Comparison of social networks derived from ecological data: implications for inferring infectious disease dynamics Export

@article{citeulike:5359329, abstract = {1. Social network analyses tend to focus on human interactions. However, there is a burgeoning interest in applying graph theory to ecological data from animal populations. Here we show how radio-tracking and capture2013mark2013recapture data collated from wild rodent populations can be used to generate contact networks. 2. Both radio-tracking and capture2013mark2013recapture were undertaken simultaneously. Contact networks were derived and the following statistics estimated: mean-contact rate, edge distribution, connectance and centrality. 3. Capture2013mark2013recapture networks produced more informative and complete networks when the rodent density was high and radio-tracking produced more informative networks when the density was low. Different data collection methods provide more data when certain ecological characteristics of the population prevail. 4. Both sets of data produced networks with comparable edge (contact) distributions that were best described by a negative binomial distribution. Connectance and closeness were statistically different between the two data sets. Only betweenness was comparable. The differences between the networks have important consequences for the transmission of infectious diseases. Care should be taken when extrapolating social networks to transmission networks for inferring disease dynamics.}, address = {Center for Infectious Disease Dynamics, 208 Mueller Laboratory, Penn State University, State College, PA 16803, USA;; Edmund Mach Foundation, Research and Innovation Centre, Via Mach 1, 38010 San Michele allAdige, Trentino, Italy}, author = {Perkins, Sarah E. and Cagnacci, Francesca and Stradiotto, Anna and Arnoldi, Daniele and Hudson, Peter J.}, citeulike-article-id = {5359329}, citeulike-linkout-0 = {http://dx.doi.org/10.1111/j.1365-2656.2009.01557.x}, citeulike-linkout-1 = {http://www3.interscience.wiley.com/cgi-bin/abstract/122399063/ABSTRACT}, doi = {10.1111/j.1365-2656.2009.01557.x}, issn = {1365-2656}, journal = {Journal of Animal Ecology}, keywords = {capture-mark-recapture, radio-tracking, rodent, social-interactions, social-network}, number = {5}, pages = {1015--1022}, posted-at = {2009-08-04 15:54:26}, priority = {2}, title = {Comparison of social networks derived from ecological data: implications for inferring infectious disease dynamics}, url = {http://dx.doi.org/10.1111/j.1365-2656.2009.01557.x}, volume = {78}, year = {2009} }

TY - JOUR ID - citeulike:5359329 L3 - citeulike-article-id:5359329 N2 - 1. Social network analyses tend to focus on human interactions. However, there is a burgeoning interest in applying graph theory to ecological data from animal populations. Here we show how radio-tracking and capture2013mark2013recapture data collated from wild rodent populations can be used to generate contact networks. 2. Both radio-tracking and capture2013mark2013recapture were undertaken simultaneously. Contact networks were derived and the following statistics estimated: mean-contact rate, edge distribution, connectance and centrality. 3. Capture2013mark2013recapture networks produced more informative and complete networks when the rodent density was high and radio-tracking produced more informative networks when the density was low. Different data collection methods provide more data when certain ecological characteristics of the population prevail. 4. Both sets of data produced networks with comparable edge (contact) distributions that were best described by a negative binomial distribution. Connectance and closeness were statistically different between the two data sets. Only betweenness was comparable. The differences between the networks have important consequences for the transmission of infectious diseases. Care should be taken when extrapolating social networks to transmission networks for inferring disease dynamics. IS - 5 JF - Journal of Animal Ecology SN - 1365-2656 AD - Center for Infectious Disease Dynamics, 208 Mueller Laboratory, Penn State University, State College, PA 16803, USA;; Edmund Mach Foundation, Research and Innovation Centre, Via Mach 1, 38010 San Michele allAdige, Trentino, Italy EP - 1022 TI - Comparison of social networks derived from ecological data: implications for inferring infectious disease dynamics VL - 78 SP - 1015 KW - capture-mark-recapture KW - radio-tracking KW - rodent KW - social-interactions KW - social-network AU - Perkins, Sarah AU - Cagnacci, Francesca AU - Stradiotto, Anna AU - Arnoldi, Daniele AU - Hudson, Peter PY - 2009/// UR - http://dx.doi.org/10.1111/j.1365-2656.2009.01557.x ER -