Management of viral plant diseases can be improved by using models to predict disease spread. Potato yellow vein virus (PYVV) of the genus Crinivirus (Closteroviridae) is transmitted in a semi-persistent manner by the greenhouse whitefly Trialeurodes vaporariorum (Hemiptera: Aleyrodidae). Although several approaches exist for modeling insect population growth, modeling vector-born virus spread remains difficult because fundamental knowledge on the relationship between virus transmission and temperature is lacking for most vector transmitted viruses. To address this challenge, we initially developed a temperature-dependent phenology model for the whitefly vector using the Insect Life Cycle Modeling (ILCYM) software. In the present study, the effect of temperature on the efficiency of virus transmission by the whitefly was determined through controlled laboratory experiments at 8 constant temperatures in the range from 10 to 25 °C. The vector capacity to transmit the virus was highest at 15 °C (about 70 % probability of infection) but decreased radically as temperature deviated from this optimum temperature to <10 % at temperatures of 10 and 20 °C, respectively. The temperature-dependent probability of virus transmission by a single adult whitefly could be described by a nonlinear function, which was validated by transmission frequencies observed at fluctuating temperatures. This function combined with life table parameters calculated from previously established temperature-dependent phenology model for the vector provided a full temperature-responsive model for predicting PYVV spread potential and transmission probabilities. For spatial risk predictions, we devised two virus transmission risk indexes and tested their performance in correctly predicting virus presence/absence with field survey data. The best performing risk index was used to generate risk maps, which reflected well the current (real) occurrence of the virus but also predicted areas at high risk, where the virus has not previously been reported. One of them in western Panama was targeted for surveillance and resulted in identification of the virus in the country, where it was not previously known to occur. Simulated risk maps for the year 2050 revealed that climate change may significantly affect, the risk of distribution, generally reducing in tropical areas of the world, but increasing in the temperate regions.

通过使用模型来预测疾病传播，可以改进病毒性植物病害的管理。Crinivirus 属（梭状病毒科）的马铃薯黄脉病毒 (PYVV)由温室粉虱Trialeurodes vaporariorum以半持久性方式传播（半翅目：粉虱科）。尽管存在多种模拟昆虫种群增长的方法，但对媒介传播的病毒传播进行建模仍然很困难，因为大多数媒介传播病毒缺乏关于病毒传播与温度之间关系的基本知识。为了应对这一挑战，我们最初使用昆虫生命周期建模 (ILCYM) 软件为粉虱载体开发了一个温度相关物候模型。在本研究中，温度对粉虱病毒传播效率的影响是通过受控实验室实验在 10 至 25 °C 范围内的 8 个恒定温度下确定的。载体传播病毒的能力在 15 °C 时最高（感染概率约为 70%），但随着温度偏离此最佳温度而急剧下降，分别在 10 °C 和 20 °C 时降至 <10%。单个成年粉虱病毒传播的温度依赖性概率可以用非线性函数来描述，该函数通过在温度波动下观察到的传播频率进行验证。该函数与根据先前建立的矢量温度相关物候模型计算的生命表参数相结合，提供了一个完整的温度响应模型，用于预测 PYVV 传播潜力和传播概率。对于空间风险预测，我们设计了两个病毒传播风险指数，并通过实地调查数据测试了它们在正确预测病毒存在/不存在方面的性能。使用表现最佳的风险指数来生成风险地图，它很好地反映了当前（真实）病毒的发生情况，但也预测了以前未报告过病毒的高风险区域。其中一个在巴拿马西部成为监视目标，结果在该国发现了该病毒，而此前并不知道该病毒在该国发生。2050 年的模拟风险图显示，气候变化可能显着影响分布风险，在世界热带地区普遍降低，但在温带地区增加。这很好地反映了病毒当前的（真实）发生情况，但也预测了以前没有报告过病毒的高风险区域。其中一个在巴拿马西部成为监视目标，结果在该国发现了该病毒，而此前并不知道该病毒在该国发生。2050 年的模拟风险图显示，气候变化可能显着影响分布风险，在世界热带地区普遍降低，但在温带地区增加。这很好地反映了病毒当前的（真实）发生情况，但也预测了以前没有报告过病毒的高风险区域。其中一个在巴拿马西部成为监视目标，结果在该国发现了该病毒，而此前并不知道该病毒在该国发生。2050 年的模拟风险图显示，气候变化可能显着影响分布风险，在世界热带地区普遍降低，但在温带地区增加。