Spatial connectivity plays an important role in mosquito-borne disease transmission. Connectivity can arise for many reasons, including shared environments, vector ecology and human movement. This systematic review synthesizes the spatial methods used to model mosquito-borne diseases, their spatial connectivity assumptions and the data used to inform spatial model components. We identified 248 papers eligible for inclusion. Most used statistical models (84.2%), although mechanistic are increasingly used. We identified 17 spatial models which used one of four methods (spatial covariates, local regression, random effects/fields and movement matrices). Over 80% of studies assumed that connectivity was distance-based despite this approach ignoring distant connections and potentially oversimplifying the process of transmission. Studies were more likely to assume connectivity was driven by human movement if the disease was transmitted by an Aedes mosquito. Connectivity arising from human movement was more commonly assumed in studies using a mechanistic model, likely influenced by a lack of statistical models able to account for these connections. Although models have been increasing in complexity, it is important to select the most appropriate, parsimonious model available based on the research question, disease transmission process, the spatial scale and availability of data, and the way spatial connectivity is assumed to occur.

空间连通性在蚊媒疾病传播中发挥着重要作用。连通性的产生有多种原因，包括共享环境、矢量生态和人类运动。本系统综述综合了用于模拟蚊媒疾病的空间方法、其空间连通性假设以及用于告知空间模型组件的数据。我们确定了 248 篇符合纳入条件的论文。尽管越来越多地使用机械模型，但大多数使用统计模型（84.2％）。我们确定了 17 个空间模型，它们使用四种方法之一（空间协变量、局部回归、随机效应/场和运动矩阵）。超过 80% 的研究假设连接是基于距离的，尽管这种方法忽略了远距离连接并可能过度简化了传输过程。如果疾病是由伊蚊传播的，研究更有可能假设连通性是由人类活动驱动的。在使用机械模型的研究中更常见地假设由人类运动产生的连接，这可能是由于缺乏能够解释这些连接的统计模型的影响。尽管模型的复杂性不断增加，但重要的是根据研究问题、疾病传播过程、数据的空间规模和可用性以及假设发生空间连通性的方式来选择最合适、最简洁的可用模型。