Spatial Transmission Models: A Taxonomy and Framework

Within risk analysis and, more broadly, the decision behind the choice of which modeling technique to use to study the spread of disease, epidemics, fires, technology, rumors, or, more generally, spatial dynamics, is not well documented. While individual models are well defined and the modeling techniques are well understood by practitioners, there is little deliberate choice made as to the type of model to be used, with modelers using techniques that are well accepted in the field, sometimes with little thought as to whether alternative modeling techniques could or should be used. In this article, we divide modeling techniques for spatial transmission into four main categories: population‐level models, where a macro‐level estimate of the infected population is required; cellular models, where the transmission takes place between connected domains, but is restricted to a fixed topology of neighboring cells; network models, where host‐to‐host transmission routes are modeled, either as planar spatial graphs or where shortcuts can take place as in social networks; and, finally, agent‐based models that model the local transmission between agents, either as host‐to‐host geographical contacts, or by modeling the movement of the disease vector, with dynamic movement of hosts and vectors possible, on a Euclidian space or a more complex space deformed by the existence of information about the topology of the landscape. We summarize these techniques by introducing a taxonomy classifying these modeling approaches. Finally, we present a framework for choosing the most appropriate spatial modeling method, highlighting the links between seemingly disparate methodologies, bearing in mind that the choice of technique rests with the subject expert.