Thakur Krishna K, Sanchez Javier, Hurnik Daniel, Poljak Zvonimir, Opps Sheldon, Revie Crawford W
Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PEI, Canada.
Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PEI, Canada.
Vet Microbiol. 2015 Nov 18;180(3-4):212-22. doi: 10.1016/j.vetmic.2015.09.010. Epub 2015 Sep 21.
Contact structure within a population can significantly affect the outcomes of infectious disease spread models. The objective of this study was to develop a network based simulation model for the between-farm spread of porcine reproductive and respiratory syndrome virus to assess the impact of contact structure on between-farm transmission of PRRS virus. For these farm level models, a hypothetical population of 500 swine farms following a multistage production system was used. The contact rates between farms were based on a study analyzing movement of pigs in Canada, while disease spread parameters were extracted from published literature. Eighteen distinct scenarios were designed and simulated by varying the mode of transmission (direct versus direct and indirect contact), type of index herd (farrowing, nursery and finishing), and the presumed network structures among swine farms (random, scale-free and small-world). PRRS virus was seeded in a randomly selected farm and 500 iterations of each scenario were simulated for 52 weeks. The median epidemic size by the end of the simulated period and percentage die-out for each scenario, were the key outcomes captured. Scenarios with scale-free network models resulted in the largest epidemic sizes, while scenarios with random and small-world network models resulted in smaller and similar epidemic sizes. Similarly, stochastic die-out percentage was least for scenarios with scale-free networks followed by random and small-world networks. Findings of the study indicated that incorporating network structures among the swine farms had a considerable impact on the spread of PRRS virus, highlighting the importance of understanding and incorporating realistic contact structures when developing infectious disease spread models for similar populations.
种群内部的接触结构会显著影响传染病传播模型的结果。本研究的目的是开发一个基于网络的模拟模型，用于猪繁殖与呼吸综合征病毒在农场间的传播，以评估接触结构对PRRS病毒农场间传播的影响。对于这些农场层面的模型，使用了一个假设的、遵循多阶段生产系统的500个猪场的种群。农场间的接触率基于一项分析加拿大猪只流动情况的研究，而疾病传播参数则从已发表的文献中提取。通过改变传播方式（直接传播与直接和间接接触）、指数猪场类型（分娩、保育和育肥）以及猪场间假定的网络结构（随机、无标度和小世界），设计并模拟了18种不同的情景。PRRS病毒被接种到一个随机选择的农场，并对每个情景进行500次迭代模拟，持续52周。模拟期结束时的疫情规模中位数以及每个情景的灭绝百分比是关键的结果指标。无标度网络模型的情景导致了最大的疫情规模，而随机和小世界网络模型的情景导致了较小且相似的疫情规模。同样，无标度网络情景的随机灭绝百分比最低，其次是随机和小世界网络。该研究结果表明，纳入猪场间的网络结构对PRRS病毒的传播有相当大的影响，突出了在为类似种群开发传染病传播模型时理解和纳入现实接触结构的重要性。
