Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EA, UK.
Institute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool L69 7ZB, UK.
J R Soc Interface. 2021 Mar;18(176):20200966. doi: 10.1098/rsif.2020.0966. Epub 2021 Mar 31.
Computer simulations of individual-based models are frequently used to compare strategies for the control of epidemics spreading through spatially distributed populations. However, computer simulations can be slow to implement for newly emerging epidemics, delaying rapid exploration of different intervention scenarios, and do not immediately give general insights, for example, to identify the control strategy with a minimal socio-economic cost. Here, we resolve this problem by applying an analytical approximation to a general epidemiological, stochastic, spatially explicit SIR(S) model where the infection is dispersed according to a finite-ranged dispersal kernel. We derive analytical conditions for a pathogen to invade a spatially explicit host population and to become endemic. To derive general insights about the likely impact of optimal control strategies on invasion and persistence: first, we distinguish between 'spatial' and 'non-spatial' control measures, based on their impact on the dispersal kernel; second, we quantify the relative impact of control interventions on the epidemic; third, we consider the relative socio-economic cost of control interventions. Overall, our study shows a trade-off between the two types of control interventions and a vaccination strategy. We identify the optimal strategy to control invading and endemic diseases with minimal socio-economic cost across all possible parameter combinations. We also demonstrate the necessary characteristics of exit strategies from control interventions. The modelling framework presented here can be applied to a wide class of diseases in populations of humans, animals and plants.
基于个体的模型的计算机模拟常用于比较通过空间分布的人群传播的传染病的控制策略。然而，对于新出现的传染病，计算机模拟的实施可能会很慢，从而延迟对不同干预方案的快速探索，并且不会立即提供一般性的见解，例如，确定具有最小社会经济成本的控制策略。在这里，我们通过将一种分析逼近应用于一般的传染病学、随机的、空间显式的 SIR(S) 模型来解决这个问题，其中感染根据有限范围的扩散核分散。我们推导出病原体入侵空间显式宿主种群并成为地方性的分析条件。为了得出关于最佳控制策略对入侵和持久性的可能影响的一般见解：首先，我们根据它们对扩散核的影响，区分“空间”和“非空间”控制措施；其次，我们量化控制干预对流行病的相对影响；第三，我们考虑控制干预的相对社会经济成本。总的来说，我们的研究表明，两种控制干预措施和一种疫苗接种策略之间存在权衡。我们确定了用最小的社会经济成本控制入侵和地方性疾病的最佳策略，涵盖了所有可能的参数组合。我们还展示了控制干预退出策略的必要特征。这里提出的建模框架可以应用于人类、动物和植物种群中广泛的疾病。
