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评估罗非鱼湖病毒在养殖罗非鱼中的群体传播动态。

Assessing the population transmission dynamics of tilapia lake virus in farmed tilapia.

作者信息

Yang Ying-Fei, Lu Tien-Hsuan, Lin Hsing-Chieh, Chen Chi-Yun, Liao Chung-Min

机构信息

Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan, ROC.

出版信息

J Fish Dis. 2018 Sep;41(9):1439-1448. doi: 10.1111/jfd.12845. Epub 2018 Jul 12.

Abstract

A novel virus, tilapia lake virus (TiLV), has been identified as a key pathogen responsible for disease outbreak and mass mortality of farmed tilapia. We used a deterministic susceptible-infectious-mortality (SIM) model to derive key disease information appraised with published TiLV-induced cumulative mortality data. The relationship between tilapia mortality and TiLV exposure dosages was described by the Hill model. Furthermore, a disease control model was proposed to determine the status of controlled TiLV infection using a parsimonious control reproduction number (R )-control line criterion. Results showed that the key disease determinants of transmission rate and basic reproduction number (R ) could be derived. The median R estimate was 2.59 in a cohabitation setting with 2.6 × 10  TCID50 fish TiLV. The present R -control model can be employed to determine whether TiLV containment is feasible in an outbreak farm by quantifying the current level of transmission. The SIM model can then be applied to predict what additional control is required to manage R  < 1. We offer valuable tools for aquaculture engineers and public health scientists the mechanistic-based assessment that allows a more rigorous evaluation of different control strategies to reduce waterborne diseases in aquaculture farming systems.

摘要

一种新型病毒——罗非鱼湖病毒(TiLV),已被确认为导致养殖罗非鱼疾病暴发和大量死亡的关键病原体。我们使用确定性易感-感染-死亡(SIM)模型,根据已发表的TiLV诱导的累积死亡率数据得出关键疾病信息。罗非鱼死亡率与TiLV暴露剂量之间的关系用希尔模型描述。此外,还提出了一个疾病控制模型,以使用简约控制繁殖数(R)-控制线标准来确定TiLV感染的控制状态。结果表明,可以得出传播率和基本繁殖数(R)等关键疾病决定因素。在与2.6×10 TCID50鱼TiLV同居的环境中,R的中位数估计值为2.59。当前的R-控制模型可用于通过量化当前传播水平来确定在暴发养殖场控制TiLV是否可行。然后可以应用SIM模型来预测为使R<1还需要采取哪些额外的控制措施。我们为水产养殖工程师和公共卫生科学家提供了有价值的工具,这种基于机制的评估能够更严格地评估不同的控制策略,以减少水产养殖系统中的水传播疾病。

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