References
BAJARDI, P. et al. Optimizing surveillance for livestock disease spreading through animal movements. Journal of The Royal Society Interface , v. 9, n. 76, p. 2814–2825, 7 nov. 2012. Disponível em: <http://rsif.royalsocietypublishing.org/content/early/2012/06/21/rsif.2012.0289.abstract>.
BORGATTI, S. P. Identifying sets of key players in a social network.Computational and Mathematical Organization Theory , v. 12, n. 1, p. 21–34, abr. 2006. Disponível em: <https://doi.org/10.1007/s10588-006-7084-x>.
BRIN, S.; PAGE, L. The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems , v. 30, n. 1–7, p. 107–117, abr. 1998. Disponível em: <http://dx.doi.org/10.1016/S0169-7552(98)00110-X>.
BÜTTNER, K. et al. Efficient Interruption of Infection Chains by Targeted Removal of Central Holdings in an Animal Trade Network.PLoS ONE , v. 8, n. 9, p. e74292, 2013. Disponível em: <https://doi.org/10.1371/journal.pone.0074292>.
BÜTTNER, K.; SALAU, J.; KRIETER, J. Quality assessment of static aggregation compared to the temporal approach based on a pig trade network in Northern Germany. Preventive Veterinary Medicine , v. 129, p. 1–8, jul. 2016. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0167587716301350>.
CHATERS, G. L. et al. Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies. Philosophical Transactions of the Royal Society B: Biological Sciences , v. 374, n. 1776, p. 20180264, 8 jul. 2019. Disponível em: <https://doi.org/10.1098/rstb.2018.0264>.
CHRISTLEY, R. M. et al. Infection in Social Networks: Using Network Analysis to Identify High-Risk Individuals. American Journal of Epidemiology , v. 162, n. 10, p. 1024–1031, 15 nov. 2005. Disponível em: <http://www.ncbi.nlm.nih.gov/pubmed/16177140>.
EMBRAPA. Empresa Brasileira de Pesquisa Agropecuária . Disponível em: <https://www.embrapa.br/suinos-e-aves/cias/estatisticas/suinos/brasil>. Acesso em: 3 jul. 2019.
FIELDING, H. R. et al. Contact chains of cattle farms in Great Britain.Royal Society Open Science , v. 6, n. 2, p. 180719, 28 fev. 2019. Disponível em: <doi.org/10.1098/rsos.180719>.
FREEMAN, L. C. Centrality in social networks conceptual clarification.Social Networks , v. 1, n. 3, p. 215–239, jan. 1978. Disponível em: <http://www.sciencedirect.com/science/article/pii/0378873378900217>.
GOLDING, with M. Adobe Illustrator CS5 : for web and interactive design Ventura, CA : Lynda.com, [2010] ©2010, , 2017. . Disponível em: <https://search.library.wisc.edu/catalog/9910101663502121>.
GORSICH, E. E. et al. Mapping U.S. cattle shipment networks: Spatial and temporal patterns of trade communities from 2009 to 2011.Preventive Veterinary Medicine , v. 134, n. Supplement C, p. 82–91, nov. 2016. Disponível em: <http://www.sciencedirect.com/science/article/pii/S016758771630410X>.
GRANOVETTER, M. S. The Strength of Weak Ties. American Journal of Sociology , v. 78, n. 6, p. 1360–1380, 1973. Disponível em: <http://www.jstor.org/stable/2776392>.
GRISI-FILHO, J. H. H. et al. Detecting livestock production zones.Preventive Veterinary Medicine , v. 110, n. 3–4, p. 304–311, 1 jul. 2013. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0167587713000044>.
GU, Z. et al. circlize implements and enhances circular visualization in R. Bioinformatics , v. 30, n. 19, p. 2811–2812, 1 out. 2014. Disponível em: <http://dx.doi.org/10.1093/bioinformatics/btu393>.
