10.15145/6SMR-V589
Balasubramaniam, Krishna
Beisner, Brianne
Vandeleest, Jessica
Atwill, Rob
McCowan, Brenda
Data associated with Balasubramaniam, Beisner et al. (PeerJ, 2016):
"Social buffering and contact transmission: Network connections have
beneficial and detrimental effects on Shigella infection risk among
captive rhesus macaques"
DataONE
2016
Social networks
Infectious disease risk
Social buffering
contact-mediated transmission
nonhuman primate
Balasubramaniam, Krishna
2016-09-30T12:47:37+00:00
Dataset
42750
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
In human and animal societies, social connections are among the most
critical factors that may influence infectious disease risk. On the one
hand, being well-connected within a social network may increase an
individual's risk of infection via contact-mediated transmission. On
the other hand, connections also strengthen ties of social support and
thereby, may socially buffer individuals against infection risk. In two
groups of captive rhesus macaques, our study reveals that animals that
were socially buffered, i.e. had increased social network connections or
“friendships” via their grooming and huddling relationships, were more
resistant to infection from an enteric bacterial pathogen: Shigella. Yet
in a third group, we reveal that increased huddling connections and
aggressive interactions enhanced the likelihood of Shigella infection,
presumably via contact-mediated transmission. Our findings emerging from
an animal model biologically and behaviorally analogous to humans. They
pave the way for a more systematic delineation of the circumstances or
contexts (e.g. social group stability, living conditions,
pathogen-specific characteristics) under which social connections may
prove to be beneficial versus detrimental to infectious disease
acquisition and general health.
Behavioral observations to record social grooming, huddling, and
aggressive interactions were conducted on three outdoor captive groups of
rhesus macaques (N=299 subjects), each group was observed for 6 weeks. For
each macaque, social network metrics of grooming and huddling degree,
betweenness, and eigenvector centralities, and aggression inand out-degree
and strength, were all calculated using the STATNET and SNA packages in R.
Dominance ranks and dominance certainties were calculated from aggressive
interactions using the recently developed PERC package in R. From each
individual, two freshly collected fecal swabs at the end of the behavioral
observation periods were processed for the isolation and subsequent
biochemical characterization of the bacterial pathogen Shigella flexneri,
using previously standardized protocols. Each macaque was then deemed as
either 'infected' or 'uninfected', based on the
outcome of these biochemical assays. Data analyses testing the effects of
social network metrics on the outcome of Shigella infection were carried
out using an Information-Theoretical approach to construct generalized
linear mixed-effects models with a logit function (the LME4 and MUMIN
packages in R). Additional methodology is available in Balasubramaniam,
Beisner et al. (2016).