Human behaviour, the flow of information and the spread and control of crop disease

虽然植物疾病的传播显然在很大程度上取决于控制传播的生物因素，但农作物中的流行病往往也有人为因素。农民决定种植哪些作物和/或品种，何时何地种植，以及在整个生长季节决定是否以及如何积极控制疾病（Thompson等人，2018）。由于这些决定通常是基于对疾病压力的不完全了解以及对控制有效性的认知，因此信息的传播以及农民个人的反应能力和风险厌恶程度是一个非常重要的因素。这需要将人类行为和疾病传播联系起来的数学模型。这在某种程度上对人类疾病进行了充分的研究，特别是在疫苗接种方面。然而，接种疫苗通常提供持久的保护，而作物农民必须在每个生长季节之间和期间做出决定。对于植物疾病来说，疾病传播往往也具有重要的空间方面，通过一系列途径（例如空中、种子上、通过媒介、通过工具、从交替或替代宿主中的流行病）进行复杂的传播，以及大量的隐性（即未被发现的）感染。关于控制疾病传播和产量反应的关键参数的具体信息往往也很少（Cunniffe et al., 2015）。这个项目将集中于建立人类行为和作物疾病的耦合模型。最初的重点将是扩展现有的玉米致命坏死的简单非空间模型（Hilker等人，2017）-一种快速传播的病毒性疾病复合物，对撒哈拉以南非洲部分地区的粮食安全构成重大威胁-包括随机性、空间传播、通过种植者网络的信息流动以及农民决策与疾病传播之间的双向耦合。然而，由于该项目的核心依赖于自利实体之间的战略决策，因此也将使用博弈论中的工具开发和研究更简单的模型。特别重要的是所谓的“迭代博弈”理论，它关注的是反复做出决策的情况。

While spread of plant disease clearly depends strongly on biological factors controlling transmission, epidemics in agricultural crops very often also have a human dimension. Farmers make decisions about which crops and/or varieties to grow and when and where to plant them, as well as deciding throughout the growing season whether and how aggressively to control disease (Thompson et al., 2018). Since these decisions are typically based on imperfect knowledge of disease pressures as well as the perceived effectiveness of control, the spread of information is a very important factor, together with individual farmer's responsiveness and level of risk-aversion.This requires mathematical models to couple human behaviour and disease spread. This is somewhat well-studied for human disease, particularly in the context of vaccination. However, vaccination typically provides long-lasting protection, whereas crop farmers must make decisions both between and within each growing season. For plant disease there is also often a significant spatial aspect to disease spread, complex transmission via a range of pathways (e.g. aerially, on seed, by vectors, via tools, from epidemics in alternate or alternative hosts) and large amount of cryptic (i.e. undetected) infection. There is also often little concrete information about key parameters controlling disease spread and yield responses (Cunniffe et al., 2015).This project will concentrate on building models coupling human behaviour and crop disease. The initial focus will be on extending an existing simple non-spatial model of maize lethal necrosis (Hilker et al., 2017) - a viral disease complex which is spreading fast and is a significant threat to food security in parts of sub-Saharan Africa - to include stochasticity, spatial spread, the flow of information through networks of growers and the two-way coupling between farmers' decisions and disease spread. However, since at its core this project depends on strategic decision making among self-interested entities, simpler models will also be developed and investigated using tools taken from game theory. Particularly important will be the theory of so-called "iterative games", which focuses on the case in which decisions are repeatedly made.