HOLME, P.; SARAMÄKI, J. Temporal networks. Physics Reports , v. 519, n. 3, p. 97–125, out. 2012. Disponível em: <https://linkinghub.elsevier.com/retrieve/pii/S0370157312000841>.
KEITT, T. et al. rgdal: Bindings for the Geospatial Data Abstraction Library , 1 jan. 2018. . Disponível em: <https://cran.r-project.org/package=rgdal>.
KNIFIC, T. et al. Implications of Cattle Trade for the Spread and Control of Infectious Diseases in Slovenia Frontiers in Veterinary Science , 2020. . Disponível em: <https://www.frontiersin.org/article/10.3389/fvets.2019.00454>.
KONSCHAKE, M. et al. On the Robustness of In- and Out-Components in a Temporal Network. PLoS ONE , v. 8, n. 2, p. e55223, 6 fev. 2013. Disponível em: <https://dx.plos.org/10.1371/journal.pone.0055223>.
LEBL, K. et al. Impact of Network Activity on the Spread of Infectious Diseases through the German Pig Trade Network. Frontiers in Veterinary Science , v. 3, n. June, p. 48, 2016. Disponível em: <http://journal.frontiersin.org/Article/10.3389/fvets.2016.00048/abstract>.
LENTZ, H. H. K. et al. Trade communities and their spatial patterns in the German pork production network. Preventive Veterinary Medicine , v. 98, n. 2–3, p. 176–181, fev. 2011. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0167587710002965>.
LENTZ, H. H. K. et al. Disease Spread through Animal Movements: A Static and Temporal Network Analysis of Pig Trade in Germany. PLoS ONE , v. 11, n. 5, p. e0155196, 6 maio 2016. Disponível em: <http://dx.doi.org/10.1371%2Fjournal.pone.0155196>.
LENTZ, H. H. K.; SELHORST, T.; SOKOLOV, I. M. Unfolding Accessibility Provides a Macroscopic Approach to Temporal Networks. Physical Review Letters , v. 110, n. 11, p. 118701, 11 mar. 2013. Disponível em: <https://link.aps.org/doi/10.1103/PhysRevLett.110.118701>.
MACHADO, G. et al. Quantifying the dynamics of pig movements improves targeted disease surveillance and control plans. Transboundary and Emerging Diseases , p. tbed.13841, 4 out. 2020. Disponível em: <https://onlinelibrary.wiley.com/doi/10.1111/tbed.13841>.
MAPA. Caracterização dos sistemas produtivos brasileiros . Disponível em: <http://www.agricultura.gov.br/assuntos/sanidade-animal-e-vegetal/saude-animal/programas-de-saude-animal/febre-aftosa/pnefa-2017-2026/arquivos/4_analise_distribuicao-espacial_usp_2.pdf>. Acesso em: 13 jul. 2018.
MARQUETOUX, N. et al. Using social network analysis to inform disease control interventions. Preventive Veterinary Medicine , v. 126, p. 94–104, abr. 2016. Disponível em: <https://linkinghub.elsevier.com/retrieve/pii/S0167587716300393>.
MOSLONKA-LEFEBVRE, M. et al. Market analyses of livestock trade networks to inform the prevention of joint economic and epidemiological risks.Journal of the Royal Society Interface , v. 13, n. 116, p. 20151099, 22 mar. 2016. Disponível em: <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4843675/>.
MOTTA, P. et al. Implications of the cattle trade network in Cameroon for regional disease prevention and control. Scientific Reports , v. 7, n. 1, p. 43932, 7 abr. 2017. Disponível em: <http://dx.doi.org/10.1038/srep43932>.
MWEU, M. M. et al. Temporal characterisation of the network of Danish cattle movements and its implication for disease control: 2000–2009.Preventive Veterinary Medicine , v. 110, n. 3–4, p. 379–387, jul. 2013. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0167587713000640>.
NEPUSZ, G. C. and T. The igraph software package for complex network research. InterJournal , v. Complex Sy, p. 1695, 2006. Disponível em: <http://igraph.org>.
