@article {Sah169573, author = {Pratha Sah and Shweta Bansal}, title = {Identifying the dynamic contact network of infectious disease spread}, elocation-id = {169573}, year = {2017}, doi = {10.1101/169573}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Pathogen propagation is a fundamental process that takes place through host contact networks. While it has been possible to characterize contact networks of several human infectious diseases (e.g., sexual contacts for HIV, physical proximity for measles), logistical difficulties and the high costs of data collection makes network modeling of infectious diseases in animal populations particularly difficult. In addition, limited knowledge about how pathogens transmit precludes an accurate definition of network edges required for constructing networks of disease transmission. We developed a new tool, INoDS (Identifying Networks of infectious Disease Spread), that utilizes Bayesian inference to provide evidence towards the underlying contact network of an infectious disease spread. We show that the tool accurately identifies the underlying contact network even when the networks are partially sampled and information on disease spread is incomplete. We next demonstrate the applicability of the tool in two real animal populations: bumble bees and Australian sleepy lizards. The performance of INoDs in synthetic and complex empirical systems highlights its role as an alternative approach to laboratory transmission experiments, in providing epidemiological insights into novel and less known host-pathogen systems, and overcoming common data-collection constraints.}, URL = {https://www.biorxiv.org/content/early/2017/07/28/169573}, eprint = {https://www.biorxiv.org/content/early/2017/07/28/169573.full.pdf}, journal = {bioRxiv} }