M Kretzschmar
Journal:  Epidemiol Infect       Date:  2007-07-18       Impact factor: 2.451

9.  Measured dynamic social contact patterns explain the spread of H1N1v influenza.

Authors:  Ken T D Eames; Natasha L Tilston; Ellen Brooks-Pollock; W John Edmunds
Journal:  PLoS Comput Biol       Date:  2012-03-08       Impact factor: 4.475

10.  Measuring social networks in British primary schools through scientific engagement.

Authors:  A J K Conlan; K T D Eames; J A Gage; J C von Kirchbach; J V Ross; R A Saenz; J R Gog
Journal:  Proc Biol Sci       Date:  2010-11-03       Impact factor: 5.349

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  43 in total

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Journal:  Sci Rep       Date:  2021-02-04       Impact factor: 4.379

Review 2.  Crossing the scale from within-host infection dynamics to between-host transmission fitness: a discussion of current assumptions and knowledge.

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Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2015-08-19       Impact factor: 6.237

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Authors:  T Alex Perkins; Valerie A Paz-Soldan; Steven T Stoddard; Amy C Morrison; Brett M Forshey; Kanya C Long; Eric S Halsey; Tadeusz J Kochel; John P Elder; Uriel Kitron; Thomas W Scott; Gonzalo M Vazquez-Prokopec
Journal:  Proc Biol Sci       Date:  2016-07-13       Impact factor: 5.349

Review 4.  Host behaviour-parasite feedback: an essential link between animal behaviour and disease ecology.

Authors:  Vanessa O Ezenwa; Elizabeth A Archie; Meggan E Craft; Dana M Hawley; Lynn B Martin; Janice Moore; Lauren White
Journal:  Proc Biol Sci       Date:  2016-04-13       Impact factor: 5.349

5.  Incorporating social contact data in spatio-temporal models for infectious disease spread.

Authors:  Sebastian Meyer; Leonhard Held
Journal:  Biostatistics       Date:  2017-04-01       Impact factor: 5.899

6.  Sideward contact tracing and the control of epidemics in large gatherings.

Authors:  Marco Mancastroppa; Andrea Guizzo; Claudio Castellano; Alessandro Vezzani; Raffaella Burioni
Journal:  J R Soc Interface       Date:  2022-05-11       Impact factor: 4.293

7.  Virulence-mediated infectiousness and activity trade-offs and their impact on transmission potential of influenza patients.

Authors:  Brian McKay; Mark Ebell; Ariella Perry Dale; Ye Shen; Andreas Handel
Journal:  Proc Biol Sci       Date:  2020-05-13       Impact factor: 5.349

8.  An amygdala circuit that suppresses social engagement.

Authors:  Changhyeon Ryu; Hyeseung Lee; Jeong-Tae Kwon; Alec Sheffield; Jingxuan Fan; Daniel H Cho; Shivani Bigler; Heather A Sullivan; Han Kyung Choe; Ian R Wickersham; Myriam Heiman; Gloria B Choi
Journal:  Nature       Date:  2021-03-31       Impact factor: 69.504

9.  Sick bats stay home alone: fruit bats practice social distancing when faced with an immunological challenge.

Authors:  Kelsey R Moreno; Maya Weinberg; Lee Harten; Valeria B Salinas Ramos; L Gerardo Herrera M; Gábor Á Czirják; Yossi Yovel
Journal:  Ann N Y Acad Sci       Date:  2021-04-19       Impact factor: 6.499

10.  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

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