2015年，我在矢量生态学会上作了介绍，感叹预测的困难西尼罗病毒在良好的空间和时间尺度上的传输风险。到目前为止，尚无广泛使用且普遍接受的方法来预测北美最普遍的Arbovirus的传播风险，其中最好的方法可能是向量索引used in the State of California.

预测西尼罗河病毒的许多困难之一是由于其生态学的复杂性，尤其是可以充当该病毒宿主的鸟类种类。这些大多是passerine鸣禽在易感蚊子被喂食的可能性上有所不同。这种异质性来自病毒作和生存的差异（共同称为宿主能力），环境变量以及它们对蚊子的丰富性和吸引力。西尼罗河病毒感染的大多数模型都不包括这种异质性，只专注于一种或少数鸟类。克服这种复杂性似乎是棘手的，特别是考虑到所需的数据仅适用于少数物种。

Now, in arecent study摩根·凯恩（Morgan P.basic reproduction number(R₀).

They obtained county-level bird abundance data, using checklists fromeBird，由康奈尔（Cornell）鸟类学实验室运营的公民科学平台，以报告偏见。描述西尼罗河病毒滴度自感染以来的时间随时间变化以及所有鸟类物种每天的存活率如何随着时间的流逝而变化，用于估计该鸟类感染的新蚊子的预期数量。然后将其乘以每种被单个感染蚊子感染的每种物种的鸟类的预期数量。对于没有此类滴度剖面和生存数据的鸟类，作者使用phylogenetic imputationto obtain reasonable estimates. This method uses the phylogenetic relationship between species that we do have data for, in order to build a statistical model explaining how these traits vary across the phylogenetic tree. This model is then used to predict the titer profile and survival for the bird species that we don’t have empirical data for, based on their phylogenetic relationship to other birds, allowing for random error. There are many technical details in the paper, but to the credit of the authors, they did everything they could to thoroughly explain their methodology.

The authors used Texas as their test location due to the availability of large amounts of citizen science collected bird abundance data, as well as the large numbers of human WNV cases in the state. They predict reasonable estimates for the basic reproduction number of West Nile virus, in accordance with other studies. Predicted WNV transmission was highest in the Spring and late Summer, and lowest in the middle of Summer and during the Winter. These differences in this model are not driven by the observed seasonal differences in mosquito abundance, but are based on the non-linear temperature-dependence of viral titer in the mosquito salivary glands. There seemed to be a negative, but non-significant relationship between human population density and basic reproduction number, possibly due to altered bird community in more densely populated areas. Different ecoregions of Texas varied in their WNV transmission risk, due to different bird communities inhabiting those ecoregions.

本文的一项重要贡献是要全面关注许多不同来源的不确定性，这通常被忽略。正如作者强调的那样，忽略不确定性不仅使它看起来像我们在预测的结果中更确定，而且还可以通过称为现象来促进偏见的估计Jensen’s inequality.

While I am amazed by this paper, the authors make the limitations of their work very clear. One clear issue is that the mechanistic model assumes a single mosquito species, and a constant ratio of birds to mosquitoes. The authors advocate for extending their work by incorporating mosquito abundance.

The authors identified several species as important sinks as well as sources of infection, either diluting (e.g. mourning dove) or amplifying (e.g. northern cardinals) transmission. One curious result was that American Robins, which are considered an important reservoir host of West Nile virus, was not listed as an important contributor to West Nile virus transmission. However, the authors highlighted that bird communities in Texas are different from those in which American Robins were found to be important.

Kain and Bolker offer their manuscript as a first step towards developing better models for predicting West Nile virus transmission. Their paper is accompanied by arepository on Github其中包含运行模型和分析所需的所有代码，这些代码已被充分记录。该模型可以应用于在美国和欧洲，在德国和意大利有足够的数据。

预测西尼罗河病毒的传播一直是我的个人任务，尤其是在我自己在华盛顿东部的社区中。去年夏天，我收集了对WNV呈阳性的Culex蚊子。相反，今年夏天我没有发现病毒。从气候上讲，今年夏天比去年夏天要冷得多，这是创纪录的热量和干旱的特征。根据Kain和Bolker的模型，看到当地鸟类社区对WNV传播的支持将非常有趣。我检查了ebird，然后大量清单exist for birds in Spokane County, providing ample data for analysis. My intention is to try and apply their model to our locality, and see how well it extrapolates. In general, I am amazed by the thorough and ingenious work they have done to make such a complicated system so much more tractable by focusing on the bird communities. This development gives me hope that, with the incorporation of mosquito dynamics, we will finally have a system that can provide realistic predictions of West Nile virus transmission risk, and contribute to protecting the public from this most prevalent arbovirus.