NÖREMARK, M. et al. Network analysis of cattle and pig movements in Sweden: Measures relevant for disease control and risk based surveillance. Preventive Veterinary Medicine , v. 99, n. 2, p. 78–90, 2011. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0167587711000043>.
NÖREMARK, M.; WIDGREN, S. EpiContactTrace: an R-package for contact tracing during livestock disease outbreaks and for risk-based surveillance. BMC Veterinary Research , v. 10, n. 1, p. 71, 2014. Disponível em: <https://doi.org/10.1186/1746-6148-10-71>.
O’HARA, K. et al. Network Analysis of Swine Shipments in China: The First Step to Inform Disease Surveillance and Risk Mitigation Strategies. Frontiers in Veterinary Science , v. 7, p. 189, abr. 2020.
OIE. Terrestrial Animal Health Code .
PAYEN, A.; TABOURIER, L.; LATAPY, M. Spreading dynamics in a cattle trade network: Size, speed, typical profile and consequences on epidemic control strategies. PLOS ONE , v. 14, n. 6, p. e0217972, 10 jun. 2019. Disponível em: <https://doi.org/10.1371/journal.pone.0217972>.
PEBESMA, E. Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal , v. 10, n. 1, p. 439, 2018. Disponível em: <https://journal.r-project.org/archive/2018/RJ-2018-009/index.html>.
R CORE TEAM. R: A language and environment for statistical computing Vienna, Austria, AustriaR fundation for Statistical Computing, , 2017. . Disponível em: <https://www.r-project.org>.
SCHULZ, J. et al. Network analysis of pig movements: Loyalty patterns and contact chains of different holding types in Denmark. PLOS ONE , v. 12, n. 6, p. e0179915, 29 jun. 2017. Disponível em: <https://doi.org/10.1371/journal.pone.0179915>.
STERCHI, M. et al. The pig transport network in Switzerland: Structure, patterns, and implications for the transmission of infectious diseases between animal holdings. PLOS ONE , v. 14, n. 5, p. e0217974, 31 maio 2019. Disponível em: <https://doi.org/10.1371/journal.pone.0217974>.
VALDANO, E. et al. Predicting Epidemic Risk from Past Temporal Contact Data. PLOS Computational Biology , v. 11, n. 3, p. e1004152, 12 mar. 2015. Disponível em: <https://doi.org/10.1371/journal.pcbi.1004152>.
VANDERWAAL, K. et al. Evaluating empirical contact networks as potential transmission pathways for infectious diseases. Journal of The Royal Society Interface , v. 13, n. 121, p. 20160166, 3 ago. 2016a. Disponível em: <http://rsif.royalsocietypublishing.org/lookup/doi/10.1098/rsif.2016.0166>.
VANDERWAAL, K. et al. Contrasting animal movement and spatial connectivity networks in shaping transmission pathways of a genetically diverse virus. Preventive Veterinary Medicine , v. 178, p. 104977, maio 2020.
VANDERWAAL, K. L. et al. Network analysis of cattle movements in Uruguay: Quantifying heterogeneity for risk-based disease surveillance and control. Preventive Veterinary Medicine , v. 123, p. 12–22, 1 jan. 2016b. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0167587715300945>.
VIDONDO, B.; VOELKL, B. Dynamic network measures reveal the impact of cattle markets and alpine summering on the risk of epidemic outbreaks in the Swiss cattle population. BMC Veterinary Research , v. 14, n. 1, p. 88, 13 dez. 2018. Disponível em: <https://doi.org/10.1186/s12917-018-1406-3>.
WASSERMAN, S.; FAUST, K. Social Network Analysis: Methods and Applications . [s.l.] Cambridge University Press, 1994.
WATTS, D. J.; STROGATZ, S. H. Collective dynamics of ‘small-world’ networks. Nature , v. 393, n. 6684, p. 440–442, jun. 1998. Disponível em: <https://doi.org/10.1038/30918>.