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Transmission of one predicts another: Apathogenic proxies for transmission dynamics of a fatal virus
bioRxiv - Ecology Pub Date : 2021-10-14 , DOI: 10.1101/2021.01.09.426055
Marie L.J. Gilbertson , Nicholas M. Fountain-Jones , Jennifer L. Malmberg , Roderick B. Gagne , Justin S. Lee , Simona Kraberger , Sarah Kechejian , Raegan Petch , Elliott Chiu , Dave Onorato , Mark W. Cunningham , Kevin R. Crooks , W. Chris Funk , Scott Carver , Sue VandeWoude , Kimberly VanderWaal , Meggan E. Craft

Identifying drivers of transmission prior to an epidemic—especially of an emerging pathogen—is a formidable challenge for proactive disease management efforts. We tested a novel approach in the Florida panther, hypothesizing that apathogenic feline immunodeficiency virus (FIV) transmission could predict transmission dynamics for pathogenic feline leukemia virus (FeLV). We derived a transmission network using FIV whole genome sequences, and used exponential random graph models to determine drivers structuring this network. We used these drivers to predict FeLV transmission pathways among panthers and compared predicted outbreak dynamics against empirical FeLV outbreak data. FIV transmission was primarily driven by panther age class and distances between panther home range centroids. Prospective FIV-based modeling predicted FeLV dynamics at least as well as simpler, often retrospective approaches, with evidence that FIV-based predictions captured the spatial structuring of the observed FeLV outbreak. Our finding that an apathogenic agent can predict transmission of an analogously transmitted pathogen is an innovative approach that warrants testing in other host-pathogen systems to determine generalizability. Use of such apathogenic agents holds promise for improving predictions of pathogen transmission in novel host populations, and could thereby provide new strategies for proactive pathogen management in human and animal systems.

中文翻译:

一种传播预示着另一种传播:致命病毒传播动力学的非致病性代理

在流行之前确定传播的驱动因素——尤其是新出现的病原体——是主动疾病管理工作的一项艰巨挑战。我们在佛罗里达黑豹中测试了一种新方法,假设无致病性猫科动物免疫缺陷病毒 (FIV) 传播可以预测致病性猫科动物白血病病毒 (FeLV) 的传播动态。我们使用 FIV 全基因组序列推导出传输网络,并使用指数随机图模型来确定构建该网络的驱动因素。我们使用这些驱动因素来预测黑豹之间的 FeLV 传播途径,并将预测的爆发动态与经验性 FeLV 爆发数据进行比较。FIV 传播主要由黑豹年龄等级和黑豹家庭范围质心之间的距离驱动。基于 FIV 的前瞻性建模预测 FeLV 动力学至少与更简单、通常是回顾性的方法一样,有证据表明基于 FIV 的预测捕获了观察到的 FeLV 爆发的空间结构。我们发现,一种无病原体病原体可以预测类似传播病原体的传播,这是一种创新方法,需要在其他宿主-病原体系统中进行测试以确定普遍性。使用此类非病原体制剂有望改善对新宿主种群中病原体传播的预测,从而为人类和动物系统中的主动病原体管理提供新的策略。我们发现,一种无病原体病原体可以预测类似传播病原体的传播,这是一种创新方法,需要在其他宿主-病原体系统中进行测试以确定普遍性。使用此类非病原体制剂有望改善对新宿主种群中病原体传播的预测,从而为人类和动物系统中的主动病原体管理提供新的策略。我们发现,一种无病原体病原体可以预测类似传播病原体的传播,这是一种创新方法,需要在其他宿主-病原体系统中进行测试以确定普遍性。使用此类非病原体制剂有望改善对新宿主种群中病原体传播的预测,从而为人类和动物系统中的主动病原体管理提供新的策略。
更新日期:2021-10-17
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