Buhnerkempe Michael G, Tildesley Michael J, Lindström Tom, Grear Daniel A, Portacci Katie, Miller Ryan S, Lombard Jason E, Werkman Marleen, Keeling Matt J, Wennergren Uno, Webb Colleen T
Department of Biology, Colorado State University, Fort Collins, Colorado, United States of America.
Center for Complexity Science, Mathematics Institute, University of Warwick, Coventry, United Kingdom.
PLoS One. 2014 Mar 26;9(3):e91724. doi: 10.1371/journal.pone.0091724. eCollection 2014.
Globalization has increased the potential for the introduction and spread of novel pathogens over large spatial scales necessitating continental-scale disease models to guide emergency preparedness. Livestock disease spread models, such as those for the 2001 foot-and-mouth disease (FMD) epidemic in the United Kingdom, represent some of the best case studies of large-scale disease spread. However, generalization of these models to explore disease outcomes in other systems, such as the United States's cattle industry, has been hampered by differences in system size and complexity and the absence of suitable livestock movement data. Here, a unique database of US cattle shipments allows estimation of synthetic movement networks that inform a near-continental scale disease model of a potential FMD-like (i.e., rapidly spreading) epidemic in US cattle. The largest epidemics may affect over one-third of the US and 120,000 cattle premises, but cattle movement restrictions from infected counties, as opposed to national movement moratoriums, are found to effectively contain outbreaks. Slow detection or weak compliance may necessitate more severe state-level bans for similar control. Such results highlight the role of large-scale disease models in emergency preparedness, particularly for systems lacking comprehensive movement and outbreak data, and the need to rapidly implement multi-scale contingency plans during a potential US outbreak.
全球化增加了新病原体在大空间尺度上引入和传播的可能性,这就需要大陆尺度的疾病模型来指导应急准备工作。牲畜疾病传播模型,比如针对2001年英国口蹄疫疫情的模型,是大规模疾病传播的一些最佳案例研究。然而,将这些模型推广到其他系统(如美国养牛业)以探索疾病结果时,受到系统规模和复杂性差异以及缺乏合适的牲畜移动数据的阻碍。在此,一个独特的美国牛运输数据库使得合成移动网络得以估算,该网络为美国牛群中类似口蹄疫(即快速传播)的潜在疫情的近大陆尺度疾病模型提供信息。最大规模的疫情可能会影响超过三分之一的美国地区以及120,000个养牛场,但与全国性移动禁令相反,发现来自感染县的牛移动限制能有效控制疫情爆发。检测缓慢或合规性差可能需要在州一级实施更严格的禁令以进行类似控制。这些结果凸显了大规模疾病模型在应急准备中的作用,特别是对于缺乏全面移动和疫情数据的系统,以及在美国潜在疫情期间迅速实施多尺度应急计划的必要性。