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

Read, Jonathan M.; Eames, Ken T. D.; Edmunds, W. John

doi:10.1098/rsif.2008.0013

Cited by 325 publications

(404 citation statements)

References 27 publications

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“…All networks were constructed using weighted data (that is, I considered relative amounts of each interaction rather than simply recording the presence or absence of an interaction). For infections such as M. bovis that require close contact for transmission to occur, both the regularity of encounters and the weight of interactions are important (Read et al 2008). For each interaction type, a single network containing all meerkats was constructed and individual network measures for each meerkat were calculated.…”

Section: Methodsmentioning

confidence: 99%

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Who infects whom? Social networks and tuberculosis transmission in wild meerkats

2009

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Transmission of infectious diseases is strongly influenced by who contacts whom. Despite the global distribution of tuberculosis (TB) in free-living wild mammal populations, little is known of the mechanisms of social transmission of Mycobacterium bovis between individuals. Here, I use a network approach to examine for correlations between five distinct types of intra-and intergroup social interaction and changes in TB status of 110 wild meerkats (Suricata suricatta) in five social groups over two years. Contrary to predictions, the most socially interactive animals were not at highest risk of acquiring infection, indicating that in addition to contact frequency, the type and direction of interactions must be considered when quantifying disease risk. Within social groups, meerkats that groomed others most were more likely to become infected than individuals who received high levels of grooming. Conversely, receiving, but not initiating, aggression was associated with M. bovis infection. Incidence of intergroup roving by male meerkats was correlated with the rovers themselves subsequently testing TB-positive, suggesting a possible route for transmission of infection between social groups. Exposure time was less important than these social interactions in influencing TB risk. This study represents a novel application of social network analysis using empirical data to elucidate the role of specific interactions in the transmission of an infectious disease in a free-living wild animal population.

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Section: Methodsmentioning

confidence: 99%

“…The effects of network structure on disease dynamics is an important and developing area of research (Corner et al 2003a;Keeling 2005;Read et al 2008;Perkins et al 2009). For social animals, an individual's position in a group may influence risk of infection.…”

Section: Introductionmentioning

confidence: 99%

Who infects whom? Social networks and tuberculosis transmission in wild meerkats

2009

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“…In the study villages many homes were in compounds that shared a courtyard which likely resulted in numerous interactions of children and adults. The extent of social interaction and mixing within the compound seemed the most important attributes for the purposes of this study, thus all of those within a compound were considered as one household for randomization [10,11].…”

Section: Study Site and Populationmentioning

confidence: 99%

Design and initiation of a study to assess the direct and indirect effects of influenza vaccine given to children in rural India

Sullender

Fowler

Krishnan

et al. 2012

Vaccine

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The burden of disease due to influenza is not well characterized for children in developing countries and the effectiveness of available influenza vaccines in lower resource settings has not been established. We initiated a prospective, longitudinal, phase IV, household-randomized, controlled, observer-blinded three year study (2009)(2010)(2011) in a rural community of India to measure the total and indirect household protective effects of immunizing children ages 6 months through 10 years with seasonal inactivated trivalent influenza vaccine (TIV) or a control vaccine (n = 3697). Active weekly surveillance was conducted year round with home visits for identification of febrile acute respiratory illness (FARI) conducted for all vaccine recipients and household members (n = 18,220). Nasal and throat swabs were collected from each FARI episode for influenza detection by real-time reverse transcription polymerase chain reaction. The primary outcome was reduction in laboratory confirmed influenza infections in the influenza vaccine versus control vaccine group, with secondary outcome assessing indirect effects among the entire study population. This report describes the study site, cluster study design, choice of study and control vaccines, and the initial enrollment in the study.

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“…The results show that there are differences in the properties of the recorded and utilised to establish the length and strength of the contacts [27,28,29,30]. In 338 modelling the diseases of animals this is harder to achieve but observation has 339 been used in the past [15].…”

mentioning

confidence: 99%

The influence of empirical contact networks on modelling diseases in cattle

Duncan

Gunn²,

Lewis

et al. 2012

Epidemics

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We present two stochastic models of the passage of an SEIR (susceptible-latent-infectedresistant) disease through herds of cattle. One model is based on a contact network constructed via continuously recorded interaction data from two herds of cattle, the other, a matching network constructed using the principles of mass-action mixing. The recorded contact data were produced by attaching proximity data loggers to two separate herds of cattle during two separate recording periods. The network constructed using the principles of mass-action mixing uses the same number of contacts as the recorded network but distributes them randomly amongst the animals. The recorded networks had a greater number of repeated contacts, lower closeness and clustering scores and greater average path length than the mass-action networks. A lower proportion of simulations of the recorded network produce any disease spread when compared to those simulations of the mass-action network and, of those that did, fewer infected animals were predicted. For all parameter values tested, within the sensitivity analysis, similar differences were found between the recorded and mass-action network models. AbstractWe present two stochastic models of the passage of an SEIR (susceptible-latentinfected-resistant) disease through herds of cattle. One model is based on a contact network constructed via continuously recorded interaction data from two herds of cattle, the other, a matching network constructed using the principles of mass-action mixing. The recorded contact data were produced by attaching proximity data loggers to two separate herds of cattle during two separate recording periods. The network constructed using the principles of mass-action mixing uses the same number of contacts as the recorded network but distributes them randomly amongst the animals. The recorded networks had a greater number of repeated contacts, lower closeness and clustering scores and greater average path length than the mass-action networks. A lower proportion of simulations of the recorded network produce any disease spread when compared to those simulations of the mass-action network and, of those that did, fewer infected animals were predicted. For all parameter values tested, within the sensitivity analysis, similar differences were found between the recorded and mass-action network models.

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

Cited by 325 publications

References 27 publications

Who infects whom? Social networks and tuberculosis transmission in wild meerkats

Who infects whom? Social networks and tuberculosis transmission in wild meerkats

Design and initiation of a study to assess the direct and indirect effects of influenza vaccine given to children in rural India

The influence of empirical contact networks on modelling diseases in cattle

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