In epidemiological studies, the complete history of the disease system is seldom available; for example, we rarely observe the infection times of individuals but rather dates of diagnosis/disease reporting. The method of back-calculation together with prior knowledge about the distribution of the time from the infection to the disease reporting, called the incubation period, can be used to estimate unobserved infection times. Here, we consider the use of back-calculation in the context of spatial infectious disease models, extending the method to incorporate spatial information in the back-calculation method itself. Such a method should improve the quality of the fitted model, allowing us to better identify characteristics of the disease system of interest. We show that it is possible to better infer the underlying disease dynamics via the method of spatial back-calculation.